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ANALYSIS OF STRUCTURES IN BIOMEDICAL

IMAGES

ANA CATARINA FREITAS DA SILVA DE JESUS

JULHO 2010

ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES

Monograph of the Master Course in Biomedical Engineering Program,

Faculty of Engineering of University of Porto

Ana Catarina Freitas da Silva de Jesus

Graduated in Biochemistry (2000)

Faculty of Science of University of Porto

Graduated in Nuclear Medicine (2006)

Superior School of Allied Health Sciences

Polytechnic Institute of Porto

Supervisor:

João Manuel R. S. Tavares

Assistant Professor of the Mechanical Engineering Department

Faculty of Engineering of University of Porto

ii

SUMMARY

The purpose of this monograph is to perform a literature search on the effect of

radiation on living systems and their use as therapy to kill cancer cells. To this end, in

this work I start with a description of the checkpoints of the cell cycle and apoptosis

phenomena as well as the cancer cell characteristics, which are important to

understand the effect of radiation on cancer cells. Then, there is a description of the

biological effects of radiation and how it interacts with normal and cancer cells.

Subsequently, there is a description of the radiological technique used to kill

cancer cells, which will be studied in my thesis dissertation, called brachytherapy. In

addition, the cell cultures and the adequate means to obtain reasonable laboratory

culture of cells, without contamination, for subsequent use to study the effect of

radiation on cells, are discussed.

To finish this monograph it is performed a description of the basic concepts of

digital image processing, highlighting the increasing importance of this technique in

the image processing and analysis.

i

ACKNOWLEDGEMENTS

To Professor João Manuel R. S. Tavares for the support provided throughout

this work, particularly for guidance, support and availability, essential for the proper

and constructive development of the same.

To all of those who make possible the development of this work.

CONTENTS

CONTENTS

ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES iii

CHAPTER I – INTRODUCTION TO THE THEME AND REPORT ORGANIZATION 1

1.1 – Introduction 3

1.2 - Main Objectives 4

1.3 - Report Organization 4

1.4 - Major Contributions 6

CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS 7


2.2 - Cell Life Cycle 10

2.2.1 – Interphase 10

2.2.2 - DNA Replication 11

2.2.3 - Cell Division 12

2.2.3.1 – Mitosis 12

2.2.3.2 – Cytokinesis 14

2.2.4 – Meiosis 14

2.3 - Progression of the cell cycle 17

2.4 - Growth characteristics of malignant cells 24

2.4.1 - Phenotypic Alterations in Cancer Cells 25

2.4.2 - Immortality of Transformed Cells in Culture 26

2.4.3 - Decreased Requirement for Growth Factors 27

2.4.4 - Loss of Anchorage Dependence 27

2.4.5 - Loss of Cell Cycle Control and Resistance to Apoptosis 28

2.5 - Cell Cycle Regulation 29

CONTENTS

ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES iv

2.5.1 - CDK Inhibitors 30

2.5.2 – Cyclins 31

2.5.3 - Cell Cycle Checkpoints 32

2.5.4 - Cell Cycle Regulatory Factors as Targets for Anticancer Agents 35

2.6 – Apoptosis 37

2.6.1 - Biochemical Mechanism of Apoptosis 39

2.6.2 – Caspases 42

2.6.3 - Bcl-2 Family 43

2.6.4 – Anoikis 43

2.7 - Resistance to Apoptosis in Cancer and Potential Targets for Therapy 45

2.8 – Summary 47

CHAPTER III – CANCER CELL 49


3.2 – Cancer cell 52

3.2.1 – Types of cancer 54

3.2.2 – The uniqueness of cancer 55

3.2.3 – The development of tumors 56

3.2.4 – Genetic influence on tumors 56

3.3 – Cancer through the ages 57

3.3.1 – Early discovery of carcinogens 58

3.3.2 – The use of microscopes demonstrated changes at a cellular level 58

3.4 – Modern day research and treatment 59

CONTENTS

ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES v

3.5 – Tissues changes in response to stimuli 59

3.5.1 – Metaplasia 60

3.5.2 – Hypertrophy and hyperplasia 63

3.5.3 – Dysplasia 64

3.6 – Feeding tumor growth by angiogenesis 65

3.7 – Characteristics of benign and malignant tumors 67

3.8 – Events that occur during the process of metastasis 70

3.8.1 – Characteristics of metastatic cells 70

3.9 – Summary 71

CHAPTER IV – RADIATION EFFECT ON NORMAL AND NEOPLASTIC TISSUES 74


4.2 – Quantities and units used in radiation dosimetry 77

4.2.1 – Radiation measurements definitions 79

4.2.2 – Quantities and units 80

4.3 – Historical perspective of radiobiology 82

4.3.1 – Law of Bergonie and Tribendeau 82

4.3.2 – Ancel and Vitemberger 83

4.3.3 – Fractionation theory 84

4.3.4 – Mutagenesis 85

4.3.5 – Effect of oxygen 85

4.3.6 – Relative biologic effectiveness 86

4.3.7 – Reproductive failure 87

CONTENTS

ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES vi

4.4 – Biologic effect of radiation 87

4.4.1 – Elementary phenomena 88

4.4.2 – Molecular damages 89

4.4.3 – Chromossomes irradiation 91

4.4.4 – Irradiation of macromolecules 96

4.4.5 – Dose-response relationship 99

4.4.5.1 – Linear-dose-response relationships 100

4.4.5.2 – Linear quadratic dose-response curves 101

4.4.5.3 – Dose-response curve linear quadratic 101

4.4.6 – Targeted theory 102

4.4.7 – Cell survival curves 103

4.5 - Cell Death in Mammalian Tissues 105

4.6 - Nature of Cell Populations in Tissue 107

4.7 - Cell Population Kinetics and Radiation Damage 109

4.7.1 - Growth Fraction and its significance 109

4.8 - Cell Kinetics in Normal Tissues and Tumors 111

4.9 - Models for Radiobiological Sensitivity of Neoplastic Tissues 112

4.9.1 - Hewitt Dilution Assay 113

4.9.2 - Lung Colony Assay System 116

4.10 - Tumor Growth and Tumor “Cure” Models 116

4.10.1 - Tumor Volume Versus Time 117

4.10.2 - TCD50, Tumor Cure 118

4.11 - Radiobiological Responses of Tumors 118

CONTENTS

ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES vii

4.12 - Hypoxia and Radiosensitivity in Tumor Cells 119

4.13 – Summary 122

CHAPTER V – CELL CULTURE AND FLOW CYTOMETRY 124


5.2 - Cell-Culture Laboratory 126

5.3 - Maintaining Cultures 127

5.3.1 – Medium 128

5.3.2 - The use of medium in analysis and alternatives 132

5.4 - Cytogenetic Analysis of Cell Lines 133

5.4.1 - The Utility of Cytogenetic Characterization 133

5.5 - Methods to Induce Cell Cycle Checkpoints 134

5.6 - Methods for Synchronizing Mammalian Cells 135

5.7 - Analysis of the Mammalian Cell Cycle by Flow Cytometry 137

5.8 – Conclusion 138

CHAPTER VI – BRACHYTHERAPY 141


6.2 – Brachytherapy 144

6.3 –Sources in brachytherapy 146

6.3.1 – Radium 146

6.3.2 - Radium substitutes 147

6.3.2 – New sources 148

6.4 – Radiobiology of brachytherapy 148

CONTENTS

ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES viii

6.4.1 – The four Rs of radiobiology 149

6.4.2 – Radiobiology of low dose-rate and fractioned irradiation 151

6.4.2.1 – Split-dose recovery from sub-lethal damages in mammalian cells 152

6.4.2.2 – Cell-cycle complication: a heterogeneous population 154

6.4.2.3 – Radiation affects cell-cycle progression itself 155

6.4.2.4 – Potentially lethal damage 157

6.5 – Dose-rate effects with human cells 157

6.5.1 – Time-scale of radiation action 158

6.5.2 – Mechanism of the dose-rate effect 159

6.5.3 – Dose-rate effect in human tumor cells 162

6.5.4 – Effect of irradiation on cell cycle progression 164

6.5.5 – Cell killing around an implanted radiation source 164

6.5.6 – Implications for clinical brachytherapy 167

6.6 – Predictive assays for radiation oncology 168

6.7 – Summary 169

CHAPTER VI I – BASIC CONCEPTS OF DIGITAL IMAGE PROCESSING 171


7.2 – Pre-processing evaluation of digital images 174

7.3 – Look-up tables 175

7.4 – Flat-field correction and background subtraction 177

7.5 – Image interpretation 181

7.6 – Digital image histogram adjustment 183

CONTENTS

ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES ix

7.7 – Spatial convolution kernels (or masks) 185

7.8 – Smoothing convolution filters (spatial averaging) 187

7.9 – Sharpening convolution filters 189

7.10 – Median filters 190

7.11 – Specialized convolution filters 191

7.12 – Unsharp mask filtering 192

7.13 – Fourier transforms 193

7.14 – Summary 195

CHAPTER VIII – CONCLUSIONS AND FUTURE WORKS 197

8.1 - Final Conclusions 199

8.2 - Future Works 200

REFERENCES 201

CHAPTER I

INTRODUCTION TO THE THEME AND REPORT ORGANIZATION

CHAPTER I – INTRODUCTION TO THE THEME AND REPORT ORGANIZATION

ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 3

1.1 – INTRODUCTION

The different types of radiation applied for radiobiological research is important

for the determination of the biological effectiveness of ionizing photon radiation as a

function of photon energy. The therapeutic dose values (few Gy per daily fraction) can

be delivered in a sufficiently small irradiation duration (dose rate ≈1 Gy/min) to be

independent from repairing processes in human cells (Zeil, 2009).

Brachytherapy is a term used to describe the short distance treatment of

cancer with radiation from small, encapsulated radionuclide sources. This type of

treatment is made by placing sources directly into or near the volume to be treated.

The dose is then delivered continuously, either over a short period of time (temporary

implants) or over the lifetime of the source to a complete decay (Suntharalingam,

2002).

When cells are exposed to ionizing radiation the standard physical effects

between radiation and the atoms or molecules of the cells occur first and the possible

biological damage to cell functions follows later. The biological effects of radiation

result mainly from damage to the DNA, which is the most critical target within the cell;

however, there are also other sites in the cell that, when damaged, may lead to cell

death (Suntharalingam, 2002).

Human tumors strongly differ in radiosensitivity and radiocurability and this is

thought to stem from differences in capacity for repair of sub-lethal damage.

Radiosensitivity varies along the cell cycle, S being the most resistant phase and G2 and

M the most sensitive. Therefore, cells surviving an exposure are preferentially in a

stage of low sensitivity (G1), i.e. synchronized in a resistant cell cycle phase. They

progress thereafter together into S and then to the more sensitive G2 and M phases. A

new irradiation exposure at this time will have a larger biological effect (more cell kill)

(Mazeron, 2005).

Brachytherapy is used to treat patients with cancer cells and the irradiated cells

will be studied by me in my dissertation thesis, as the continued work from this

monograph.

One of the most widely used steps in the process of obtaining information from

images is image segmentation: dividing the input image into regions that hopefully



correspond to structural units in the scene or distinguish objects of interest (Russ,

1998).

1.2 – MAIN OBJECTIVES

Since the 1980s, radiation oncologists and biologists have recognized the need

for additional assays on an individual patient basis that would select the most

advantageous treatment approach. Though, it’s important to have in mind that the

cellular radiation sensitivity of the tumor may differ among individuals, even for

tumors of the same histological type. If the radiosensitivity of the individual's tumor

were precisely known, perhaps total radiation doses could be adjusted before the end

of therapy to maximize tumor response (Joslin, 2001).

The main objective of this monograph is to emphasize the importance and

application of brachytherapy in the cure of cancer patients. To do this, it’s performed a

description of the theory important to understand the underlying biochemical events

upon irradiation of the cells.

These concepts include the knowledge of the cancer cell, regulation of cell cycle

and apoptosis and the biological effects of radiation. This theoretic knowledge is

important to proceed with to my dissertation thesis which consists in the image

processing and analysis of the electron microscopic cell images of cancer irradiated

cells with the brachytherapy radiation technique.

1.3 – REPORT ORGANIZATION

It was intended to organize this document in a self-directed and self-regulating

approach to improve the access to various topics structured in eight chapters. So, it

will be described very succinctly what is treated in each remaining chapter:



Chapter II – Cell cycle regulation and apoptosis

In this chapter takes place a description of key concepts related to the cell cycle

checkpoints, to the behavior of the malignant cells and to the cellular death

mechanisms among other information related to the normal and malignant cells.

Chapter III – Cancer cell

This chapter focuses the characteristics of the cancer cells in comparison with

normal cells, as well as the stages that the normal cell passes to become a cancer cell.

Chapter IV – Radiation and biological effects in cancer cells

In this chapter it is presented a description of the irradiated carcinogenesis as

well as the cell death mechanisms. It is also described important issues regarding the

cellular behavior upon irradiation.

Chapter V – Cell culture and flow cytometry

In this fifth chapter it is performed an approach of some important issues

regarding the safety manipulation and maintenance of cells when performing cell

culture techniques. It is also described the methods to induce cell cycle checkpoints

and the flow cytometry technique.

Chapter VI – Brachytherapy

In this chapter a description of one of the radiation technique to kill cancer cells

is made. In addition it is mentioned the types of sources used in this radiation

technique as well as the biological events occurring in the cancer cells upon irradiation.



Chapter VII – Image Processing and Analysis

In this chapter it is performed a description of the basic concepts of the image

processing. This chapter is important to emphasize the image processing and

segmentation that will be performed in my thesis to extract information of the

irradiated cancer cell images. This analysis will be performed using the MATLAB image

processing toolbox.

Chapter VIII – Final Conclusions and Future Works

In the last chapter it is presented the final conclusions of the work performed,

as well as the future perspectives regarding the execution of the correspondent thesis.

1.4 – MAJOR CONTRIBUTIONS

This work consists in exposing the theory about cell cycle regulation and

checkpoints that help to understand the behavior of cells when they are irradiated

with the radiation technique named brachytherapy. This information will be helpful to

study the electron microscopy images of breast cancer cells submitted to

brachytherapy for the thesis work.

In addition a description of the image processing and analysis is made, which is

very important to understand the steps that need to the performed to be able to

extract useful information of images. It is also important to highlight the importance of

this tool as a technical aid and complement to the extraction of information on

biological and biochemical events.

CHAPTER II

CELL CYCLE REGULATION AND APOPTOSIS

CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS


2.1 - INTRODUCTION

The development of knowledge about the biochemistry and cell biology of

cancer comes from a number of disciplines. Some of this knowledge has come from

research initiated a century or more ago. There has been a flow of information about

genetics into a knowledge base about cancer, starting with Gregor Mendel and the

discovery of the principle of inherited traits and leading through Theodor Boveri’s work

on the chromosomal mode of heredity and chromosomal damage in malignant cells to

Avery’s discovery of DNA as the hereditary principle, Watson and Crick’s determination

of the structure of DNA, the human genome project, DNA microarrays, and

proteomics. Not only has this information provided a clearer understanding of the

carcinogenic process, it has also provided better diagnostic approaches and new

therapeutic targets for anticancer therapies (Ruddon, 2007).

Cancer cells contain many alterations, which accumulate as tumors develop.

Over the last 25 years, considerable information has been gathered on the regulation

of cell growth and proliferation leading to the identification of the proto-oncogenes

and the tumor suppressor genes. The proto-oncogenes encode proteins, which are

important in the control of cell proliferation, differentiation, cell cycle control and

apoptosis. Mutations in these genes act dominantly and lead to a gain in function. In

contrast the tumor suppressor genes inhibit cell proliferation by arresting progression

through the cell cycle and block differentiation. They are recessive at the level of the

cell although they show a dominant mode of inheritance. In addition, other genes are

also important in the development of tumors. Mutations leading to increase genomic

instability suggest defects in mismatch and excision repair pathways. Genes involved in

DNA repair, when mutated, also predispose the patient to developing cancer

(Macdonald, 2005).

A crucial decision in every proliferating cell is the decision to continue with a

further round of cell division or to exit the cell cycle and return to the stationary phase.

Similarly quiescent cells must make the decision, whether to remain in the stationary

phase (G0) or to enter into the cell cycle. Entry into the cycle occurs in response to

mitogenic signals and exit in response to withdrawal of these signals. To ensure that



DNA replication is complete and that any damaged DNA is repaired, cells must pass

through specific checkpoints. Tumor cells undergo uncontrolled proliferation either

due to mutations in the signal transduction pathways or because of mutations in the

regulatory mechanism of the cell cycle (Macdonald, 2005).

In this chapter, it is provided a detailed description of the cell cycle, its

progression and the cellular events involved in transforming normal cells into

malignant cells. For this purpose, the chapter starts with the explanation of the cell

cycle followed by the description of the progression of the cell cycle, the growth

characteristics of the malignant cells and the cell cycle regulation. After this, the

chapter focuses the importance of the apoptosis phenomena and ends referring the

resistance to apoptosis in cancer cells and potential targets for therapy.

2.2 – CELL LIFE CYCLE

The cell life cycle includes the changes a cell undergoes from the time it is

formed until it divides to produce two new cells. The life cycle of a cell has two stages,

an interphase and a cell division stage, Figure 2.1 (Seelev, 2004).

Figure 2.1 – Cell cycle (from (Seeley, 2004))

2.2.1 – Interphase

Interphase is the phase between cell divisions. Ninety percent or more of the

life cycle of a typical cell is spent in interphase and, during this time the cell carries out



the metabolic activities necessary for life and performs its specialized functions such as

secreting digestive enzymes. In addition, the cell prepares to divide which includes an

increase in cell size; because many cell components double in quantity, and a

replication of the cell’s DNA. Consequently, the centrioles within the centrosome are

also duplicated, when the cell divides, each new cell receives the organelles and DNA

necessary for continued functioning. Interphase can be divided into three subphases,

called G1, S, and G2. During G1 (the first gap phase) and G2 (the second gap phase), the

cell carries out routine metabolic activities. During the S phase (the synthesis phase),

the DNA is replicated (new DNA is synthesized) (Seelev, 2004).

Many cells in the human body do not divide for days, months, or even years.

These “resting” cells exit and enter the cell cycle that is called the G0 phase, in which

they remain, unless, stimulated to divide (Seelev, 2004).

2.2.2 - DNA Replication

DNA replication is the process by which two new strands of DNA are made,

using the two existing strands as templates. During interphase, DNA and its associated

proteins appear as dispersed chromatin threads within the nucleus. When DNA

replication begins, the two strands of each DNA molecule separate from each other for

some distance, Figure 2.2. Then, each strand functions as a template, or pattern, for

the production of a new strand of DNA, which is formed as new nucleotides pair with

the existing nucleotides of each strand of the separated DNA molecule. The production

of the new nucleotide strands is catalyzed by DNA polymerase, which adds new

nucleotides at the 3` end of the growing strands. One strand, called the leading strand,

is formed as a continuous strand, whereas the other strand, called the lagging strand,

is formed in short segments going in the opposite direction. The short segments are

then spliced by DNA ligase. As a result of DNA replication, two identical DNA molecules

are produced, each of them having one strand of nucleotides derived from the original

DNA molecule and one newly synthesized strand (Seelev, 2004).



Figure 2.2 – Replication of DNA (from (Seelev, 2004))

2.2.3 - Cell Division

New cells necessary for growth and tissue repair are produced by cell division.

A parent cell divides to form two daughter cells, each of which has the same amount

and type of DNA as the parent cell. Because DNA determines cell structure and

function, the daughter cells have identical structure and perform the same functions as

the parent cell. Cell division involves two major events: the division of the nucleus to

form two new nuclei, and the division of the cytoplasm to form two new cells. Each of

the new cells contains one of the newly formed nuclei. The division of the nucleus

occurs by mitosis, and the division of the cytoplasm is called cytokinesis (Seelev, 2004).

2.2.3.1 - Mitosis

Mitosis is the division of the nucleus into two nuclei, each of which has the

same amount and type of DNA as the original nucleus. The DNA, which was dispersed

as chromatin in interphase, condenses in mitosis to form chromosomes. All human

somatic cells, which include all cells except the sex cells, contain 46 chromosomes,

which are referred to as a diploid number of chromosomes. Sex cells have half the

number of chromosomes as somatic cells (Seelev, 2004).

The 46 chromosomes in somatic cells are organized into 23 pairs of

chromosomes. Twenty-two of these pairs are called autosomes. Each member of an



autosomal pair of chromosomes looks structurally alike, and together they are called a

homologous pair of chromosomes. One member of each autosomal pair is derived

from the person’s father, and the other is derived from the mother. The remaining pair

of chromosomes is the sex chromosomes. In females, the sex chromosomes look alike,

and each is called an X chromosome. In males, the sex chromosomes do not look

similar. One chromosome is an X chromosome, and the other is smaller and is called a

Y chromosome. One X chromosome of a female is derived from her mother and the

other is derived from her father. The X chromosome of a male is derived from his

mother and the Y chromosome is derived from his father (Seelev, 2004).

Mitosis is divided into four phases: prophase, metaphase, anaphase, and

telophase. Although each phase represents major events, mitosis is a continuous

process, and no discrete jumps occur from one phase to another. Learning the

characteristics associated with each phase is helpful, but a more important concept is

how each daughter cell obtains the same number and type of chromosomes as the

parent cell. The major events of mitosis are summarized in Figure 2.3 (Seelev, 2004).

Figure 2.3 – Mitosis. (1) Interphase; (2) Prophase; (3) Metaphase; (4) Anaphase; (5) Telophase; (6) Interphase,

Cytokinesis (from (Seelev, 2004))



2.2.3.2 - Cytokinesis

Cytokinesis is the division of the cytoplasm of the cell to produce two new cells

(Figure 2.3). Cytokinesis begins in anaphase continues through telophase and ends in

the following interphase. The first sign of cytokinesis is the formation of a cleavage

furrow, or puckering of the plasma membrane, which forms midway between the

centrioles. A contractile ring composed primarily of actin filaments pulls the plasma

membrane inward, dividing the cell into two halves. Cytokinesis is complete when the

membranes of the two halves separate at the cleavage furrow to form two separate

cells (Seelev, 2004).

2.2.4 – Meiosis

All cells of the body are formed by mitosis, except sex cells that are formed by

meiosis. In meiosis the nucleus undergoes two divisions resulting in four nuclei, each

containing half as many chromosomes as the parent cell. The daughter cells that are

produced by cytokinesis differentiate into gametes, or sex cells.

The gametes are reproductive cells—sperm cells in males and oocytes (egg

cells) in females. Each gamete not only has half the number of chromosomes found in

a somatic cell but also has one chromosome from each of the homologous pairs

verified in the parent cell. The complement of chromosomes in a gamete is referred to

as a haploid number. Oocytes contain one autosomal chromosome from each of the

22 homologous pairs and an X chromosome. Sperm cells have 22 autosomal

chromosomes and either an X or Y chromosome. During fertilization, when a sperm

cell fuses with an oocyte, the normal number of 46 chromosomes in 23 pairs is

reestablished. The sex of the baby is determined by the sperm cell that fertilizes the

oocyte. The sex is male if a Y chromosome is carried by the sperm cell that fertilizes the

oocyte and female if the sperm cell carries an X chromosome (Seelev, 2004).

The first division during meiosis is divided into four phases: prophase I,

metaphase I, anaphase I, and telophase I, Figure 2.4. As in prophase of mitosis, the

nuclear envelope degenerates, spindle fibers form, and the already duplicated

chromosomes become visible. Each chromosome consists of two chromatids joined by

a centromere. In prophase I, however, the four chromatids of a homologous pair of



chromosomes join together, or synapse, to form a tetrad. In metaphase I the tetrads

align at the equatorial plane and in anaphase I each pair of homologous chromosomes

separate and move toward opposite poles of the cell (Seelev, 2004).

For each pair of homologous chromosomes, one daughter cell receives one

member of the pair, and the other daughter cell receives the other member. Thus each

daughter cell has 23 chromosomes, each of which is composed of two chromatids.

Telophase I with cytokinesis is similar to telophase of mitosis and two daughter cells

are produced. Interkinesis is the phase between the formation of the daughter cells

and the second meiotic division. No duplication of DNA occurs during this phase. The

second division of meiosis also has four phases: prophase II, metaphase II, anaphase II,

and telophase II. These stages occur much as they do in mitosis, except that 23

chromosomes are present instead of 46 (Seelev, 2004).

The chromosomes align at the equatorial plane in metaphase II, and their

chromatids split apart in anaphase II. The chromatids then are called chromosomes,

and each new cell receives 23 chromosomes. In addition to reducing the number of

chromosomes in a cell from 46 to 23, meiosis is also responsible for genetic diversity

for two reasons:

A random distribution of the chromosomes is received from each

parent. One member of each homologous pair of chromosomes was

derived from the person’s father and the other member from the

person’s mother. The homologous chromosomes align randomly during

metaphase I when they split apart, each daughter cell receives some of

the father’s and some of the mother’s chromosomes. The number of

chromosomes each daughter cell receives from each parent is

determined by chance;

However, when tetrads are formed, some of the chromatids may break

apart, and part of one chromatid from one homologous pair may be

exchanged for part of another chromatid from the other homologous

pair, Figure 2.5. This exchange is called crossing-over; as a result,

chromatids with different DNA content are formed, Figure 2.5.



With random assortment of homologous chromosomes and crossing-over, the

possible number of gametes with different genetic makeup is practically unlimited.

When the distinct gametes of two individuals unite, it is virtually certain that the

resulting genetic makeup never has occurred before and never will occur again. The

genetic makeup of each new human being is unique (Seelev, 2004).

Figure 2.4 – Meiosis (from (Seelev, 2004))



Figure 2.5 – Crossing-over (from (Seelev, 2004))

2.3 - PROGRESSION OF THE CELL CYCLE

The cell cycle is controlled by a complex pattern of synthesis and degradation of

regulators together with careful control of their spatial organization in specific

subcellular compartments. In addition, checkpoint controls can modulate the

progression of the cycle in response to adverse conditions such as DNA damage.

Cells either enter G1 from G0 in response to mitogenic stimulation or follow on

from cytokinesis if actively proliferating (i.e. from M to G1). Removal of mitogens

allows them to return to G0. The critical point between mitogen dependence and

independence is the restriction point or R which occurs during G1. It is here that cells

reach the ‘point of no return’ and are committed to a round of replication (Macdonald,

2005), Figure 2.6.

Figure 2.6 – Restriction point, R (from (Griffiths, 1999))



Synthesis of the D-type cyclins begins at the G0/G1 transition and continues so

long as growth factor stimulation persists. This mitogen stimulation of cyclin D is in

part dependent on RAS activation, a role which is highlighted by the ability of anti-RAS

antibodies to block the progression of the cell cycle if added to cells prior to mitogen

stimulation. The availability of cyclin D activates CDK4 and 6 and these complexes then

drive the cell from early G1 through R to late G1; largely by regulation of RB which

exists in a phosphorylated state at the start of G1 complexed to a large number of

proteins. Cyclin D-CDK4/6 activation begins phosphorylation of Rb during early G1. This

initial phosphorylation leads to release of histone deacetylase activity from the

complex alleviating transcriptional repression. The E2F transcription factor remains

bound to Rb at this stage but can still transcribe some genes including cyclin E.

Therefore, levels of cyclin E increase and lead to activation of CDK2, which can then

complete phosphorylation of Rb. Consequently, complete phosphorylation of Rb

results in the release of E2F to activate genes required to drive cells through the G1/S

transition (Macdonald, 2005), Figure 2.7.

Figure 2.7 – Regulation of the G1 to S transition (from (Griffiths, 1999))

The CKIs also play a role in control of cell cycle progression at this stage and in

response to antimitogenic signals, oppose the activity of the CDKs and cause cell cycle

arrest. INK4 inhibitors bind to CDK4/6 to prevent cyclin D binding and CIP/KIP

inhibitors similarly inhibit the kinase activity of cyclin ECDK2, Figure 2.8. CIP/KIP

inhibitors also interact with cyclin D-CDK4/6 complexes during G1, but rather than

blocking cell cycle progression, this interaction is required for the complete function of



the complex and allows G1 progression. This interaction sequesters CIP/KIP, preventing

its inhibition of cyclin E-CDK2 and thereby facilitating its full activation to contribute to

G1 progression. In the presence of an antimitogenic signal, levels of cyclin D-CDK4/6

are reduced, CIP/KIP is released, which can then interact with and inhibit CDK2 to

cause cell cycle arrest (Macdonald, 2005).

Cells which have suffered DNA damage are prevented from entering S phase

and are blocked at G1. This process is dependent on the tumor suppressor gene p53

and p21. Activation of p53 by DNA damage results in increased p21 levels which can

then inactivate cyclin E-CDK2 to prevent phosphorylation of Rb and inhibit the release

of E2F to promote transcription of genes involved in DNA synthesis, Figure 2.8. This

causes the cell cycle to arrest in G1. Clearly, loss or mutation of p53 will lead to loss of

this checkpoint control and cells will be able to enter S phase with damaged DNA. After

cells have entered S phase, cyclin E is rapidly degraded and CDK2 is released. In S

phase, a further set of cyclins and CDKs, cyclin A-CDK2, are required for continued DNA

replication. Two A-type cyclins have been identified to date: cyclin A1 is expressed

during meiosis and in early cleavage embryos whereas cyclin A2 is present in all

proliferating cells. Cyclin A2 is also induced by E2F and is expressed from S phase

through G2 and M until prometaphase when it is degraded by ubiquitin-dependent

proteolysis (Macdonald, 2005).

Cyclin A2 binds to two different CDKs. Initially, during S phase, it is found

complexed to CDK2 following its release from cyclin E and subsequently in G2 and M it

is found complexed to CDC2 (also known as CDK1). Cyclin A2 has a role in both

transcriptional regulation and DNA replication and its nuclear localization is crucial to

its function. Cyclin A regulates the E2F transcription factor and in S phase, when E2F

directed transcription is no longer required, cyclin A directs its phosphorylation by

CDK2 leading to its degradation. This down-regulation by cyclin A2 is required for

orderly S phase progression and in its absence apoptosis occurs. Recently, cyclin A as

well as cyclin E have been shown to be regulators of centrosome replication and are

able to do so because of their ability to shuttle between nucleus and cytoplasm, Figure

2.9 (Macdonald, 2005).



Figure 2.8 – Cell cycle arrest at G1/S, mediated by cdk inhibitors (from (Shapiro, 1999))

Figure 2.9 – Dynamics of the DNA synthesome (from (Frouin, 2003))



The final phase of the cycle is M phase that comprises mitosis and cytokinesis.

The purpose of mitosis is to segregate sister chromatids into two daughter cells so that

each cell receives a complete set of chromosomes, a process that requires the

assembly of the mitotic spindle. Mitosis is split into a number of stages that includes

prophase, prometaphase, metaphase, anaphase and telophase (Macdonald, 2005).

Cytokinesis, the process of cytoplasmic cleavage, follows the end of mitosis and

its regulation is closely linked to mitotic progression. Mitosis involves the last of

cyclin/CDKs, cyclin B1 and CDC2 as well as additional mitotic kinases. These include

members of the Polo family (PLK1), the aurora family (aurora A, B and C) and the NIMA

family (NEK2) plus kinases implicated at the mitotic checkpoints (BUB1), mitotic exit

and cytokinesis (Macdonald, 2005).

Entry into the final phase of the cell cycle, mitosis, is signaled by the activation

of the cyclin B1-CDC2 complex also known as the M phase promoting factor or MPF.

This complex accumulates during S and G2, but is kept in the inactive state by

phosphorylation of tyrosine 15 and threonine 14 residues on CDC2 by two kinases,

WEE1 and MYT1. WEE1 is nuclear and phosphorylates tyrosine 15, whereas MYT1 is

cytoplasmic and phosphorylates threonine 14. At the end of G2, the CDC25

phosphatase is stimulated to dephosphorylate these residues thereby activating CDC2.

These enzymes are all controlled by DNA structure checkpoints which delay the onset

of mitosis if DNA is damaged. Regulation of cyclin B1-CDC2 is also regulated by

localization of specific subcellular compartments. It is initially localized to the

cytoplasm during G2, but is translocated to the nucleus at the beginning of mitosis. A

second cyclin B, cyclin B2, also exists in mammalian cells and is localized to the Golgi

and endoplasmic reticulum where it may play a role in disassembly of the Golgi

apparatus at mitosis (Macdonald, 2005).

A further checkpoint exists at the end of G2 which checks that DNA is not

damaged before entry into M. Once more p21 activation by p53 can arrest the cell

cycle as at the end of G1. In addition, the CHK1 kinase can phosphorylate CDC25 to

create a binding site for the 14–3–3 protein, a process which inactivates CDC25,

thereby preventing dephosphorylation of CDC2 and halting the cell cycle, Figure 2.10

(Macdonald, 2005).



Tumor cells can enter mitosis with damaged DNA, suggesting a defect in the

G2/M checkpoint. Tumor cell lines have been shown to activate the cyclin B-CDC2

complex irrespective of the state of the DNA. Activation of cyclin B1-CDC2 leads to

phosphorylation of numerous substrates including the nuclear lamins, microtubule-

binding proteins, condensins and Golgi matrix components that are all needed for

nuclear envelope breakdown, centrosome separation, spindle assembly, chromosome

condensation and Golgi fragmentation respectively. During prophase, the

centrosomes—structures which organize the microtubules and which were duplicated

during G2—separate to define the poles of the future spindle apparatus, a process

regulated by several kinases including the NIMA family member NEK2, as well as

aurora A. At the same time centrosomes begin nucleating the microtubules which

make up the mitotic spindle (Macdonald, 2005).

Chromatin condensation also occurs accompanied by extensive histone

phosphorylation to produce well defined chromosomes. Nuclear envelope breakdown

occurs shortly after centrosome separation. The nuclear envelope is normally

stabilized by a structure known as the nuclear lamin which is composed of lamin

intermediate filament proteins. This envelope is broken down as a result of

hyperphosphorylation of lamins by cyclin B-CDC2 (Macdonald, 2005).

During prometaphase, the microtubules are captured by kinetochores, the

structure which binds to the centromere of the chromosome. Paired sister chromatids

interact with the microtubules emanating from opposite poles resulting in a stable

bipolar attachment. Chromosomes then sit on the metaphase plate where they

oscillate during metaphase. Once all bipolar attachments are complete anaphase is

triggered. This is characterized by simultaneous separation of all sister chromatids.

Each chromosome must be aligned in the center of the bipolar spindle such that its

two sister chromatids are attached to opposite poles. If this is correct, the anaphase-

promoting complex (APC) together with CDC20 is activated to control degradation of

proteins such as securin. This in turn activates the separin protease which cleaves the

cohesion molecules between the sister chromatids allowing them to separate. At this

stage, there is one final checkpoint, the spindle assembly checkpoint, at the

metaphase to anaphase transition, which checks the correct assembly of the mitotic



apparatus and the alignment of chromosomes on the metaphase plate. The

gatekeeper at this checkpoint is the APC complex. Unaligned kinetochores are

recognized and associate with the MAD2 and BUB proteins which can prevent

activation of APC and cell arrest at metaphase preventing exit from mitosis. In tumor

cell abnormalities of spindle formation are found, suggesting that checkpoint control is

lost (Macdonald, 2005).

Mitotic exit requires that sister chromatids have separated to opposite poles.

During telophase, nuclear envelopes can begin to form around the daughter

chromosomes and chromatin decondensation occurs. The spindle is also disassembled

and cytokinesis is completed. The control of these processes requires destruction of

both the cyclins and other kinases such as NIMA and aurora family members by

ubiquitin dependent proteolysis mediated by APC. Daughter cells can now re-enter the

cell cycle (Macdonald, 2005).

Figure 2.10 – Cell cycle regulation of cyclin dependent kinase (Cdk1) Cyclin-B (CycB) complex (from (Novák, 2010))



2.4 - GROWTH CHARACTERISTICS OF MALIGNANT CELLS

Cancer can be characterized as a disease of genetic instability, altered cellular

behavior and altered cell–extracellular matrix interactions. These alterations lead to

dysregulated cell proliferation, and ultimately to invasion and metastasis. There are

interactions between the genes involved in these steps. For example, the genes

associated with loss of control of cell proliferation may also be involved in genetic

instability (rapidly proliferating cells have less time to repair DNA damage) and tumor

vascularization that leads to dysregulated proliferation of cells, which in turn eats up

more oxygen, creates hypoxia, and turns on HIF-1 and additional angiogenesis.

Similarly, genes involved in tumor cell invasion may also be involved in loss of growth

control (invasive cells have acquired the skills to survive in ‘‘hostile’’ new

environments) and evasion of apoptosis (less cell death even in the face of a normal

rate of cell proliferation produces more cells). The molecular genetic alterations of

cancer cells lead to cells that can generate their own growth-promoting signals are less

sensitive to cell cycle checkpoint controls, evade apoptosis, and thus have almost

limitless replication potential. This redundancy makes design of effective signal

transduction-targeted chemotherapeutic drugs that target a single pathway very

difficult indeed (Ruddon, 2007).

Cancer cells can also subvert the environment in which they proliferate.

Alterations in both cell–cell and cell–extracellular matrix interactions also occur,

leading to creation of a cancer-facilitating environment. For example, a common

alteration in epithelial carcinomas is alteration of E-cadherin expression, which is a

cell–cell adhesion molecule found on all epithelial cells. Cancer cells exhibit remarkable

plasticity and have the ability to mimic some of the characteristics of other cell types

as they progress and became less well differentiated. For example, cancer cells may

assume some of the structure and function of vascular cells. As cancer cells

metastasize, they may eventually take on a new phenotype such that the tissues of

origin may become unclear—so-called cancers of unknown primary site (Ruddon,

2007).



2.4.1 - Phenotypic Alterations in Cancer Cells

Treatment of animals or cells in culture with carcinogenic agents is a means of

studying discrete biochemical events that lead to malignant transformation, Figure

2.11. However, studies of cell transformation in vitro have many pitfalls. These ‘‘tissue

culture artifacts’’ include overgrowth of cells not characteristic of the original

population of cultured cells (e.g., overgrowth of fibroblasts in cultures that were

originally primarily epithelial cells), selection for a small population of variant cells with

continued passage in vitro, or appearance of cells with an abnormal chromosomal

number or structure (karyotype). Such changes in the characteristics of cultured cell

populations can lead to ‘‘spontaneous’’ transformation that mimics some of the

changes seen in populations of cultured cells treated with oncogenic agents. Thus, it is

often difficult to sort out the critical malignant events from the noncritical ones

(Ruddon, 2007).

Figure 2.11 – Cellular response (from (Gil, 2006))

Although closer to the carcinogenic process in humans, malignant

transformation induced in vivo by treatment of susceptible experimental animals with

carcinogenic chemicals or oncogenic viruses or by irradiation, is even more difficult

because it is hard to discriminate toxic from malignant events and to determine what

role a myriad of factors, such as the nutritional state of the animal, hormone levels, or

endogenous infections with microorganisms or parasites, might have on the in vivo

carcinogenic events. Moreover, tissues in vivo are a mixture of cell types, and it is



difficult to determine in which cells the critical transformation events are occurring

and what role the microenvironment of the tissue plays. Thus, most studies designed

to identify discrete biochemical events occurring in cells during malignant

transformation have been done with cultured cells, since clones of relatively

homogeneous cell populations can be studied and the cellular environment defined

and manipulated. The ultimate criterion that establishes whether cells have been

transformed, however, is their ability to form a tumor in an appropriate host animal.

The generation of immortalized ‘‘normal’’ cell lines of a given differentiated phenotype

from human embryonic stem cells, has enhanced the ability to study cells of a normal

genotype from a single source. Such cell lines may also be generated by transfection of

the telomerase gene into cells to maintain chromosomal length (Ruddon, 2007).

Over the past 60 years, much scientific effort has gone into research aimed at

identifying the phenotypic characteristics of in vitro transformed cells that correlate

with the growth of a cancer in vivo. This research has tremendously increased our

knowledge of the biochemistry of cancer cells. However, many of the biochemical

characteristics initially thought to be closely associated with the malignant phenotype

of cells in culture has subsequently been found to be dissociable from the ability of

those cells to produce tumors in animals. Furthermore, individual cells of malignant

tumors growing in animals or in humans exhibit marked biochemical heterogeneity, as

reflected in their cell surface composition, enzyme levels, immunogenicity, response to

anticancer drugs, and so on. This has made it extremely difficult to identify the

essential changes that produce the malignant phenotype (Ruddon, 2007).

2.4.2 - Immortality of Transformed Cells in Culture

Most normal diploid mammalian cells have a limited life expectancy in culture.

For example, normal human fibroblast lines may live for 50 to 60 population doublings

(the ‘‘Hayflick index’’), but then viability begins to decrease rapidly, unless they

transform spontaneously or are transformed by oncogenic agents. However, malignant

cells, once they become established in culture, will generally live for an indefinite

number of population doublings, provided the right nutrients and growth factors

(Ruddon, 2007).



It is not clear what limits the life expectancy of normal diploid cells in culture,

but it may be related to the continual shortening of chromosomal telomeres each time

cells divide. Transformed cells are known to have elevated levels of telomerase that

maintain telomere length. Transformed cells that become established in culture also

frequently undergo karyotypic changes, usually marked by an increase in

chromosomes (polyploidy), with continual passage. This suggests that cells with

increased amounts of certain growth-promoting genes are generated and/or selected

during continual passage in culture. The more undifferentiated cells from cancers of

animals or patients also often have an atypical karyology, thus the same selection

process may be going on in vivo with progression over time of malignancy from a lower

to a higher grade (Ruddon, 2007).

2.4.3 - Decreased Requirement for Growth Factors

Other properties that distinguish transformed cells from their non transformed

counterparts are decreased density-dependent inhibition of proliferation and the

requirement for growth factors for replication in culture. Cells transformed by

oncogenic viruses have lower serum growth requirements than do normal cells. Cancer

cells may also produce their own growth factors that may be secreted and activate

proliferation in neighboring cells (paracrine effect) or, if the same malignant cell type

has both the receptor for a growth factor and the means to produce the factor, self-

stimulation of cell proliferation (autocrine effect) may occur. One example of such an

autocrine loop is the production of tumor necrosis factor-alpha (TNF-α) and its

receptor TNFR1 by diffuse large cell lymphoma. Co-expression of TNF-α and its

receptor are negative prognostic indicators of survival, suggesting that autocrine loops

can be powerful stimuli for tumor aggressiveness and thus potentially important

diagnostic and therapeutic targets.

2.4.4 - Loss of Anchorage Dependence

Most freshly isolated normal animal cells and cells from cultures of normal

diploid cells do not grow well when they are suspended in fluid or a semisolid agar gel.



However, if these cells contact with a suitable surface they attach, spread, and

proliferate. This type of growth is called anchorage-dependent growth. Many cell lines

derived from tumors and cells transformed by oncogenic agents are able to proliferate

in suspension cultures or in a semi solid medium (methylcellulose or agarose) without

attachment to a surface. This is called anchorage-independent growth and this

property of transformed cells has been used to develop clones of malignant cells. This

technique has been widely used to compare the growth properties of normal and

malignant cells. Another advantage that has been derived from the ability of malignant

cells to grow in soft agar (agarose), is the ability to grow cancer cells derived from

human tumors to test their sensitivity to chemotherapeutic agents and to screen for

potential new anticancer drugs (Ruddon, 2007).

2.4.5 - Loss of Cell Cycle Control and Resistance to Apoptosis

Normal cells respond to a variety of suboptimal growth conditions by entering a

quiescent phase in the cell division cycle, the G0 state. There appears to be a decision

point in the G1 phase of the cell cycle, at which time the cell must make a commitment

to continue into the S phase, the DNA synthesis step, or to stop in G1 and wait until

conditions are more optimal for cell replication to occur. If this waiting period is

prolonged, the cells are said to be in a G0 phase. Once cells make a commitment to

divide, they must continue through S, G2, and M to return to G1. If the cells are blocked

in S, G2, or M for any length of time, they die. The events that regulate the cell cycle

are called cell cycle checkpoints (Ruddon, 2007).

The loss of cell cycle check point control by cancer cells may contribute to their

increased susceptibility to anticancer drugs. Normal cells have mechanisms to protect

themselves from exposure to growth-limiting conditions or toxic agents by calling on

these check point control mechanisms. Cancer cells, by contrast, can continue through

these checkpoints into cell cycle phases that make them more susceptible to the

cytotoxic effects of drugs or irradiation. For example, if normal cells accrue DNA

damage due to ultraviolet (UV) or X-irradiation, they arrest in G1 so that the damaged

DNA can be repaired prior to DNA replication. Another check point in the G2 phase

allows repair of chromosome breaks before chromosomes are segregated at mitosis,



Figure 2.12. Cancer cells, which exhibit poor or absent check point controls, proceed to

replicate the damaged DNA, thus accounting for persisting and accumulating

mutations (Ruddon, 2007).

2.5 - CELL CYCLE REGULATION

Cyclin-dependent protein kinases (CDKs), of which CDC2 is only one, are crucial

regulators of the timing and coordination of eukaryotic cell cycle events. Transient

activation of members of this family of serine/threonine kinases occurs at specific cell

cycle phases (Ruddon, 2007).

Figure 2.12 - Major pathways where Plks may play a role in intra-S-phase checkpoint in mammalian systems (from

(Suqing, 2005))

In budding yeast G1 cyclins encoded by the CLN genes, interact with and are

necessary for the activation of, the CDC2 kinase (also called p34cdc2), driving the cell

cycle through a regulatory point called START (because it is regulated by the cdc2 or

start gene) and committing cells to enter S phase. START is analogous to the G1

restriction point in mammalian cells. The CDKs work by forming active heterodimeric

complexes following binding to cyclins, their regulatory subunits. CDK2, 4, and 6, and



possibly CDK3 cooperate to push cells through G1 into S phase. CDK4 and CDK6 form

complexes with cyclins D1, D2, and D3, and these complexes are involved in

completion of G1. Cyclin D–dependent kinases accumulate in response to mitogenic

signals and this leads to phosphorylation of the Rb protein. This process is completed

by the cyclin E1- and E2-CDK2 complexes. Once cells enter S phase, cyclin E is degraded

and A1 and A2 cyclins get involved by forming a complex with CDK2. There are a

number of regulators of CDK activities; where they act in the cell cycle is depicted in

Figure 2.13 (Ruddon, 2007).

Figure 2.13 - Restriction point control and the G1-S transition (from (Ruddon, 2007))

2.5.1 - CDK Inhibitors

The inhibitors of CDKs include the Cip/Kip and INK4 family of polypeptides. The

Cip/Kip family includes p21cip1, p27kip1, and p57kip2. The actions of these proteins

are complex. Although the Cip/Kip proteins can inhibit CDK2, they are also involved in

the sequestration of cyclin D-dependent kinases that facilitates cyclin E-CDK2

activation necessary for G1/S transition (Ruddon, 2007).

The INK4 proteins target the CDK4 and CDK6 kinases, sequester them into

binary CDKINK4 complexes, and liberate bound Cip/Kip proteins. This indirectly inhibits

cyclin E–CDK and promotes cell cycle arrest. The INK4-directed arrest of the cell cycle

in G1 keeps Rb in a hypophosphorylated state and represses the expression of S-phase

genes. Four INK4 proteins have been identified: p16INK4a, p15INK4b, p18INK4c, and



p19INK4d. INKA4a loss of function occurs in a variety of cancers including pancreatic

and small cell lung carcinomas and glioblastomas. INK4a fulfills the criteria of a tumor

suppressor and appears to be the INK4 family member with the most active role in this

regard. The INK4a gene encodes another tumor suppressor protein called ARF

(p14ARF). Mice with a disrupted ARF gene have a high propensity to develop tumors,

including sarcomas, lymphomas, carcinomas, and CNS tumors. These animals

frequently die at less than 15 months of age. ARF and p53 act in the same pathway to

insure growth arrest and apoptosis in response to abnormal mitogenic signals such as

myc-induced carcinogenesis, Figure 2.14 (Ruddon, 2007).

Figure 2.14 - Regulation of the Rho pathway and the cytoskeleton by cyclin-dependent kinase (CDK) inhibitors (from

(Besson, 2004))

2.5.2 - Cyclins

The originally discovered cyclins, cyclin A and B, identified in sea urchins, act at

different phases of the cell cycle. Cyclin A is first detected near the G1/S transition and



cyclin B is first synthesized during S phase and accumulates in complexes with p34cdc2

as cells approach the G2-to-M transition. Cyclin B is then abruptly degraded during

mitosis. Thus, cyclins A and B regulate S and M phase, but do not appear to play a role

in G1 control points such as the restriction point (R point), which is the point where key

factors have accumulated to commit cells to enter S phase (Ruddon, 2007).

Three more recently discovered mammalian cyclins, C, D1, and E, are the

cyclins that regulate the key G1 and G1/S transition points. Unlike cyclins A and B,

cyclins C, D1, and E are synthesized during the G1 phase in mammalian cells. Cyclin C

levels change only slightly during the cell cycle but peak in early G1. Cyclin E peaks at

the G1–S transition, suggesting that it controls entry into S. Three distinct cyclin D

forms, D1, 2, and 3, have been discovered and are differentially expressed in different

mouse cell lineages. These D cyclins all have human counterparts and cyclin D levels

are growth factor dependent in mammalian cells: when resting cells are stimulated by

growth factors, D-type cyclin levels rise earlier than cyclin E levels, implying that they

act earlier in G1 than E cyclins. Cyclin D levels drop rapidly when growth factors are

removed from the medium of cultured cells. All of these cyclins (C, D, and E) form

complexes with, and regulate the activity of various CDKs and these complexes control

the various G1, G1–S, and G2–M transition points, Figure 2.15 (Ruddon, 2007).

Interestingly, negative growth regulators also interact with the cyclin-CDK system. For

example, TGF-b1, which inhibits proliferation of epithelial cells by interfering with G1-S

transition, reduced the stable assembly of cyclin E-CDK2 complexes in mink lung

epithelial cells, and prevented the activation of CDK2 kinase activity and the

phosphorylation of Rb. This was one of the first pieces of data suggesting that the

mammalian G1 cyclin-dependent kinases are targets for negative regulators of the cell

cycle (Ruddon, 2007).

2.5.3 - Cell Cycle Checkpoints

The role of various CDKs, cyclins, and other gene products in regulating

checkpoints at G1 to S, G2 to M, and mitotic spindle segregation have been described in

detail previously. Alterations of one or more of these checkpoint controls occur in

most, if not all, human cancers at some stage in their progression to invasive cancer. A



key player in the G1–S checkpoint system is the retinoblastoma gene Rb (Ruddon,

2007).

Figure 2.15 - Cell-cycle regulation (from (Charles, 2004))

Phosphorylation of the Rb protein by cyclin D–dependent kinase releases Rb

from the transcriptional regulator E2F and activates E2F function. Inactivation of Rb by

genetic alterations occurs in retinoblastoma and is also observed in other human

cancers, for example, small cell lung carcinomas and osteogenic sarcomas (Ruddon,

2007).

The p53 gene product is an important cell cycle checkpoint regulator at both

the G1–S and G2–M checkpoints but does not appear to be important at the mitotic

spindle checkpoint because gene knockout of p53 does not alter mitosis. The p53

tumor suppressor gene is the most frequently mutated gene in human cancer,

indicating its important role in conservation of normal cell cycle progression. One of

p53’s essential roles is to arrest cells in G1 after genotoxic damage, to allow for DNA

repair prior to DNA replication and cell division. In response to massive DNA damage,

p53 triggers the apoptotic cell death pathway. Data from short-term cell-killing assays,

using normal and minimally transformed cells, have led to the conclusion that mutated

p53 protein confers resistance to genotoxic agents (Ruddon, 2007).

The spindle assembly checkpoint machinery involves genes called bub (budding

uninhibited by benomyl) and mad (mitotic arrest deficient). There are three bub genes

and three mad genes involved in the formation of this checkpoint complex. A protein



kinase called Mps1 also functions in this checkpoint function. The chromosomal

instability, leading to aneuploidy in many human cancers, appears to be due to

defective control of the spindle assembly checkpoint. Mutant alleles of the human

bub1 gene have been observed in colorectal tumors displaying aneuploidy. Mutations

in these spindle checkpoint genes may also result in increased sensitivity to drugs that

affect microtubule function because drug-treated cancer cells do not undergo mitotic

arrest and go on to die (Ruddon, 2007).

Maintaining the integrity of the genome is a crucial task of the cell cycle

checkpoints. Two checkpoint kinases, called Chk1 and Chk2 (also called Cds1), are

involved in checkpoint controls that affect a number of genes involved in maintenance

of genome integrity. Chk1 and Chk2 are activated by DNA damage and initiate a

number of cellular defense mechanisms that modulate DNA repair pathways and slow

down the cell division cycle to allow time for repair. If DNA is not successfully mended,

the damaged cells usually undergo cell death via apoptosis. This process prevents the

defective genome from extending its paternity into daughter cells (Ruddon, 2007).

Upstream elements activating the checkpoint signaling pathways such as those

turned on by irradiation or agents causing DNA double strand breaks include the ATM

kinase, a member of the phosphatidylinositol 3-kinase (PI3K) family, which activates

Chk2 and its relative ATR kinase that activates Chk1. There is also cross talk between

ATM and ATR that mediates these responses. Chk1 and Chk2 phosphorylate CDC25A

and C, which inactivate them. In its dephosporylated state CDC25A activates the CDK2-

cyclin E complex that promotes progression through S phase. It should be noted that

this is an example of dephosphorylation rather than phosphorylation activating a key

biological function. This is in contrast to most signal transduction pathways, where the

phosphorylated state of a protein (often a kinase) is the active state and the

dephosphorylated state is the inactive one. In addition, Chk1 renders CDC25A

unstable, which also diminishes its activity. CDC25A also binds to and activates CDK1-

cyclin B, which facilitates entry into mitosis. G2 arrest induced by DNA damage induces

CDC25A degradation and, in contrast, G2 arrest is lost when CDC25A is overexpressed.

A number of proteins are now known to act as mediators of checkpoint responses by

impinging on the Chk1 and 2 pathways. These include the BRCT domain–containing



proteins 53BP1, BRCA1, and MDC1.These proteins are involved in activation of Chk1

and Chk2 by acting through protein–protein interactions that modulate the activity of

these checkpoint kinases. In general, these modulators are thought to be tumor

suppressors (Ruddon, 2007).

Chk1 and 2 have overlapping roles in cell cycle regulation, but different roles during

development. Chk1 but not Chk2 is essential for mammalian development, as

evidenced by the early embryonic lethality of Chk1 knockout mice. Chk2-deficient mice

are viable and fertile and do not have a tumor-prone phenotype unless exposed to

carcinogens, and this effect is more evident later in life. As illustrated in Figure 2.16,

there are interactions between the Chk kinases and the p53 pathway. Chk2

phosphorylates threonine-18 or serine-20 on p53, which attenuates p53’s interaction

with its inhibitor MDM2, thus contributing to p53 stabilization and activation.

However, Chk2 and p53 only have partially overlapping roles in checkpoint regulation

because not all DNA-damaging events activate both pathways, Figure 2.16 (Ruddon,

2007).

2.5.4 - Cell Cycle Regulatory Factors as Targets for Anticancer Agents

The commonly observed defects in cell cycle regulatory pathways in cancer

cells distinguish them from normal cells and provide potential targets for therapeutic

agents. One approach is to inhibit cell cycle checkpoints in combination with DNA-

damaging drugs or irradiation. The rationale for this is that normal cells have a full

complement of checkpoint controls, whereas tumor cells are defective in one or more

of these and thus are more subject to undergoing apoptosis in response to excessive

DNA damage. This has been accomplished by combining ATM/ATR inhibitors such as

caffeine or Chk1 inhibitors in combination with DNA-damaging drugs. So far this

approach has not been demonstrated clinically, and indeed is somewhat counter

intuitive, since p53 mutant tumor cells are more resistant to many chemotherapeutic

drugs. p53 is a key player in causing cell death in drug treated, DNA-damaged cells

(one exception to that is the microtubule inhibitor paclitaxel), and active, unmutated

p53 is needed for this response (Ruddon, 2007).



Figure 2.16 - Simplified scheme of cell-cycle checkpoint pathways induced in response to DNA damage (here

DSBs), with highlighted tumor suppressors shown in red and proto-oncogenes shown in green (from (Kastan,

2004))

Another approach is to target the cyclin dependent kinases directly. Alteration

of the G1–S checkpoint occurs in many human cancers. Cyclin D1 gene amplification

occurs in a subset of breast, esophageal, bladder, lung, and squamous cell carcinomas.

Cyclins D2 and D3 are overexpressed in some colorectal carcinomas. In addition, the

cyclin D–associated kinases CDK4 and CDK6 are over expressed or mutated in some



cancers. Mutations or deletions in the CDK4 and CDK6 inhibitor INK4 have been

observed in familial melanomas, and in biliary tract, esophageal, pancreatic, head and

neck, non small cell lung, and ovarian carcinomas. Inactivating mutations of CDK4

inhibitory modulators p15, p16, and p18 have been observed in a wide variety of

human cancers. Cyclin E is also amplified and overexpressed in some breast and colon

carcinomas and leukemias (Ruddon, 2007).

Human cancers have a variety of mutations in cell cycle regulatory genes. This

includes overexpression of D1 and E1 cyclins and CDKs (mainly CDK4 and CDK6) as

noted above. Loss of CDK inhibitory functions (mainly INK4a and 4b and Kip1) also

occurs, as does loss of Rb, one of the first tumor suppressor genes identified. Loss of

Kip1 function and overexpression of cyclin E1 occur frequently and are associated with

poor prognosis in breast and ovarian cancers (Ruddon, 2007).

The mitogen-stimulated proliferation of cells is mediated via a retinoblastoma

(Rb) pathway that involves phosphorylation of Rb, its dissociation form and activation

of the E2F family of transcription factors, and subsequent turn-on of genes involved in

G1–S transition and DNA synthesis. Disruption of this pathway by overexpression of

cyclin D1, loss of the INK4 inhibitor p16, mutation of CDK4 to a p16-resistant form, or

loss or mutation of Rb is frequently seen in cancer cells. The activation of CDK

inhibitory factors such as p16INK4 or p27kip1 and inhibition of cyclin dependent

kinases are, therefore, potential ways to interdict the overactive cell proliferation

pathways in cancer cells. Thus, inhibition of cyclins D1 and E and CDKs, especially CDK4

and CDK6, could be targets for inhibiting growth of cancers. As more knowledge of the

complicated steps in cell cycle regulation is gained, more potential targets become

available (Ruddon, 2007).

2.6 - APOPTOSIS

Apoptosis (sometimes called programmed cell death) is a cell suicide

mechanism that enables multicellular organisms to regulate cell number in tissues and

to eliminate unneeded or aging cells as an organism develops. The biochemistry of

apoptosis has been well studied in recent years, and the mechanisms are now

reasonably well understood (Ruddon, 2007).



The apoptosis pathway involves a series of positive and negative regulators of

proteases called caspases, which cleave substrates, such as poly (ADP-ribose)

polymerase, actin and lamin. In addition, apoptosis is accompanied by the

intranucleosomal degradation of chromosomal DNA, producing the typical DNA ladder

seen for chromatin isolated from cells undergoing apoptosis. The endonuclease

responsible for this effect is called caspase-activated DNase, or CAD (Ruddon, 2007).

A number of ‘‘death receptors’’ have also been identified, they are cell surface

receptors that transmit apoptotic signals initiated by death ligands, Figure 2.17. The

death receptors sense signals that tell the cell that it is in an uncompromising

environment and needs to die. These receptors can activate the death caspases within

seconds of ligand binding and induce apoptosis within hours. Death receptors belong

to the tumor necrosis factor (TNF) receptor gene superfamily and have the typical

cystine rich extracellular domains and an additional cytoplasmic sequence termed the

death domain (Ruddon, 2007).

Figure 2.17 - Apoptosis signaling through death receptors (from (Frederik, 2002))



The best-characterized death receptors are CD95 (also called Fas or Apo1) and

TNF receptor TNFR1 (also called p55 or CD120a). The importance of the apoptotic

pathway in cancer progression is seen when there are mutations that alter the ability

of the cell to undergo apoptosis and allow transformed cells to keep proliferating

rather than die. Such genetic alterations include the translocation of the bcl-2 gene in

lymphomas that prevents apoptosis and promotes resistance to cytotoxic drugs. Other

genes involved as players on the apoptosis stage include c-myc, p53, c-fos, and the

gene for interleukin-1b-converting enzyme (ICE). Various oncogene products can

suppress apoptosis, like the adenovirus protein E1b, ras, and n-abl (Ruddon, 2007).

Mitochondria plays a pivotal role in the events of apoptosis by at least three

mechanisms:

1) Release of proteins, e.g., cytochrome c, that triggers activation of caspases;

2) Alteration of cellular redox potential;

3) Production and release of reactive oxygen species after mitochondrial

membrane damage.

Another mitochondrial link to apoptosis is implied by the fact that Bcl-2, the

anti-apoptotic factor, is a mitochondrial membrane protein that appears to regulate

mitochondrial ion channels and proton pumps, Figure 2.18 (Ruddon, 2007).

2.6.1 - Biochemical Mechanism of Apoptosis

Multicellular organisms, from the lowest to the highest species, must have a

way to get rid of excess cells or cells that are damaged in order for the organism to

survive. Apoptosis is the mechanism that they use to do this. It is the way that the

organism controls cell numbers and tissue size and protects itself from ‘‘rogue’’ cells.

A simplified version of the apoptotic pathways can be visualized in Figure 2.19

(Ruddon, 2007).



Figure 2.18 - Apoptosis signaling through mitochondria (from (Frederik, 2002))

The death receptor–mediated pathway is turned on by members of the death

receptor superfamily of receptors including Fas receptor (CD95) and TNF receptor 1,

which are activated by Fas ligand and TNF, respectively. Interaction of these ligands

with their receptors induces receptor clustering, binding of the receptor clusters to

Fas-associated death domain protein (FADD), and activation of caspase-8, Figure 2.20.

This activation step is regulated by c-FLIP. Caspase-8, in turn, activates caspase-3 and

other ‘‘executioner’’ caspases, which induce a number of apoptotic substrates. The

DNA damage–induced pathway invokes a mitochondrial-mediated cell death pathway

that involves pro-apoptotic factors like Bax (blocked by the anti-apoptotic protein Bcl-

2). This results in cytochrome c release from the mitochondria and triggering of

downstream effects facilitating caspase-3 activation, which is where the two pathways

intersect. There are both positive and negative regulators that also interact on these

pathways (Ruddon, 2007).



Figure 2.19 - The two main apoptotic signaling pathways (from (Frederik, 2002))

Figure 2.20 - Illustration of the main TNF receptor signaling pathways (from (Dash, 2003))



2.6.2 - Caspases

Caspases are a family of cysteine proteases that are activated specifically in

apoptotic cells. This family of proteases is highly conserved through evolution all the

way from hydra and nematodes up to humans. Over 12 caspases have been identified

and although most of them appear to function during apoptosis, the function of all of

them is not yet clear. The caspases are called cysteine-proteases because they have a

cysteine in the active site that cleaves substrates after asparagines in a sequence of

asp-X, with the four amino acids amino-terminal to the cleavage site determining a

caspase’s substrate specificity (Ruddon, 2007).

The importance of the caspases in apoptosis is demonstrated by the inhibitory

effects of mutation or drugs that inhibit their activity. Caspases can either inactivate a

protein substrate by cleaving it into an inactive form or activate a protein by cleaving a

pro-enzyme negative regulatory domain. In addition, caspases themselves are

synthesized as pro-enzymes and are activated by cleavage at asp-x sites. Thus, they can

be activated by other caspases, producing elements of the ‘‘caspase cascade’’ shown

in Figure 2.21.

Figure 2.21 – Caspase activation (from (Dash, 2003))



Also, as illustrated in Figure 2.21, caspases are activated in a number of steps

by proteolytic cleavage by an upstream caspase or by protein–protein interactions,

such as that seen for the activation of caspase-8 and the interaction of cytochrome c

and Apaf-1 in the activation of caspase-9. A number of important substrates of

caspases have been identified, including the caspase-activated DNase (CAD), noted

above, which is the nuclease responsible for the DNA ladder of cells undergoing

apoptosis. Activation of CAD is mediated by caspase-3 cleavage of the CAD-inhibitory

subunit. Caspase-mediated cleavage of other specific substrates has been shown to be

responsible for other typical changes seen in apoptotic cells, such as the cleavage of

nuclear lamins required for nuclear shrinkage and budding, loss of overall cell shape by

cleavage of cytoskeleton proteins, and cleavage of PAK2, a member of the p21-

activated kinase family, that mediates the blebbing seen in dying cells.

2.6.3 - Bcl-2 Family

Mammalian Bcl-2 was first identified as anti-apoptotic protein in lymphomas

cells. It turned out to be a homolog of an anti-apoptotic protein called Ced-9 described

in C. elegans and protects from cell death by binding to the pro-apoptotic factor Ced-4.

Similarly, in mammalian cells, Bcl-2 binds to a number of pro-apoptotic factors such as

Bax, Figure 2.22. One concept is that pro- and anti- apoptotic members of the Bcl-2

family of proteins form heterodimers, which can be looked on as reservoirs of plus and

minus apoptotic factors waiting for the appropriate signals to be released (Ruddon,

2007).

2.6.4 - Anoikis

Anoikis is a form of apoptosis that occurs in normal cells that lose their

adhesion to the substrate or extracellular matrix (ECM) on which they are growing.

Adherence to a matrix is crucial for the survival of epithelial, endothelial, and muscle

cells. Prevention of their adhesion usually results in rapid cell death, which occurs via

apoptosis. Thus, anoikis is a specialized form of apoptosis caused by prevention of cell

adhesion (Ruddon, 2007).



Figure 2.22 – Apoptotic pathways. Two major pathways lead to apoptosis: the intrinsic cell death pathway

controlled by Bcl-2 family members and the extrinsic cell death pathway controlled by death receptor signaling

(from (Zhang, 2005))

The term anoikis means ‘‘homelessness’’ in Greek and although the observation

of this phenomen occurs only with cultured cells, it is likely to occur also in vivo

because it is known that cell-cell and cell-ECM interactions are crucial to cell

proliferation, organ development, and maintenance of a differentiated state. This may

be a way that a multicellular organism protects itself from free-floating or wandering

cells (such as occurs in tumor metastasis). The basic rule for epithelial and endothelial

cells appears to be ‘‘attach or die’’. Interestedly, cells that normally circulate in the

body such as hematopoietic cells do not undergo anoikis (Ruddon, 2007).

Cell attachment is mediated by integrins, and ECM integrin interactions

transduce intracellular signaling pathways that activate genes involved in cell



proliferation and differentiation. Although the cell death pathways induced by

disruption of these cell attachment processes are not clearly worked out, cell

detachment–induced anoikis does result in activation of caspases-8 and -3 and is

inhibited by Bcl-2 and Bcl-XL, indicating some similarities to the typical apoptosis

mechanisms. In addition, integrin-ECM interaction activates focal adhesion kinase

(FAK) and attachment-mediated activation of PI3-kinase. Both of these steps protect

cells from anoikis, whereas inhibition of the PI3-kinase pathway induces anoikis

(Ruddon, 2007).

Disruption of cell-matrix interactions also turns on the JNK /p38 pathway, a

stress-activated protein kinase. The mitogen-activated kinase system may also be

involved, since caspase mediated cleavage of MEKK-1 occurs in cells undergoing

anoikis. As stated earlier, one of the hallmarks of malignantly transformed cells

growing in culture is their ability to grow in an anchorage independent manner,

whereas normal cells do not. Thus, cancer cells may develop resistance to anoikis. This

may be a way that metastatic cancer cells can survive in the bloodstream until they

seed out in a metastatic site (Ruddon, 2007).

2.7 - RESISTANCE TO APOPTOSIS IN CANCER AND POTENTIAL TARGETS FOR THERAPY

It would be a mistake to portray apoptosis as only a mechanism to kill cells

damaged by some exogenous insult such as DNA-damaging toxins, drugs, or

irradiation. Apoptosis is, in fact, a usual mechanism used by all multicellular organisms

to facilitate normal development, selection of differentiated cells that the organism

needs, and control of tissue size. For example, studies of nematodes (C. elegans), fruit

flies, and mice indicate that apoptotic-mediated mechanisms similar to those

described here are intrinsic and required for normal development. Dysfunction of

these pathway results in developmental abnormalities and disease states (Ruddon,

2007).

In the human, development of the immune system is perhaps the best example

of the role for apoptosis in normal development. In the immune system, apoptosis is a

fundamental process that regulates T- and B-cell proliferation and survival and is used

to eliminate immune cells that would potentially recognize and destroy host tissues



(‘‘anti-self ’’). Mechanisms involving Apo-1/FAS (CD95)-mediated signaling of the

caspase cascade are employed in lymphocytic cell selection. In the case of T

lymphocytes, pre-T cells are produced in the bone marrow and circulate to the thymus

where they differentiate and rearrange their T-cell receptors (TCRs). Those cells that

fail to rearrange appropriately their TCR genes, and thus cannot respond to self–major

histocompatibility complex (MHC)–peptide complexes, die by ‘‘neglect’’, Figure 2.23.

Those T cells that pass the TCR selection tests mature and leave the thymus to become

the adult peripheral T-cell pool. The mature T-cell pool thus passes through a number

of selection steps to ensure self-MHC restriction and self-tolerance. Apoptosis also is

used to delete mature peripheral T cells that are insufficiently stimulated by positive

growth signals, and this is a mechanism to downregulate, or terminate, an immune

response (Ruddon, 2007).

B lymphocytes undergo selection and maturation in the bone marrow and

germinal centers of the spleen and other secondary lymphoid organs. Those with low

antigen affinity or those autoreactive are eliminated by apoptosis. Those that pass this

test mature into memory B cells and long-lived plasma cells. The ability of lymphoid

progeny cells to avoid apoptosis may lead to lymphatic leukemias or lymphomas. In

addition, cancers develop multiple mechanisms to evade destruction by the immune

system such as a decreased expression of MHC molecules on cancer cell surfaces and

production of immunosuppressive cytokines. Several cell proliferations promoting

events take place in cancer cells as they evolve over time into growth dysregulated,

invasive, metastatic cell types. These events include activation of proliferation-

promoting oncogenes such as ras and myc, overexpression of cell cycle regulatory

factors such as cyclin D, increased telomerase to overcome cell senescence, and

increased angiogenesis to enhance blood supply to tumor tissue (Ruddon, 2007).

The cancer-related alterations in the apoptotic pathway provide a number of

cancer chemotherapeutic targets.



Figure 2.23 - The role of apoptosis in the development and function of T lymphocytes. Major pro-apoptotic and anti-

apoptotic signals/molecules (from (Zhang, 2005))

2.8 - SUMMARY

At the end of this chapter is possible to conclude that many of the controls that

govern the transition between quiescence and active cell cycling in mammals operate

in G1 phase. Loss of R point control appears to be a common, possibly even universal

step in tumor development, and a number of genetic lesions that can contribute to this

deregulation have been identified.

Loss of survival proteins can also contribute to apoptosis. The antiapoptotic

gene, BCL2, has been shown to be repressed by p53 and, therefore, contributes to

apoptosis by blocking survival signals mediated by BCL2. The choice as to whether a

cell undergoes apoptosis or cell cycle arrest and DNA repair depends on a number of

factors. Some may be independent of p53 such as extracellular survival factors, the

existence of oncogenic alterations and the availability of additional transcription

factors. However, the extent of DNA damage may also contribute to the choice by

affecting the level of activity of p53 induced. Activation of apoptosis has been

associated with higher levels of p53 than those required for cell cycle arrest which may

reflect a lower affinity of cell cycle arrest target gene promoters for p53. In addition,

the type of cell may affect the response to p53. Importantly, it is vital to identify why

transformed cells die in response to p53, whereas normal cells undergo cell cycle



arrest and DNA repair as this may be of great potential for the development of cancer

therapies (Macdonald, 2005).

This loss of cell cycle check point control by cancer cells may contribute to their

increased susceptibility to anticancer drugs. Normal cells have mechanisms to protect

themselves from exposure to growth-limiting conditions or toxic agents by calling on

these check point control mechanisms. Cancer cells, by contrast, can continue through

these checkpoints into cell cycle phases that make them more susceptible to the

cytotoxic effects of drugs or irradiation (Ruddon, 2007).

Apoptosis occurs in most, if not all, solid cancers. Ischemia, infiltration of

cytotoxic lymphocytes, and release of TNF may all play a role in this and it would be

therapeutically advantageous to tip the balance in favor of apoptosis over mitosis in

tumors, if that could be done.

Clearly, a number of anticancer drugs induce apoptosis in cancer cells but the

problem is that they usually do this in normal proliferating cells as well. Therefore, the

goal should be to manipulate selectively the genes involved in inducing apoptosis in

tumor cells, although understanding how those genes work may go a long way to

achieving this goal.

CHAPTER III

CANCER CELL

CHAPTER III – CANCER CELL


3.1 - INTRODUCTION

Cancer is an abnormal growth of cells caused by multiple changes in gene

expression leading to dysregulated balance of cell proliferation and cell death and,

ultimately evolving into a population of cells that can invade tissues and metastasize to

distant sites, causing significant morbidity and, if untreated, death of the host

(Ruddon, 2007).

Cancer is a group of diseases of higher multicellular organisms. It is

characterized by alterations in the expression of multiple genes, leading to

dysregulation of the normal cellular program for cell division and cell differentiation.

This results in an imbalance of cell replication and cell death that favors growth of a

tumor cell population (Ruddon, 2007).

The characteristics that delineate a malignant cancer from a benign tumor are

the abilities to invade locally, to spread to regional lymph nodes, and to metastasize to

distant organs in the body (Ruddon, 2007).

Cancer cells contain many alterations which accumulate as tumors develop.

Over the last 25 years, considerable information has been gathered on the regulation

of cell growth and proliferation leading to the identification of the proto-oncogenes

and the tumor suppressor genes. The proto-oncogenes encode proteins which are

important in the control of cell proliferation, differentiation, cell cycle control and

apoptosis (MacDonald, 2005).

Mutations in these genes act dominantly and lead to a gain in function. In

contrast the tumor suppressor genes inhibit cell proliferation by arresting progression

through the cell cycle and block differentiation. They are recessive at the level of the

cell although they show a dominant mode of inheritance. In addition, other genes are

also important in the development of tumors. Mutations leading to increased genomic

instability suggest defects in mismatch and excision repair pathways. Genes involved in

DNA repair, when mutated, also predispose the patient to developing cancer, as

described in chapter 3 (MacDonald, 2005).

In this chapter is held a description of the tumor cell; the types of cancers;

ongoing research and treatments; tissue changes upon stimuli; tumor angiogenesis;

benign and malignant cell characteristics and the process of metastasis.



The description of the tumor cell is important in this work since then, in my

thesis, I will focus on studies of cancer cells.

This chapter and the chapters three and four complement each other,

describing the steps for the formation of a tumor cell, the changes in the cell cycle and

finally the role of radiation in killing/give rise to cancer cells.

3.2 – CANCER CELL

In normal cell growth there is a finely controlled balance between growth-

promoting and growth-restraining signals such that proliferation occurs only when

required. The balance is tilted when increased cell numbers are required, for example

during wound healing and during normal tissue turnover. Differentiation of cells during

this process occurs in an ordered manner and proliferation ceases when no longer

required. In tumor cells this process is disrupted, continued cell proliferation occurs

and loss of differentiation may be found (MacDonald, 2005).

In addition the normal process of programmed cell death may no longer

operate and cancers arise from a single cell which has undergone mutation. Gene

mutations give the cell increased growth advantages compared to others and allow

them to escape normal controls on proliferation. The initial mutation will cause cells to

divide to produce a genetically homogeneous clone. In turn, additional mutations

occurs which further enhance the cells’ growth potential. These mutations give rise to

subclones within the tumor each with differing properties so that most tumors are

heterogeneous (MacDonald, 2005).

Tumors can be divided into two main groups, benign or malignant. Benign

tumors are rarely life threatening, grow within a well-defined capsule which limits their

size and maintain the characteristics of the cell of origin and are thus usually well

differentiated. Malignant tumors invade surrounding tissues and spread to different

areas of the body to generate further growths or metastases. It is this process which is

often the most life threatening. Different clones within a tumor will have differing

abilities to metastasize, a property which is genetically determined. The process of



metastasis is likely to involve several different steps and only a few clones within a

tumor will have all of these properties (MacDonald, 2005).

Tumor cells show a number of features which differentiate them from normal

cells: (1) They are no longer as dependent on growth factors as normal cells either

because they are capable of secreting their own growth factors to stimulate their own

proliferation, a process termed autocrine stimulation, or because growth factor

receptors on the surface are altered in such a way that binding of growth factors is no

longer necessary to stimulate proliferation; (2) normal cells require contact with the

surface in the extracellular environment to be able to grow whereas tumor cells are

anchorage independent; (3) normal cells respond to the presence of other cells, and in

culture will form a monolayer due to contact inhibition, whereas tumor cells lack this

and often grow over or under each other; (4) tumor cells are less adhesive than normal

cells; (5) normal cells stop proliferating once they reach a certain density but tumor

cells continue to proliferate (MacDonald, 2005).

In the most basic sense, cancer is the abnormal, uncontrolled growth of

previously normal cells. The transformation of a cell results from alterations to its DNA

that accumulates over time. The change in the genetic information causes a cell to no

longer carry out its functions properly. A primary characteristic of cancer cells is their

ability to rapidly divide, and the resulting accumulation of cancer cells is termed a

tumor. As the tumor grows and if it does not invade the surrounding tissues, it is

referred to as being benign (Figure 3.1a). If, however, the tumor has spread to nearby

or distant tissues then it is classified as malignant (Figure 3.1b) (Almeida, 2010).

Metastasis is the breaking free of cancer cells from the original primary tumor

and their migration to either local or distant locations in the body where they will

divide and form secondary tumors (Almeida, 2010).



Figure 3.1 – Benign vs. malignant cancers. (a) Benign tumor (b) Malignant tumor (from Almeida, 2010).

3.2.1 - Types of cancer

Cancer is not a single disease; there are over 100 identified types, all with

different causes and symptoms. To distinguish one form from another the cancers are

named according to the part of the body in which they originate. Some tumors are

identified to reflect the type of tissues they arise from, with the suffix -oma, meaning

tumor, added on. For example, myelos- is a Greek term for marrow. Thus, myeloma is

a tumor of the bone marrow, whereas hepatoma is liver cancer (hepato- = liver), and

melanoma is a cancer of melanocytes, cells found primarily in the skin that produce

the pigment melanin (Almeida, 2010).

The four major types of cancer are carcinomas, sarcomas, leukemias, and

lymphomas. Approximately 90% of human cancers are carcinomas, which arise in the

skin or epithelium (outer lining of cells) of the internal organs, glands, and body

cavities. Tissues that commonly give rise to carcinomas are breast, colorectal, lung,

prostate, and skin (Almeida, 2010). In my thesis I will study, in term of image

processing, adenocarcinomas of the prostate and breast before and after irradiation of

the cells (Figure 3.2).



Figure 3.2 – Adenocarcinoma of the prostate (from IPO Porto, radiobiology department).

Sarcomas are less common than carcinomas and involve the transformation of

cells in connective tissue such as cartilage, bone, muscle, or fat. There are a variety of

sarcoma subtypes and they can develop in any part of the body, but most often arise in

the arms or legs. Liposarcoma is a malignant tumor of fat tissue (lipo- = fat) whereas a

sarcoma that originates in the bone is called osteosarcoma (osteo- = bone). Certain

forms of cancer do not form solid tumors. For example, leukemias are cancers of the

bone marrow, which leads to the overproduction and early release of immature

leukocytes (white blood cells). Lymphomas are cancers of the lymphatic system. This

system, which is a component of the body’s immune defense, consisting of lymph,

lymph vessels, and lymph nodes, serves as a filtering system for the blood and tissues

(Almeida, 2010).

3.2.2 – The uniqueness of cancer

While there are certain commonalities shared by cancers of a particular type,

each may be unique to a single individual. This is because of different cellular

mutations that are possible, and can depend on whether the disease is detected at an



early or advanced stage. As a result, two women diagnosed with breast cancer may or

may not receive the same treatment (Almeida, 2010).

The impact of the disease on the individual, as well as the final outcome of the

disease, is unique in every case. Still, several types of cancers can have a similar set of

symptoms, which may be shared with several other conditions, making screening,

detection, and diagnosis a complex problem. A tumor can impact the function of the

tissue in which it resides or those in the surrounding areas. Tumors provide no useful

function themselves and may be considered “parasites”, with every step of their

advance being at the expense of healthy tissue. While most types of cancers form

tumors, many do not form discrete masses. As previously stated, leukemia is a cancer

of the blood that does not produce a tumor, but rather rapidly produces abnormal

blood cells in the bone marrow at the expense of normal blood cells (Almeida, 2010).

3.2.3 - The development of tumors

All tumors begin with mutations (changes) that accumulate in the DNA (genetic

information) of a single cell causing it and its offspring to function abnormally. DNA

alterations can be sporadic or inherited. Sporadic mutations occur spontaneously

during the lifespan of a cell for a number of reasons: a consequence of a mistake made

when a cell copies its DNA prior to dividing, the incorrect repair of a damaged DNA

molecule, or chemical modification of the DNA, each of which interferes with

expression of the genetic information. Inherited mutations are present in the DNA

contributed by the sperm and/or egg at the moment of conception. To date, 90–95%

of diagnosed cancers appear to be sporadic in nature and thus have no heredity basis.

Whether the mutations that result in a cancer are sporadic or inherited, certain genes

are altered that negatively affect the function of the cells (Almeida, 2010).

3.2.4 – Genetic influence on tumors

A link between a particular genetic mutation and one or more types of cancers

is made by analyzing and comparing the DNA of malignant tissue samples obtained



from patients and members of families with a high incidence of a particular cancer and

comparing it to the DNA from healthy individuals. For example, a study could be

conducted in which the DNA isolated from tumor cells obtained from liver cancer

patients is analyzed and determined to possess certain versions of genes whereas

different versions of those same genes are present in the DNA of liver cells of healthy

persons. An association could then be drawn between the “bad” versions of those

genes and liver cancer (Almeida, 2010).

This type of analysis has been crucial in identifying certain versions of genes

associated with a predisposition for the development of particular forms of cancer. For

example, studies have demonstrated that there is an elevated risk of breast or ovarian

cancer associated with certain versions of the BRCA1 and/or BRCA2 genes. Another

example is retinoblastoma, a rare tumor of the eye typically found in infants and young

children, which is associated with alterations within the Rb gene (Almeida, 2010).

3.3 – CANCER THROUGH THE AGES

Although not specifically identified as such, cancer has been known for many

centuries. In fact, there is evidence of tumors in the bones of five thousand year old

mummies from Egypt and Peru. The disease itself was not very common, nor explored

or understood, because in ancient times fatal infectious diseases resulted in shorter

lifespan. Given that the vast majority of cancers are sporadic, there was less

opportunity for the accumulation of the mutations necessary to transform normal cells

into cancerous ones (Almeida, 2010).

The word “cancer” was first introduced by Hippocrates (460–370 BC), the Greek

physician and “father of medicine”. He coined the term carcinoma, from the Greek

word karcinos, meaning “crab,” when describing tumors. This is because tumors often

have a central cell mass with extensions radiating outward that mimic the shape of the

shellfish (Figure 3.3) (Almeida, 2010).



Figure 3.3 – Cancer cell (from Almeida, 2010).

3.3.1 – Early discovery of carcinogens

Also published in 1761 was a paper by John Hill, an English physician. In it he

made the first causal link between substances in the environment and cancer when he

described a relationship between tobacco snuff and nasal cancer. This brought about

the awareness of carcinogens (chemical agents that have been demonstrated to cause

cancer). In 1775, the English surgeon Sir Percivall Pott observed and noted a high rate

of scrotal cancer among chimney sweepers. He postulated that it was caused by long-

term exposure to the chemicals in the soot-soaked ropes worn as harnesses. His

research led to studies that associated particular occupations with an increased risk of

developing specific forms of cancer – the forerunner to the field of public health and

cancer (Almeida, 2010).

3.3.2 – The use of microscopes demonstrated changes at a cellular level

The development of improved microscopes in the late nineteenth century

allowed for more thorough examinations of cells and their activities than was

previously possible. It was realized that cancer cells were different in both appearance

and behavior from normal cells within the same tissue or organ (Figure 3.4). Early

twentieth century accomplishments in the development of cell culture, new and

improved diagnostic techniques, the discovery of chemical carcinogens, and the use of



chemotherapy (powerful anticancer drugs) all had significant impacts upon the

understanding and treatment of cancer (Almeida, 2010).

Figure 3.4 – (a) Note the abundance of the thin, sheet-like extensions from the cell bodies of the healthy cells. (b) Note the rounded appearance of the cancer cells (from Almeida, 2010).

3.4 – MODERN DAY RESEARCH AND TREATMENT

The radioactive element radium, isolated by Marie and Pierre Curie in 1898,

was found to be effective in the treatment of tumors in 1903. While both healthy and

cancerous cells are susceptible to the damage caused by X-rays, cancer cells are

inherently less able to repair the damage and recover. Once safe dosage levels were

determined, radiation therapy became a standard form of treatment for many cancers

(Almeida, 2010).

Tumor formation, growth, and metastasis reflect that the regulation of the cell

cycle is critical in maintaining the structural and functional integrity of all tissues. The

inability to control passage of a cell through each of the cycle checkpoints can result in

unwanted growth within a tissue. The growth not only can disrupt the function of that

tissue but also of those nearby. The situation becomes much more serious if cells

break free from the tumor and travel to other tissues where they may take up

residence, multiply, and create additional problems (Almeida, 2010).

3.5 – TISSUES CHANGES IN RESPONSE TO STIMULI

Our cells experience many different types of chemical and physical stimuli on

an almost constant basis. For example, our cells are exposed to both beneficial and



harmful chemicals in the air, food, and water we take into our bodies, hormones

surging through our bloodstreams relaying messages to the cells to which they bind,

and stresses and strains are applied when we move heavy objects. The type and

strength of the stimuli cells receive or are subjected to affect the structural and

functional changes they will undergo. The cellular changes that occur in response to

stimuli are an indication of both the susceptibility to signals and the adaptability that

cells exhibit in response to changes in their environment (Almeida, 2010).

It is logical to expect that if a certain stimulus causes a cell to change in a

particular way, then the cell should revert back to its original condition upon removal

of the stimulus. The transformation that cells in a tumor have undergone is often the

result of changes brought about by certain stimuli. A unique aspect of tumor cells is

that the cellular changes remain even after the stimulus that led to their

transformation is no longer present (Almeida, 2010).

3.5.1 - Metaplasia

Epithelial cells that line certain portions of the respiratory tract are known to

undergo changes in appearance and function when exposed to noxious chemicals in

the air. The pathway of air through the respiratory tract begins in the nose or back of

the throat and travels down through the trachea or windpipe, the tube that leads from

the back of the throat to the lungs (Figure 3.5). The base of the trachea branches to

form two bronchi, one going to each of the lungs, which then progressively branch into

many smaller tubes called bronchioles that spread to all areas of the lungs. At the ends

of the bronchioles are tiny balloon-like sacs called alveoli where gas exchange between

the area and bloodstream occurs. The surface layer of the trachea, bronchi and some

of the bronchioles consists of pseudostratified columnar epithelial cells (Figure 3.6)

(Almeida, 2010).

These cells are somewhat rectangular in shape and aligned side by side in a

single layer. The term pseudostratified comes from the fact that there appears to be

more than one layer of cells present (pseudo- = false; stratified = layered) because the



position of the nuclei in adjacent cells alternates from being centrally located to being

at the bottom of the cell(Almeida, 2010).

Figure 3.5 – Respiratory system (from Almeida, 2010).

Figure 3.6 – Pseudostratified columnar epithelium (from Almeida, 2010).

The respiratory epithelium serves a protective function. Among the columnar

cells are specialized goblet cells that secrete thick, sticky mucus that coats the

epithelium. The sticky mucus traps particulate matter in the air, such as dust and

microorganisms, preventing it from getting deeper into the lungs. The exposed surface

of a columnar epithelial cell possesses cilia, short hair like structures that beat back



and forth to sweep the mucus and anything trapped in it upward to the back of the

throat. The material brought up by the so-called ciliary escalator can be either

swallowed and destroyed in the highly acidic environment of the stomach or

expectorated (spat out) (Almeida, 2010).

Smoke is a mixture of many different types of chemicals, liquids, and solids and

is an irritant of the respiratory epithelium. Over time, smoke paralyzes the cilia of the

respiratory epithelium, allowing mucus to build up in the airways and material to travel

deeper into the lungs. Also observed in tobacco smokers is the replacement of

pseudostratified columnar epithelium with stratified squamous epithelium (Figure 3.6).

The multiple layers of flattened cells in this form of epithelium protect underlying

tissues against abrasion. The cells in the outer layers are regularly sloughed off and

replaced by the replication of the cells in the lower layers. Stratified squamous

epithelium is normally present in the outer layer of skin and the inner lining of the

digestive tract, but not in the respiratory tract (Almeida, 2010).

The previously described condition is often exhibited in the airways of smokers.

It is an example of metaplasia, which is the change of mature and differentiated cells

from one normal cell type to another normal cell type. It is important to note that

what is abnormal about metaplastic tissue when observed under the microscope is not

the presence of abnormal cells, but rather the presence of a type of cell that is

normally found in other types of tissue. The stratified squamous epithelium that may

be present along the airway of a smoker can have a normal appearance (Almeida,

2010).

The problem is that it should not be present in that location. Metaplasia is not a

normal process that cells undergo; there must be an inciting stimulus that triggers the

structural and functional changes that occur. A typical characteristic of metaplasia is

that it is reversible – when the signal that initiated the changes is no longer present,

healthy cells should revert back to their original form. A concern arises when the

inciting stimulus that resulted in the metaplastic changes is no longer present, yet the

cells do not revert back to their normal structure and function. In some cases, the

permanent alterations are the result of genetic mutations that have negatively



affected oncogenes and tumor suppressor genes. These types of cellular mutations

certainly enhance the likelihood that cells will become cancerous (Almeida, 2010).

3.5.2 - Hypertrophy and hyperplasia

Metaplasia is not a form of growth, which means either an increase in

individual cell size or an increase in the number of cells. The purpose of the majority of

new growth that occurs between conception and adulthood is to form the variety of

differentiated body tissues. In adults, tissues are mature in their size, structure, and

function, and the primary role of cell division is the replacement of those cells that

have either died of old age, are lost due to abrasion (occurs to outer layer of skin and

inner lining of the digestive tract), or are damaged beyond repair (Almeida, 2010).

There are, however, times when growth does occur in adults. For example, the

goal of resistance or weight training is the growth of muscle tissue. A muscle is

composed of individual muscle cells known as muscle fibers, and each fiber contains

bundles of particular proteins that are responsible for contraction and relaxation. The

lifting of heavy weights damages the protein bundles. During the recovery or repair

period, the cells destroy and replace the damaged proteins. The cells, in an attempt to

be stronger and prevent similar damage from occurring again, increase the number of

protein bundles. This form of growth, which is due to an increase in size but not

number, is known as hypertrophy (Figure 3.7a) (Almeida, 2010).

Similar to metaplasia, hypertrophic growth occurs in response to an inciting

stimulus and is reversed when that stimulus is no longer present. When resistance

training is stopped, there will be a loss in muscle size and tone since there is no longer

a need to maintain the greater number of protein bundles. Another example of growth

that occurs in adulthood is the increase in breast size that occurs during pregnancy.

This form of growth is known as hyperplasia and is the result of an increase in the

number of cells in a tissue (Figure 3.7b). The combinations and levels of hormones

produced during pregnancy act as an inciting signal for the cells of the breast’s

mammary tissue to progress through the cell cycle and divide. This growth results in

the development of mammary glands and ducts that produce milk to nourish the



newborn child. A mother will continue to lactate (produce milk) for as long as the child

breast feeds (Almeida, 2010).

When a woman stops breast feeding, there is an absence of the inciting stimuli

(i.e., pregnancy hormones and infant suckling) that led to the development, activity,

and maintenance of the mammary tissues. The result is that the cells formed in

response to the stimuli now undergo apoptosis, effectively reverting the tissue to its

original state. Hyperplastic growth can also occur in the absence of proper stimuli. This

occurs when there is a loss of regulation at the checkpoints of the cell cycle. The most

common cause for a loss of cell cycle regulation is an accumulation of gain-of-function

mutations within proto-oncogenes, converting them into oncogenes, and/or loss-of-

function mutations in tumor suppressor genes. Mutations in caretaker tumor

suppressor genes may cause structural and functional changes that do not allow cells

to interact with one another in an organized fashion (Almeida, 2010).

3.5.3 - Dysplasia

A Pap test is often part of a woman’s routine gynecological exam. The test

entails obtaining cells from the inner surface of the cervix and the lower portion of the

uterus, followed by their examination under a microscope. Less than 5% of Pap tests

display dysplasia, a disorganized arrangement of cells, which is typically reported as

mild, moderate, or severe (Figure 3.7c). Mild cases often clear up on their own and are

typically followed up with repeat Pap tests every 3–6 months. Moderate and severe

cases require the use of treatment methods to remove the abnormal cells. The stimuli

that result in cervical dysplasia, which is most common in women between 25 and 35

years of age, are unknown, although women who are infected with the human

papilloma virus have an increased risk of exhibiting the condition (Almeida, 2010).

Dysplasia is an indication that the cells are not functioning properly, and is

considered a pre-cancerous condition. The risk associated with dysplasia is the

potential for the cells to progress to a state of neoplasia. A neoplastic growth has, in

addition to a disorganized arrangement of cells, a larger than normal number of cells

capable of dividing (Figure 3.7d) (Almeida, 2010).



Figure 3.7 – Types of tissue growth (from Almeida, 2010).

A neoplasm is also known as a cancer or tumor because its growth is the result

of disruptions to the normal regulation of the cell cycle resulting in uncontrolled

progression through the cell cycle and cell division (Almeida, 2010).

3.6 – FEEDING TUMOR GROWTH BY ANGIOGENESIS

The formation of new blood vessels, a process known as angiogenesis (angio =

blood and lymph vessel; genesis = production), first occurs during embryonic

development and continues until early adulthood. Expansion of a blood supply is the

result of the division and proliferation of the cells of the blood vessels currently in a

tissue. Therefore, it is a form of growth. As mentioned previously, growth of new

tissue is not a regular occurrence in adults but typically occurs only during the repair of

injured tissue (Almeida, 2010).

Similar to the way that the cell cycle is regulated by balancing a set of opposing

signals from the activities of protooncogenic and tumor suppressor proteins,



angiogenesis is under the control of competing signals from many activator and

inhibitor molecules. To date, there are more than two dozen proteins and small

molecules that have been identified as angiogenic activators and inhibitors. In adults,

the concentration of angiogenic inhibitors is higher than that of activators, thus

restricting angiogenesis. A shift in the balance so that the concentration of the

activators is higher than that of the inhibitors will have an opposite effect and result in

the formation of new blood vessels (Almeida, 2010).

Capillaries, the smallest blood vessels, are abundant in tissues to ensure that

the nearby cells are provided with a continuous supply of essential nutrients and a way

to remove the metabolic waste products. New tissue growth without a concomitant

expansion of the blood supply is limited to 1–2 mm3 in size, which is approximately the

size of the head of a pin. Tumors are able to exceed that growth limit by stimulating

angiogenesis. In an attempt to support growth, tumor cells may secrete the potent

angiogenic activator vascular endothelial growth factor (VEGF; vascular = pertaining to

vessels) (Figure 3.8a). This protein diffuses to the endothelial cells of a nearby blood

vessel. The binding of VEGF to the appropriate receptors in the outer membranes of

endothelial cells initiates a signal transduction cascade within the cells that results in

changes in gene expression and cell function. For example, the expression of proto-

oncogenes is enhanced while that of tumor suppressor genes is inhibited so that the

cells will progress through the cell cycle and divide (Almeida, 2010).

As the endothelial cells divide, they will form a bud that protrudes from the

blood vessel wall into the surrounding tissue (Figure 3.8b). As the number of

endothelial cells increases, the bud elongates and the endothelial cells produce matrix

metalloproteinases (MMPs). MMPs are enzymes that breakdown the extracellular

matrix proteins to enable the growing blood vessel to migrate between the tissue cells

toward the cancer cells. Once established, a tumor’s blood supply will grow along with

the tumor, nourishing it and removing its wastes (Figure 3.8c). Angiostatin and

endostatin are two angiogenic inhibitors that have been used in extensive animal

studies and human trials. Tests conducted with mice have indicated that the treatment

of tumors with angiogenic inhibitors are effective at inhibiting their growth and can

limit the number of secondary tumors that may form (Almeida, 2010).



Figure 3.8 – Tumor angiogenesis. (a) Cancer cells secrete vascular endothelial growth factor (VEGF), an angiogenic

activator, which binds to VEGF receptors on endothelial cells of a capillary causing a change in gene expression

within the endothelial cells of the capillary. In response to VEGF signaling an endothelial cell will divide and secrete

matrix metalloproteinases (MMPs). (b) Many rounds of endothelial cell division produce a bud off of a capillary that

grows and forms additional branches. (c) Endothelial cell growth toward a tumor supports its growth (from Almeida,

2010).

3.7 – CHARACTERISTICS OF BENIGN AND MALIGNANT TUMORS

Neoplasms are classified into two broad categories, benign and malignant. The

classification of a tumor is most often done by a pathologist, a physician who

specializes in interpreting and diagnosing changes in bodily fluids and tissues that

occur in response to disease. The assessment of a neoplastic growth is based on a

biopsy (bio- = life; -opsy = look or appearance), a macro- and microscopic examination

of either a portion of or an entire tumor that has been surgically removed. Microscopic



analysis provides a number of distinguishing features that are key to differentiating

between benign and malignant tissue (Almeida, 2010).

A benign tumor is noncancerous and classified as in situ, or contained solely

within the tissue in which it originated; the abnormal cells have not spread to

surrounding tissues or other areas of the body. In fact, there is typically a well-defined

border between a benign neoplastic growth and normal tissue. Benign neoplastic

growths are usually slow growing and although they are generally not life-threatening,

they can become dangerous based on their location and whether or not their growth

disrupts or interferes with normal healthy tissue functions. Their self-contained nature

is an added benefit that often allows the entire tumor to be surgically removed, unless

it is in an inoperable position, such as within an organ rather than on the surface or

adjacent to major blood vessels or the spinal cord (Almeida, 2010).

A concern with benign growths is that they can progress into the far more

serious malignant or cancerous neoplasms. Principal among the distinguishing features

of malignant tumors is that they are not contained solely within the tissue in which

they originally developed. This means that a portion of the tumor has grown into one

or more of the surrounding tissues or has spread to a distant location in the body.

Metastasis, the process by which malignant cells travel from the original (primary)

tumor to other (secondary) sites in the body, is often accomplished through the use of

either the circulatory or lymphatic systems (Figure 3.9) (Almeida, 2010).

Normal tissues consist of differentiated cells performing specific functions.

Malignant tissue typically exhibits anaplasia, the presence of undifferentiated cells that

bear no resemblance to the cells normally found in that location. The presence of

undifferentiated cells is a reflection of what is normally present during embryonic and

fetal development when tissues are going through their formative stages. Since

undifferentiated cells are involved in tissue formation they divide frequently. As a

result, malignant tissues often exhibit a high mitotic index, the ratio between the

number of cells undergoing mitosis and the total number of cells within the field of

view. This accounts for the faster growth rate of malignant tumors. Malignant tumors

are considered life-threatening because of the rapid growth and production of



undifferentiated cells that are invasive and disruptive to the structure and function of

surrounding tissues. In addition, the anaplastic nature of malignant cells is an

important factor in the likelihood that they will metastasize and wreak similar havoc

on other locations in the body. Surgery alone is not a sufficient form of treatment for

malignant tumors because of the possibility that some of the cells have spread to

locations throughout the body. Chemotherapy, the use of toxic drugs, is a more

systemic form of treatment used to target the destruction of undetectable metastatic

cancer cells in an attempt to prevent the growth and formation of new tumors

(Almeida, 2010).

Figure 3.9 – Metastasis. (a) Neoplastic cells grow, (b) produce proteases that breakdown the basement membrane,

and then invade the surrounding tissue. (c) Malignant cells can gain access to the circulatory or lymphatic system,

and then (d) exit and take up residence elsewhere in the body. (from Almeida, 2010).



3.8 – EVENTS THAT OCCUR DURING THE PROCESS OF METASTASIS

The structural and functional changes that occur to the cells within a tumor can

be a consequence of external growth factor signals and/or mutations to DNA. It is

common for tumors, particularly those that are malignant, to exhibit tumor

progression – the cells mutate independently of one another as they grow, thereby

generating a collection of genetically different subpopulations. The genetic differences

between cells result in their unique growth and metastatic potentials (Figure 3.10). It is

only the more potent cells that are likely to have the ability to invade the surrounding

tissues, gain access to the circulatory or lymphatic systems, travel to and invade a

tissue in a new location in the body, proliferate, stimulate angiogenesis, and form a

secondary tumor (Almeida, 2010).

Figure 3.10 – Tumor progression (from Almeida, 2010).

3.8.1 - Characteristics of metastatic cells

Approximately 90% of all human cancers are carcinomas, which mean that

epithelial cells have undergone a neoplastic transformation. All epithelial tissue is

attached to a basement membrane, a upporting layer of extracellular material

composed of a variety of glycoproteins (proteins with sugars bound to them) and

carbohydrates (Figure 3.11). The membrane provides a defining boundary between the



epithelium and an underlying layer of connective tissue. In order for cells within a

carcinoma to invade surrounding tissue, they must be able to maneuver between

other cells of that tissue and among the extracellular matrix, as well as degrade the

basement membrane (Figure 3.9). These functions are the result of specific cellular

changes that occur during the malignant transformation and tumor progression

processes. Certain cells develop the ability to secrete proteases, the enzymes that

destroy the proteins involved in cell-to-cell and cell-to-extracellular matrix connections

as well as those of the basement membrane (Almeida, 2010).

Figure 3.11 – Basement membrane of epithelium (from Almeida, 2010).

Associated with the fixed location most cells in the body have within tissues is

an absolute requirement for anchorage dependence – they adhere themselves to

neighboring cells and the extracellular matrix. Red and white blood cells are the

exception to the rule since they circulate freely in the blood stream. The ability to

migrate through tissues depends on having a reduced need to be anchored. Malignant

cells that encounter and gain entrance to capillaries and lymphatic vessels by migrating

between their outer layer of endothelial cells can be carried to secondary tissue sites

(Figure 3.9d) (Almeida, 2010).

3.9 – SUMMARY

At the end of this chapter is possible to conclude that a neoplasm can be either

malignant, able to spread and become worse, or benign, not inclined to spread and not

likely to become worse. Although benign tumors are usually less dangerous than



malignant tumors, they can cause problems. As a benign tumor enlarges, it can

compress surrounding tissues and impair their functions. In some cases (e.g., brain

tumors), the result can be death (Seeley, 2004).

Malignant tumors can spread by local growth and expansion or by metastasis,

which results from tumor cells separating from the main neoplasm and being carried

by the lymphatic or circulatory system to a new site, where a second neoplasm forms.

Malignant neoplasms lack the normal growth control that is exhibited by most other

adult tissues, and in many ways they resemble embryonic tissue. Rapid growth is one

characteristic of embryonic tissue, but as the tissue begins to reach its adult size and

function, it slows or stops growing completely. This cessation of growth is controlled at

the individual cell level (Seeley, 2004).

Cancer results when a cell or group of cells, for some reason, breaks away from

that control. This breaking loose involves the genetic machinery and can be induced by

viruses, environmental toxins, and other causes. The illness associated with cancer

usually occurs as the tumor invades and destroys the healthy surrounding tissues,

eliminating their functions (Seeley, 2004).

Tumors tend to acquire more aggressive characteristics as they develop, and in

1957 Foulds pointed out that tumor progression occurred in a stepwise fashion, each

step determined by the activation, mutation or loss of specific genes. Over the next

two decades biochemical and cytogenetic studies demonstrated the sequential

appearance of subpopulations of cells within a tumor, attributable, in part at least, to

changes in the genes themselves (MacDonald, 2005).

The evidence suggests that, in the majority of cases, cancers arise from a single

cell which has acquired some heritable form of growth advantage. This initiation step

is believed to be caused frequently by some form of genotoxic agent such as radiation

or a chemical carcinogen. The cells at this stage, although altered at the DNA level, are

phenotypically normal. Further mutational events involving genes responsible for

control of cell growth lead to the emergence of clones with additional properties

associated with tumor cell progression. Finally, additional changes allow the outgrowth

of clones with metastatic potential. Each of these successive events is likely to make

the cell more unstable so that the risk of subsequent changes increases. Animal

models of carcinogenesis, primarily based on models of skin cancer development in



mice, have enabled these steps to be divided into initiation events, promotion,

malignant transformation and metastasis (MacDonald, 2005).

Although it is clear that multiple changes are necessary for tumor development,

it is not clear whether the order in which the changes occur is critical. Evidence

suggests, however, that it is the accumulation of events that is important rather than

the order in which they occur (MacDonald, 2005).

CHAPTER IV

RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELLS

CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL


4.1 - INTRODUCTION

When cells are exposed to ionizing radiation the standard physical effects

between radiation and the atoms or molecules of the cells occur first and the possible

biological damage to cell functions follows later. The biological effects of radiation

result mainly from damage to the DNA, which is the most critical target within the cell;

however, there are also other sites in the cell that, when damaged, may lead to cell

death (Suntharalingam, 2002).

Many aspects of the response of tissue systems are strongly affected by the

state of the cell in its cycle, for example, the state of oxygenation of the cell. The

supply of metabolic substrates and the removal of metabolic products also play a role

in modifying the response of tissue systems. The most significant aspect of the

radiosensitivity of a tissue or organ system centers on the state of reproductive activity

and, this proliferative state varies widely among the tissues of any mammalian species.

At one extreme are the tissues of the central nervous system, some of which rarely, if

ever, undergo division during the organism's adult life, and for which loss of clonogenic

ability is an irrelevant end point. At the other extreme are the blood forming organs,

which are proliferating at a rate approaching that of an exponentially growing, in vitro

culture (Alpen, 1998).

This chapter focuses on the most relevant aspects of radiation and provides a

detailed description of the effects of radiation on normal and neoplastic tissues. The

main objectives covered in this chapter include: knowledge about radiation dosimetry;

description of some important milestones in radiobiology, the types of cell death in

mammalian cells and undertake a relative exhaustive description of the radiation

effects in the environment. After this item, it is performed a description of the nature

of cell population in tissues and of the cell population kinetics and radiation damage.

Subsequently, the chapter focuses on the cell kinetics in normal and tumor tissues, on

the models for radiobiology sensitivity of neoplastic tissues and the tumor growth and

“cure” models. Finally, it ends with a description of the radiobiological responses,

hypoxia and radiosensitivity of the tumor cell.



4.2 – QUANTITIES AND UNITS USED IN RADIATION DOSIMETRY

The physical interactions of the various types of ionizing radiation with living

matter are the first stage of a series of events that lead to biological changes, whose

manifestations may occur over time, until many years after irradiation occurred.

The radiation gives energy to the medium, thus inducing physical, chemical and

biological processes that will lead to the changes mentioned previously. That part of

biology that studies the chain of phenomena, from physical interaction to the external

consequences, it is called Radiobiology. Given its complexity, not yet known in detail,

many of the physic-chemical triggered the constituent molecules of living cells after

irradiation (Dendy, 2000).

The disproportion between the kinetic energy and its biological consequences

emphasizes this complexity. Indeed, if the energy transferred to the body of an animal,

subject to deadly radiation, was transformed into heat it would only raise the body

temperature of a few thousandths of a degree. However, the kinetic energy that is

transferred to the cells upon irradiation with ionizing radiation, though small, has

major implications as it is released at the molecular level (Dendy, 2000).

Ionizing radiation can then be defined as any type of radiation capable of

removing an orbital electron of an atom or may carry electrons to higher energy levels

(outer orbital), causing their activation or arousal.

Radiation can be divided into:

a) Particulate radiation (corpuscular) (Dendy, 2000):

i. Alpha particles (α) - is a particle equivalent to a

helium nucleus 2He4 (2p + 2n) and has two positive charges. Due

to its high density of ionization, the energy of the α-particle is

rapidly transferred to the medium, which makes its power of

penetration rather limited (approximately 5 cm in air or about

100 mm in soft tissue).

ii. Beta particles (β) - is a more common process

among the light nuclei, which have excess of neutrons or protons

in relation to the corresponding stable structure, Figure 4.1.



Depending on their energy, a β-particle can go through 10 to 100

cm in air and 1 to 2 cm in biological tissue.

b) Radiation of electromagnetic waves: are high intranuclear

energies transmitted in the form of wave motion, generated by

radioactive isotopes. This emission is for the release of excess energy

from the nucleus core and/or is produced by special equipment such as

x-ray machines or linear accelerators. These waves have neither mass

nor electric charge and can be divided into (Dendy, 2000):

i. X-rays - are produced when fast-moving electrons

collide with a metal object. The kinetic energy of the electron is

transformed into electromagnetic energy. It is important to

remember that the origin of this radiation is extranuclear; that

is, is formed in the electronic layer of the atom. The function of

the X-ray machine is to provide a sufficient flow intensity of

electrons in a controlled manner, for the production of an X-ray

beam with the quality and quantity desired.

ii. Gamma (γ) radiation - are bundles of energy, of

nuclear origin, transmitted in the form of wave motion, and with

great power of penetration, Figure 4.2. This emission is intended

to release excess energy of an unstable atomic nucleus.

Figure 4.1 – Particulate radiation emission (from Jefferson, 2007).



Figure 4.2 – Penetration power of the main forms of radioactivity (from Suntharalingam, 2002).

When a beam of ionizing radiation passes through the matter, there are three

types of important physical information:

1. Their spectral energy distribution;

2. The intensity of the flow of particles;

3. The amount of energy that is released per unit mass in the area of

irradiated material(Yadunath, 2010).

The action of ionizing radiation in air can be used to evaluate the last two

physical information’s, although the measurement of radiation is complex given the

large number of units involved (Pisco, 2003).

4.2.1 – RADIATION MEASUREMENTS DEFINITIONS

i. Directly Ionizing Particles

Directly ionizing particles are charged particles that have sufficient kinetic

energy to produce ionization by collision. This energy certainly must be greater than

the minimum electron binding energy in the medium in which the interaction takes

place (Alpen, 1998).

ii. Indirectly Ionizing Particles

Indirectly ionizing particles are uncharged particles that can produce ionizing

particles through kinetic interaction with the medium or that can initiate a nuclear



transformation. For example, neutrons can interact with the medium to produce high

kinetic energy protons or, atomic nuclei through collisions or through the release of

secondary directly ionizing particles after nuclear interactions between the neutron

and a target atom (Alpen, 1998).

iii. Gamma Rays and X-Rays

Gamma rays and X-rays are electromagnetic radiations, that is, photons, of high

enough energy to produce ionization. Gamma rays are identical to X-rays in their

physical properties, but, by convention, it has become practice to call ionizing photons

produced in "machines" X-rays, whereas ionizing photons from radioactive sources are

called gamma rays (Alpen, 1998).

4.2.2 – QUANTITIES AND UNITS

Usually the exposure is a term related with the radiation source and is used to

express the intensity of radiation, from a beam of X-rays or γ rays, measuring the

ability of ionizing radiation in ionizing the air. The exposure is defined as the total

charge released per unit mass of air when all electrons released by interactions with

photons are completely stopped in air. The display units come in coulombs per

kilogram [C/kg] in the international system (SI) or roentgens [R] with 1R = 2.58 x10-4

C/kg. The exposure of a beam of X-rays or γ rays varies inversely with the square of the

distance from the source (Pisco, 2003).

The Kerma (Kinetics Energy Released in the Medium) is the kinetic energy

released in the medium, being defined as the kinetic energy transferred from neutral

particles (photons and neutrons) to charged particles (electrons and protons) when

radiation interacts with matter. The Kerma is specified in units of joules per kilogram

[J/kg]. Additionally, in air or water Kerma can replace roentgen as a measure of

exposure (Pisco, 2003).



Absorbed dose (D) translate the amount of radiation energy (E) absorbed per

unit mass (M) of the absorbing medium: , being specified in gray (G) in the

SI system and in rad (radiation absorbed dose). One gray equals 1 J of energy

deposited per kilogram and 1 rad equals 100 ergs of energy deposited per kg: 1 Gy =

100 rad, 1 rad = 10 mGy. The absorbed dose is independent of the radiation source,

being dependent of the absorbing medium, which is placed in the radiation field, so

both the absorbing medium and the location should be specified (Pisco, 2003).

The factor-f is a conversion factor between exposure and absorbed dose,

determined by the relationship between the absorbed dose (D) and exposure

(X): where f is the conversion factor from roentgen to rad (Pisco, 2003).

The linear energy transfer (LET) is the energy absorbed by the medium per unit

of the traversed distance [keV/mm]. The high LET radiation is more effective in

producing biological damage than low LET radiation. When considering the biological

effect of radiation, the total amount of energy absorbed (dose) and the effectiveness

of radiation in causing biological damage (LET) should be considered parameters

(Pisco, 2003).

The dose equivalent (H) quantifies the biological damage resulting from the

deposition of ionizing radiation in tissues and is mainly used in radiation protection. It

is defined as the absorbed dose (D) multiplied by the quality factor (QF) of the

radiation . The quality factor depends on the LET value: for sources with

low LET (electrons, beta particles, X-rays and γ rays) QF=1, for sources with high LET

(protons, neutrons and α particles) QF can reach the value 20. The dose equivalent is

expressed in sievert (Sv) in the SI system and in rems: 1 Sv=100 rem and 1 rem= 10

mSv (Pisco, 2003).



4.3 – HISTORICAL PERSPECTIVE OF RADIOBIOLOGY

Three incidents triggered the beginning of radiobiology: Wilhelm Conrad

Roentgen's discovery of X-rays in 1895; Henri Becquerel's observance of rays being

given off by a uranium-containing substance in 1896 (Marie Curie subsequently would

call this radioactivity); the discovery of radium by Pierre and Marie Curie in 1898

(Forshier, 2008).

Early radiobiology observations included skin erythema (radiation induced skin

reddening), epilation (radiation induced hair loss), and anemia. Because of unshielded

fluoroscopic apparatus, radiologists had to have fingers amputated, and compared

with other doctors, had superior incidence of leukemia (Forshier, 2008).

The first United States X-rays fatality occurred in 1906. Clarence Daly, an

assistant of Thomas Edison, had collaborated with him in producing the fluoroscope

and fluorescent screens. In working long days, Daly was subjected to doses above

modern lifetime limits. In Edison´s day, shielding was seldom used for personnel or x-

ray tubes (Forshier, 2008).

The early observations of Becquerel, the Curies, and early radiologists sparked

much research into the effects of radiation exposure on biological processes.

Beginning in the early 1900s through the 1950s and 1960s, many theories were

developed to define and explain these effects (Forshier, 2008).

4.3.1 – Law of Bergonie and Tribendeau

In 1906 two Frenchmen, J. Bergonie and L. Tribendeau, exposed rodent

testicles to X-rays, and observed the effect of radiation. These researchers selected the

testicles since this organ contains both mature cells (spermatozoa), which execute the

organ´s principal function and immature cells (spermatogonia and spermatocytes),

whose only purpose is t evolve into mature, functional cells. Not only do these cells´

functions differ, but their rate of mitosis also differs. The spermatogonia (immature)

cells divide frequently, whereas the spermatozoa (mature) cells do not divide. After

exposing the testicles to radiation, Bergonie and Tribendeau noticed that the

immature cells were injured at doses lower than mature cells. Supported by these



founds, they proposed a law describing the radiation sensitivity for all body cells. Their

law maintains that actively mitotic and undifferentiated cells are most susceptible to

damage from ionizing radiation (Forshier, 2008).

The law of Bergonie and Tribondeau states that:

1. Steam cells are more radiosensitive than mature cells. The more mature

a cell is, the more radioresistant.

2. Younger tissues and organs are more radiosensitive than older tissues

and organs.

3. The higher the metabolic activity of a cell, the more radiosensitive it is.

4. The greater the proliferation and growth rate for tissues, the greater the

radiosensitivity.

This law informs us that compared to a child or mature adult, the fetus is

most radiosensitive (Forshier, 2008).

4.3.2 – Ancel and Vitemberger

In 1925 the law of Bergonie and Tribondeau was modified by P. Ancel and P.

Wittenberg. These researchers suggested that the intrinsic susceptibility of damage by

any cell by ionizing radiation is the same, but that the timing of manifestation of

radiation-produced damage varies according to the types of cells. In experiments on

mammals, they determined that there are two factors, which affect the appearance of

radiation damage to the cell (Forshier, 2008):

1. The amount of biological stress the cell receives.

2. Pre- and post-irradiation conditions that the cell is exposed to.

Ancel and Vitemberger theorized that the most significant biological stress on

the cell is the need to division. In their terms, a given dose of radiation will cause the

same degree of damage to all cells (the innate susceptibility is comparable for all cells)

but only if and when a cell divides will damage be demonstrated (Forshier, 2008).

Although Ancel and Vitemberge communicate radiosensitivity differently than

Bergonie and Tribondeau, they do agree with them by placing a significant emphasis

on the amount of mitotic activity involved (Forshier, 2008).



In the 1920s researchers learned that the process of ionization in tissues was

the cause of biologic results. The two mechanisms recognized were, Figure 4.3:

Direct ionization along charged particles tracks caused direct effects

(original ionization occurs directly on the targeted molecule).

The formation of free radicals caused indirect effects (original ionization

occurs with water, and transfers ionization to target molecule).

Figure 4.3 –Radiation path with low and high LET (from Yadunath, 2010).

4.3.3 – Fractionation Theory

The 20s and 30s brought the fractionation theory from France. Ram testicles

were exposed to large doses of ionizing radiation. Even though the rams could be

sterilized with one large dose, this quantity of radiation also caused the skin next to

the ram´s scrotum to have a reaction. However, it was found, that if the large dose was

fractioned (smaller doses spread out over a period of time, Figure 4.4), the animals

would still become sterile, but with considerably less damage to their skin (Forshier,

2008).

Figure 4.4 – Effect of fractionation (from Cherry, 2006).

X-rays

Neutrons

Cel

l su

rviv

al

Dose (Gy)



4.3.4 – Mutagenesis

In 1927, H. Muller discovered that ionizing radiation produced mutations

through his experiments with fruit flies. His finding is termed mutagenesis. This

researcher found that the radiation-induced mutations were the same as those

produced by nature. Irradiating the fruit flies did not create any unusual effects, but

the frequency of mutations was intensified. This implies that the effects of ionizing

were not unique to radiation, that is, they could have been caused by things other

than radiation (Forshier, 2008).

4.3.5 – Effect of Oxygen

The oxygen effect was the subject of experimentation during the 1940s and

1950s. Oxygen is a radiosensitizer because it increases the cell-killing effects of a given

dose of radiation. This occurs as a result of the increased production of free radicals

when ionizing radiation is delivered in the presence of oxygen (Forshier, 2008).

The oxygen effect is known as Oxygen Enhancement Ratio (OER) and

numerically defined as (Forshier, 2008):

It is necessary the presence of oxygen in order to form free radicals during

ionization of water. Without free radicals, hydrogen peroxide is not formed, and thus

cell damage is reduced (Forshier, 2008).

The OER is dependent on LET, being more pronounced for low LET radiation

and less effective for high LET radiation. Because of the physical differences between

high and low LET radiations the quantity of damage done by high LET radiation would

be beyond repair. Thus, having oxygen present would not intensify the response to

radiation the same magnitude, as would be the case with the low LET radiation,

(Forshier, 2008), Figure 4.5.



Figure 4.5 - Oxygen effect of the LET (from Forshier, 2008).

4.3.6 – Relative Biologic Effectiveness

The relative effect of LET is quantitatively described by the relative biologic

effectiveness (RBE). RBE is a comparison of a dose of test radiation to a dose of 250

keV X-ray which produces the same biologic response, being expressed as follows

(Forshier, 2008):

The RBE measures the biological effectiveness of radiation having different LET

values. Factors which influence RBE include radiation type, cell or tissue kind,

physiologic conditions, biologic result being examined, and the radiation dose rate. In

comparing LET and RBE, as LET increases, RBE increases also, Figure 6. Accordingly, low

LET radiations have a low RBE, and high LET radiation have a high RBE (Forshier, 2008).



Figure 4.6 - RBE versus LET (from Forshier, 2008).

4.3.7 – Reproductive Failure

In 1956, Puck and Marcus exposed human uterine cervix cells to varying doses

of radiation. Thus, experimentally determined reproductive failure by counting the

number of colonies formed by these irradiated cells (Forshier, 2008).

As scientists began to research the effects of radiation exposure had on

biological processes, there occurred a need to measure the levels of radiation causing

specific effects. Units of measurement were developed to quantify radiation levels and

thus track the effects of exposure to varying the levels of exposure (Forshier, 2008).

4.4 – BIOLOGIC EFFECTS OF RADIATION

Ionizing radiation transferring energy to biologic systems causes, in several

successive stages, biological consequences.



4.4.1 - Elementary phenomena

Physic interactions - these interactions vary according to the nature of

radiation. Photons (X-rays or gamma rays) put in motion, during collisions with atoms

of the medium, electrons to which they transfer whole or part of its energy in the

form of kinetic energy. This kinetic energy is expended in the course of interactions

with electrons belonging to atoms of the medium, and is subjected to the electric

field of the incident electron (excitation and ionization) and these interactions

"consume" an energy that was subsequently transferred, through ionizing radiation,

to the medium. This phase is very brief (Pedroso Lima, 2003).

The proportion of these modified atoms is minimal; however, they are

grouped along the path of electrons, at varying distances. Although the amount of

energy transferred is low, its concentration along these trajectories into bundles of

energy whose value is relatively high (10 to 100 eV) gives a great efficiency. The other

charged particles (alpha particles, protons set in motion when the interactions of

neutrons with the medium) cause the same excitations and ionizations along its own

path but at much shorter distances (the beam energy has the same value but is

closer) (Pedroso Lima, 2003).

Radiochemical phenomena – in a second phase, equally brief, the ionization of

an atom within a molecule leads, in general, to her collapse and the fragments

formed, called radicals. These radicals are chemically very "active" since they are able

to react with other molecules initiating various chemical reactions. The effect is direct

when the ionization directly affects the molecules damaging them, or indirect when

the injury is caused by free radicals formed during the breakdown of water molecules

- radiolysis - which constitute the bulk of biologic systems, Figure 4.7. The final

product of the water radiolysis is the formation of an ion pair, H+ and OH-, and two

free radicals H* and OH*. These chemical species are highly reactive radicals that play

an important role and constitute the starting point of many molecular changes. Half

of the molecular injuries are due to direct effect and the other half to indirect effect.

When the distance between ionizations is short, these radicals react with each other

and their concentration along the trajectories increases the effectiveness of these



reactions. Therefore, for the same amount of energy absorbed the number of

damaged molecules is larger (Pedroso Lima, 2003).

Figure 4.7 – Radiolysis of water molecules (Forshier, 2008).

The human body is composed of 80% water so the irradiation of water is

involved in most interactions involving radiation.

4.4.2 – Molecular Damages

All biological molecules can be altered but the consequences vary according to

the importance of the injured molecules.

The molecules of deoxyribonucleic acid or DNA are those where the damage is

more serious, since each has a specific role. Indeed, each cell “contains” information

that will allow, according to a preconceived plan, the appropriate development and

reaction to external events. The genetic material, or hereditary material, consists of

DNA molecules that are the backbone of information. Damage to DNA molecules is

the key mechanism of ionizing radiation action (Suntharalingam, 2002).

Deoxyribonucleic acid or DNA - The structure is the same in all living species.

The elementary constituent of DNA molecule is the nucleotide, which is formed by a

phosphate group, a sugar (desoxirribose) and one base. A DNA molecule consists of

two long strands or fibers of millions of nucleotides that form as a ladder whose bars

would be the sequence of alternating sugars and phosphate groups, and the lanes

Radicais livres

OH*, H*

Iões

OH- , H-

Iões

HOH+ , HOH-

Água

H2O



would be two bases joined together. This string wraps around its axis

(Suntharalingam, 2002), Figure 4.8.

Figure 4.8 - Deoxyribonucleic acid molecule (DNA) (from Seeley, 2004).

There are four different types of bases: adenine (A), cytosine (C), guanine (G)

and thymidine (T), that are always available to form these dishes, paired as follows:

adenine with thymine and guanine with cytosine, forming these four pairs possible:

AT, TA, GC and GC. The order of bases in one of the molecule chains determines,

unambiguously, the order of bases on the other chain (from Seeley, 2004).

The orders in which the bases follow one other constitute one code, and a

sequence of three bases (triplets) determines the amino acid that is present in the

encoded protein. The set of "triplets" that encode a protein constitutes a gene. Thus,

a gene consists of a sequence of several thousand of nucleotides coding for a specific

protein that is synthesized from the information contained in this gene. This

information is transmitted to the cytoplasm by a messenger RNA (from Seeley, 2004).

Besides the coding genes, other DNA sequences constitute regulatory systems

that, for example, activate ('operators' genes) or repress ('repressive' genes) the

expression of a gene and, consequently, the synthesis of the protein encoded by this

gene. These regulatory mechanisms, not yet fully understood, and to which are

certainly devoted numerous DNA sequences, definitely explain the disproportion



between the number of genes identified and the total of DNA mass (from Seeley,

2004).

When radiation interacts with the cell, the ionization and excitation may occur

in the macromolecules (for example, DNA) or in the medium they are (for example,

water). Depending on the site of interaction, the effect is called direct or indirect

(Suntharalingam, 2002).

The direct interaction occurs when a first ionization reaches a macromolecule

(for example, DNA, RNA, proteins or enzymes). If the macromolecule is ionized it is

considered abnormal or mutated (Suntharalingam, 2002).

The indirect interaction occurs if the initial ionization takes place at a distance

not critical of the macromolecule and, then takes place the transfer of ionization

energy to the molecule (Suntharalingam, 2002).

4.4.3 – Chromosomes Irradiation

In multicellular species the DNA molecules are the heart of chromosomes,

which are essential constituents of the cell nucleus. Each species is characterized by

the number and shape of chromosomes. Human cells, for example, have 46

chromosomes grouped in 23 pairs of 2 chromosomes apparently identical (size,

shape, etc.), one from the mother and one from the father. One of these 23 pairs is

unique, the sex chromosomes. In women, the two chromosomes called X are similar;

in men, they look different: one, called X, is similar to the woman and the other called

Y, is much smaller (Forshier, 2008).

Each chromosome consists of a single molecule of DNA coiled about itself and

closely tied to protein molecules, Figure 4.9. The length of a chromosome is about 0.1

μm, but if the DNA molecule was stretched it would have a length of approximately 4

cm that is 400 000 times longer. Its width is 2 nm (Forshier, 2008).



Figure 4.9 – DNA Compaction (from Seeley, 2004).

At the time of cell division, chromosomes can be observed microscopically. It

is then possible to count them and identify them by size, shape and after stained, by

structure. In this phase, it is feasible to study chromosomal abnormalities (Forshier,

2008).

When the chromosomes are irradiated, the radiation interaction can be direct

or indirect. The result of any of the interactions is a mutation. The mutation causes a

visible chromosomal change, Figure 4.10, and represents critical lesions in DNA

(Forshier, 2008).

Figure 4.11 depicts the effects of a single mutation caused by an irradiation in

the G1 phase of the cell cycle.



Figure 4.10 - Chromossome Aberrations (from Forshier, 2008).

Figure 4.11 - Simple Mutation in G1 phase (from Forshier, 2008).

Radiochemical effects on DNA and chromosomes - the main damage caused by

ionizing radiation are:

Modifications of bases: adenine, cytosine, guanine and

specially thymidine. A pair of bases may be absent or replaced by

A. O

ne

bre

ak in

on

e

chro

mo

sso

me

B. T

wo

bre

ak in

on

e

chro

mo

sso

me

C. O

ne

bre

ak in

tw

o

chro

mo

sso

mes

Tran

slo

cati

on

D. O

ne

bre

ak in

tw

o

chro

mo

sso

mes

Dic

entr

ics

Quebra Recombinação Replicação Separação Anafásica

Irradiation

in G1 phase Causes chromatid

breaks

Visualization

in M phase

Replication in S and pass

through the G2 phase



another. The modification of the order or nature of the bases causes

an alteration of the information carried by the gene (point mutation).

Changes in DNA conformation: a rupture in one of the

two chains (these lesions are easily repairable - Figure 4.12) or rupture

of the two chains (these injuries are difficult to repair).

Figure 4.12 – Schematic of the repair mechanism of excision-resynthesis (from Forshier, 2008).

Other intersection injuries (cross links) form links, for

example, between two DNA strands, DNA-DNA bonds, or between one

nucleic acid and protein: DNA-binding protein.

Several remodeling of chromosome structure: a single or

multiple rupture can cause the loss of a fragment - deletion - if it

occurs in S phase of the cell cycle takes place the replication of the

deletion and, in metaphase the abnormal chromosome looks like the

normal chromosome despite lacking information in the terminal

region; the setting of this fragment on another chromosome is called

translocation. When two chromosomes exchange pieces thus speaks of

reciprocal translocation. This fragment can then re-weld abnormally on

the same chromosome (inversion). If in G1 phase of the cell cycle

occurs two mutations in the same chromosome, the two ends can

3´

5´

3´

5´

3´

5´

3´

5´

3´

5´

5´

3´

5´

3´

5´

3´

5´

3´

5´

3´

Endonuclease

Polimerase Χ

Ligase



'weld' and form a 'ring' chromosome; chromossomes can weld again in

a more complex way, forming dicentric chromosomes, etc. The quality

of the adhesion ability of damaged chromosomes is a determining

factor in the joining of the chromatid, Figure 4.13 (Forshier, 2008).

Figure 4.13 - Chromosomal aberrations of multiple mutations (from Forshier, 2008).

The morphological study of chromosomes in a cell is of enormous practical

interest, since the number of abnormalities is dose dependent and can assess their

importance from relatively low values (0.25 Gy). Chromosomal aberrations may make

it impossible the balance of genetic material between two daughter cells and, lead to

cell death at the time of cell division or non-viability of the two daughter cells

(Forshier, 2008).

Cellular constituents other than DNA can suffer injuries caused by ionizing

radiation, for example, fatty acids that make up cell membranes, proteins such as

enzymes, involved in all stages of cellular life. Although, if the points of impact of

ionizing radiation are numerous, the biological effect resulting primarily from lesions

in the DNA molecules (Forshier, 2008).

Molecular DNA repair – there are many chemical or physical agents that can

damage DNA and so life would not be possible without repair. The total length of DNA

Ring

Dicentric

Irradiation

in G1 phase

Causes

chromatid

breaks

Bind during

S phase

Visualization

in M phase



contained in the cells of the body (2m in length per cell) is about 60 million

kilometers. Per day is born 200 billion cells, the length of DNA synthesized is 400

million kilometers a day. These long and narrow molecules are fragile and therefore

the thermal agitation and chemical reactions harm it constantly. Consequently,

becomes, necessary systems to repair the damage, particularly, due to external factors

such as ultraviolet radiation, chemicals, etc. If the injuries were permanent, the impact

of a single photon at the level of a molecule would result in an irreversible alteration

of a gene, and the smallest radiation harm. Thanks to the final repair the damage is

much less than the damage we would get if were added all the molecular lesions

(Forshier, 2008).

When the injuries are related to one of the two chains, restoration is usually

full; however, if the two chains simultaneously suffer injury, repair mechanisms are

more complex and can result in a repair deficient, that is, has an error (mutation)

whose consequences can lead to cell death or start their cancer (Forshier, 2008).

Biological consequences of irradiation - At the cell level the effects are multiple.

Irreversible DNA injuries can result: a mutation, that is, a final modification of the

property inherited from the cell; loss of viability, that is, the inability to divide and give

rise to normal daughter cells, which can express themselves since the first cell division

or during the first five divisions (delayed death). The proportion of surviving cells, i.e.,

is, those which retained the ability to divide many times, it decreases with the dose.

Besides depending on the dose, this ratio also depends on the nature of radiation and

dose rate, as well as suffering from the influence of the environment of cells (for

example, the decrease of oxygen content increases radiation resistance) (Forshier,

2008).

4.4.4 – Irradiation of Macromolecules

The occurrence of molecular derangements or injuries may be classified either

effects on macromolecules or effects on water. Irradiating macromolecules gives very

different results when compared to the irradiation of water, Figure 4.14. If



macromolecules are exposed to ionizing radiation in vitro (outside the body or cell), a

significant dose of radiation is needed to produce a measurable effect. Irradiating

macromolecules in vivo (inside the living cell) shows that when cells are in their natural

conditions, they are much more radiosensitive (Forshier, 2008).

Figure 4.14 – Macromolecules mutations (from Forshier, 2008).

The three primary effects of irradiating macromolecules in vitro include main-

chain scission, cross-linking and point lesions.

Main chain scission - occurs when the thread or backbone of the long-chain

molecule is broken. This results in the long-chain molecule being reduced to

numerous smaller molecules, which can still be macromolecular in nature. Not only

the size of the macromolecule is reduced, but its viscosity (thickness) is also reduced

(Forshier, 2008).

Cross-linking - certain macromolecules have spurlike extensions off the main

chain. Others develop these spurs after being irradiated. After being irradiated, these

spurs can as if they had a sticky material on their ends. This stickiness causes the

macromolecule to connect to another macromolecule, or to another section of the

same molecule. This is termed cross-linking. Viscosity is increased by radiation-

produced molecular cross-linking (Forshier, 2008).

Point lesions - Irradiating macromolecules may result in disturbance of single

chemical bonds, which create molecular lesions or point lesions. Point lesions may



cause slight molecular changes, which in turn cause the cell to function incorrectly

(Forshier, 2008).

At low doses of radiation, point lesions are regarded to be the cellular

radiation damage that is responsible for late radiation effects, which are observed at

the whole-body level (Forshier, 2008).

Irradiating macromolecules may result in either death of the cell or late

effects. Throughout the cell cycle proteins are constantly being created, and occur in

greater number than nucleic acids. Abundant copies of unique protein molecules

always exist in the cell. These factors allow protein to be more radioresistant than the

nucleic acids. In addition, numerous copies of m-RNA and t-RNA exist in the cell,

although they are not as plentiful as the protein molecules. Conversely, DNA

molecules, having their distinctive base arrangements, are not so frequent. Because

of this, DNA molecule is considered the most radioresistant macromolecule. RNA

radiosensitivity is midway between that of DNA and protein macromolecules

(Forshier, 2008).

There can be visible chromossome abnormalities or cytogenetic damage if the

radiation damage to the DNA is intense enough. DNA can be injured without

producing visible chromosomal aberrations. Even though this damage is reversible, it

can lead to death of the cell, and ultimately destroy tissues and organs (Forshier,

2008).

Metabolic activity can also be affected by DNA damage. The primary

characteristic of radiation-induced malignancies is the uncontrolled reproduction of

cells. If germ cells receive DNA damage, the response may be detected in future

offspring (Forshier, 2008).

Figures 4.15 A-D, illustrate DNA aberrations that are reversible types of

damage. They may involve the sequence of bases being changed, thus changing the

triplet code of codons. This is considered a genetic mutation at the molecular level

(Forshier, 2008).



Damage type shown in Figure 4.15-E also involves the change of or loss of a

base. This type of damage destroys the triplet code as well, and may not be

reversible; this is considered a genetic mutation (Forshier, 2008).

These molecular genetic mutations are termed point mutations, and are

common with low LET radiation. Point mutations may be either of minor or major

significance to the cell. A key effect of these point mutations would be the genetic

code being incorrectly transferred to daughter cells (Forshier, 2008).

Figure 4.15 – DNA aberrations (from Forshier, 2008).

4.4.5– Dose-response relationship

The dose-response relationships, also referred to as dose-response curves, are

graphical correlations between the observed effects (response) from radiation and

dose of radiation received, Figure 4.16 (Forshier, 2008).

A base deletion

B base substitution

C Hydrogen bond disruption

or or

Low LET (x-ray)

Single strand

or

High LET (α particle)

Double strand

(not repairable)

E D



Dose-response curves differ in two ways (Forshier, 2008):

They are either linear or non-linear;

They are either threshold or nonthreshold.

Figure 4.16 - Dose-response Relationship (from Forshier, 2008).

Linear means that an observed response is directly proportional to the dose. On

the other hand, nonlinear means that an observed response is not directly

proportional to the dose. Additionally, threshold assumes that there is a radiation level

reached below which there would be no effects observed, and nonthreshold assumes

that any radiation dose produces an effect. Diagnostic radiology is primarily concerned

with linear, nonthreshold dose-response relationships (Forshier, 2008).

4.4.5.1 - Linear-Dose-Response Relationships

Since dose-response relationship A and B intersect the dose (x) axis at either

zero or on the y-axis, they are considered linear, nonthreshold, Figure 4.16.

All linear dose-response relationships exhibit an effect regardless of the dose.

This is demonstrated by relationship A. Even at zero doses, A exhibits a measurable

response (RA). This RA is termed the ambient or natural response. Dose-response

relationships C and D intercept the dose axis (x) at a dose value greater than zero.

Thus, C and D are considered linear, threshold. At doses below the respective C and D

values, o response would be anticipated (Forshier, 2008).



4.4.5.2 - Linear Quadratic Dose-Response Curves

In 1980, the Committee on the Biological Effects of Ionizing Radiation (BEIR

Committee) concluded that the effects of low doses of low LET radiation follow a

linear, quadratic dose-response relationship, Figure 4.17. At low doses, the curve is

linear and at high doses, the curve becomes curvilinear and is no threshold (Forshier,

2008).

The portion of the curve where increases in dose shows no or light increase in

the effect is named as the toe. The shoulder is considered the area of the curve in

which a leveling off occurs, again demonstrating no or little increase off or flattened

(Forshier, 2008).

In 1990, with 10 additional years of human data, the BEIR committee revised its

radiation risk estimates and adopted the linear, nonthreshold dose-response

relationship as most relevant (Forshier, 2008).

Current radiation dose-response curve, there is a nonlinear relationship

between dose and effect, meaning that the effect is not directly proportional to the

dose (Forshier, 2008).

Figure 4.17 – Linear quadratic dose-response curve (from Forshier, 2008).

4.4.5.3 - Dose-response curve linear quadratic

The sigmoid dose-response curve s applied predominantly to the high dose

effects observed in radiotherapy, Figure 4.18. Sigmoid means S-shaped. There is

usually a threshold below which no observable effects occur. With a sigmoid dose-



response curve, there is a nonlinear relationship between dose and effect, meaning

that the effect is not directly proportional to dose (Forshier, 2008).

Figure 4.18 – Sigmoid dose-response curve (from Forshier, 2008).

4.4.6 – Targeted Theory

As cells contain a profusion of molecules, radiation damage to these molecules

is not likely to result in significant cell injury because additional molecules are present

to assist in cell survival. However, there are molecules that are not in abundance that

are considered necessary for the cell survival. Irradiating these could have serious

consequences, because there may not be others available to maintain cell survival.

This idea of a sensitive critical molecule is the foundation for the targeted theory.

According to the targeted theory, there will be cell death only if cell´s targeted

molecules is inactivated. It is theorized that DNA is the critical molecular target

(Forshier, 2008).

The target is regarded to be the area of the cell that contains the target

molecule. Because radiation interaction with cells is random, target interactions also

occur randomly. The radiation shows no favoritism toward the targeted molecules

(Forshier, 2008).

When a target is irradiated, this is considered a hit. Both direct and indirect

effects cause hits, Figure 4.19. Direct versus indirect hits are not distinguishable.

With low LET radiation in an anoxic condition, chances for a hit on the targeted

molecule are low because of the large distances between ionizing events (Forshier,

2008).



In an aerobic state with low LET radiation, the indirect effect is intensified, as

more free radicals are formed, and the volume of action surrounding each interaction

enlarged. This increases the likelihood of a hit (Forshier, 2008).

Using high LET radiation, ionization distances are so close together that there is

a high probability that a direct hit will take place, probably even higher than for the

low LET, indirect effect (Forshier, 2008).

Adding oxygen to high LET radiation will probably not result in additional hits,

as the high LET has already produced the maximum number of hits possible (Forshier,

2008).

4.4.7 – Cell Survival Curves

Cellular sensitivity studies began in the middle 1950s with Puck and Marcus.

They performed in vitro studies using HeLa cells. Their initial study was on failure of

reproduction in which they exposed HeLa cells to differing radiation doses and then

totaled the number of colonies formed (Forshier, 2008).

Figure 4.19 – Targeted theory (from Forshier, 2008).



This information may be illustrated graphically by plotting the radiation doses

on a linear scale on the x-axis, and plotting the fraction of surviving cells on a

logarithmic scale on the y-axis. This graphical representation of the relationship

between the dose and surviving cells is a survival curve (Forshier, 2008).

It was stated previously that radiation interaction is random in nature.

Therefore, it must be determined how many hits are necessary to cause cell death.

This may be demonstrated using a cell survival curve (Forshier, 2008).

The model most used is the linear-quadratic model, whereby there are two

components responsible for cell death: a dose-proportional, which corresponds to the

initial portion of the curve and represents the cell death caused by lethal damage, and

another component proportional to the square of the dose, related to the steeper

region of the curve and is linked to the deaths caused by lethal damage, potentially

lethal damage, and especially the accumulation of sub-lethal damage (Suntharalingam,

2002).

In simple cells such as bacteria, if there are additional hits to the same cell,

these hits do not matter. In complex cells such as human cells, it is theorized that in

order to cause cell death, more than one hit is required (Forshier, 2008).

The graphs of simple versus complex cells are very different, Figure 4.20. Graph

A represents a survival curve for simple cells, represented by a straight line. Graph B

represents a survival curve for complex cells, represented by a line which displays a

shouldered area where effects are not apparent until some targets have received

enough multiple hits to be killed. The targeted theory can be used to explain this

shoulder section of the curve (Forshier, 2008).

The shoulder of the cell survival curve shows that some damage must accrue

before there can be cell death. The accumulated damage is called sub-lethal damage.

The wider the shoulder, the more sub-lethal damage the cell can endure.



Figure 4.20 – Simple versus complex cell survival curves (from Forshier, 2008).

4.5 – CELL DEATH IN MAMMALIAN TISSUES

The clonogenic potential is the essential element for the maintenance of a cell

line, either in vitro or in organized tissues, although there are other important issues in

the maintenance associated with complex tissue systems. Normal senescence of cells

is one of these important issues and the other is the removal of cells that are in the

wrong place at the wrong time. Examples of this would be the metastatic arrival of

tumor cells transported from a primary tumor elsewhere or the resolution of

inflammatory processes (Alpen, 1998).

It is possible to define at least two different types of cell death that go beyond

the end point of clonogenic potential and involve the actual disappearance of the cell:

necrosis and apoptosis (Alpen, 1998).

Necrosis is characterized by a tendency for cells to swell and ultimately to lyse,

which allows the cell's contents to flow into the extracellular space, this is usually

accompanied by an inflammatory response. In the case of neoplasms, necrosis is most

often seen in rapidly growing tumors, where the tumor mass outgrows its blood supply

and regions of the tumor become undernourished in oxygen and energy sources. In

this case inflammation is not a characteristic of the necrotic process (Alpen, 1998).



Apoptosis involves shrinkage of the nucleus and cytoplasm, followed by

fragmentation and phagocytosis of these fragments by neighboring cells or

macrophages. The contents of the cell do not usually leak into extracellular space, so

there is no inflammation. Since there is no inflammation accompanying apoptosis, the

process is histologically quite inconspicuous (Alpen, 1998).

Figure 4.21 - Structural changes of cells undergoing necrosis or apoptosis (from Goodlett, 2001).

The concept of apoptosis as a mechanism for the control of cell population

numbers and cell senescence has been around for several decades, but the

mechanisms of apoptosis have received extensive research attention only in the

nineties. This interest in apoptosis was engendered by the discovery that tumor

suppressor genes and oncogenes were central control agents for the process. The

principal focus of these studies has been the role of the p53 tumor suppressor gene,

already described in chapter II. The p53 gene is a transcriptional activator that may

include activation of genes that regulate genomic stability, cell cycle progression, and

cellular response to DNA damage. The synthesis of the p53 product is known to be

responsible for the induction of apoptosis in many cell lines in which this gene is

present in unmutated form. The mutational absence of this gene is often accompanied

by the inability of a cell line to initiate apoptosis. For radiation pathology, the

important finding is that even small amounts of DNA damage in G1 cells cause



synthesis of the p53 product and ultimate apoptosis of the cells. It is pertinent for

radiation pathology that cells of the lymphoid system generate high concentrations of

p53 gene product after cell damage. This is particularly true for low doses of ionizing

radiation. Clearly, the generation of the p53 product is not sufficient for the onset of

apoptosis, but it is certainly necessary (Alpen, 1998).

Another significant gene involved in apoptosis is the bcl-2 gene (described in

chapter II). This gene encodes a protein that blocks physiological cell death (apoptosis)

in many mammalian cell types, including neurons, myeloid cells, and lymphocytes. This

gene is able to prevent cell death after the action of many noxious agents (Alpen,

1998).

The role of apoptosis as a mechanism for cell death following ionizing radiation

exposure remains unclear at this time, particularly the relative importance of the

agonistic role of p53 and the antagonistic role of bcl-2. However, it must be important,

as that the detection of small nicks and errors in the DNA of G1 cells is crucial to the

recovery of irradiated tissues and the reduction of genomic misinformation (Alpen,

1998).

4.6 – NATURE OF CELL POPULATIONS IN TISSUE

One of the earlier systematic overviews of the nature of cell population kinetics

in normal and malignant tissues was that of Gilbert, 1965. Their classification of the

various kinetic systems found in mammalian (and, incidentally, in other organisms)

organs and tissues is shown in Figure 4.22 (Alpen, 1998).

Figure 4.22 - Classification of cell kinetic types in the system of Gilbert, 1965 (from (Alpen, 1998)).



From Figure 4.22, the definitions of each of the systems are the following (the

double arrows in classifications D, E, and F, are meant to signify the mitotic division of

one of the cells of the compartment, giving rise to two daughter cells):

A. Simple transit population. Fully functional cells are added to the

compartment while a population of either aging or randomly destroyed cells disappear

from the pool. There are many examples of functional end cells that are in this

category. Examples are spermatozoa, which are constantly being replaced, as well as

red cells or other end cells of the blood.

B. Decaying population. The cell numbers decrease with time without

replacement. The population of oocytes in the mammalian female is often quoted as

an example, if not the only example. Populations of this classification are rare in

mammalian systems, but not in insects.

C. Closed, static population. There is neither decrease nor increase in cell

numbers during life. It is unlikely that such a population truly exists. The differentiated

neurons of the central nervous system are quoted as an example of a static

population, but there is probably a decline in cell numbers even in this population.

D. Dividing, transit population. In addition to the transiting cells, division of the

cells within the compartment occurs that leads to a larger number leaving than

entering. It is assumed in this model that the number of cells in the compartment

remains more or less static. The differentiating and proliferating blood cell types (for

example, the proerythroblast of the bone marrow) that follow the stem cell are

examples of this type of population.

E. Stem cell population. A self-sustaining population, that relies on self-

maintenance for its continued existence. All the progeny of this type of cell line

depend upon the continued existence of the stem cell pool. Every self-maintaining,

dividing cell population must have such a precursor pool. Examples are the stem cells

responsible for sustained spermatogenesis or hematopoiesis.

F. Closed, dividing population. Such a population is best represented by

neoplastic growth. No cells enter or leave the compartment in the early stages of

tumor growth. In the long run, neoplastic growth is probably best represented as a

stem cell population, since as the tumor enlarges, there is cell death, suppression of

growth by metabolic and other nutrient shortages, and a highly variable rate of



division. The epithelial cells responsible for cell renewal in the lens of the eye are

another example of this type of population (Alpen, 1998).

4.7 – CELL POPULATION KINETICS AND RADIATION DAMAGE

It should be almost self-evident that the kinetic types represented by D, E, and

F of Figure 4.22 will be most vulnerable to radiation damage. It has been established

that for clonogenic death of the cell the principal target of ionizing radiation is the

genome, and the genome is certainly at its most vulnerable to radiation damage during

G2 and mitosis (M), when replication has been completed. The principal outcome of

disturbances to the dynamic replicative activity of the genome is altered clonogenic

ability. That is indeed the case, and the most critically sensitive of these systems would

be the stem-cell-type tissue (E), which depends for its continuing function on its own

continued clonogenic potential, since there is no precursor compartment to replace

deficiencies (Alpen, 1998).

The ultimate functional viability of a tissue that is dependent on stem cell

activity will be determined by whether, after radiation exposure, there are adequate

numbers of surviving and still clonogenic stem cells to repopulate the compartment

and finally to produce functionally competent progeny. The most resistant tissues are

those that require neither input of cells from a prior compartment nor division within

the compartment. The closed static model is such a case, and in the case of the central

nervous system, its high degree of radioresistance can be attributed to its lack of need

for cell replication and replacement (Alpen, 1998).

4.7.1 – Growth Fraction and its significance

The concept of growth fraction as a descriptive parameter for the kinetics of

proliferating tissue appears to have been first proposed by Mendelsohn (1962) as the

result of his observations that all cells in a growing tumor are not in the active process

of proliferation as determined by the cellular incorporation of radioactive labels of

DNA synthesis. Lajtha (1963), based on his own studies as well as those of others,

proposed the concept of the G0 phase of the cell cycle, a state of the cell in which the



cell was not engaged in active proliferation, but in which the cell could reenter the

proliferative state. The G0 cell was visualized as a cell that has been removed from the

actively dividing population by regulatory activities rather than as a result of metabolic

deprivation. Subsequently, it became apparent that cells also could be removed from

active division in a reversible manner by deprivation of oxygen, glucose, or other

metabolites (Hlatky et al., 1988). Restoration of the lacking nutrient led to reentry of

the cell into active proliferation (Alpen, 1998).

Figure 4.23 – Cell cycle phases (from (Goldwein, 2006)).

The growth fraction is defined as the fraction of the total cellular population

that is clonogenically competent and is actually in the active process of DNA replication

and cell division. The growth fraction may be estimated by any one of several

techniques, most of which depend on incorporation of a radioactively labeled DNA

precursor into those cells that are actively dividing. One of the simpler methods for

determination of the growth fraction is the exposure of a growing culture of cells, in

vitro or in vivo, to an appropriate radioactive label for the synthesis of DNA. A typical

and frequently used label is 3H-thymidine. The cells are exposed to the radioactive

label in the medium or by injection into the intact animal for at least the full length of a

cell cycle (and usually for half again as long). Under these conditions, all cells that

synthesize DNA, thus indicating their passage through the S period of the cell cycle, are

labeled and can be identified by autoradiography. The percentage of cells that is

labeled constitutes the growth fraction, since every cell in cycle will have passed



through the S period at least once during exposure to the radioactive label (Alpen,

1998).

The radiobiological significance of the growth fraction was unclear until the

appearance of new data in the late 1980s. In 1980, Dethlefsen indicated that the role

of quiescent cells in radiobiological response was not satisfactorily delineated. Recent

studies indicate that cells that are out of cycle are capable of a more significant

amount of repair of potentially lethal damage, simply because there is more time

before the cell is called on to replicate its DNA. It is possible, but by no means proved,

that the concentration of enzymes necessary for repair of DNA damage may be

depleted in the noncycling cell, but, in spite of this, the additional time allows effective

repair to proceed with the lower concentration of repair enzymes (Alpen, 1998).

4.8 – CELL KINETICS IN NORMAL TISSUES AND TUMORS

Both normal and neoplastic tissues have a cellular kinetic pattern that follows

the accepted model of a G1-S-G2-M cycle, and, indeed, the cell cycle parameters are

not very different for tumors as compared to other growing tissues. The total cycle

time and the time devoted to DNA synthesis in the S period are very much alike for

both tissue types. However, there are significant differences in some of the

characteristics of the kinetic pattern as the tumor reaches a size where vascularization

is required for continued tumor growth. The orderly vascularization of normal tissues

that originates in embryonic life and that is maintained throughout the existence of

normal, nonpathological function assures that the supply of oxygen and nutrients is

adequate for survival of cells. Most, if not all, tumors, on the other hand, originate as

nonvascularized aggregations of cells and develop a vascular supply sometime after

the origination of tumor growth. The development of vascular supply in a tumor

depends on the activities of angiogenic factors that occur in normal tissues. The newly

developing vascular supply is, at best, chaotic and disorganized (Alpen, 1998).

Some parts of the tumor tissue will be so far from the source of oxygen and

nutrients that cell survival will be impossible, Figure 4.24. Other parts of the tumor will

have nutrient and oxygen supplies that are adequate only for survival of cells without

replication. The lack of oxygen and glucose can lead to a decrease in the growth



fraction, and probably to cell death and necrosis. Several nutrients and metabolic

products, including oxygen, glucose, and lactic acid, play an important role in the

determination of quiescent and proliferating cells in tumors (Alpen, 1998).

One important difference between normal tissues and tumor tissues is the

determinant of the fraction of quiescent cells in the organ or tumor. Because of the

orderly vascular architecture of normal tissue, the movement of cells from the

proliferating to the quiescent compartment is probably not the result of nutrient lack,

but, rather, the result of the activity of normal soluble growth factors and naturally

occurring inhibitors that regulate the growth and development of the tissue (Alpen,

1998).

4.9 – MODELS FOR RADIOBIOLOGICAL SENSITIVITY OF NEOPLASTIC TISSUES

The earliest attempts to assay the sensitivity of organized tissue systems were

directed at establishing the radiosensitivity of tumor tissues. This was partly because

these tissues offered opportunities for analysis that were not available for normal

tissues. The possibility for syngeneic transplantation of the cell lines from host to

recipient animal was the most important characteristic of these in vivo tissue systems.

Figure 4.24 - Role of hypoxia in tumour angiogenesis (from Carmeliet, 2000).



After irradiation of the tumor in the host in which it was growing, it was

possible to transplant the tumor cells to an unirradiated recipient animal and to

observe the growth response of the irradiated tumor cells. There was also strong

interest in understanding tumor biology arising from the treatment of cancer by

radiotherapy. It was important to establish the role of oxygen in the sensitivity of

cancer cells, as well as the importance of the fraction of G0 cells and repair or

repopulation in these tissues. The overall goal was practical: to maximize the

effectiveness of radiotherapy for cancer control in patients, while reducing damage to

normal tissues in the radiation field (Alpen, 1998).

4.9.1 – Hewitt Dilution Assay

Probably the first in vivo assay for mammalian tissues was that developed by

Hewitt and Wilson (1959) with a syngeneic mouse tumor system. At that time a

number of tumor cell lines that were grown in the peritoneal cavity of mice had been

developed. The cells from these ascites tumors could be harvested or allowed to

continue to grow in the peritoneal cavity of the host, which would cause the death of

the animal. It occurred to Hewitt and Wilson that this end point - death of the host

animal could be used to measure the clonogenic potential of the tumor cells after

irradiation. Figure 4.25 shows the essentials of a Hewitt assay for a single dose point at

10 Gy (Alpen, 1998).

Figure 4.25 - Typical data set for a Hewitt dilution assay (from Alpen, 1998).



Cells harvested from the mouse ascites tumor P388 and unirradiated cells were

collected from the donor and a series of dilutions was prepared from a stock

suspension of the tumor cells. A typical microbiological-type binary dilution was

carried out to produce cell suspensions with low concentrations of cells that will allow

the recipient animal to be injected with cell numbers that are correct for killing about

half of the animals. For the tumor line used, the usual cell dose required to kill half of

the animals is about two to three cells. A small number of animals (5-10) are injected

with the same cell dose and the survival is followed. The same procedure is used for

several additional cell doses. The resulting data on percent survival at each of the cell

doses are plotted as shown in Figure 4.25, and the LD50 (lethal dose for 50% of the

animals) is determined by graphical or analytical means. The procedure is repeated,

but with the cell suspension prepared from animals that were irradiated before cell

collection. Animals are irradiated at several doses and injections proceed as just

described for each dose. The LD50 values can be used to construct a survival curve.

Figure 4.25 shows an example for only one radiation dose on the right panel and for

unirradiated cells on the left panel, with the calculated surviving fraction. The surviving

fraction is estimated for each of the other doses, and a survival curve of surviving

fraction against dose is plotted in the usual way (Alpen, 1998).

The Hewitt assay has been the tool used for a number of significant studies of

tumor cell sensitivity to radiation. Figure 4.26 is a very good example of such studies.

Andrews and Berry (1962) developed survival curves for three mouse tumors, two

leukemias, and a sarcoma. Some of the data were Berry's own previously unpublished

observations and some were provided by Hewitt. The clonogenic survival curves were

developed for both anoxic and oxic conditions. All three cell lines could be plotted on

the same curve for oxic cells or for anoxic cells as appropriate, and the line produced

was a good fit for the appropriate condition of oxygenation. The oxygen enhancement

ratio (OER) for these cells was about 2.4, which is not far from the 2.8 or so for cell

lines that are irradiated in vitro and analyzed for clonogenic survival in vitro. The Do for

the cells irradiated under oxic conditions was about 150 cGy, and the extrapolation

number was about 3-4 for this set of data (Alpen, 1998).

A significant shortcoming of the dilution assay system is that donor cells that

are grown in ascites fluid are usually irradiated when the cell number in the peritoneal



cavity is very large. Under these conditions, it is not always clear that the cells are fully

oxygenated at the time of irradiation. If that is indeed the case, there is the possibility

of significant anoxic protection of the cells and, subsequently, there is an

overestimation of the resistance of the cells to the irradiation. The data reported in the

Berry study do not seem to be affected by such hypoxia. The Do (oxic) is about 150 cGy,

a number quite consistent with that found for many cell systems in vitro. The OER of

2.4 or so is, again, not very different from the 2.5-2.8 seen for in vitro systems. We

must conclude, at least for the cell lines reported in this study, that adequate

oxygenation probably existed at the time of irradiation (Alpen, 1998).

Another shortcoming of the Hewitt method is that the irradiated tumor cells

must be capable of expressing clonogenic potential while growing in the ascites

medium. For example, most leukemias grow readily in this environment, and usually

require an inoculum of only 1-3 cells to cause the death of 50% of the recipient

animals. For the Berry data just described, the sarcoma cells required an inoculum of

more than 80 cells to kill 50% of the recipients. In many cases no cell growth is seen

and no assay is possible. To avoid this shortcoming, other assays have been developed

(Alpen, 1998).

Figure 4.26 - The survival curve obtained by Berry (1964) via the Hewitt assay method for two mouse leukemias and a sarcoma (from Alpen, 1998).



4.9.2– Lung Colony Assay System

A modification to the Hewitt assay was developed by Hill and Bush (1969) to

measure clonogenic survival of cells derived from solid tumors. In principle, the assay

measures the clonogenic survival of tumor cells by determining their ability to form

colonies in the lung of recipient syngeneic mice. The cells from a tumor, irradiated

either in vivo or, after dissection and cell dissociation, in vitro, are injected into a

recipient mouse, and after 18-20 days the animals are killed, the lungs are dissected,

and the number of tumor colonies in the lung is counted. Hill and Bush were able to

demonstrate a linear relationship between cell number injected and the number of

colonies formed in the lung. A very large enhancement of the number of colonies in

the lung was found if, along with the experimentally irradiated cells, a large number of

heavily irradiated, nonclonogenic cells were injected. Typically, such a procedure

produced a 10-50-fold increase in the number of colonies formed from the clonogenic

survivors. Hill and Bush were not able to establish the mechanism of this

enhancement, but it was not due to an immune response on the part of the recipient.

Very consistent survival curves were obtained, and, for the KHT transplantable

sarcoma, the Do was 134 cGy, with an extrapolation number of about 9.5. Again, these

data were found to be quite consistent with the values found for the same tumor with

the Hewitt assay. Such an agreement not only validates the lung colony assay, it also

demonstrates that there was little protection from radiation damage due to partial

hypoxia for the KHT cells irradiated as solid tumors and tested by the dilution assay

(Alpen, 1998).

A significant limitation of the lung colony assay is that cells must be injected

into syngeneic recipient mice, that is, inbred mouse lines of the same genotype as that

from which the tumor is derived (Alpen, 1998).

4.10 – TUMOR GROWTH AND TUMOR “CURE” MODELS

Since there is a very limited set of models for examining the clonogenic

potential of tumor cells, much of the radiation biology of tumors has been developed

using a set of tools that was developed for general use in tumor biology. Therefore,



some of these tools have been more valuable than others for radiation effect studies

because of the inherent inability to effect precise quantitation.

4.10.1 – Tumor Volume versus Time

A widely used and relatively powerful tool in tumor radiobiology is the tumor

growth curve after implantation of an inoculum of cells, usually in the flank region of

recipient syngeneic mice or rats. The simplest application of the growth curve for

implanted tumors is the analysis on the increase rate of the tumor volume. For analysis

of the radiation effect we can measure the time for the tumor to reach a preselected

volume. The measurements of tumor volume are at best imprecise. The volume is

usually determined from a caliper measurement of two or more diameters of the

growing tumor and calculation of the volume from the average diameter (Alpen,

1998).

After the tumor has been irradiated, the time course of volume change is as

shown in Figure 4.27. There may be a slowing of growth for a brief time, followed by a

period of decreasing tumor volume. This decrease is due to lack of replacement of the

normal cell loss from tumors, associated with local necrosis, nutrient lack, or other

causes unrelated to the radiation exposure. It is not due to the interphase death of

cells as the result of irradiation. As the surviving clonogenic cells repopulate the tumor,

regrowth will be observed; the surviving clonogenic cells will ultimately produce

progeny exceeding the cell-loss factor (Alpen, 1998).

Figure 4.27 - Tumor volume versus time (from Alpen, 1998).



The criterion for measurement of the radiation dependent response is the time

for the cell volume to again reach the value observed at the time of irradiation. This

time is shown in Figure 4.27, and it is measured, as shown, as the time from irradiation

until the tumor volume achieves the value existing at the time irradiation occurred.

This time value is called the growth delay. The important limitation of the growth delay

model for testing the radiobiological response of tumors is that a significant number of

transplantable tumors does not show any decrease in the volume of tumor after

irradiation (Alpen, 1998).

Presumably, this failure to decrease in volume is the result of a small cell-loss

fraction in the growing tumor. When irradiation takes place, clonogenic activity is

reduced until repopulation from competent clonogenic cells occurs. During the period

before regrowth commences as the result of repopulation, the normally small cell-loss

fraction of the tumor does not lead to reduction in tumor volume. In these cases it is

necessary to revert to the simpler measure of tumor volume versus time and the use

of the time to reach a preset volume. Alternatively, differences in this time for control

and irradiated tumors may be taken as the end point (Alpen, 1998).

4.10.2 – TCD50, Tumor Cure

Another end point that is widely used in tumor biology is the dose required to

"cure" an implanted tumor. For this model, a large number of implanted tumors are

irradiated with graded doses at the same time period after implantation of the tumor

inoculum. The end point is the fraction of animals that has received a given dose in

which the growth of the tumor is controlled. This local control index can be plotted for

each of the doses, and the dose required to control tumor growth in 50% of the

animals is estimated by a variety of statistical techniques. This value is usually called

the 50% tumor cure dose -TCD50 (Alpen, 1998).

4.11 – RADIOBIOLOGICAL RESPONSES OF TUMORS

Using a number of end points, including dilution assay, lung colony assay,

primary cell cultures, and tissue derived in vitro cultures, it has been possible to define



rather clearly the radiobiological responsiveness of various tumor lines, both animal

and human. With only a few important exceptions, the various tumor cell lines in wide

and long term experimental use have been found to have clonogenic survival

characteristics that are generally stable and for which the relevant survival parameters

are not very variable, considering the range of cell types and tissues from which these

transformed and immortal cell lines have been derived (Alpen, 1998).

Rather different findings have been reported for the survival curve parameters

of freshly derived culture systems grown from naturally occurring malignant tumors.

Extensive efforts have been devoted to characterization of the radiosensitivity of cell

lines from human tumors. The best fit to the data for a large number of human cell

lines, both nontransformed fibroblasts and tumors, is the linear-quadratic (LQ) model.

The radiosensitivity of the various cell lines can be divided into three groups with a

very good correlation with the known responsiveness of the tumors to radiotherapy:

lymphomata, known to be highly curable, were the most radiosensitive of the derived

cell lines, and melanomata revealed to be the most resistant for tumor curability and

the most radioresistant in the survival of the cell lines in culture (Alpen, 1998).

It is important to realize that the immediate responsiveness of a tumor to

radiation, as determined by reduction in the tumor volume, does not necessarily

predict the curability of the tumor with high efficiency. The degree of responsiveness

will be determined by many of the cell kinetic parameters of the tumor system. A high

cell-loss factor and a high growth factor associated with a small fraction of cells out of

cycle and associated with inherent cellular radiosensitivity, will assure a high degree of

responsiveness of the tumor, as measured by volume changes. Curability, on the other

hand, will depend in a complex way on the ability of the few remaining clonogenic cells

to repopulate the tumor after irradiation is over (Alpen, 1998).

4.12 – HYPOXIA AND RADIOSENSITIVITY IN TUMOR CELLS

Under circumstances where severe anoxia can occur in tissues or cellular

preparations, one should expect to see significant protection from the effects of

ionizing radiation. It is expected to find conditions of moderate to severe anoxia in

growing tumors in vivo. For cells grown in suspension, careful attention to culture



conditions usually will prevent the development of such anoxic conditions with

concomitant radioprotection. For the tissue assay systems, such as the Hewitt dilution

assay and others, there is clearly a protective effect of oxygen lack under the correct

conditions. Figure 4.26 shows such radioprotection for cells deliberately made anoxic

by killing the host animal or by allowing the cell number for cells growing in the

peritoneal cavity to reach very high levels. Figure 4.28 demonstrates methods by which

the fraction of hypoxic cells in a mixture with fully oxygenated cells can be detected

and measured quantitatively. The radioresistant "tail" for the dashed line survival

curve shown in Figure 4.28 (10% anoxic cells) is a common observation for cells from

tumors and indicates the presence of a mixed population of cells, part of which have a

radioresistance relative to the remainder of the population. This resistant fraction may

be due to hypoxia and the radioprotection that this state affords (Alpen, 1998).

Figure 4.28 - Survival curve for the irradiation of a cell suspension containing a fraction of hypoxic cells (from Alpen, 1998).



The well known work of Thomlinson and Gray (1955) laid the foundations for

our understanding of hypoxia as well as reoxygenation in tumors during growth and

regrowth. Figure 4.29 (from Thomlinson, 1967) illustrates the processes proposed by

this author. The very young tumor is well oxygenated, since it is so small that no cells

are beyond the effective diffusion distance of oxygen from nearby capillaries. As the

tumor continues to grow, portions of the tumor volume may be beyond easy access to

diffusing oxygen. The tumor must depend for its supply of oxygen on the development

of newly formed vessels that arise from the adjacent normal tissue and penetrate the

tumor volume. This neovascularization of the tumor is not as well organized as the

blood supply in normal tissues, and the expanding volume of tumor will contain

regions in which oxygen is inadequate for the maintenance of metabolism, and some

fraction of the cells will be anoxic. Figure 4.29 illustrates that the fraction of anoxic

cells in the growing tumor may rise to several percent and in some tumor types, to as

much as 10%. According to the model of Thomlinson, when the tumor is irradiated

(position R1 in the figure) the more radiosensitive, fully oxygenated cells are killed, and

the remaining hypoxic cells are in an environment of dead and dying cells with lesser

demand for metabolic oxygen (Alpen, 1998).

Figure 4.29 - Development of hypoxia and reoxygenation in an irradiated tumor (from Alpen, 1998).



Shrinking of the tumor volume and lowered oxygen demand allow for

reoxygenation of the hypoxic cells, which is indicated by a rapid fall to near zero for the

anoxic fraction. After this period of reoxygenation, tumor regrowth commences and

the complete cycle is repeated. The significance of the reoxygenation phase in

fractionated radiotherapy of human tumors is undergoing careful reexamination,

partly because treatment modalities designed to optimize the kill of anoxic cells (high

linear energy transfer (LET) radiation, radiation under hyperbaric oxygen conditions,

and so on) have not been particularly successful. According to Figure 4.29, the

optimum time for a second irradiation of a fractionated scheme would be at point H in

the curve, when the population of hypoxic clonogenic cells is at a minimum. Recent

data suggest that the reoxygenation phenomenon actually occurs very soon after

irradiation, and indeed may take place while the irradiation is in progress (Alpen,

1998).

4.13 – SUMMARY

Human tumors strongly differ in radiosensitivity and radiocurability and this is

thought to stem from differences in capacity for repair of sub-lethal damage.

Radiosensitivity varies along the cell cycle, S being the most resistant phase and G2 and

M the most sensitive. Therefore, cells surviving an exposure are preferentially in a

stage of low sensitivity (G1), i.e. synchronized in a resistant cell cycle phase. They

progress thereafter together into S and then to the more sensitive G2 and M phases. A

new irradiation exposure at this time will have a larger biological effect (more cell kill).

However, while this synchronization effect has explained some experimental results,

redistribution has never been shown to play a measurable role in the clinic of

radiotherapy (Mazeron, 2005).

Cells surviving an irradiation keep proliferating, increasing the number of

clonogenic cells, i.e. the number that must eventually be sterilized to eradicate cancer.

An inappropriate development of intratumoral vasculature leads to a large proportion

of poorly oxygenated cells and the proportion of hypoxic cells increases with the tumor

size (Mazeron, 2005).



Acutely hypoxic cells are far more radioresistant than well oxygenated cells.

Hypoxic cells usually survive irradiation, but they progressively (re)oxygenate due to

the better supply of oxygen available after well oxygenated cells have died. This

restores radiosensitivity in the tumor by several mechanisms, but re-oxygenation

occurring at long intervals is probably due to tumor shrinkage leading to a reduction of

the intercapillar distance (Mazeron, 2005).

The effects of ionizing radiation, even at low doses, are potentially capable of

causing serious and lasting biological damage. The potentially harmful effects of

ionizing radiation must be recognized and understood. It is important that radiologists

should have a good appreciation of the risks associated with the examinations they

carry out.

CHAPTER V

CELL CULTURE AND FLOW CYTOMETRY

CHAPTER V – CELL CULTURE AND FLOW CYTOMETRY



Cell culture is an invaluable tool for researchers in numerous fields. It facilitates

the analysis of biological properties and processes that are not readily accessible at the

level of the intact organism. Successful maintenance of cells in culture, whether

primary or immortalized, requires knowledge and practice of a few essential

techniques (Helgason, 2005).

The use of cells in analytical chemistry, engineering, and biology requires a

dedicated space for cell culture and maintenance. The proper handling of cells and

tissues requires a level of diligence and constant education, to mitigate health and

safety risks. Cell culture requires a system of mutual separation of sample and scientist

to avoid contamination of either. Each time a culture flask and the dish is opened is, in

essence, an opportunity for a single bacterium or fungal cell to ruin an experiment.

Likewise, every time cell cultures or tissues are handled, there is a risk to the scientist.

It is therefore needed to understand the protective countermeasures required to

handle cells properly (Pappas, 2010).

This chapter presents the importance of the laboratory conditions in the

manipulation and maintenance of cell culture. Subsequently, it is explained the

cytogenetic analysis of cell line and I performed a description of the methods to induce

cell cycle checkpoints. In the end of the chapter, it is presented a description of the

methods for synchronizing mammalian cells and the analysis of the mammalian cell

cycle by flow cytometry.

5.2 - CELL-CULTURE LABORATORY

Setting up a laboratory (or space within an existing lab) for cell culture is not a

daunting task, but requires some planning and strict adherence to regulations. Most

universities, research institutes, and hospitals have a safety committee (some

committees specialize in biosafety) that is in place in part to help a research establish a

cell lab. While the government guidelines typically set the standard for safety rules, the

research institution may have additional guidelines to follow. Therefore, the safety



committee is therefore indispensable in the planning and setting up of a cell lab, as

well as in the subsequent (and often frequent) safety inspections. The main issues

when setting up and maintaining a culture lab are safety, sterility, and contamination.

All three of these issues are linked by the common safe practices and proper use of

equipment, and all three require that individuals working in the lab are properly

educated (Pappas, 2010).

Working in the lab requires universal precautions, assuming that all cell cultures

and related materials may contain hazardous pathogens. This assumption maintains a

more vigilant attitude, and reduces the risk of accidental exposure to a real pathogen.

Moreover, the possibility that cultures can be cross-contaminated requires additional –

albeit similar – precautions. In short, careful procedures will result in productive

research in a safe environment for cells and individuals. For those new to cells and cell

culture, this chapter will not only serve as an introduction to the tools required for a

cell lab, but will also detail some of the practical aspects to setting up a culture facility.

For those with cell culture experience, the discussion of analytical equipment should

prove useful (Pappas, 2010).

5.3 – MAINTAINING CULTURES

The proper maintenance of cells includes homeostasis during culture, cell

storage and the correct preparation of cells for analysis. The latter case is of the most

importance, as often analysis and homeostasis are incongruent. Buffers must be

changed, different media used, and the cells, at times, are exposed to drastically

diverdse conditions for analysis. In some cases, the change in conditions can affect the

outcome of the experiment negatively. In other instances, the conditions suitable for

cell analysis are fatal to the cell (e.g., electron microscopy). There are many works

available on the culture of almost every cell type imaginable (Pappas, 2010).

When culturing primary or immortal cells for analysis, sterility and cross-

contamination must also be monitored at all times. A few bacteria in a sample can

wreak havoc in a short time, rendering any analytical data useless. The cross-

contamination of cultures is at best a nightmare, as extensive genetic testing is

required to purify cell populations and yield accurate data. Considering the cost of



cells, reagents, instrumentation, and lab upkeep, at least as much thought should be

placed on the maintenance of cell cultures for appropriate analysis. The type of

environment the cell encounters can directly affect the outcome of an analytical

experiment: cell-growth conditions, analysis buffers and reagents can affect the cell

phenotype, cell signaling, and a host of other parameters. By careful maintenance of

primary and immortal cells, accurate and reproducible cell analyses can be conducted

(Pappas, 2010).

5.3.1 – Medium

More than any other reagent in a cell-analysis laboratory, a steady supply of

culture medium – and the choice of correct medium type – is essential for cell analysis.

There are, in general, two classes of medium one can consider for cell analysis. First,

medium that is used to maintain a culture in between experiments, and second,

medium used in the analysis itself. Often these two can be one in the same, although

in some cases a modified medium or supplemented buffer is needed during the

analysis or processing phase (Pappas, 2010).

There are many types of medium available and the supplements that can be

added to them expand the palette of options even further. Table 4.1 lists some

medium types that are common to cellular analysis, by cell type. The table is not

inclusive, but serves to highlight the differences in medium types, and that some

medium formulations are applicable to many cell lines. In most cases, the medium in

Table 4.1 is used during the culture (maintenance) phase, and a different buffer or

medium may be used during the analysis itself (Pappas, 2010).

Medium can be classified as basic or complete, depending on whether or not

serum is included, respectively. Basic medium has many of the components required

for cell metabolism. Basic media, such as DMEM and RPMI 1640 (see Table 4.1),

contain salts (partly from buffer action), amino acids, vitamins (such as biotin, folic

acid, B-12, etc.), and molecules involved in energy production (glucose, pyruvate).

Basic medium also often contains other buffers (such as HEPES) and a colorimetric

acid–base indicator, such as phenol red. The latter serves as a quick visual inspection



of the “age” of the medium in culture. As cells consume nutrients and produce waste,

the culture medium acidifies, resulting in a shift in color for the pH indicator. The

formulations of most culture media are available and should be examined for potential

interference in the analysis. For example, staining using Annexin-V-based apoptosis

probes requires relatively high Ca2+ concentrations and at the same time, the presence

of phenol red in the medium will interfere with fluorescence measurements of

fluorescein, green fluorescent protein (GFP), and other fluorophores with similar

emission spectra. Fluorescence from phenol red itself makes sensitive fluorescence

measurements nearly impossible (Pappas, 2010).

Table 1 – Medium types common to cell analysis (from (Pappas, 2010))

Medium Serum Additives Cell lines

RPMI 1640 10% FBS Antibacterial-Antifungal

Jurkat, HuT 78, RPMI

8226, CCRF-CEM, U937,

HL-60

Dulbecco`s modified

Eagle Medium (DMEM) 10% FBS

Antibacterial-Antifungal,

L-Glutamine

NIH 3T3, RBL-1, HT-29,

HeLa

Clavcomb`s Medium 10% FBS

Antibacterial-Antifungal,

Norepunephrine, L-

Glutamine

HL-1

Cell Mab 0-10% FBS Varies

Designed for

monoclonal antibody

production

Leibovitz`s L-15 Hemolymph Bag neuronal cells

Eagle`s Minimum

Essential Medium 0-10% FBS L-Glutamine

F-12 0-10% FBS L-Glutamine Designed for primary

cells

Iscove`s Modified

DMEM 0-10% FBS L-Glutamine HuT 78 T Cells

FBS = Fetal Bovine Serum

Medium is, in essence, a man-made attempt to mimic the life support found in

vivo. It is, therefore, lacking in many essential compounds for cell growth. Many cell



lines can function in basic medium without additional materials, but for the most

routine culture and analysis, serum must be added to form the complete medium

(Pappas, 2010).

Serum is typically derived from animal sources, the most common being fetal

bovine serum (FBS). FBS and other sera contain growth factors such as epidermal

growth factor (EGF), some interleukins, and transferrin. Furthermore, present are

adhesion-promoting proteins and peptides, for example, fibronectin and laminin and

other components including insulin and various minerals. FBS and other animal-based

sera are by far the most common supplements used for culture maintenance (Pappas,

2010).

Being derived from animal sources, serum is inherently difficult to use from a

quality-control perspective and since it is derived from different animal types this can

affect experiment outcome. For example, the use of FBS instead of native rat serum

was shown to affect the outcome of rat leukocyte immunological response. In addition

to species variability, serum varies from lot to lot, as well as by country of origin, so if

cell products are to be analyzed over long time periods (months of experimentation) it

is best to purchase a large quantity of serum from one particular lot. Given the high

cost of medium, this may not always be practical since serum cost increases as the

level of quality control improves. The more consistent and well characterized the

medium, the higher the cost (Pappas, 2010).

Another negative aspect of dealing with serum is that the serum, or animal of

origin, is subject to contamination, just like any other primary derived material. Certain

viruses, bacteria, and mycoplasma have been shown to be transmitted via serum.

There are several replacement sera that can be substituted for FBS. For example, the

FetalClone series and Bovine Growth Serum, both from HyClone, are non-fetal animal

sera supplemented with various growth factors, minerals, and other compounds. Since

they are not derived from fetal animals, there is less variability between lots (especially

for the added compounds). None of the alternative sera offers much relief as far as

cost is concerned, but the increase in quality control is a major improvement (Pappas,

2010).

Some cells readily grow in serum-free medium; most, however, must be

acclimated to a serum-free environment. This requirement is especially true if the cell



line in question is already being cultured in serum-enriched medium (typically 10%

v/v). It is possible to reduce serum content in medium; in some cases, it is advisable to

do so, because reducing the amount of serum added can reduce costs, as serum is the

most expensive component of the complete medium. Reducing serum also lowers the

total protein content of the medium, facilitating collection of cell products, and

minimizing sources of contamination. For cells growing in serum-enriched medium, a

method of systematically reducing medium can be implemented (Pappas, 2010).

One must first consider the growth of cells in culture, before discussion of how

to achieve serum reduction can initiate, Figure 4.1. Cell growth in culture – whether

the cells are adherent or suspended – is characterized by several stages. The lag phase,

during which minimal or no cell division occurs, is a brief period after inoculation. The

lag phase occurs as cells adjust to a new cell-culture environment, and as adherent

cells begin the process of reattaching to the culture substrate. The lag phase is

followed by the log or exponential phase. This is the major phase of cell division. The

doubling time, an indicator of cell growth, is determined during this period (Pappas,

2010).

Figure 5.1 - Cell growth in culture (from (Pappas, 2010)).

The time for the cell population to double, Figure 5.1, can be determined at any

point during the log phase, although it is most accurate at the center of that phase.

After the log phase, the culture reaches the stationary phase (Pappas, 2010).

High cell density, contact inhibition, and consumption of nutrients signal a

slowing of the cell cycle, and the cell concentration remains constant. Cell crowding,



depletion of nutrients and accumulation of waste eventually causes a sharp drop in cell

concentration, called the death phase. This latter phase can be confirmed by

microscopy, where the presence of a large number of dead cells, cell debris, and

acidified medium (if an indicator is present) can be observed (Pappas, 2010).

The glucose content of basic medium varies and is sometimes supplemented

with additional glucose. The high glucose content of many medium types is intended

to stimulate growth of the culture. However, some cell lines change phenotypic

properties in high or low glucose. When culturing for conditions close to those

encountered in vivo, the glucose concentration should be adjusted to reflecting the

physiological value as much as possible. Like serum reduction, the impact of changes in

glucose concentration can be monitored using the culture doubling time (Pappas,

2010).

When formulating complete medium, care must be taken to preserve sterility

of the final mixture. If all components are sterile to begin with, then aseptic handling in

the biosafety cabinet will prevent contamination of the complete medium. If any of

the reagents are not sterile at the onset, then filtration can be employed to remove

contaminating organisms.

5.3.2 – The use of medium in analysis and alternatives

Medium is primarily used to maintain cultures and samples before analysis. The

medium can also be used during the analysis; in other instances, components of the

medium may produce artifacts or otherwise interfere. The presence of several

components of medium can interfere with fluorescence measurements. Phenol red,

one of the most common pH indicators added to medium, has a broad absorption

band that interferes with most green fluorescence. Phenol red is also weakly

fluorescent, creating an additional problem for green-emitting fluorophores. If the cell

homeostasis is not required, then any buffer devoid of phenol red will work for

fluorescence. On the other hand, if the cells are to be kept alive for long periods, then

phenol-red-free medium is available from most medium manufacturers. In addition to

the weakly fluorescent properties of phenol red, other compounds present at



relatively high concentrations can interfere with fluorescence detection. Riboflavin is

also weakly fluorescent, but the relatively large volume of the medium contributes to

an unacceptable background signal. Proteins such as albumin, one of the major

components of serum, also contribute strongly to autofluorescence of medium. The

exact medium used for culture depends on the cell type, the culture conditions, and

the desired end result. For analysis, a similar selection process must be undertaken.

The final medium or buffer used for analysis must be of low background, minimal

interference, and – when possible – capable of sustaining cell viability and function for

the experiment duration (Pappas, 2010).

5.4 – CYTOGENETIC ANALYSIS OF CELL LINES

5.4.1 - The Utility of Cytogenetic Characterization

Countless cell lines have been established—more than 1000 from human

hematopoietic tumors alone —and the novelty and utility of each new example should

be proven prior to publication. For several reasons, karyotypic analysis has become a

core element for characterizing cell lines, mainly because of the unique key

cytogenetics provides for classifying cancer cells. Recurrent chromosome changes

provide a portal to underlying mutations at the DNA level in cancer, and cell lines are

rich territory for mining them. Cancer changes might reflect developmentally

programmed patterns of gene expression and responsiveness within diverse cell

lineages. Dysregulation of certain genes facilitates evasion of existing antineoplastic

controls, including those mediated by cell cycle checkpoints or apoptosis. The

tendency of cells to produce neoplastic mutations via chromosomal mechanisms,

principally translocations, duplications, and deletions, renders these changes

microscopically visible, facilitating cancer diagnosis by chromosome analysis. Arguably,

of all neoplastic changes, those affecting chromosomal structures combine the

greatest informational content with the least likelihood of reversal. This is particularly

true of the primary cytogenetic changes that play key roles in neoplastic

transformation and upon the presence of which the neoplastic phenotype and cell

proliferation ultimately depend. Nevertheless, the usefulness of karyotype analysis for



the characterization of cell lines lies principally among those derived from tumors with

stronger associations with specific chromosome rearrangements (i.e., hematopoietic,

mesenchymal, and neuronal, rather than epithelial tumors) (Helgason, 2005).

Cytogenetic methods facilitate observations performed at the single-cell level,

thus allowing detection of intercellular differences. Accordingly, a second virtue of

cytogenetic data lies in the detection of distinct subclones and the monitoring of

stability therein. Except for doublings in their modal chromosome number from 2n to

4n “tetraploidization,” cell lines appear to be rather more stable than is commonly

supposed. Indeed, chromosomal rearrangement in cells of the immune system could

reach peak intensity in vivo during the various phases of lymphocyte development in

vivo. A further application of cytogenetic data is to minimize the risk of using false or

misidentified cell lines. At least 18% of new human tumor cell lines have been cross-

contaminated by older, mainly “classic,” cell lines, which tend to be widely circulated.

This problem, first publicized over 30 years ago but neglected of late, poses an

insidious threat to research using cell lines (Helgason, 2005).

In the event of cross-contamination with cells of other species, cytogenetic

analysis provides a ready means of detection. Although modal chromosome numbers

were formerly used to identify cell lines, their virtue as descriptors has declined along

with the remorseless increase in the numbers of different cell lines in circulation. Thus,

species identification necessarily rests on the ability to distinguish the chromosome

banding patterns of diverse species. Fortunately, cells of the most prolific mammalian

species represented in cell lines (primate, rodent, simian, as well as those of domestic

animals) are distinguishable by experienced operators (Helgason, 2005).

5.5 – METHODS TO INDUCE CELL CYCLE CHECKPOINTS

The way cells respond to radiation or chemical exposure that damages

deoxyribonucleic acid (DNA) is important because induced lesions left unrepaired, or

those that are misrepaired, can lead to mutation, cancer, or lethality. Prokaryotic and

eukaryotic cells have evolved mechanisms that repair damaged DNA directly, such as

nucleotide excision repair, base excision repair, homology-based recombinational

repair, or nonhomologous end joining, which promote survival and reduce potential



deleterious effects. However, at least eukaryotic cells also have cell cycle checkpoints

capable of sensing DNA damage or blocks in DNA replication, signaling the cell cycle

machinery, and causing transient delays in progression at specific phases of the cell

cycle. These delays are thought to provide cells with extra time for mending DNA

lesions before entry into critical phases of the cell cycle, such as S or M, events that

could be lethal with damaged DNA (Lieberman, 2004).

The precise mechanisms by which checkpoints function is under intensive

investigation and details of the molecular events involved are being pursued

vigorously. This owes not only to the complexity and the intellectually and technically

challenging aspects of the process but also to the relevance of these pathways to the

stabilization of the genome and carcinogenesis. Nevertheless, it is clear that

checkpoint mechanisms are very sensitive and can be induced by the presence of

relatively small amounts of DNA damage. For example, in the yeast Saccharomyces

cerevisiae, as little as a single double-strand break in DNA can cause a delay in cell

cycle progression. One important aspect of studying cell cycle checkpoint mechanisms

is an understanding of how to induce the process (Lieberman, 2004).

The application of radiations, such as gamma rays and ultraviolet (UV) light, are

capable of causing DNA damage, and thus leading to the induction of cell cycle

checkpoints. Certain chemicals or the use of temperature- sensitive mutants to disrupt

DNA replication, are also used routinely to induce checkpoints. Gamma rays cause

primarily single- and double-strand breaks in DNA but can infrequently induce

nitrogenous base damage as well. In contrast, UV light (i.e., 254 nm) causes a

preponderance of bulky lesions, such as pyrimidine dimers, although single-base

damage and strand breaks are a smaller part of the array of lesions that can be

produced. Regulation of cell cycle checkpoints induced by ionizing radiation versus UV

light is mediated by overlapping but not identical genetic elements (Lieberman, 2004).

5.6 – METHODS FOR SYNCHRONIZING MAMMALIAN CELLS

When studying cell cycle checkpoints, it is often very useful to have large

numbers of cells that are synchronized in various stages of the cell cycle. A variety of

methods have been developed to obtain synchronous (or partially synchronous) cells,



all of which have some drawbacks. Many cell types that attach to plastic culture dishes

round up in mitosis and can then be dislodged by agitation. This mitotic shake-off

method is useful for cells synchronized in metaphase, which on plating into culture

dishes move into G1 phase in a synchronous manner. A drawback to the mitotic shake-

off method is that only a low percentage (2–4%) of cells are in mitosis at any given

time, so the yield is very small. Also, cells rapidly become asynchronous as they

progress through G1 phase, so the synchronization in S phase and especially G2 phase is

not very good. The first limitation can be overcome by plating multiple T150 flasks with

cells, using roller bottles, or blocking cells in mitosis by inhibitors such as Colcemid or

nocodazole (Lieberman, 2004).

Mitotic cells that are collected can be held on ice for an hour or so while

multiple collections are done to obtain larger numbers of cells. To obtain more highly

synchronous populations of cells in S phase, the mitotic shake-off procedure can be

combined with the use of deoxyribonucleic acid (DNA) synthesis inhibitors, such as

hydroxyurea (HU) or aphidicolin (APH), to block cells at the G1/S border (but probably

past the G1 checkpoint). APH inhibits DNA polymerase α, whereas HU inhibits the

enzyme ribonucleotide reductase, though it may operate by other mechanisms also.

On release from the block, cells move in a highly synchronized fashion through S phase

and into G2 phase. In terms of the number of synchronized cells, this method has the

same limitation as discussed above, because the starting cell population derives from

the mitotic shake-off procedure. In addition, the block of cells with drugs can cause

unbalanced cell growth, so one cannot necessarily conclude that all biochemical

processes are also synchronized (Lieberman, 2004).

Large numbers of synchronous cells can be obtained using centrifugal

elutriation, Figure 5.2. This method requires the use of a special rotor in a large floor

centrifuge and separates cells into the cell cycle based on cell size. Cells may be

obtained in early or late G1 phase, or primarily in S phase. However, the cell

populations are not highly synchronous in S phase but instead have significant

populations of G1- and G2-phase cells included. Nevertheless, it is possible to

synchronize very large numbers of cells using this method, and biochemical processes

are not perturbed (Lieberman, 2004).



Figure 5.2 - Centrifugal elutriation (from (Wahl, 2001)).

Another method that results in highly synchronous populations is based on

labeling cells with a viable dye for DNA (Hoechst 33342). Cells stained with this dye can

then be sorted by cell cycle phase. Sorted G1 cells will be distributed throughout G1,

cells in S phase can be sorted into a small window in S phase and thus will be highly

synchronized, but only a small number of cells can be obtained. G2 phase cells will be

contaminated with late S phase cells. Furthermore, some cell types do not stain well

with Hoechst 33342, so sufficiently good DNA histograms cannot be obtained Hoechst

33342 (Lieberman, 2004).

5.7 – ANALYSIS OF THE MAMMALIAN CELL CYCLE BY FLOW CYTOMETRY

One of the most common uses of flow cytometry is to analyze the cell cycle of

mammalian cells. Flow cytometry can measure the deoxyribonucleic acid (DNA)

content of individual cells at a rate of several thousand cells per second and thus

conveniently reveals the distribution of cells through the cell cycle (Lieberman, 2004).

The DNA-content distribution of a typical exponentially growing cell population

is composed of two peaks (cells in G1/G0 and G2/M phases) and a valley of cells in S

phase, Figure 5.3. G2/M-phase cells have twice the amount of DNA as G1/G0-phase

cells, and S-phase cells contain varying amounts of DNA between that found in G1 and



G2 cells. Most flow-cytometric methods of cell cycle analysis cannot distinguish

between G1 and G0 cells or G2 and M cells, so they are grouped together as G1/G0 and

G2/M. However, there are flow cytometric methods that can distinguish four or even

all five cell cycle subpopulations: G0, G1, S, G2, and M. Furthermore, each

subpopulation can be quantified. Obviously, flow cytometry with these unique

features is irreplaceable for monitoring the cell cycle status and its regulation

(Lieberman, 2004).

Figure 5.3 - A typical cell cycle distribution of DNA content (from (Cooper,2004)).

Cell cycle checkpoint genes are key elements in cell cycle regulation.

Checkpoint gene mutation can lead to defects in one or more cell cycle checkpoint

controls, which can then result in cell death or cancer. Many of the cell cycle

checkpoint genes are tumor suppressors, such as p53, ataxia-telangiectasia mutant

(ATM), ataxia-telangiectasia and Rad3 (ATR), and BRCA1 (Lieberman, 2004).

In mammalian cells, the cell cycle checkpoint controls that can be analyzed by

flow cytometry are G1 arrest, suppression of DNA replication, and ATM dependent as

well as independent G2 arrest. Exposure to a genotoxic agent can activate some or all

the checkpoints (Lieberman, 2004).

5.8 – CONCLUSION

Effective in vitro maintenance and growth of animal cells requires culture

conditions similar to those found in vivo with respect to temperature, oxygen and



carbon dioxide concentrations, pH, osmolality, and nutrients. Within normal tissue in

vivo, animal cells receive nutrients through blood circulation. For growth in vitro,

animal cells require an equivalent supply of a complex combination of nutrients. For

this reason, the first attempts in animal cell culture were based on the use of biological

fluids such as plasma, lymph and serum, as well as on extracts from embryonic-derived

tissue (Castilho, 2008).

Medium composition is one of the most important factors in the culture of

animal cells. Its function is to provide appropriate pH and osmolality for cell survival

and multiplication, as well as to supply all chemical substances required by the cells

that they are unable to synthesize themselves. Some of these substances can be

provided by a culture medium consisting of low molecular weight compounds, known

as basal media. However, most basal media fail to promote successful cell growth by

themselves and require supplementation with more complex and chemically

undefined additives such as blood serum (Castilho, 2008).

Some cultivation processes are based on operational strategies that allow cells

to remain viable, but in a nonproliferative state, so as to prolong the productive phase

and to increase the productivity of the process. By these strategies cell proliferation

may be controlled by adding chemical additives that arrest the cell cycle, usually in the

G1 phase, increasing specific productivity. However, concomitantly undesirable effects

such as cytotoxicity may be observed, which result in a decrease in cell viability and in

the impossibility of maintaining the culture in a nonproliferative state for long periods

of time. Deprivation of specific nutrients and growth factors can also stop cell

proliferation, but in this case cell viability decreases and programmed cell death –

apoptosis – is activated. Currently, much research on the biochemical control of cell

cultures based on preventing the cell death mechanisms, to avoid cell death instead of

inhibiting cell growth, is being carried out with the aim of prolonging the productive

period of a cell culture process (Castilho, 2008).

Any process, industrial or laboratory-based, presents a series of important

variables that represent its state. In the case of cell culture, there are the variables

related to the environment to which the cells are exposed, such as temperature, pH,

dissolved oxygen, nutrients in the culture medium, and metabolite concentrations, as



well as those related to the cell itself, such as concentration, average size, or the

profile of intracellular enzyme activities (Castilho, 2008).

CHAPTER VI

BRACHYTHERAPY

CHAPTER VI – BRACHYTHERAPY



Brachytherapy was for many years in a state of decline, principally because of

the radiation hazards to users and those associated with the management of patients.

The introduction of afterloading machines in the 1960s provided the means to control

the movement and position of individual radioactive sources and greatly reduced the

radiation exposure to staff. As a result, brachytherapy underwent a renaissance and

provided the necessary stimulus to promote the development of afterloading

brachytherapy techniques. These developments have been further supported by the

availability of nuclides, particularly cobalt-60, cesium-137, and iridium-192 and, more

recently, radioactive seeds of iodine-125 and palladium-105. In parallel with the

technological advances in afterloading machines, there have been major

developments in imaging techniques and computerized planning (Joslin, 2001).

Cancer management generally has undergone major advances since the 1960s

and brachytherapy has played an increasingly important role. The optimal

management of cancer patients requires expert teams who specialize in certain cancer

sites within which brachytherapy may have a specific place. Much of this work is now

being provided on an outpatient or day-care basis and prolonged hospital stay is

proving to be unnecessary (Joslin, 2001).

This chapter starts with a brief explanation of the brachytherapy fundaments to

further understand the mechanisms used by this technique to kill the cancer cells. So,

it will be made a description of the sources used in brachytherapy followed by an

approach of the radiobiology of brachytherapy. At the end of the chapter a description

is made about the dose-rate effect in human cells and a brief come up about predictive

assays for radiation oncology.

The present chapter is central in this thesis project since it is with this

technique that the cancer cells will be killed. The changes that occur in the cells will be

analyzed by image processing and analysis techniques.



6.2 – BRACHYTHERAPY

The different types of radiation applied for radiobiological research has one

important issue: there the determination of the biological effectiveness of ionizing

photon radiation as a function of photon energy represents a major scientific

objective. Very intense, low-energetic, quasi-monochromatic, and energy tunable (10–

100 keV) channeling radiation (CR) is generated by channeling of relativistic electrons

in diamond crystals (Zeil, 2009).

Usually radiobiological studies are performed on conventional high-voltage X-

ray tubes or medical acceleration facilities. Both sources deliver broad polychromatic

bremsstrahlung with a high photon flux. Thus, therapeutic dose values (few Gy per

daily fraction) can be delivered in a sufficiently small irradiation duration (dose rate ≈1

Gy/min) to be independent from repairing processes in human cells. Due to the high

reproducibility of beam parameters of conventional radiation sources, a large number

of samples can be irradiated in stable conditions in order to cope with the biological

diversity. Considering the dosimetry a standardized radiation field is used. All changes

in the radiation geometry resulting in differences of beam absorption, scattering or

dose build up effect are taken into consideration by applying tabled correction factors.

In practical irradiation experiments, cell samples are irradiated at a vertical beam and

the delivered dose is controlled by presetting certain irradiation duration (Zeil, 2009).

Brachytherapy (sometimes referred to as curietherapy or endocurie therapy) is

a term used to describe the short distance treatment of cancer with radiation from

small, encapsulated radionuclide sources. This type of treatment is made by placing

sources directly into or near the volume to be treated. The dose is then delivered

continuously, either over a short period of time (temporary implants) or over the

lifetime of the source to a complete decay (permanent implants). Most common

brachytherapy sources emit photons; however, in a few specialized situations β or

neutron emitting sources are used. There are two main types of brachytherapy

treatment (Suntharalingam, 2002):

Intracavitary, in which the sources are placed in body cavities close to the

tumor volume;

Interstitial, in which the sources are implanted within the tumor volume.



The biological effects of radiotherapy depend on dose distribution, treated

volume, dose rate, fractionation and treatment duration. However, these various

factors are of different importance in determining the outcome of external beam

radiotherapy or of brachytherapy (Suntharalingam, 2002).

In brachytherapy, the dose is prescribed to an isodose encircling a small

targeted volume with a very heterogeneous dose distribution. It is minimal at distance

of the radioactive sources, but much higher doses and dose rates are delivered in their

immediate vicinity (Suntharalingam, 2002).

Therefore, the average dose given to the targeted volume is always higher than

the prescribed dose, prescribed at the periphery of the target. This is an important

point to notice as the treatment report contains information regarding only the dose

and dose rate at the reference isodose (Suntharalingam, 2002).

Another distinct feature of brachytherapy is that the doses within an implant

are higher than the tolerance dose levels accepted in external beam irradiation, yet

they are well tolerated because of the volume-effect relationship (very small volumes

can tolerate very high dose levels) (Suntharalingam, 2002).

Finally, time-dose factors differ widely between external beam radiotherapy

and brachytherapy. In external beam radiotherapy, the total dose is delivered in small,

daily fractions of a few seconds or minutes, allowing for full repair between exposures.

The treatment is protracted over several weeks. In contrast, in brachytherapy the dose

is delivered continuously, and treatments tend to be short (several hours to several

days). However, there is a variety of schedules depending on the type of equipment

used (Suntharalingam, 2002).

According to International Comission on Radiation Units & Measurements

(ICRU) report 38, treatment dose rates fall into three categories (Mazeron, 2005):

Low Dose Rate (LDR) brachytherapy ranges between 0.4 and 2 Gy/h. On the

other hand, in routine clinical practice, LDR brachytherapy is usually delivered

at dose rates between 0.3 and 1 Gy/h. This is compatible with conventional

manual or automatic afterloading techniques.



Medium Dose Rate (MDR) brachytherapy ranges between 2 and 12 Gy/h. MDR

can also be delivered by manual or automatic afterloading, although the latter

is far more frequent.

High Dose Rate (HDR) brachytherapy delivers the dose at 12 Gy/h or more, and

only automatic afterloading can be used because of the high source activity.

A new category is pulsed dose rate (PDR) brachytherapy, which delivers the

dose in a large number of small fractions with short intervals, allowing only for

incomplete repair, aiming at achieving a radiobiological effect similar to low dose rate

over the same treatment time, typically a few days. Finally, permanent implants

deliver a high total dose (for example, 150 Gy) at a very low dose rate, over several

months (Mazeron, 2005).

6.3 – SOURCES IN BRACHYTHERAPY

6.3.1 – RADIUM

Radium was discovered by Marie Curie in 1898. Within 3 years of this discovery,

the first patients were treated with radium implanted into their tumors (Joslin, 2001).

In the UK, St Bartholomew's Hospital received its first radium for clinical use in

1906. Early clinical experience with these sources led to radiation necrosis, and it

became clear that this was due, in part, to the intense beta-ray dose from the radium.

It was not until 1920 that successful filtration of the beta-rays was achieved (Joslin,

2001).

Radium was then used extensively throughout the world. Physicists in the

major clinical centers developed dosimetry systems for interstitial and intracavity

brachytherapy. However, in general, radium has been replaced by other radionuclides

because, although it has a long half-life, it has several disadvantages (Joslin, 2001):

Radium and several of its descendant products, including radon, are alpha

emitters. Radon is a noble gas which is soluble in tissue. This gas could escape

through a hairline crack - not easily detected by a visual check - in the radium

capsule. If an implanted radium source were to be ruptured within the patient's



body, radium and its daughter products may become deposited more or less

permanently in the bone.

There is also the possibility of damage – by incineration or mechanical means -

when the sources are lost, or while they are being processed, with the

subsequent release of toxic radioactivity to the environment.

The gamma radiation from a radium source is of higher energy than is

necessary for brachytherapy. Radiation protection for these sources requires

large thicknesses of lead, which can cause problems when it comes to:

o transporting sources in heavy containers using very weighty protective

screens around the patient;

o the need for a heavy rectal shield in applicators used for gynecological

treatment.

The practical maximum activity concentration (the specific activity) of radium

salt is low (approximately 50 MBq mm-3 of active volume). Therephore, sources

of higher activity are bulky and u suitable for afterloading systems.

6.3.2 – RADIUM SUBSTITUTES

This was the phrase used to describe the first set of new (artificial)

radionuclides which were found useful for brachytherapy from about 1950 onwards,

though it is only very recently that most radiotherapy centers have stopped using

radium. It was found that there were very few radionuclides with the appropriate

properties of the ideal brachytherapy source. These properties are as follows (Joslin,

2001):

Photon energy should be low to medium (0.03-0.5 MeV) to minimize radiation

protection problems (with the proviso that low-energy radionuclides should not

be used near bone because of the enhanced dose to bone at these energies).

For permanent stock, a long half-life is desirable such that the radioactive

decay within the practical lifetime of the source and its container (typically 10

years) is small.



For permanent implantation, a fairly short half-life is essential in order to

minimize the time over which special precautions, towards relatives of a

radioactive patient and members of the public, need to be in place.

The nuclide should be available at high specific activity.

There should be no gaseous disintegration product.

The nuclide should be available in a form which does not powder or otherwise

disperse if the source is damaged or incinerated.

The first sources to be used as alternatives to radium were cobalt-60, gold-198,

cesium-137 and iridium-192. These are all described briefly below. The most

commonly used sources at this time are cesium-137 and iridium-192, both of which are

used in after-loading systems. Iridium-192 has the possibility of high specific activity,

which allows it to be used as a high dose-rate (HDR) source (Joslin, 2001).

6.3.3 – NEW SOURCES

The newer sources are not known as radium substitutes, mainly because they

have very different properties from radium, namely very much higher specific activity

(for example, the HDR iridium-192 source) and very different energy. The only new

source that has been accepted into routine clinical use in certain centers throughout

the world is iodine-125. Palladium-103 is also now available as a standard commercial

source (Joslin, 2001).

The other sources that are still at the research stage of development, to find

out whether they can be of use clinically, are samarium-145, americium-241, and

ytterbium-169 (Joslin, 2001).

6.4 – RADIOBIOLOGY OF BRACHYTHERAPY

The biological damage inflicted by irradiation of human cells with ionizing

radiation can be divided into three consecutive steps (Mazeron, 2005):

A very short initial physical phase (about 10-18 s), during which photons interact

with orbital electrons, raising them to higher energy levels inside the atoms



(excitation), or ejecting some of them from the atoms (ionization). This is the

energy deposition phase.

A chemical phase, again very short (about 10-3 s), during which ionized and

excited atoms interact, leading either directly or indirectly effects through the

formation of free radicals to the breakage of chemical bonds. Free radicals are

highly reactive and can induce chemical changes in biologically important

molecules like DNA. Single-strand or double-strand break in DNA appears to be

the basic damage leading to biological effects.

A biological phase, much longer (seconds to years), during which the cells react

to the inflicted chemical damage. Specific repair enzymes can successfully

repair the vast majority of lesions in DNA. However, few lesions however may

not be repaired and may consequently lead to cell death. Cell death is not

immediate and usually occurs during the next cell division (apoptosis is a minor

process in most human cells). On the other hand, death due to a lethal lesion

may be delayed for a limited number of mitotic divisions (up to 5 or 6). Because

the stem cells are the only cells which divide in normal tissues, the earliest

effect observed is a deficit in stem cells. Later, the loss of stem cells will lead to

a deficit in differentiated cells causing the observed clinical reactions. The early

reactions are seen during the first days or weeks after irradiation (for example,

diarrhea or acute mucositis). They are temporary because the cell deficit is

compensated for by the repopulation of stem cells and subsequently of

differentiated cells. Late reactions due to damage to the late-reacting tissues,

for instance blood vessel damage, fibrosis, telangiectasia, etc., may be seen

after months or years. Damage to these late reacting normal tissues is poorly

repaired and is responsible for most severe complications of radiotherapy.

Tolerance of these tissues is the limiting factor for radiation therapy.

6.4.1 – THE FOUR RS OF RADIOBIOLOGY

A number of biological processes take place during irradiation and modify the

radiation response. These processes are often described as the four Rs of radiobiology.

Each follows a specific time pattern (Mazeron, 2005):



Repair of DNA damage - it is often referred as repair of “sub-lethal” damage.

Experimental and clinical studies have shown that human tumors strongly differ

in radiosensitivity and radiocurability. This is thought to stem from differences

in capacity for repair of sub-lethal damage. Similar differences are seen

between normal tissues, the haemopoetic system being more sensitive than

the kidney.

Reassortment or redistribution - the cell cycle is divided in four consecutive

stages: G1, S, G2 and M. G1 is a gap of apparent inactivity after a mitosis (M),

before DNA synthesis (S-phase) resumes in view of the following cell division.

G2 is a second gap of apparent inactivity between S phase and M, Figure 6.1.

Radiosensitivity varies along the cell cycle, S being the most resistant phase and

G2 and M the most sensitive. Therefore, cells surviving an exposure are

preferentially in a stage of low sensitivity (G1), i.e. synchronized in a resistant

cell cycle phase. They progress thereafter together into S and then to the more

sensitive G2 and M phases. A new irradiation exposure at this time will have a

larger biological effect (more cells killed). However, while this synchronization

effect has explained some experimental results, redistribution has never been

shown to play a measurable role in the clinic of radiotherapy.

Repopulation - cells surviving an irradiation keep proliferating. This increases

the number of clonogenic cells, i.e. the number that must eventually be

sterilized to eradicate cancer. Consequently, repopulation has a detrimental

effect as far as cancer control is concerned. Stem cells do also proliferate in

normal tissues, which has in this case a protective effect (it helps the tissue to

recover from radiation damage and it adds to DNA repair in cells).

Reoxygenation - because of an inappropriate development of intratumoral

vasculature, every tumor of clinically detectable size contains a large

proportion of poorly oxygenated cells. In addition, the proportion of hypoxic

cells increases with the tumor size. Acutely hypoxic cells are far more

radioresistant than well oxygenated cells. This is expressed by the oxygen

enhancement ratio (OER), i.e. the ratio between radiation doses required in

hypoxia and air to produce the same biological effect. Hypoxic cells usually

survive irradiation, but they progressively (re)oxygenate due to the better



supply of oxygen available after well oxygenated cells have died, Figure 6.2.

This restores radiosensitivity in the tumor by several mechanisms, but re-

oxygenation occurring at long intervals is probably due to tumor shrinkage

leading to a reduction of the intercapillar distance.

Figure 6.1 - The cell cycle (from Murray, 1993).

Figure 6.2 - Re-oxygenation due to tumor shrinkage (from Mazeron, 2005).

6.4.2 – RADIOBIOLOGY OF LOW DOSE-RATE AND FRACTIONED IRRADIATION

For exposure to sparsely ionizing radiations such as X-rays or gamma-rays, the

degree of a biological effect produced can depend as much on the dose rate as on the



total dose received. The importance of dose rate and dose fractionation effects has

been recognized for more than 70 years (Joslin, 2001).

Studies of Regaud and his collaborators were perhaps the first to show the

potential therapeutic advantages of dose fractionation in the treatment of patients

with cancer by radiation. Since that time, the evolution of treatment regimes involving

dose time variations have increasingly improved cancer radiotherapy and the evolution

continues even today. In cancer radiotherapy, the dose rate and dose fractionation are

not the only important factors, but also in connection with the mutagenic and

oncogenic hazards of radiation exposure (Joslin, 2001).

Normally, reducing the dose rate decreases the biological effectiveness, that is,

decreasing the dose rate generally increases the dose necessary to yield the same level

of effect. A number of factors can contribute to the dose rate or dose fractionation

effect, depending on the conditions and cell or tissue system involved. For example, in

a tissue or tumor exposed over a period of weeks or months, cells may migrate into or

out of the radiation field, or the oxygenation status may change to alter the intrinsic

radiosensitivity of the cells during the course of treatment (Joslin, 2001).

6.4.2.1 – SPLIT-DOSE RECOVERY FROM SUB-LETHAL DAMAGE IN MAMMALIAN CELLS

For ionizing radiation damage in mammalian cells, the first direct

demonstration of a cellular repair process affecting cell killing that could explain dose

rate and dose fractionation effects seen in mammalian tissues or tumors was provided

by Elkind and Sutton. These researchers reasoned that because the shouldered survival

curves for mammalian cells exposed to X-rays or gamma-rays indicate the involvement

of a damage accumulation process in cell killing, then cells surviving a dose beyond the

shoulder region of the curve (survivals below about 10%) would contain sub-lethal

damage capable of interacting with further damage to become lethal. Elkind and

Sutton questioned whether this sub-lethal damage might remain in surviving cells, in

which case their dose response at some later time would not be 'shouldered'.

Alternatively, if the sub-lethal damage were repaired, the cells would be expected to

respond as if they had never been irradiated, i.e., the surviving cells would display the



same shouldered survival curve for subsequent irradiation. The latter was found to be

the case, as is illustrated in Figure 6.3 from their early work (Joslin, 2001).

The curve indicated by filled circles in Figure 6.3 illustrates a dose-response

curve for irradiations requiring only a few minutes each - high dose rate (HDR) or

'acute' exposures - over a range of doses from 0 (zero) to about 12.5 Gy. Curves

starting at a dose of 5.05 Gy illustrate dose-response curves for cells surviving a first

dose of 5.05 Gy followed by various additional doses given either immediately after

the first dose (filled circles) or 18 h following the first dose (open circles). During the

time interval between the first and second doses, the surviving cells 'restored

themselves to good (original) condition. They had repaired this so-called sub-lethal

damage so they again had to accumulate damage for cell killing (Joslin, 2001).

This sub-lethal damage repair (SLDR) is a repair process operationally defined in

terms of the observations demonstrating the phenomenon, i.e., the increase in the

fraction of cells surviving. It says nothing about what is being damaged and repaired

(Joslin, 2001).

Figure 6.3 – Initial survival curve (closed circles) and fractionation curve (open circles) for ‘clone A’ cultured Chinese

hamster cells (from Joslin, 2001).



6.4.2.2 – CELL-CYCLE COMPLICATION: A HETEROGENEOUS POPULATION

In the early 1960s, Terasima and Tolmach first showed with synchronized

cultures of HeLa cells that cellular responses varied greatly throughout the cell cycle.

During mitosis cells become very loosely attached to the surface of the culture vessel

and these were collected by a 'shakeoff method', leaving the interphase cells behind in

the flask. Appropriate numbers of mitotic cell populations were inoculated into dishes.

After various periods of incubation, different sets of the synchronously progressing

cells were irradiated when they were (for the most part) at a particular stage of the

cycle. When the dose was the same for all cultures, but the time after mitotic shake-off

was varied, the proportion surviving to form colonies varied. Parallel cultures were

flash labeled with tritiated thymidine (3H TdR) to monitor the synchronous progression

of cells into and out of S phase.

For irradiation of mitotic cells survival was low, indicating a high sensitivity for

this cell cycle phase. As cells progressed into mid-G1 (2-6 h), the cells were more

resistant. At around the G1/S border and in early S phase cells were again more

sensitive, and as cells progressed toward late S phase and early G2 the cells again

became more resistant. Because there is some variation from one cell to the next in

the cell cycle transit times, particularly through G1, there is an increasing decay in

synchrony and therefore the resolution of experimental data on cycle-dependent

radiosensitivity with time. Nevertheless, there is clearly a large variation in the

radiation response of cells through the cell cycle. Other cells have shown similar cell-

cycle-dependent variations in radiosensitivity, although the peak of resistance in G1 is

not well resolved experimentally in cells with very short G1 transit times.

The sensitivity of cells in different parts of G2 is difficult to determine by the

synchronization procedure described above, because of synchrony decay during the

passage of the starting population of mitotic cells through their first G1 and S phase,

and because G2 transit times are relatively short (about 1-2 h). However, a

modification of the technique allows a much greater resolution for studying G2

sensitivity. This is sometimes called 'retroactive synchronization': cells are first

irradiated and then, as a function of time, cells arriving in mitosis are harvested by

mitotic shake-off and plated for survival (Joslin, 2001).



6.4.2.3 – RADIATION AFFECTS CELL-CYCLE PROGRESSION ITSELF

Radiation effects on cell cycle progression are yet another factor that influences

dose rate effects. Ionizing radiation reduces the mitotic index within a short time after

exposure (mitotic delay). This delay has been studied extensively in more recent times,

and the timing for the reduction in mitotic index and subsequent recovery clearly

indicates the delay is reversible and occurs sometime during G2. The production of this

effect is very radiosensitive (Joslin, 2001).

Appreciable proportions of the cells are delayed by doses of the order of tens

of cGy. The G2 delay increases with dose and frequently corresponds to about 1-3 hGy1

depending on the particular cells and on the stage in the cycle when the cells are

irradiated. Most of the extensive work on cell cycle progression delays in cultured

mammalian cells was carried out in the 20-year period between about 1965 and 1985

using 'transformed' or tumorigenic cell lines. Delays in G1 or S phase were relatively

minor and, in many cases, undetectable in the 0-5 Gy dose range. As it turned out, the

generalization or extrapolation of the results to normal or untransformed cells was

unwarranted. Some investigators during this period, even as early as 1968, reported

appreciable delays in the progression of 'non-transformed' cells from G1 into S phase

or in the transition from the non-cycling G0 to the cycling state after low dose or low

dose-rate (LDR) irradiation (Joslin, 2001).

In a split-dose experiment, the first dose kills a fraction of the cells, but this

fraction is different in all portions of the cell cycle. Survival for cells in the most

sensitive phases will be much lower and, in resistant phases much higher than the

average. Thus, after the first dose the population of cells surviving will not be

distributed around the cell cycle as it normally is, but will be highly enriched in cells

from more radioresistant phases. It is these surviving cells that determine the further

reduction in survival measured by the second dose. If the first dose is of sufficient

magnitude to bring the survival down to, say, 10% or less, then these surviving cells

will still contain sub-lethal damage capable of interacting with an additional dose.

Thus, if the additional dose were given immediately after the first, the survival

reduction would effectively continue down along the single dose survival curve. With a

time delay, however, three things happen (Joslin, 2001):



First, the sub-lethal damage begins to repair, and the half-time for this process

is relatively fast being 0.5-2h depending on the system. The effect of this repair

process on the surviving cells is to make them more resistant to a second dose,

so the proportion surviving will increase with an increasing time interval

between the first and second doses. This process is 90% or more complete

within about 2-4 h.

Second, the cells surviving the first dose which were already in the more

resistant phases of the cycle begin to progress and, at least for the first few

hours; this progression can only be toward a more sensitive state. For initially

log phase populations it is no longer surprising then that with increasing time,

between about 3 to 6 or 7 h after the first dose, the survival after the second

dose actually decreases. The first dose also produces a mitotic and division

delay, so the increase in number of surviving colonies with increasing time

before the second dose is not due to an actual increase in numbers of surviving

cells from cell division, at least for the first few hours. For example, after a first

dose of 5 Gy, there would be essentially no cell division for some 5-10 h,

depending on the cells.

Third, after the mitotic delay, cell division would resume, so instead of having

only one viable cell per surviving colony, as would be the case immediately

after the first dose, some, and eventually all, would have two or more viable

cells, both of which would have to be killed to prevent colony formation at that

locus.

Especially appropriate for cell culture applications are 'normal' or 'non-

transformed' cells, which form so-called contact-inhibited monolayers. In such

monolayers, the cells enter a non-cycling G0 state, where they are no longer a

heterogeneous population with respect to the radiosensitivity of subpopulations and,

of course, where cell cycle progression and cell division during treatment do not

complicate the picture. One additional issue that does arise with the use of contact-

inhibited monolayer systems as well as organized tissues in vivo is that another,

perhaps related, repair process known as 'potentially lethal damage' repair (PLDR),

also plays an important role (Joslin, 2001).



6.4.2.4 – POTENTIALLY LETHAL DAMAGE

When contact-inhibited monolayers of non-transformed cells are irradiated for

a cell survival experiment, the flasks must, of course, be sub-cultured and plated at a

low enough density to allow surviving cells to form colonies for the surviving fraction

to be assessed. As it turns out, the proportion of irradiated cells surviving a single

acute dose in such cultures depends greatly on whether the cells are sub-cultured,

diluted, and plated for the colony forming assay immediately after irradiation, or the

sub-culture is delayed for some hours, in which case the survival is much higher. The

interpretation of this phenomenon is that because damage is lethal in some cells under

one set of circumstances (e.g., immediate subculture) but is not under another set

(e.g., delayed subculture), such damage must be considered not as 'inevitably lethal'

but only 'potentially lethal', depending on the circumstances (Joslin, 2001).

Another factor for the study of cellular radiation responses relevant to normal

tissue effects, is that virtually no normal tissue contains cells existing in the abundant

nutrient conditions of in vitro culture and which are proliferating with growth fractions

near 1.0 and doubling times of 12-24 h. Perhaps intestinal crypt stem cells come as

close to this unusual situation as any in vivo. The non-cycling contact-inhibited state for

normal cells in culture may fail to simulate all conditions in vivo, but the conditions are

perhaps a little closer in general to those in most cell renewal tissues, and much closer

with respect to the cell cycling status (Joslin, 2001).

6.5 – DOSE-RATE EFFECTS WITH HUMAN CELLS

The term 'dose-rate effect' refers to the change in sensitivity or tissue response

when the dose rate of irradiation is modified. Dose-rate effects are common in

mammalian cell systems, including human tumors and normal tissues. The response of

these tissues is complex, depending in part on the radiosensitivity of the stem cells (or

'clonogenic' cells) of the tissue, but also on the modifying effects of cell proliferation

and such physiological parameters as oxygenation and growth factors (Joslin, 2001).



6.5.1 – TIME-SCALE OF RADIATION ACTION

Time-scale of biological effects of ionizing radiation is illustrated in Figure 6.4. It

is the operation of some of the processes represented in this chart that gives rise to

dose-rate effects. Immediately after exposure, free-radical processes take place

leading to damage of many constituents of the cell. Because of its vital nature and the

relative uniqueness of its genetic message, DNA is the most important of these

damaged molecules (Joslin, 2001).

Under physiological conditions the rapid free-radical reactions are complete

within around 1 ms, during the subsequent few minutes enzymatic processes begin to

operate on the damaged molecules. Some of these act to repair the damage; others

leave the molecules in a changed but stable form and this is described as 'misrepair.'

Within a few hours these enzymatic processes will be complete (Joslin, 2001).

Repair of radiation damage to DNA is highly effective in most cell types: a 1 Gy

dose will induce upwards of 1000 DNA strand breaks in every irradiated cell. Roughly

half of the cells will survive this dose, so strand-break rejoining must be a remarkably

error-free process. Most strand breaks are to one strand only of the double helix, but a

small proportion can be recognized as affecting both DNA strands (double-strand

breaks - dsb). There is evidence that these are much more serious for the viability of

the cell. Even so, the great majority of dsb are also successfully repaired, and of

particular importance are dsb that arise from clusters of ionizations at the end of the

tracks of secondary electrons: these can involve severe damage to the DNA molecule

(so-called 'multiply damaged sites') and, it may be that these events have a relatively

low probability of successful repair and a correspondingly high likelihood of leading to

cell death or mutation (Joslin, 2001).

At longer intervals after irradiation cell proliferation will take place within

tissues, leading to the replacement of radiation-damaged cells. In tumors this may lead

to recurrence or to a reduced likelihood of success as a result of subsequent treatment

(Joslin, 2001).

In normal tissues, proliferation may prevent tissue breakdown and the

observed early effects of irradiation will then be minimal. However, if the level of cell

killing is greater and of such a severity that it cannot be counteracted by proliferation,



then serious tissue damage may appear. At even longer time intervals after irradiation

(months to years), the very long-term effects will become apparent, including tissue

failure, formation of new tumors and mutational effects in germ cells (Joslin, 2001).

Figure 6.4 - Time-scale of the effects of radiation exposure on biological systems (from Joslin, 2001).

6.5.2 – MECHANISMS OF THE DOSE-RATE EFFECT

Observed dose-rate effects derive from the operation of the processes just

described. Usually, clinical external-beam treatments are given within a few minutes.

These brief exposures are long enough for the initial chemical effects of irradiation to

be complete, but are too short for the subsequent enzymatic and proliferation

processes to take place. As radiation dose rate is lowered, the irradiation time for a

given dose, increases and it becomes possible for such processes to take place during

radiation exposure. These will modify the extent of damage and thus lead to a dose-

rate effect (Joslin, 2001).

Four main processes lead in this way to the dose-rate effect. They are the '4Rs

of radiobiology': repair, redistribution, repopulation, and reoxygenation, as described

before. Among these repair is the fastest, the time required to repair half the induced

damage is about 1 h. This means that as soon as the duration of exposure becomes a

significant fraction of an hour some repair will take place during irradiation. At the



other extreme, repopulation is a much slower process: repopulation requires cell

multiplication and human cells cannot divide in less than about a day. Therefore,

repopulation will only have a significant effect when the exposure time is a day or

more. Redistribution and reoxygenation probably have a speed that is intermediate

between these two processes. Figure 6.5 illustrates the range of dose rates over which

each of these processes might be expected to influence radiation action. For dose

rates in excess of a few gray per minute none of the processes will take place

significantly during irradiation and there will be no dose-rate effect due to them

(Joslin, 2001).

At much higher dose rates than illustrated a further process, the consumption

of oxygen by radiochemical reactions leading to partial hypoxia, may have an effect. At

dose rates around 1 Gymin-1, sometimes used for 'high dose rate' or 'acute'

irradiations, there may be a small amount of repair during irradiation and such

treatments will be slightly less effective than if given at a higher dose rate (Joslin,

2001).

Figure 6.5 - Range of dose rates over which repair, reassortment, and repopulation may influence radiation effects

(from Joslin, 2001).

The curves drawn in Figure 6.5 to represent the effects of repopulation or

reassortment are diagrammatic. Repopulation is a much slower process than repair

and, only when the exposure time becomes a significant proportion of a cell cycle time

(perhaps 1-4 days in human tumor and normal tissue cells) will it have a significant



effect during the period of irradiation. Reassortment (otherwise known as

redistribution) refers to the effects that derive from the movement of surviving cells

through the cell cycle after a first dose or increment of dose radiation (Joslin, 2001).

These effects may modify the response of a tissue or cell system to subsequent

irradiation and, occur over a dose rate range that is somewhere intermediate between

those of repair and repopulation. The comparative effects of repair and repopulation

are further illustrated in Figure 6.6. This figure shows actual calculations for a typical

human cell line, based on a repair half-time of 0.85 h and an α/β ratio of 3.7 Gy (Joslin,

2001).

Curves of Figure 6.6 are drawn for four different cell population doubling times

and the calculations show the radiation doses (i.e., ED50 values) for a survival of 0.01.

For these parameter values, there is no effect of proliferation at dose rates above 1

cGymin-1, but as dose rate is lowered to 0.01 cGymin-1 dramatic effects are predicted,

depending on the cell population doubling time. The implication for brachytherapy is

that above 1 cGymin-1 repopulation effects can be ignored, but below this dose rate

they can, under some circumstances, predominate over effects due to incomplete

repair (Joslin, 2001).

Figure 6.6 - In human cell systems proliferation probably affects radiation response for dose rates below about

1Gyh-1

(from Joslin, 2001).

6.5.3 – DOSE-RATE EFFECTS IN HUMAN TUMOR CELLS

Pioneering experimental studies of the dose-rate effect were made in a number

of publications by Hall, Bedford and Mitchell (“Dose rate: its effect on the survival of



HeLa cells irradiated with gamma rays”, Radiat Res 1964; 22: 305-15). The experiments

were performed on a variety of cell lines, mainly derived from experimental animals

but also including the long established HeLa cell line (derived from a human cervix

carcinoma). They showed that the dose rate effect mainly appeared over the range of

dose rates from 1 Gymin-1 down to 0.1 cGymin-1. There was considerable variation in

the magnitude of the dose-rate effect (i.e., the relative radiosensitivities at high and

low dose rates). Steel et al. analyzed these data and showed that derived values for

the half-time for repair of radiation damage ranged widely: from below 0.1 h to above

than 1 h (Joslin, 2001).

Studies on human tumor cell lines taken from a variety of tumor types were

reported by Steel et al (“The dose-rate effect in human tumor cells”, Radiother Oncol

1987; 9: 299-310). Most of the cell lines were newly established. In some cases the

cells were taken directly from human tumors that had first been grown as xenografts

in immune-deficient mice; other studies were made on cell lines established in tissue

culture. They were irradiated with cobalt-60 gamma-radiation at dose rates ranging

from 1 to 150 cGymin-1 at body temperature and under conditions of controlled

oxygenation. Cell survival was measured using a colony assay, either in soft agar or in

monolayer, depending on the growth characteristics of the cell line. Data on four cell

lines are shown in Figure 6.7, covering the range of responses seen in a larger group of

human tumor cell lines. Figure 6.7a shows results at high dose rate. The data are fitted

by a linear quadratic equation; there is a well-defined initial slope to the data, which

are clearly consistent with a continuously bending relationship. The range of

sensitivities is considerable (Joslin, 2001).

The doses required for a survival of 0.01 range from 3.6 Gy in the HX142

neuroblastoma to 10.9 Gy in the RT112 bladder carcinoma (i.e., by a factor of 3). In the

initial dose region the factor is greater. Figure 6.7b shows the results for the same cell

lines at the low dose rate of 1.6 cGy min '. The curves have fanned-out and become

straight or almost so on the semi-logarithmic plot. It can be seen that at low dose rate

the lines seem to extrapolate the initial slopes of the high dose-rate curves (Joslin,

2001).

The range of sensitivities among the cell lines is now larger: by a factor of

approximately 10. The data shown in Figure 6.7 indicate the range of sensitivities seen



among tumors of different histological types. Less information is available about the

range of sensitivities among tumors of the same type, from diverse patients. Kelland

and Steel (“Differences in radiation response among human cervix carcinoma cell

lines”, Radiother. Oncol., 13,225-32) studied five cell lines newly established from

human cervical carcinomas. They found that at high dose rate the dose to produce a

surviving fraction of 0.01 ranged from 5 to 10.5 Gy. The dose-rate sparing factors (the

dose at 1.6 cGymin-1 compared with the dose at 150 cGymin-1) ranged from 1.1 to 1.6.

This showed that among tumors of the same type there were considerable

radiobiological differences that could be clinically significant. There may be a number

of causes of failure in brachytherapy and these include the inherent insensitivity of the

tumor cells to radiation. A so-far insufficiently explored aspect of brachytherapy is the

attempt to develop predictive tests of radiosensitivity in order to identify patients

most at risk of recurrence. The data in Figure 6.7 clearly indicate that such tests should

be made at low dose rate, where the differences among cell lines are greatest (Joslin,

2001).

Figure 6.7 - Cell survival curves for four human tumor cell lines irradiated at (a) 150 cGy min-1 or (b) 7.6 cGy min-1

HX142, neuroblastoma; HX58, pancreas carcinoma; HX156, cervix carcinoma; RT112, bladder carcinoma (from

Joslin, 2001).

6.5.4 – EFFECT OF IRRADIATION ON CELL CYCLE PROGRESSION

Irradiation at high dose rate blocks cell entry into mitosis. The cell cycle may be

interrupted at a number of so called 'check-points', and the biochemical processes



involved in these arrests are the subject of intense laboratory research at the present

time. At high dose rate, there are two reasons why proliferation effects during

irradiation are unimportant: irradiation times are too short, and the cells are subject to

mitotic delay and therefore inhibited from proliferating. As dose rate is reduced, both

these factors become less severe and cell cycling takes place during irradiation, thus

counteracting the effect of irradiation (Joslin, 2001).

Skladowski et al. (“Cell-cycle progression during continuous irradiation of a

human bladder carcinoma cell line” Radiother. Oncol., 28,219-27) concluded that cell-

cycle effects in tumor cells are unlikely to be of any great significance, in relation to the

cell-killing effect at different distances from an implanted radiation source. Overall

treatment times in brachytherapy tend to be short compared with external-beam

treatment and proliferation effects are correspondingly of less significance (Joslin,

2001).

6.5.5 –CELL KILLING AROUND AN IMPLANTED RADIATION SOURCE

The non-uniformity of radiation field around an implanted source has

important radiobiological consequences. Close to the source, the dose rate is high and

the amount of cell killing will be close to that indicated by the acute-radiation survival

curve. As the distance from the source is increased, two changes take place: cells will

be less sensitive to lower dose rates, and within a given period of implantation the

accumulated dose will also be less. These two factors lead to a very rapid change of

cell killing with distance from the source.

This is illustrated in Figure 6.8 for the case of a point radioactive source. A

source strength was chosen that gives 75 Gy in 6 days at a range of 2 cm. Three

different tumor-cell sensitivities were assumed, as shown in the upper panel. It is the

low dose-rate sensitivities that matter for this calculation. For spherical shells

containing 109 clonogenic cells at different distances from the source, it was possible

to calculate the surviving fraction from 6 days irradiation, the absolute number of

surviving clonogenic cells, and thus the probability that all cells in the shell would be

killed. The results are shown in the lower panel. For cells of any given level of

radiosensitivity there will be cliff-like change from high to low local cure probability,



taking place over a radial distance of a few millimeters. Note that the order of the lines

in the upper and lower panels of this figure is reversed: very sensitive tumor cells (lines

A) can be cured out to a greater radius than less sensitive cells (B) or very

radioresistant cells (C). The steepness of the tumor control curves derives in part from

the underlying assumed Poisson relationship between the average number of surviving

cells per shell and the control probability. As is the case with tumor control by

external-beam irradiation, in reality, there will be factors that make the tumor control

curves less shallow: heterogeneity, for instance (Joslin, 2001).

Within tissues (tumor or normal) that are close to the source, the level of cell

killing will be so high that cells of any radiosensitivity will be killed. Further out, the

effects will be so low that even the most radiosensitive cells will survive. Between

these extremes there is a critical zone in which differential cell killing will occur. In this

critical region the radiation dose rate will be low. For this reason, one would argue that

the low dose-rate survival curves as shown in Figures 6.5 and 6.6 are more clinically

realistic than the high dose-rate curves, certainly for brachytherapy. Figure 6.9

contrasts this situation with external beam radiotherapy, where the aim is to deliver a

uniform radiation dose across the tumor. Only in a narrow zone around an implanted

source (where the surviving fraction changes from, say, 10-20 to 10-6) will

radiobiological considerations be of interest or importance in relation to tumor

control. The same principle will apply to normal tissue damage: serious damage to

normal structures depends on making sure that they are outside the corresponding

'cliff' (Joslin, 2001).



Figure 6.8 - The likelihood of cure varies steeply with distance from a point radiation source. The radius at which

failure occurs depends upon the steepness of the survival curve at low dose rate (upper panel) (from Joslin, 2001).

Figure 6.9 - Variation of cell kill around a point source of radiation (from Joslin, 2001).



6.5.6 – IMPLICATIONS FOR CLINICAL BRACHYTHERAPY

The radiobiology of low dose-rate irradiation is now fairly well understood.

Although data are not available on a wide range of human tumors, the data that one

have do indicate the range of responses that are seen for human cells in tissue culture.

It is likely that these will be realistic for effects on well-oxygenated cells in the patient.

Much less is known about the effects of low dose-rate irradiation on hypoxic cells in

vivo. These are, of course, less sensitive to high dose-rate irradiation. The work of Ling

et al. (“The variation of OER with dose rate”, Int. J. Radial. Oncol. Biol. Phys.,11, 1367-

73) showed that the sparing effect of low dose-rate irradiation as a function of oxygen

concentration was complex. Lowering the dose rate initially had more effect on the

oxic cells than on the hypoxic cells. Further lowering of dose rate had consequently

more effect on the hypoxic cells. Although for such reasons there is much that still

needs to be understood about the tumor effects of brachytherapy, some simple

conclusions can be drawn:

1. In the dose-rate range from a few Gymin-1 down to a few cGymn-1, repair of

radiation damage is the main modifying process on radiosensitivity. The effects

are large, leading to a change in the isoeffective radiation dose by a factor of 2

or more. Below 1 cGymhr-1, cell proliferation will play an increasingly strong

role in making tumors or normal tissues less sensitive to radiation damage.

2. There is evidence for a dose-rate effect in the region of 1 Gymin-1. If, in

external-beam radiotherapy, a change of machine or of source-skin distance

leads to a substantial lowering of dose rate, then a dose rate correction should

be considered.

3. The biological effect of irradiation changes rapidly at dose rates around 10

cGymin-1. This may mean that greater precision in dosimetry and dose

prescription is required in high dose-rate brachytherapy than when a low dose

rate is used.

4. Tumor cells of different origins show very different response to low dose-rate

irradiation. Theoretical calculations suggest that as one move out from an

implanted radiation source the local tumor control probability will change

rapidly, i.e., there will be sudden failure to eradicate all clonogenic tumor cells.



The prediction that the range at which this occurs will depend strongly on the

low dose-rate radiosensitivity of the tumor cells could be clinically important.

There is a strong case for predictive testing of tumors that are to be treated

with curative intent by brachytherapy in order to predict those that require a

greater or lesser range of dose distribution (Joslin, 2001).

6.6 – PREDICTIVE ASSAYS FOR RADIATION ONCOLOGY

Since the 1980s, radiation oncologists and biologists have recognized the need

for additional assays on an individual patient basis that would select the most

advantageous treatment approach. Hence, it should emphasize assays for individual

patients for several reasons (Joslin, 2001).

First, the cellular radiation sensitivity of the tumor may differ among

individuals, even for tumors of the same histological type. If the radiosensitivity of the

individual's tumor were precisely known, perhaps total radiation doses could be

adjusted before the end of therapy to maximize tumor response. Alternatively, the

option of using radiation sensitizers for 'radioresistant' tumors would have a more

rational basis (Joslin, 2001).

Second, normal-tissue radiation sensitivity may differ among individuals. This is

an important point because the total radiation dose that can be delivered to a

patient's tumor is often limited by normal tissue tolerance. Stated differently,

frequently radiation oncologists are compelled to treat a patient's tumor with

radiation doses that are dictated not by tumor sensitivity but by normal-tissue

tolerance, which in many instances results in inadequate dose to the tumor. If one

assumes there is a Gaussian distribution of normal-tissue radiosensitivities among

humans, then the most sensitive individuals in the population may well dictate

radiation tumor doses utilized in the clinic. Because the radiation tumor control dose

response curve is quite steep for many tumors, modest increases in the total radiation

dose delivered would be expected greatly to enhance tumor control. If it were

determined that the patient's normal-tissue radiation response were toward the

'radioresistant' edge of the Gaussian distribution, consideration could be given to



administering higher radiation doses. Alternatively, if the patient's normal-tissue

radiation response was toward the 'radiosensitive' edge of the Gaussian distribution,

the use of radioprotectors could be considered. Unfortunately, selective normal-tissue

radioprotectors have yet to be identified (Joslin, 2001).

Third, biological, environmental, and physiological factors of tumors may differ

among individuals. Factors such as tumor pH, hypoxia, blood flow, and growth of the

tumor in terms of cell-cycle parameters and potential tumor doubling times (Tpot) can

influence the overall radiation responsiveness of the tumor. If these factors were

known prior to therapy, the use of hypoxic cell radiosensitizers or, in the case of Tpot

values, alteration of fractionation/time schedules could be considered (Joslin, 2001).

Numerous predictive assays have been developed over the past two decades to

address many of the points cited above and several have been evaluated in a clinical

setting (Joslin, 2001).

6.7– SUMMARY

Brachytherapy is an important radiation technique in the treatment of

malignant disease that allows conformal treatment without heavy technological

involvement. However, since it generally involves invasive procedures (interstitial

brachytherapy), except for special instances in which intracavitary techniques may be

employed, brachytherapy is relegated to second place behind external beam

radiotherapy in the treatment of malignant disease (Suntharalingam, 2002).

A typical radiation oncology department will treat about 80% of its patients

with the various external beam techniques and about 10–20% of its patients with

brachytherapy. The basic principles of brachytherapy have not changed much during

the past 100 years of radiotherapy; however, the advent of remote afterloading

brachytherapy has made brachytherapy much more efficient for the patient and safer

for staff from the radiation protection point of view. In terms of physics human

resource needs, a brachytherapy patient requires considerably more involvement than

an average external beam patient (Suntharalingam, 2002).



Nearly every malignant disease in the human body has been treated with

brachytherapy; however, gynaecological cancer treatments provide the greatest

success and permanent prostate implants are becoming increasingly common.

(Suntharalingam, 2002)

There are also various sites for which brachytherapy has proven a complete

failure. The newest application of brachytherapy is intravascular (also referred to as

endovascular) brachytherapy, used for the prevention of restenosis in arteries

following coronary arterial angioplasty (Suntharalingam, 2002).

This radiation technique was used to kill the prostate and breast cancer cells

that will be studied by me in my dissertation thesis.

CHAPTER VII

BASIC CONCEPTS OF DIGITAL IMAGE PROCESSING

CHAPTER VII – BASIC CONCEPTS OF DIGITAL IMAGE PROCESSING


7.1 - INTRODUCTION

Digital image processing is an area characterized by the need for extensive

experimental work to establish the viability of proposed solutions to a given problem.

An important characteristic underlying the design of an image processing system is the

significant level of testing and experimentation that normally is required before

arriving at an acceptable solution. This characteristic implies that the ability to

formulate approaches and quickly prototype candidate solutions generally plays a

major role in reducing the cost and time required to arrive at a viable system

implementation (González, 2004).

MATLAB is a high-performance language for technical computing. It integrates

computation, visualization, and programming in an easy-to-use environment where

problems and solutions are expressed in familiar mathematical notation. Typical uses

include the following:

Math and computation;

Algorithm development;

Data acquisition;

Modeling, simulation and prototyping;

Data analysis, exploration and visualization;

Scientific and engineering graphics;

Application development, including graphical user interface building.

MATLAB is an interactive system whose basic data element is an array that

does not require dimensioning. This allows formulating solutions to many technical

computing problems, especially that involving matrix representation, in a fraction of

the time it would take to write a program in a scalar non-interactive language such as C

or Fortran (González, 2004).

The name MATLAB stands for matrix laboratory and was written originally to

provide easy access to matrix software developed by the LINPACK (Linear System

Package) and EISPACK (Eigen System Package) projects (González, 2004).

The Image Processing Toolbox is a collection of MATLAB functions (called M-

functions or M-files) has extended the capability of the MATLAB environment for the

solution of digital image processing problems (González, 2004).



In this chapter, it is performed a description of the basic concepts of digital

image processing to provide background information of what is performed with the

cells images that I will study in my dissertation thesis. The cell images will be processed

using the image processing program MATLAB.

7.2 – PRE-PROCESSING EVALUATION OF DIGITAL IMAGES

After digital images have been captured, and prior to initiating processing

algorithm applications, each image should be evaluated with regard to its general

characteristics, including noise, blur, background intensity variations, brightness and

contrast, and the general pixel value distribution (histogram profile). Attention should

be given to shadowed regions to determine how much detail is present, as well as

bright features (or highlights) and areas of intermediate pixel intensity (Davidson,

2007).

Each image-editing program has a statistics or status window that enables the

user to translate the mouse cursor over the image and obtain information about

specific pixel values at any location in the image. For example, the Photoshop Info

Palette provides continuously updated pixel information, including x and y coordinates,

RGB (red, green, and blue) color values, CMYK (cyan, magenta, yellow, black)

conversion percentages, and the height and width of a marquee selection within the

image. Preference options in the palette display include selecting alternative color-

space models for information readout. Among the models available in Photoshop are

grayscale, HSB (hue, saturation, and brightness), web color (the 216 colors that overlap

in the Windows and Macintosh 8-bit or 256 color display palettes), actual color,

opacity, and Lab color (device-independent color space) (Davidson, 2007).

By evaluating the intensities (grayscale and color) and histogram positions of

various image features, the black and white set points for stretching and sliding of the

entire histogram for contrast adjustments can be determined. The image should also

be checked for clipping, which is manifested by the appearance of saturated white or

underexposed black regions in the image. In general, clipping should be avoided, both

during image acquisition, and while the image is being processed. Images that have

been adversely affected by background intensity variations should be corrected by flat-



field techniques or background subtraction prior to applying histogram manipulations

(Davidson, 2007).

7.3 – LOOK-UP TABLES

Several of the fundamental digital image processing algorithms commonly

employed in optical microscopy function through a technique known as single-image

pixel point operations, which perform manipulations on sequential individual pixels

rather than large arrays. The general equation utilized to describe single-image pixel

point processes for an entire image array is given by the relationship:

where I(x,y) represents the input image pixel at coordinate location (x,y), O(x,y) is the

output image pixel having the same coordinates, and M is a linear mapping function. In

general, the mapping function is an equation that converts the brightness value of the

input pixel to another value in the output pixel. Because some of the mapping

functions utilized in image processing can be quite complex, performing these

operations on a large image, pixel-by-pixel, can be extremely time-consuming and

wasteful of computer resources. An alternative technique used to map large images is

known as a look-up table (LUT), which stores an intensity transformation function

(mapping function) designed so that its output gray-level values are a selected

transformation of the corresponding input values (Davidson, 2007).

Figure 7.1 – Inversion and threshold map look-up table operation (from Davidson, 2007).

(a) (b) (c)



When quantized to 8 bits (256 gray levels) each pixel has a brightness value that

ranges between 0 (black) and 255 (white), to yield a total of 256 possible output

values. A look-up table utilizes a 256-element array of computer memory, which is

preloaded with a set of integer values defining the look-up table mapping function.

Thus, when a single-pixel process must be applied to an image using a look-up table,

the integer gray value for each input pixel is utilized as an address specifying a single

element in the 256-element array. The memory content of that element (also an

integer between 0 and 255) overrides the brightness value (gray level) of the input

pixel and becomes the output gray value for the pixel. For example, if a look-up table is

configured to return a value of 0 for input values between 0 and 127 and to return a

value of 1 for input values between 128 and 255, then the overall point process will

result in binary output images that have only two sets of pixels (0 and 1). Alternatively,

to invert contrast in an image, a look-up table can return inverse values of 0 for 255, 1

for 254, 2 for 253, and so forth. Look-up tables have a significant amount of versatility

and can be utilized to produce a wide variety of manipulations on digital images

(Davidson, 2007).

Image transformations that involve look-up tables can be implemented by

either one of two mechanisms: at the input so that the original image data are

transformed, or at the output so that the transformed image is displayed but the

original image remains unmodified. A permanent transformation of the original input

image may be necessary to correct for known defects in detector properties (for

example, nonlinear gain characteristics) or to transform the data to a new coordinate

system (from linear to logarithmic or exponential). When only the output image should

be modified, the image transformation is performed just before the digital image is

converted back to analog form by the digital-to-analog converter for display on a

computer monitor. In some cases, the results of the transformation specified by the

output look-up table(s) are displayed visually on the monitor, but the original image

data are not altered (Davidson, 2007).

Look-up tables are not restricted to linear or monotonic functions and a variety

of nonlinear look-up tables are utilized in signal processing to correct for camera

response characteristics or to emphasize a narrow region of gray levels. A good

example of the utility of a nonlinear look-up table is the correction of recorded images



that have been inadvertently captured with an incorrect camera gamma adjustment.

In addition, monochrome or color images can also be converted to generate negatives

for photography. Other applications include pseudocoloring and sigmoidal look-up

tables that emphasize a selected range of gray values targeted to enhance desired

features or to adjust the amount of image contrast (Davidson, 2007).

Presented in Figure 7.1 are look-up table mapping functions for image contrast

inversion using both a 256-element memory pre-loaded register and a table map

(Figure 7.1(a)), and a thresholding operation using only a table map (Figure 7.1(b)). The

input pixel gray level is utilized to specify the address of the look-up table element

whose content provides the gray level of the output pixel in the memory register

(Figure 7.1(a)). The square look-up table map presents an alternative method of

calculating output pixel values based on those of the input pixel. To use the map, first

determine the input pixel gray-level value, and then extend a vertical line from the

input value to the mapping function. A horizontal line is then drawn from the

intersection of the vertical line and the mapping function to produce the output pixel

gray level on the vertical axis of the map (Figure 7.1(b) and 7.1(c)). In the case of the

thresholding operation (Figure 7.1(c)), all pixels having an input value below 100 are

mapped to black (0), while other input pixel intensities are unaltered (Davidson, 2007).

7.4 – FLAT-FIELD CORRECTION AND BACKGROUND SUBTRACTION

A digital image acquired from a microscope, camera, or other optical device is

often described as a raw image prior to processing and adjustment of critical pixel

values (see Figure 7.2). In many cases, the raw image is suitable for use in target

applications (printing, web display, reports, etc.), but such an image usually exhibits a

significant level of noise and other artifacts arising from the optical and capture

system, such as distortions from lens aberrations, detector irregularities (pixel non-

uniformity and fixed-pattern noise), dust, scratches, and uneven illumination. In

addition, improper bias signal adjustment can increase pixel values beyond their true

photometric values, a condition that leads to significant errors in measuring the

amplitudes of specific image features. Errors in the raw image are manifested as dark

shadows, excessively bright highlights, specks, mottles, and intensity gradients that



alter the true pixel values. In general, these errors are particularly evident in digital

images having bright, uniform backgrounds, which are produced by a variety of

common microscope illumination modes, including brightfield, oblique, phase

contrast, and differential interference contrast (DIC). Fluorescence images having

medium gray or bright backgrounds, though relatively rare, may suffer from similar

errors (Davidson, 2007).

Figure 7.2 – Flat-field correction of a digital image (from Davidson, 2007).

Applying flat-field correction techniques to raw digital images can often ensure

photometric accuracy and remove common image defects to restore the fidelity of

features and achieve a visual balance. These correction steps should be undertaken

before measuring light amplitudes or obtaining other quantitative information from

pixel intensity values, although the corrections are not necessary in order to display or

print an image. Flat-field and background subtraction techniques usually require

collection of additional image frames under conditions similar to those employed to

capture the primary raw specimen image (Davidson, 2007).

Most of the flat-field correction schemes utilize two supplemental image

frames, in addition to the raw image, to calculate final image parameters (Figure 7.2).

A flat-field reference frame can be obtained by removing the specimen and capturing

the featureless view field at the same focus level as the raw image frame. Flat-field

reference frames should display the same brightness level as the raw image and take



advantage of the full dynamic range of the camera system to minimize noise in the

corrected image. If both the raw image and flat-field reference frame have low signal

amplitudes and contain a significant amount of noise, the corrected image will also be

dark and noisy. In order to compensate for noise and low intensity, flat-field reference

frames can be exposed for longer periods than those used for capturing raw images.

Several averaged frames (3-20) can be added together to create a master flat-field

reference frame with a very low noise level (Davidson, 2007).

In addition to a flat-field reference frame, a dark reference frame is collected,

which effectively records the output level of each pixel when the image sensor is

exposed to a dark scene, absent microscope illumination. The dark frame contains the

pixel bias offset level and noise acquired from electronic and thermal sources that

contaminate the raw image. Offset pixel values derive from the positive voltage

applied to the image sensor in order to digitize analog intensity information from each

photodiode. Electronic noise originates from camera readout and related sources, and

thermal noise is generated by kinetic vibration of silicon atoms in the collection wells

and substrate of semiconductor-based sensors. Collectively, these noise sources are

referred to as dark noise, and are a common artifact in digital image sensors, which

can contribute up to 20 percent of apparent pixel amplitudes. In order to ensure

photometric accuracy, these sources must be subtracted from the flat-field reference

frame and raw image. Dark frames are generated by integrating the image sensor

output for the same period as the raw image, but without opening the camera shutter.

Master dark frames can be prepared by averaging several individual dark frames

together to increase signal intensity (Davidson, 2007).

Once the necessary frames have been collected, flat-field correction is a

relatively simple operation that involves several sequential functions. First, the master

dark frame is subtracted from both the raw image and flat-field reference frames,

followed by the division of the resulting values (Figure 3). In effect, the raw frame is

divided by the flat-field frame after the dark frame has been subtracted from each

frame and the quotient is multiplied by the mean pixel value in order to maintain

consistency between the raw and corrected image intensities. Individual pixels in the

corrected image are constrained to have a gray level value between 0 and 255, as a

precaution against sign inversion in cases where the dark reference frame pixel value



exceeds that of the raw image. The flat-field correction illustrated in Figure 3 shows a

plot of intensity profile across a selected region of the image versus pixel number for

the raw, flat-field, and dark frames, as well as that for the corrected image (Davidson,

2007).

Background subtraction is a technique that results in localized alterations of

each pixel value in the raw image, depending upon the intensity of a corresponding

pixel at the same coordinate location in the background image. As a result, non

uniformities in detector sensitivity or illumination (including mottle, dirt, scratches,

and intensity gradients) can be compensated by storing a background image of an

empty microscope field as a reference image. Video-enhanced contrast (VEC)

microscopy is critically dependent on background subtraction for removal of both stray

light and artifacts from highly magnified images of specimens having poor contrast. In

this case, the background image is obtained by defocusing or displacing the specimen

from the field of view. The resulting background image is stored and continuously

subtracted from the raw image, producing a dramatic improvement in contrast. This

technique is also useful for temporal comparisons to display changes or motion

between view fields (Davidson, 2007).

Figure 7.3 – Surface function background subtraction technique (from Davidson, 2007).

When it is not feasible to capture a background image in the microscope, a

surrogate image can be created artificially by fitting a surface function to the

background of the captured specimen image (see Figure 7.3). This artificial background

image can then be subtracted from the specimen image. By selecting a number of

points in the image that are located in the background, a list of brightness values at

(a) (b)



various positions is obtained. The resulting information can then be utilized to obtain a

least squares fit of a surface function that approximates the background. In Figure 7.3,

eight adjustable control points are used to obtain a least squares fit of the background

image with a surface function B(x, y) of the form:

where c(0) ... c(5) are the least squares solutions, and (x, y) represents the coordinates

of a pixel in the fitted background image. The specimen presented in Figure 7.3 is a

young starfish captured digitally with an optical microscope configured to operate in

oblique illumination. The control points should be chosen so that they are evenly

distributed across the image, and the brightness level at each control point should be

representative of the background intensity. Placing many points within a small region

of the image while very few or none are distributed into surrounding regions will result

in a poorly constructed background image. In general, background subtraction is

utilized as an initial step in improving image quality, although (in practice) additional

image enhancement techniques must often be applied to the subtraction image in

order to obtain a useful result (Davidson, 2007).

Images modified by flat-field correction appear similar to those obtained with

background subtraction, but performing the operation by division (flat-field correction)

is preferred because the technique yields images that are photometrically more

accurate. The primary reason for this difference is that images result from light

amplitude values derived by a multiplicative process that combines the luminous flux

and exposure time. After application of flat-field correction techniques (but not

necessarily background subtraction algorithms), the relative amplitudes of specimen

features will be photometrically accurate. As an added benefit, flat-field correction

removes a majority of the optical defects that are present in the raw image (Davidson,

2007).

7.5 – IMAGE INTEGRATION

Because a digital image is composed of a matrix of integers, operations such as

the summation or integration of images can readily be conducted at high speed. If the



original images were digitized with 8-bit resolution, the storage region, or digital frame

memory, which holds the accumulated images, must have sufficient capacity to

accommodate a sum that exceeds 8 bits. If it is assumed that a few pixels in an 8-bit

digital image have the maximum gray-level value of 255, then summation of 30 frames

would result in a local pixel gray-level value of 7650 and require a storage register with

13-bit capacity. To sum 256 frames, the storage capacity must equal 65,536 gray levels,

or 16 bits, to accommodate the brightest pixels (Davidson, 2007).

Although modern computer monitors are capable of displaying images having

more than 256 gray levels, the limited response of the human eye (35-50 gray levels)

suggests that 16-bit digital images should be scaled to match the limitations of the

display and human visual ability. When the useful information of the image resides

only in a subregion of the 16-bit stored image, only this portion should be displayed.

This is a beneficial approach when displaying images captured by a slow-scan CCD

camera of a view field with a large intrascene range of intensities. The process involves

searching through the 16-bit image for the visually meaningful portion (Davidson,

2007).

When images obtained with a video-rate analog or CCD camera are summed

into a 16-bit frame memory, display of a meaningful 8-bit image is usually

accomplished by dividing the stored sum by a constant. For example, a 96-frame

summation of a view field can be divided by 96, 64, 32, or 24. Division by 32 is

equivalent to a threefold increase in gain and results in utilization of the full 255 gray-

level range. However, division by 24 is equivalent to a fourfold gain increase and

results in image saturation and loss of information (Davidson, 2007).

Image integration using digital image processing techniques often enables

visualization of a faint object that is barely detectable above the camera noise.

Integration may be of particular value in low-light-level imaging when the brightness of

the image cannot be increased by additional image intensification. However, it is

important to realize that, from signal-to-noise considerations, integration directly on

the sensor is always preferable to integration in the processing software. Each image

integration step in the software introduces analog-to-digital noise as well as camera

readout noise (Davidson, 2007).



7.6 – DIGITAL IMAGE HISTOGRAM ADJUSTMENT

A majority of the digital images captured in an optical device, such as a camera

or microscope, require adjustments to either the look-up table or the image histogram

to optimize brightness, contrast, and general image visibility. Histograms of digital

images provide a graphical representation of image contrast and brightness

characteristics, and are useful in evaluating contrast deficiencies such as low or high

contrast, and inadequate dynamic range. An image histogram is a graphical plot

displaying input pixel values on the x-axis (referred to as a bin) versus the number (or

relative number) of pixels for any given bin value on the y axis. Each bin in a grayscale

histogram depicts a subgroup of pixels in the image, sorted by gray level. The numeric

range of input values, or bins, on the x-axis usually corresponds to the bit depth of the

captured image (0-255 for 8-bit images, 0-1023 for 10-bit images, and 0-4095 for 12-bit

images). Mathematical operations may be performed on the histogram itself to alter

the relative distribution of bins at any gray level. Manipulation of the histogram can

correct poor contrast and brightness to dramatically improve the quality of digital

images (Davidson, 2007).

Histogram stretching involves modifying the brightness (intensity) values of

pixels in the image according to a mapping function that specifies an output pixel

brightness value for each input pixel brightness value (see Figure 7.4). For a grayscale

digital image, this process is straightforward. For an RGB color space digital image,

histogram stretching can be accomplished by converting the image to a hue,

saturation, intensity (HSI) color space representation of the image and applying the

brightness mapping operation to the intensity information alone. The following

mapping function is often utilized to compute pixel brightness values:

In the above equation, the intensity range is assumed to lie between 0.0 and

1.0, with 0.0 representing black and 1.0 representing white. The variable B represents

the intensity value corresponding to the black level, while the intensity value



corresponding to the white level is represented by the variable W. In some instances, it

is desirable to apply a nonlinear mapping function to a digital image in order to

selectively modify portions of the image (Davidson, 2007).

Histogram equalization (also referred to as histogram leveling) is a related

technique, which results in the reassignment of pixel gray-level values so that the

entire range of gray levels is utilized and the number of counts per bin remains

constant. The process yields a flat image histogram with a horizontal profile that is

devoid of peaks. Pixel values are reassigned to ensure that each gray level contains an

equal number of pixels while retaining the rank order of pixel values in the original

image. Equalization is often utilized to enhance contrast in images with extremely low

contrast where a majority of the pixels have nearly the same value, and which do not

respond well to conventional histogram stretching algorithms. The technique is

effective in treating featureless dark, and flat-field frames, and to rescue images with

low-amplitude gradients. In contrast, histogram stretching spaces gray-level values to

cover the entire range evenly. The auto-enhance or automatic levels (contrast)

features of many image processing software packages utilize one of these histogram-

based transformations of the image (Davidson, 2007).

Figure 7.4 – Contrast enhancement by histogram stretching (from Davidson, 2007).



Digital image histograms can be displayed in several motifs that differ from the

conventional linear x and y plots of pixel number versus gray level value. Logarithmic

histograms chart the input pixel value on the x-axis versus the number of pixels having

that value on the y-axis, using a log scale. These histograms are useful to examine pixel

values that comprise a minority of the image, but exhibit a strong response to

histogram stretching. Another commonly employed variation, the integrated or

cumulative histogram, plots input pixel values on the x-axis and the cumulative

number of all pixels having a value of x, and lower, on the y-axis. Cumulative

histograms are often utilized to adjust contrast and brightness for images gathered in

phase contrast, DIC, and bright field illumination modes, which tend to have light

backgrounds (Davidson, 2007).

In some cases, images have regions of very high intensity, manifested by large

peaks near the histogram 255 gray level, where the video signal is saturated and all

pixels have been rendered at the maximum gray value. This situation is termed gray-

level clipping and usually indicates that a certain degree of detail has been lost in the

digital image because some regions of the original image that might have different

intensities have each been assigned to the same gray value. Clipping of the histogram

may be acceptable in some circumstances if detail is lost only from unimportant parts

of the image. Such a situation might occur, for example, if the system has been

adjusted to maximize the contrast of stained histological slides under brightfield

illumination, with the clipping occurring only in bright background regions where there

is no cellular structure (Davidson, 2007).

7.7 – SPATIAL CONVOLUTION KERNELS (OR MASKS)

Some of the most powerful image processing tools utilize multipixel operations,

in which the integer value of each output pixel is altered by contributions from a

number of adjoining input pixel values. These operations are classically referred to as

spatial convolutions and involve multiplication of a selected set of pixels from the

original image with a corresponding array of pixels in the form of a convolution kernel

or convolution mask. Convolutions are mathematical transformations of pixels, carried

out in a manner that differs from simple addition, multiplication, or division, as



illustrated in Figure 7.5 for a simple sharpening convolution kernel mask (Davidson,

2007).

In the simplest form, a two-dimensional convolution operation on a digital

image utilizes a box convolution kernel. Convolution kernels typically feature an odd

number of rows and columns in the form of a square, with a 3 x 3 pixel mask

(convolution kernel) being the most common form, but 5 x 5 and 7 x 7 kernels are also

frequently employed. The convolution operation is performed individually on each

pixel of the original input image, and involves three sequential operations, which are

presented in Figure 7.5. The operation begins when the convolution kernel is overlaid

on the original image in such a manner that the center pixel of the mask is matched

with the single pixel location to be convolved from the input image. This pixel is

referred to as the target pixel (Davidson, 2007).

Figure 7.5 – The convolution operation sequence (from Davidson, 2007).

Next, each pixel integer value in the original (often termed the source) image is

multiplied by the corresponding value in the overlying mask (Figure 7.5). These

products are summed and the grayscale value of the target pixel in the destination

image is replaced by the sum of all the products, ending the operation. The

convolution kernel is then translocated to the next pixel in the source image, which



becomes the target pixel in the destination image, until every pixel in the original

image has been targeted by the kernel (Davidson, 2007).

Convolution kernels may contain all positive, or positive and negative values,

and thus can result in negative totals, or results that exceed the maximum 255 limit

that a pixel can hold. Appropriate divisor and offset values are needed to correct this.

The smoothing convolution kernel illustrated in Figure 7.6(a) has a value of unity for

each cell in the matrix, with a divisor value of 9 and an offset of zero. Kernel matrices

for 8-bit grayscale images are often constrained with divisors and offsets that are

chosen so that all processed values following the convolution fall between 0 and 255.

Many of the popular software packages have user-specified convolution kernels

designed to fine-tune the type of information that is extracted for a particular

application (Davidson, 2007).

Convolution kernels are useful for a wide variety of digital image processing

operations, including smoothing of noisy images (spatial averaging) and sharpening

images by edge enhancement utilizing Laplacian, sharpening, or gradient filters (in the

form of a convolution kernel). In addition to convolution operations, local contrast can

be adjusted through the application of maximum, minimum, or median filters that rank

the pixels within each local neighborhood. Furthermore, the use of a Fourier transform

to convert images from the spatial to the frequency domain makes possible another

class of filtering operations. The total number of algorithms developed for image

processing is enormous, but several operations enjoy widespread application among

many of the popular image processing software packages (Davidson, 2007).

7.8 – SMOOTHING CONVOLUTION FILTERS (SPATIAL AVERAGING)

Specialized convolution kernels, often termed smoothing filters, are often used

for reducing random noise in digital images. A typical smoothing convolution filter is

illustrated in Figure 7.6(a), and is essentially a matrix having an integer value of 1 for

each row and column. When an image is convolved with this type of kernel, the gray

value of each pixel is replaced by the average intensity of its eight nearest neighbors

and itself. Random noise in digital images is manifested by spurious pixels having

unusually high or low intensity values. If the gray value of any pixel overlaid by the



convolution kernel is dramatically different than that of its neighbors, the averaging

effect of the filter will tend to reduce the effect of the noise by distributing it among all

of the neighboring pixels (Davidson, 2007).

Figure 7.6 – Smoothing and sharpening convolution kernels (from Davidson, 2007).

The nine integers in each smoothing kernel illustrated in Figure 7.6 add to a

value of 1 when summed and divided by the number of values in the matrix. These

kernels are designed so that the convolution operation will produce an output image

having an average brightness that is equal to that of the input images (however, in

some cases, this may be only approximate). In general, the sum of terms in most

convolution kernels will add to a value between zero and one in order to avoid

creating an output image having gray values that exceed the dynamic range of the

digital-to-analog converter utilized to display the image (Davidson, 2007).

Smoothing convolution kernels act as low-pass filters to suppress the

contribution of high spatial frequencies in the image. The term spatial frequency is

analogous to the concept of frequency with respect to time (temporal frequency), and

describes how rapidly a signal changes with respect to position in the image. A low

spatial frequency might exhibit only a few cycles across the width of an image, while a

high spatial frequency often displays numerous cycles in the same linear dimensions.

An excellent example is the minute orderly arrays of miniature pores and striate

exhibited by diatom frustules, which alternate between very high and low intensities

over very short distances. A low spatial frequency might exhibit only a few cycles

across the width of an image (manifested as widely spaced stripes, for example),



whereas a high spatial frequency undergoes numerous cycles across the lateral

dimensions of an image. The highest spatial frequency that can be displayed in a digital

image has a period equal to the width of two pixels (Davidson, 2007).

The type of random noise typically observed in digital images has a high spatial

frequency that can be effectively removed by applying a smoothing convolution kernel

to the image, pixel by pixel. However, other "real" image features that are desirable,

such as object boundaries and fine structural details, may also have high spatial

frequencies that can unfortunately be suppressed by the smoothing filter.

Consequently, application of a smoothing convolution kernel will often have the

undesirable effect of blurring an input image. Furthermore, the larger the kernel (5 x 5,

7 x 7, and 9 x 9), the more severe this blurring effect will be (Figure 8). For most

applications, the size and form of the smoothing kernel must be carefully chosen to

optimize the tradeoff between noise reduction and image degradation. A Gaussian

filter is a smoothing filter based on a convolution kernel that is a Gaussian function,

and provides the least amount of spatial blurring for any desired amount of random

noise reduction. Smoothing filters are good tools for making simple cosmetic

improvements to grainy images that have a low signal-to-noise ratio, but these filters

can also undesirably reduce the image resolution as a consequence (Davidson, 2007).

7.9 – SHARPENING CONVOLUTION FILTERS

In direct contrast to the action of smoothing convolution filters, sharpening

filters are designed to enhance the higher spatial frequencies in a digital image, while

simultaneously suppressing lower frequencies. A typical 3 x 3 convolution mask and its

effect on a digital image captured with an optical microscope is illustrated in Figure

7(c). In addition to enhancing specimen boundaries and fine details, sharpening filters

also have the effect of removing slowly varying background shading. Thus, these filters

can sometimes be utilized to correct for shading distortion in an image without having

to resort to background subtraction algorithms. Unfortunately, sharpening convolution

filters have the undesirable effect of enhancing random noise in digital images

(Davidson, 2007).



Figure 7.7 – Kernel size effects on smoothing convolution operations (from Davidson, 2007).

The kernel size can be adjusted to optimize the effects of sharpening filters and

to fine-tune the masks to operate on a specific range of spatial frequencies. A typical 3

x 3 mask (see Figures 7.5 and 7.6) has the greatest effect on image features that vary

over the spacing interval of a single pixel. Doubling or tripling the size of the kernel will

target lower spatial frequencies that extend over two or more pixels (Davidson, 2007).

7.10 – MEDIAN FILTERS

Median filters are primarily designed to remove image noise, but are also very

effective at eliminating faulty pixels (having unusually high or low brightness values)

and reducing the deterioration caused by fine scratches. These filters are often more

effective at removing noise than smoothing (low pass) convolution kernels. Median

kernels are applied in a manner that is different from standard smoothing or

sharpening kernels. Although the median filter operates in a local neighborhood that is

translated from pixel to pixel, there is no convolution matrix applied. At each

successive pixel location, the pixels under scrutiny are ordered in rank according to

their intensity magnitude. A median value is then determined for all of the pixels

covered by the neighborhood, and that value is assigned to the central pixel location in

the output image (Davidson, 2007).

Median filters are useful for removing random intensity spikes that often occur

in digital images captured in the microscope. Pixels contributing to the spike are

replaced with the median value of the local neighborhood pixels, which produces a

more uniform appearance in the processed image. Background regions that contain

infrequent intensity spikes are rendered in a uniform manner by the median filter. In



addition, because the median filter preserves edges, fine specimen detail, and

boundaries, it is often employed for processing images having high contrast (Davidson,

2007).

7.11 – SPECIALIZED CONVOLUTION FILTERS

Derivative filters provide a quantitative measurement for the rate of change in

pixel brightness information present in a digital image. When a derivative filter is

applied to a digital image, the resulting data concerning brightness fluctuation rates

can be used to enhance contrast, detect edges and boundaries, and to measure

feature orientation. One of the most important derivative filters is the Sobel filter,

which combines two orthogonal derivatives (produced by 3 x 3 kernel convolutions) to

calculate the vector gradient of brightness. These convolutions are very useful for edge

enhancement of digital images captured in the microscope. Edges are usually one of

the most important features in a microscopic structure, and can often be utilized for

measurements after appropriate enhancement algorithms have been applied

(Davidson, 2007).

Laplacian filters (often termed operators) are employed to calculate the second

derivative of intensity with respect to position and are useful for determining whether

a pixel resides on the dark or light side of an edge. The Laplacian enhancement

operation generates sharp peaks at the edges, and any brightness slope, regardless of

whether it is positive or negative, is accentuated, bestowing an omnidirectional quality

to this filter. It is interesting to note that in the human visual system, the eye-brain

network applies a Laplacian-style enhancement to every object in the viewfield.

Human vision can be simulated by applying a Laplacian-enhanced image to the original

image, using a dual-image point process, to produce a modified image that appears

much sharper and more pleasing (Davidson, 2007).

An important issue that arises within the convolution process methodology

centers on the fact that the convolution kernel will extend beyond the borders of the

image when it is applied to border pixels. One technique commonly utilized to remedy

this problem, referred to as centered, zero boundary superposition, is simply to ignore

the problematic pixels and to perform the convolution operation only on those pixels



that are located at a sufficient distance from the borders. This method has the

disadvantage of producing an output image that is smaller than the input image. A

second technique, called centered, zero padded superposition, involves padding the

missing pixels with zeroes. Yet a third technique regards the image as a single element

in a tiled array of identical images, so that the missing pixels are taken from the

opposite side of the image. This method is called centered, reflected boundary

superposition and has the advantage of allowing for the use of modulo arithmetic in

the calculation of pixel addresses to eliminate the need for considering border pixels as

a special case. Each of these techniques is useful for specific image-processing

applications. The zero padded and reflected boundary methods are commonly applied

to image enhancement filtering techniques, while the zero boundary method is often

utilized in edge detection and in the computation of spatial derivatives (Davidson,

2007).

7.12 – UNSHARP MASK FILTERING

Unsharp mask algorithms operate by subtraction of a blurred image from the

original image, followed by adjustment of gray level values in the difference image.

This operation enables preservation of high-frequency detail while allowing shading

correction and background suppression. The popular technique is an excellent vehicle

to enhance fine specimen detail and sharpen edges that are not clearly defined in the

original image. The first step in an unsharp mask process is to produce a slight blur (by

passage through a Gaussian low-pass filter) and a reduction in amplitude of the

original image, which is then subtracted from the unmodified original to produce a

sharpened image. Regions in the image that have uniform amplitude are rendered in a

medium gray brightness level, whereas regions with larger slopes (edges and

boundaries) appear as lighter or darker gradients (Davidson, 2007).

In general, unsharp mask filters operate by subtracting appropriately weighted

segments of the unsharp mask (the blurred original) from the original image. Such a

subtraction operation enhances high-frequency spatial detail at the expense

(attenuation) of low-frequency spatial information in the image. This effect occurs

because high-frequency spatial detail removed from the unsharp mask by the Gaussian



filter is not subtracted from the original image. In addition, low-frequency spatial detail

that is passed by the Gaussian filter (to the unsharp mask) is almost entirely subtracted

from the original image. Increasing the size of the Gaussian filter allows the smoothing

operation to remove larger size detail, so that those details are retained in the

difference image (Davidson, 2007).

One of the primary advantages of the unsharp mask filter over other

sharpening filters is the flexibility of control, because a majority of the other filters do

not provide any user-adjustable parameters. Like other sharpening filters, the unsharp

mask filter enhances edges and fine detail in a digital image. Because sharpening filters

also suppress low frequency detail, these filters can be used to correct shading

distortion throughout an image that is commonly manifested in the form of slowly

varying background intensities. Unfortunately, sharpening filters also have the

undesirable side effect of increasing noise in the filtered image. For this reason, the

unsharp mask filter should be used conservatively, and a reasonable balance should

always be sought between the enhancement of detail and the propagation of noise

(Davidson, 2007).

7.13 – FOURIER TRANSFORMS

The Fourier transform is based on the theorem that any harmonic function can

be represented by a series of sine and cosine functions, differing only in frequency,

amplitude, and phase. These transforms display the frequency and amplitude

relationship between the harmonic components of the original functions from which

they were derived. The Fourier transform converts a function that varies in space to

another function that varies with frequency. It should also be noted that the highest

spatial frequencies of the original function are found the farthest away from the origin

in the Fourier transform (Davidson, 2007).



Figure 7.8 – Fourier transform filtering (from Davidson, 2007).

Spatial filtering involving Fourier techniques can be utilized to manipulate

images through deletion of high or low spatial-frequency information from an image

by designing a Fourier filter that is nontransmitting at the appropriate frequency. This

technique is especially useful for removing harmonic noise from an image such as the

herringbone or sawtooth patterns often apparent in video images (see Figure 7.8).

Because the added noise is harmonic, it will be found in localized discrete regions of

the Fourier transform. When these local peaks are removed from the transform with

the appropriate filter, the re-formed image is essentially unaltered except that the

offending pattern is absent. Similar filtering techniques can also be applied to remove

sine wave, moiré, halftone, and interference patterns, as well as noise from video

signals, CCDs, power supplies, and electromagnetic induction (Davidson, 2007).

Illustrated in Figure 7.8(a) is a video image of a diatom frustule imaged in

darkfield illumination with a superimposed sawtooth interference pattern. Adjacent to

the diatom image (Figure 7.8(b)) is the Fourier transform power spectrum for the

image, which contains the spatial frequency information. After applying several filters

(Figure 7.8(d)) and re-forming the image, the sawtooth pattern has been effectively

eliminated (Figure 7.8(c)), leaving only the image of the frustules (Davidson, 2007).

The decision as to whether to utilize Fourier filtering or convolution kernel

masks depends on the application being considered. The Fourier transform is an



involved operation that takes more computer horsepower and memory than a

convolution operation using a small mask. However, the Fourier filtering technique is

generally faster than the equivalent convolution operation, especially when the

convolution mask is large and approaches the size of the original image. Appropriate

choice of equivalent Fourier and convolution operations may reduce the complexity of

their respective masks. For example, a simple Fourier filter, such as one designed to

remove harmonic noise, would produce a large and complex convolution mask that

would be difficult to use (Davidson, 2007).

Another useful feature of the Fourier transform stems from its relationship to

the convolution operation, which involves several multiplication and addition

operations, according to the contents of the convolution mask, to determine the

intensity of each target pixel. This operation can be compared to Fourier filtering,

where each value in the Fourier filter is simply multiplied by its corresponding pixel in

the Fourier transform of an image. The two operations are related because the

convolution operation is identical to the Fourier filtering operation when the Fourier

filter is the Fourier transform of the convolution mask. This equivalence indicates that

either of these two techniques can be employed to obtain identical results from an

image, depending only on whether the operator decides to work in image space or

Fourier space (Davidson, 2007).

7.14 – SUMMARY

The extent of the increased processing power of the digital approach may not

be appreciated at first glance, particularly in comparison to the older and apparently

simpler analog methods, such as traditional photomicrography on film. In fact, digital

image processing enables reversible, virtually noise-free modification of an image as a

matrix of integers instead of as a series of time-dependent voltages or, even more

primitively, using a photographic enlarger in the darkroom (Davidson, 2007).

Much of the recent progress in high-resolution transmitted optical microscopy

and low-light-level reflected fluorescence microscopy of living cells has relied heavily

on digital image processing. In addition, most confocal and multiphoton microscopes

depend strictly on high-speed, high fidelity digitization of the scanned image, and on



the subsequent digital manipulation of the view field to be displayed. Newer

microscope designs lacking eyepieces (oculars) and coupled directly to image capture

software also depend on image processing technology to produce high-quality digital

images from the microscope (Davidson, 2007).

The power of digital image processing to extract information from noisy or low-

contrast images and to enhance the appearance of these images has led some

investigators to rely on the technology instead of optimally adjusting and using the

microscope or image sensor. Invariably, beginning with a higher-quality optical image,

free of dirt, debris, noise, aberration, glare, scratches, and artifacts, yields a superior

electronic image. Careful adjustment and proper calibration of the image sensor will

lead to a higher-quality digital image that fully utilizes the dynamic range of both the

sensor and the digital image processing system (Davidson, 2007).

In the study that I will perform in the next year, in my dissertation thesis, the

digital image processing with MATLAB will be used as a work tool to enhance the

details in the cancer cell images of prostate and breast carcinomas. My goal is to

extract information from the referred images, obtaining data that is not possible to get

with biochemical methods of study.

CHAPTER VIII

CONCLUSIONS AND FUTURE WORKS

CHAPTER VII – CONCLUSIONS AND FUTURE WORKS


8.1 – FINAL CONCLUSIONS

The main clinical advantages of brachytherapy are consequently based on the

sharp reduction of dose with distance; showing a reduction of both dose and dose rate

with distance. Therefore, a fall of dose and dose rate causes a larger reduction in cell

kill than a reduced dose or dose rate used in isolation.

Repair of sub-lethally damaged DNA can occur if the cell contains the full

complement of DNA damage detection proteins and repair enzyme systems, but there

must also be sufficient time for these mechanisms to operate. If successful sub-lethal

damage repair has not occurred at a particular site before further sub-lethal damage is

deposited in an appropriately near site, then sub-letal/unrepairable damage will form.

The lower the dose rate of radiation that a cell is exposed to, more likely it is

that repair will occur, because there will be more time for sub-lethal damage repair

before a second “hit” confers the unrepairable damage. Late reacting normal tissues

have a higher capacity for repair than do some tumor cells, probably because the latter

posses mutations that affect repair fidelity and cell cycle checkpoint control, so that

tumor is preferentially killed when compared with normal tissues.

The dividing cell is significantly more sensitive to damage and death from

ionizing radiation because of the need to replicate DNA during cell division. The

decision of G1-phase cells to proceed to S-phase is a critical regulatory step (designated

Start or the restriction point in late G1 cells) in both normal and neoplastic cell growth.

Once a cell reaches S-phase, progression to G2 becomes independent of extracellular

influences, that is, the cell becomes committed to completing DNA synthesis (S-G2

traverse).

One particularly important function of p53 is DNA damage signaling. Here, to

suppress tumorigenesis, p53 halts the cell cycle and induces apoptosis in primary cells

and in tumor cell lines. Since stem cells provide the pool of proliferative

pluri/toti/omni-potent cells within organisms, they are more likely to propagate DNA

lesions and mutations to daughter cells compared to differentiated cells.

From this research work, I expect to find morphological alterations in cancer

cells in comparison with normal cells and after the irradiation of the cancer cells I

CHAPTER VII – CONCLUSIONS AND FUTURE WORKS


expect to find accumulation of p53 in the nucleus of irradiated cells to repair the sub-

lethal damage caused by radiation.

Once again, to highlight these results, the light microscopy photos obtained

with this study will be processed using MATLAB.

8.2 – FUTURE WORKS

The future prospect of this thesis is to continue the study with cells, performing

the analysis and image processing of breast and prostate cancer cells submitted to

brachytherapy. Hence, the study of morphological changes that occur in the irradiated

cells, as well as the modifications in the cellular environment to obtain the maximum

information of the electron microscopy images of these cells, will be done.

Additionally, computational algorithms will be developed to help that study in an

automate and robust manner.

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