European Journal of Pharmacology 714 (2013) 239–248

Contents lists available at SciVerse ScienceDirect

European Journal of Pharmacology

0014-29http://d

n CorrE-m

journal homepage: www.elsevier.com/locate/ejphar

Review

Molecular approaches towards development of purified naturalproducts and their structurally known derivatives as efficientanti-cancer drugs: Current trends

Santu Kumar Saha, Anisur Rahman Khuda-Bukhsh n

Cytogenetics and Molecular Biology Laboratory, Department of Zoology, University of Kalyani, Kalyani-741235, India

a r t i c l e i n f o

Article history:Received 8 February 2013Received in revised form1 June 2013Accepted 8 June 2013Available online 29 June 2013

Keywords:Natural productsHigh throughput screeningStructure activity relationshipTargeted cancer therapyChemo-resistanceDrug formulation

99/$ - see front matter & 2013 Elsevier B.V. Ax.doi.org/10.1016/j.ejphar.2013.06.009

esponding author. Tel.: +91 33 25828768; faxail addresses: prof_arkb@yahoo.co.in, khudabu

a b s t r a c t

Several natural products and their derivatives, either in purified or structurally identified form, exhibitimmense pharmacological and biological properties, some of them showing considerable anticancerpotential. Although the molecular mechanisms of action of some of these products are yet to beelucidated, extensive research in this area continues to generate new data that are clinically exploitable.Recent advancement in molecular biology, high throughput screening, biomarker identifications, targetselection and genomic approaches have enabled us to understand salient interactions of natural productsand their derivatives with cancer cells vis-à-vis normal cells. In this review we highlight the recentapproaches and application of innovative technologies made to improve quality as well as efficiency ofstructurally identified natural products and their derivatives, particularly in small molecular formscapable of being used in “targeted therapies” in oncology. These products preferentially involve multiplemechanistic pathways and overcome chemo-resistance in tumor types with cumulative action. We alsomention briefly a few physico-chemical features that compare natural products with drugs in recentnatural product discovery approaches. We further report here a few purified natural products asexamples that provide molecular interventions in cancer therapeutics to give the reader a glimpse of thecurrent trends of approach for discovering useful anticancer drugs.

& 2013 Elsevier B.V. All rights reserved.

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2402. Recent approaches towards molecular cancer therapies with purified natural products. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240

2.1. Structurally identified and purified natural product libraries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2412.2. High throughput screening–identification of genomic markers of natural product sensitivity in cancer cells . . . . . . . . . . . . . . . . . . . . . 2412.3. Lead generation—A critical step of optimization for drug design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2412.4. Structure based approaches for drug discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2422.5. Emerging strategies of using interferons in anti-cancer drug development programme. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2422.6. Aptamer as cancer therapeutic agent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242

3. Genomic construction vs. natural products in cancer therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2424. Targeted cancer therapy and signalling events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242

4.1. Driving cells into apoptosis—The process of “programmed cell death” as drug target . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2434.2. Insensitivity to growth signals—“Cell-cycle” as molecular targets. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2434.3. Limitless replicative potential—“Telomeric-DNA” as drug target . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2434.4. “Angiogenesis” signals as therapeutic target. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2434.5. Targeting tissue invasion and “metastasis” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2434.6. Targeting self sufficiency in growth signals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2434.7. Targeting chaperone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2444.8. Targeting histone deacetylase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2444.9. Autophagy as cancer drug targets. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244

ll rights reserved.

: +91 33 25828750.khsh_48@rediffmail.com (A.R. Khuda-Bukhsh).

S.K. Saha, A.R. Khuda-Bukhsh / European Journal of Pharmacology 714 (2013) 239–248240

5. Role of some purified and structurally defined natural products in targeted cancer therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2456. Outlook and future challenges—Application of innovative technologies in cancer therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2457. Methodological drawbacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2468. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246

1. Introduction

Compounds with biological activities, and products derivedfrom natural sources, e.g. plants, animals and microorganisms aredefined broadly as “natural products” that constitute the majorsources of chemical diversity, in purified or structurally identifiedform. These compounds can also be classified as crude therapeuticformulations, semi-synthetic natural products, natural productderived compounds, herbal medicines and complementary andalternative medicines. Many drugs used recently for therapeuticapplications are complex natural products or natural productderivatives (Salvador et al., 2012; Clardy and Walsh, 2004). Cancerremains a major public health issue as more than one millionpeople are diagnosed with cancer each year (Howlader et al.,2012). Development of resistance against chemotherapy, toxicityand side-effects necessitates the search for relatively non-toxicdrugs or natural products, to wage a more humane war againstcancer (Pan and Ho, 2008). However, orthodox approaches forcancer therapy including surgery, radiotherapy and adjuvanttherapies are still necessary.

In this review, we will focus more on the following aspects:(a) evaluation of purified natural products and their furtherstrategic up-gradation for more specific use in future anticancerdrugs; (b) developmental application of innovative technologiesuseful in tissue-specific targeting, chemo-resistant cancer typesand (c) recent trends of molecular approaches towards targetedcancer therapeutics.

But at the onset, we will briefly dwell upon the features thatcompare natural products with drugs. The architectural determi-nants that highlight comparison between natural products andsynthetic drug molecules in pharmacological applications havebeen depicted in Fig. 1 and outlined below.

Physico-chemical properties of

natural products comparable with

drugs

Follow “Lipinski’s” rules of drug formulations

Evolutionary selected for

biological targets

Greater water solubility

Higher chemical diversity

More carbon, hydrogen, oxygen and less nitrogen

Fig. 1. Physico-chemical properties of natural products comparable with drugs—indicate natural products contain more carbon, hydrogen oxygen and less nitrogen;evolutionary selected as biological targets; greater water soluble in nature andcontain huge chemical diversity. These are important features to follow pharmaco-kinetics guidelines of “Lipinski's rule” of drug formulation and adsorption in body.

Both the natural products and synthetic molecules share highchemical diversity, biochemical specificity, molecular mass, num-ber of chiral centres, molecular flexibility and distribution of heavymetals suitable for therapeutic applications (Henkel et al., 1999).Compared to synthetic medicinal agents, natural products containmore number of carbon, hydrogen, oxygen and less nitrogen andother elements. Further, the molecular rigidity is greater in naturalproducts as compared to synthetic drugs and other combinatorialdrugs (Feher and Schmidt, 2003). Many useful natural productshave high polarity rendering them greater water solubility, animportant feature in maintaining pharmacokinetics guidelines oforal administration in terms of better adsorption, distribution,metabolism and elimination from body (Butler, 2008). Naturalproduct structures are evolutionarily selected to interact with awide variety of proteins and other biological targets for specificpurposes. The ability of natural products to bind a variety ofprotein domains and folding motifs leads to modulate or inhibitprotein–protein interaction, making these molecules behave aseffective modulators of cellular processes such as immuneresponses, signal transduction, mitosis and apoptosis. By virtueof increased size and binding affinity to gene products naturalproducts provide effective scaffolds for the biological function(Peczuh and Hamilton, 2000). Most of the natural products showseveral key properties as specified in the “Lipinski's rule of five”(Lipinski et al., 1997) appropriate for oral administration. Thus,these criteria clearly point out that natural products can play asignificant role in the selection and design of the most effectivedrug in respect of its specific application.

2. Recent approaches towards molecular cancer therapieswith purified natural products

Cancer is a disease of uncontrolled proliferation and growth ofcells at inappropriate times and locations in the body. When cellsacquire mutations that affect the regulation of cell division, theyundergo unlimited multiplications to form tumors (Hanahan andWeinberg, 2011); these proliferating cells consequently transforminto malignant ones and invade other tissues as a result ofmetastasis.

Recent drug discovery program seeks for rapid screening, hitidentification and hit-to-lead generation. In these circumstances,traditional natural product development programs which arebased on extract-library screening, bioassay-guided isolation,structure elucidation and subsequent product scale up processes,are lagging behind as compared to the approaches that havelargely been utilized in the synthetic chemical process. However,the high throughput screening methods in combination withapproaches of human genetics and genomics towards functionalvalidation of target regions, especially by over expression orknockdown by RNA-interference in transgenic animals and modelorganisms (Benson et al., 2006) are yielding interesting results.This outcome is also creating interest in pursuing studies onnatural products as a source of chemical diversity and leadgeneration. New approaches with natural products for drug

Natural

product

library

Product purification and

characterization

High throughput screening

(in vitroassay)

Structure activity

relationship

(biological targets or

hitidentificati

on)

Lead generation ( product

optimization) to improve target

specificity

Evaluation of drug

targets in animal model

Randomized

controlled clinical trials

Approval from drug administration and marketing

Chemical biology

+

Structural biology

Fig. 2. Recent approaches towards molecular cancer therapy with natural products—is a combinational procedure of chemical biology and structural biology thatstarts from natural product library preparation, followed by product purification/characterization, in vitro assay of high throughput screening, biological targets orhit identification, product optimization for target specific delivery, evaluating ofrole by in vivo assay and randomized controlled trial that finally lead to drugapproval by food and drug administration of marketing.

S.K. Saha, A.R. Khuda-Bukhsh / European Journal of Pharmacology 714 (2013) 239–248 241

designing and their further strategic up-gradation for specific usein molecular cancer therapeutics are outlined below (Fig. 2).

2.1. Structurally identified and purified natural product libraries

Natural product samples are stored as “crude extract library” forfurther screening purposes. The crude extract is further concentrated,fractionated and purified to yield essential biologically active com-ponent(s) and stored as “pure compound library” (Koehn and Carter,2005). With the advancement of technology such as HPLC-massspectrometer, and natural product database resources [e.g. Dictionaryof Natural Products, SciFinder and Antibase] identification of knowncompounds, if any, after purification process became simplified(Strege, 1999). In those cases where the criteria of biological activityand selectivity persist, preliminary structure activity relationshiphelps in de novo complex structure determination and additionaloptimization procedure proceeds onward following medicinal chem-istry guidelines of drug development. Due to time limiting process ofseparation, isolation and purity check of crude mixture collection;the present focus is more on keeping “semi purified chemicalcompounds” as the base stock; but the interest is still persistingtowards making the “fully purified compounds” readily available foruse when needed (Baker et al., 2007).

2.2. High throughput screening–identification of genomicmarkers of natural product sensitivity in cancer cells

The exercise of automated testing of huge collections of com-pounds (natural products as well as synthetic molecule libraries)

for any specific biological targets (inhibitors, activators, cell surfacereceptors etc.) to identify any potential drug is commonly known ashigh throughput screening. Human tumor derived cell line modelsmaintained and propagated either in culture or in mice xenograftsand more recently, genetically engineered mouse models of humantumorigenic applications are very effective to the discovery andevaluation of potential new anticancer agents (Sharma et al., 2010).National Cancer Institute 60 platform established in 1986, intro-duced the concept of high throughput cell based profiling. NationalCancer Institute 60 panel comprises approximately 6–9 humantumor derived cell lines, representative of each cancer type usedto capture frequencies of drug response (Adams, 2001). Researchersat the Cancer Chemotherapy Center of the Japanese Foundation forCancer Research established a panel of 39 human tumor derivedcell lines in 1999, that included a subset of the National CancerInstitute 60 cell lines and additional gastric cancer cell lines (basedon prevalence in Japanese population). This platform is alsosuccessful in identifying anticancer agents as well as cancerbiomarker identification (Shiwa et al., 2003). Considering theconserved nature of 20 different tissue origins with equal repre-sentation, an ideal human tumor cell line profiling panel shouldconsist of 2000–6000 cell lines. With this goal in mind, a human cellline platform, with as broad representation as possible, has recentlybeen established (2006), which currently includes 1200 cell linespanel. The Center for Molecular Therapeutics 1000 platform pro-filed 127 candidates of anticancer agents and interrogated forcytostatic and cytotoxic activity against approximately 700 humantumor derived adherent cell lines (corresponding to around 70,000drug-cell lines pairing as of May 2009 report) (Sharma et al., 2010).Genetically defined cancer subsets, irrespective of the tissue oforigin is also associated with response to drug sensitivity. Thuscurrent standard practice in medical oncology follows patient'sgenotypic information for therapy (McDermott et al., 2007,http://www.ox.ac.uk/media/news_stories/2013/130325.html). Dueto genomic heterogeneity present in tumors in different humanpopulations, heterogeneity of cell types in tumor cell populations isalso likely to have an important role in drug sensitivity (Rosen andJordan, 2009). Therefore mutation analysis data for these cell lineswith drug sensitivity are now being integrated in an effort to betterunderstand the genomic determinants of drug response to variouscancer therapeutic approaches. Validation and prioritization of thebest targets for the targeted cancer therapy is also very critical.There is certainly no shortage of potential drug targets. More than350 cancer genes have been catalogued (Futreal et al., 2004) fordrug sensitivity. With these cell-line based approaches of drugsensitivity, a very recent work dealing with screening of 130 drugs(under clinical and preclinical investigation) has identified 64cancer biomarkers successfully (Garnett et al., 2012).

2.3. Lead generation—A critical step of optimization for drug design

The next major step after target selection is lead generation.Lead generation is an optimization procedure. This is accom-plished through chemical modification by employing structureactivity relationship and structure-based designing (if structuralinformation of biological proteins as well as chemical structure ofthe compound are known) to improve potency, reduce off targetactivities and develop pharmacokinetics of the compound to betested as therapeutic drug molecule. Chemical biology and struc-tural biology data are combined together to reach the goal. Thechemical biology process involves, phenotypic screening for leadgeneration and for lead optimization the process incorporatesbiomarker selection and probing selectivity. On the other hand,the structural biology includes library designing and virtualscreening for lead generation, followed by the process of designingpotency and understanding selectivity for lead optimization

S.K. Saha, A.R. Khuda-Bukhsh / European Journal of Pharmacology 714 (2013) 239–248242

(Collins and Workman, 2006). Phenotypic screening method inintact cells or in organisms such as Caenorhabditis elegans orzebrafish embryos is applicable to target identification and leadgeneration (Clemons, 2004) for some small molecule's targetscreening that are incompatible with in vitro biochemical assaysand many molecular targets to be probed simultaneously in thecellular environment. Some imaging based high content screensinterrogate the phenotype directly at the molecular level(Lundholt et al., 2005). Sensitive biophysical techniques such asnuclear magnetic resonance and X-ray diffraction can detect theweak bindings of much smaller compounds. The finding of p38mitogen activated protein kinase inhibitor is one such example oflead generation (Gill et al., 2005). Combining biochemical highthroughput screening and biophysical methods, protein–ligand co-crystallography is a powerful and efficient lead generation strategy(Card et al., 2005). Computational chemistry provides empiricalparameters that describe appropriate physiochemical properties ofdrugs that are routinely incorporated into new compound librarydesign (Vieth et al., 2004). Examples of some natural products thatenter into clinical trial after these high throughput screening andlead generations include camptothecins, vinca alkaloids, andepothilones (Mann, 2002).

2.4. Structure based approaches for drug discovery

Computational chemistry is an important ally that is contribut-ing to a great extent towards screening strategies. Some structuralmotifs that confer promiscuous nonspecific activity are associatedwith toxicity can be eliminated in this process. The variousapproaches require generation of huge compound libraries. Iden-tification of several protein classes such as kinases and Heat ShockProtein 90 are examples of structure based designing approaches.The structure based approach with natural products, such asgeldanamycin and radicicol, which are bound to N-terminalATPase domains of Heat Shock Protein 90 revealed a uniquefolding pattern in the ATP binding site (Roe et al., 1999). The drugdiscovery programwas conducted by Developmental TherapeuticsProgram of the National Cancer Institute, USA, which maintainssome important databases and tools for cancer therapeutics. Linksto these and additional databases can be found at http://dtp.nci.nih.gov/. Molecular pharmacology and drug discovery strategiesmake use of three important databases: (A) activity patterndatabase; (B) molecular structural features of tested compounddatabase; (C) possible targets or modulators of activity in the celldatabase (Weinstein et al., 1997). “Patterns of activity” of anycompound often indicate similarity in mechanism of action, modeof resistance and molecular structure and this can be analyzedusing “COMPARE” tools. Patterns of activity could predict a com-pound mechanism of action (Weinstein et al., 1997). The informa-tion intensive approach to molecular pharmacology shakes handswith recent approaches in cancer therapeutics.

2.5. Emerging strategies of using interferons in anti-cancer drugdevelopment programme

Type 1 interferons, which comprise a group of cytokines, arecurrently used as a novel therapeutic strategy in the treatment ofcancer. Interferon-α demonstrates response through Epidermalgrowth factor dependent ras/MEK1/erk and adenylate cyclise/cAMP signaling events in cancer cells. The AKT/NFκβ pathwaymediated survival response has also been shown when cells wereexposed to Interferon-α. Combinatorial effect of Interferon-α eitherwith single or multiple pathway inhibitors might be useful inchemotherapeutic approach with its low concentration. As forexample, when epidermal growth factor receptor inhibitor gefiti-nib was used along with IFN-α, effective co-operative antitumor

activity (Caraglia et al., 2013) was noted. Interferon-α induces bothapoptosis and a counteracting epidermal growth factor dependentsurvival response in cancer cells (Lamberti et al., 2007).

2.6. Aptamer as cancer therapeutic agent

Aptamers are non immunogenic, short oligonucleotides orpeptides representing a valid alternative to antibodies that targetspecific cancer cell surface proteins in clinical diagnosis andtherapy. Cell “Systematic Evolution of Ligands by Exponentialenrichment” approach is the method of choice to develop nucleaseor proteinase resistance aptamers for target specific delivery inphysiological conditions. Wu et al. (2010) reported self assembledaptamer-micelle nano structure that achieved selective and strongbindings to targets, low in off rate once bound with target, rapidrecognition ability, dual drug delivery ability and with in vivo drugdelivery applications as its property. Li et al. (2011) and Espositoet al. (2011) devised independently anti-epidermal growth factorreceptor aptamer for cancer cell death. Cancer cells that areresistant to epidermal growth factor receptor inhibitors such asgefitinib and cetuximab showed significant response when com-bined treatment with cetuximab and RNA-aptamer were used astherapy (Esposito et al., 2011). Application of DNA aptamer asmolecular probe for human papilloma virus associated cervicalcancer cells is also reported (Graham and Zarbl, 2012).

3. Genomic construction vs. natural products in cancertherapy

Dietary habitats, food and lifestyle factors can influence devel-opment of cancer risk to an individual by targeting the geneticsusceptibility. Several of the most common susceptible geneticvariations are single nucleotide polymorphisms like CYP1A1,CPY1A2, CYP2D6, GSTM1 and NAT2) which cause differences inmetabolic or detoxification activities (Perera, 1996). Incidence ofincreased lung cancer risk has been correlated with variant formsof CYP1A1 that catalyse the oxygenation of polyaromatic hydro-carbons; polyaromatic hydrocarbons are present in cigarettesmoke and therefore smoking increases the cancer risk. Othergenes such as CYP2D6 (acts on an unknown substrate, possiblytobacco-specific nitrosamines), and GSTM1 (detoxifies reactive,electrophilic compounds such as polyaromatic hydrocarbons)(Perera, 1996) also have similar functional role in increasing riskof cancer. The relative prevalence and distribution of such poly-morphisms in populations that may affect individual responses toboth risk and protective factors can be targeted by antioxidantsand other naturally occurring dietary constituents for cancertherapeutic strategy.

4. Targeted cancer therapy and signalling events

The term “targeted cancer therapeutics” describe small molecularagents that are not only rationally designed but also acts on diseasecausing oncogenic targets. Various well defined phenotypic hallmarktraits of cancer (Hanahan and Weinberg, 2011) can be good targetsfor cancer therapy; these include (a) self sufficiency in growthsignals, (b) evasion of apoptosis, (c) limitless replicative potentials,(d) angiogenesis, (e) tissue invasion and (f) metastasis. Oncogeneproducts themselves and their downstream signalling proteins arealso suitable targets (e.g. mTOR, PI3 kinase, RAS–RAF–MEK–ERKpathway). In addition, protein chaperone (e.g. heat shock protein90), chromatin regulation (e.g. histone deacetylase) and autophagycan also provide valuable drug targets (McDonald et al., 2006;Minucci and Pelicci, 2006; Lamy et al., 2013) (Fig. 3). Therapeutic

Apoptosis

Chemotherapeutic

targets

Angiogenesis

Metastasis

Telomeric DNA

Growth signals

Cell cycle

Histone deacetylas

Chaperone

Autophagy

Fig. 3. Chemotherapeutic molecular targets—identified some signalling, epigeneticand cellular events for target specific drug delivery. These targets include:apoptosis, angiogenesis, metastasis, cell cycle, growth signals, telomeric DNA,chaperon, histone deacetylase and autophagy.

S.K. Saha, A.R. Khuda-Bukhsh / European Journal of Pharmacology 714 (2013) 239–248 243

approaches that can target more than one of these mechanisms gainpreference and attention for drug formulation in cancer therapy.Treatment of cancer by targeting any one of the above mentionedacquired capabilities by administration of one or more chemicalentities attracts interest of the recent workers on cancer therapy.

4.1. Driving cells into apoptosis—The process of “programmed celldeath” as drug target

The ability of tumor cell population to expand in number isdetermined not only by the rate of cell proliferation but also by therate of cell death. Programmed cell death—“apoptosis” representsa major source of this attrition. Members of the Bcl-2 family ofproteins, whose members have either pro-apoptotic (Bax, Bak, Bid,and Bim) or anti-apoptotic (Bcl-2, Bcl-XL, Bcl-W) functions, act inpart by governing mitochondrial death signalling through cyto-chrome c release. The p53 tumor repressor protein can elicitapoptosis by up-regulating expression of pro-apoptotic Bax inresponse to sensing DNA damage; Bax in turn stimulates mito-chondria to release cytochrome c. The ultimate effectors ofapoptosis include an array of intracellular proteases termed ascaspases (Thornberry and Lazebnik., 1998).

4.2. Insensitivity to growth signals—“Cell-cycle” as molecular targets

Cancer cells must evade anti-proliferative signals if they are toprosper. Much of the circuitry that enables cells to respond to anti-growth signals is associated with cell cycle clock, specially thecomponent governing the transition of the cell through the G1phase of its growth cycle. Cyclin dependent kinases with theirdifferent cyclin subunits are catalytic components that regulatekey switches throughout cell cycle. Regulation of transcription,differentiation, nutrient uptake and other functions of cells aretightly controlled by these protein kinases (Massague, 2004).

4.3. Limitless replicative potential—“Telomeric-DNA” as drug target

Telomerase maintenance is evident in virtually all types ofmalignant cells (Shay and Bacchetti., 1997). 85–90% of them succeed

in doing so by up-regulating expression of the telomerase enzymegene, which adds hexa-nucleotide repeats onto the ends of telo-meric DNA (Bryan and Cech, 1999), while the remainder haveinvented a way of activating mechanism termed alternative length-ening of telomerase which appears to maintain telomerase throughrecombination based in terchromosomal exchange of sequenceinformation (Bryan et al., 1995). By one or the other mechanism,telomerase is maintained at a length above a critical threshold, andthis in turn permits unlimited multiplication of descendant cells.Both mechanisms seem to be strongly suppressed in most normalhuman cells in order to deny them unlimited replicative potential.

4.4. “Angiogenesis” signals as therapeutic target

The oxygen and nutrients supplied by the vasculature are crucialfor cell function and survival, obligating virtually all cells in a tissue toreside within a capillary blood vessel. Once a tissue is formed, thegrowth of new blood vessels the process of angiogenesis is transitoryand carefully regulated. The angiogenesis initiating signals are exem-plified by vascular endothelial growth factor and acidic and basicfibroblast growth factors. Each binds to transmembrane tyrosinekinase receptors displayed by endothelial cells (Veikkola and Alitalo,1999). Tumors appear to activate the angiogenic switch by changingthe balance of angiogenesis inducers and countervailing inhibitors.Triphala and its active constituent chebulinic acid are found to benatural inhibitors of vascular endothelial growth factor (Lu et al., 2012).

4.5. Targeting tissue invasion and “metastasis”

Sooner or later during the development of most types ofhuman cancer, primary tumor masses spawn pioneer cells thatmove out, invade adjacent tissues, and hence travel to distant siteswhere they may succeed in founding new colonies. The capabilityfor invasion and metastasis enables cancer cells to escape theprimary tumor mass and colonize new terrain in the body where,at least initially, nutrients arise as amalgams of cancer cells andnormally supporting cells conscripted from the host tissues.Matrix metalloproteinase 15 is identified as an anti-apoptoticfactor in cancer cells (Abraham et al., 2005).

4.6. Targeting self sufficiency in growth signals

Normal cells require mitogenic growth signals before they canshift from a quiescent state into an active proliferative state. Notype of normal cell can proliferate in the absence of suchstimulatory signals. On the other hand cancer cells act by mimick-ing normal growth signalling events in one way or another toachieve the characteristics of self regulation to promote thegrowth without depending on others. Cancer cells acquire theability to synthesize growth factors to which they are responsive,creating a positive feedback signalling loop often termed autocrinestimulation (Hanahan and Weinberg, 2011). The production ofplatelet derived growth factor and tumor growth factor-α byglioblastomas and sarcomas, respectively, are two illustrativeexamples (Hanahan and Weinberg, 2011).Cancer cells can alsoswitch on both ligand activated growth factor receptors andpro-growth integrins engaged to extracellular matrix componentto activate SOS–Ras–Raf–MAP kinase pathway (Aplin et al., 1998).Ras proteins are present in structurally altered forms that enablethem to release a flux of mitogenic signals into cells, withoutongoing stimulation by their normal upstream regulators(Medema and Bos, 1993).

S.K. Saha, A.R. Khuda-Bukhsh / European Journal of Pharmacology 714 (2013) 239–248244

4.7. Targeting chaperone

The proteasome is a catalytic complex that is found in bothnucleus and cytoplasm of eukaryotic cells. The function of theproteasome is to degrade or process intracellular proteins—e.g.mediators of cell cycle progression (cyclins), apoptosis (caspases,Bcl2, and NFκβ). Proteasome inhibitors are the choice of recentcancer therapeutic targets (Adams, 2004). Members of heat shockprotein family exhibit a good target for molecular cancer therapy.Heat shock protein 90 is over expressed in many human cancers.X-ray crystallography data of heat shock protein 90 revealedconserved water molecules in the active sites of hydrogen bondingnetwork that are the potent target for natural product as well assynthetic compounds. Natural products such as geldanamycin,radicicol, and novobiocin are good examples of heat shock protein90 target. Among these, geldanamycin analogues entered into thestage of clinical trials (McDonald et al., 2006).

4.8. Targeting histone deacetylase

Re-programming of cellular metabolism is a key event duringtumorigenesis. The histone deacetylase SIRT6 acts as a tumor

Table 1Selected structurally identified and purified natural products causing cancer cell death

Naturalproducts

Molecular targets

Berberine Modifies cysteine 179 of IKBα kinase with suppression of NFκβ and inG2/M cell cycle arrest associated with increased expression of P53, Wexpression of Cyclin BAndrogen-insensitive (DU145 and PC-3) and androgen-sensitive (LNCcycle arrest by targeting cdki-cdk-cyclin cascadeMetastasis inhibition on nasopharyngeal carcinoma 5–8F cells by targphosphorylation at threonine 567Antitumor effect on malignancies such as esophageal cancer, hepatomcancer, prostate carcinoma and gastric carcinomaSignificant DNA binding and anti-tumor activity against HL-60 leukae

Sanguinarine ROS mediated induction of apoptosisNFκβ mediated differential apoptotic responseInduction of cyclin kinase inhibition p21/WAF1 and p27/ KIP1, down-redependent kinase 2, 4, 6Effective against multidrug resistance human cervical cells

Chelerythrine Induction of cell cycle and apoptosis in cancer cells

Lycopodine ROS mediated MMP depolarization, release of Cytochrome-c and activclosely involved in apoptosis and G1 cell cycle arrest

Palmatine Inhibition of reverse transcriptase, topoisomerase I and II and structurbe probable reason for antitumor activity

Chelidonine Transcriptional down regulation of catalytic subunit of telomerase (hTreported in HepG2 cells

Ukrain Bcl-2 controlled mitochondrial signalling events leading to apoptosis

Coptisine Cytotoxic on human tumor colon cell line (LoVo) and colon carcinommurine leukaemia (L-1210). It was effective on the LoVo cell resistantcell line (L-1210) resistant to cisplatin

Lycorine Potential use of lycorine showed to treat leukaemia cells resistant toPotential use as therapeutic agent has recently led to studies into thehighlighting it as a potential lead for drug development

Curcumin Many health benefits such as antioxidants, antibacterial, anti-inflammcarcinogenic effects have been investigated

suppressor that regulates aerobic glycolysis in cancer cells(Sebastian et al., 2012). Histone deacetylases are currently beingtested in phase I/II clinical trials (Minucci and Pelicci, 2006) forcancer drug targets.

4.9. Autophagy as cancer drug targets

Another very important targeted cancer therapy in resistantchemotherapy is “autophagy”. Autophagy is a multistep lysosomaldegradation process in which a cell destroys long lived proteinsand damaged organelles. Drugs targeting autophagy induced celldeath also sensitize apoptosis. The cross talk between apoptosisand autophagy is mediated via PI3K/Akt/mTOR Pathway (Sunet al., 2012). Some natural products such as curcumin, resveratrol,paclitaxel, oridonin, quercetin and plant lectin may lead to cancercell death by regulating some core autophagic pathways involvedin Ras–Raf signalling, Beclin-1 interactome, BCR-ABL, PI3KCI/Akt/mTOR, FOXO1 and p53 signalling (Zhang et al., 2012). A recentreport of Lamy et al. (2013) discusses autophagic control inmultiple myeloma by caspase 10 and provides an in-depth ideaabout the important molecular target in cancer therapeutics.

following specific signalling cascades as targeted therapy.

References

duce apoptosis Pandey et al. (2008)ee 1 and CDk 1 and decreased Lin et al. (2006)

aP) prostate cancer cells also show cell Mantena et al. (2006)

eting Rho-Kinase mediated Ezrin Tang et al.,2009

a, lung carcinoma, leukaemia, uterine Iizuka et al. (2000), Mitani et al. (2001),Letasiova et al. (2006)

mia cells Kuo et al. (1995)

Malikova et al. (2006)Ahmad et al. (2000)

gulation of cyclin E, D1, D2 and cyclin- Adhami et al. (2003)

Ding et al. (2002)

Malikova et al. (2006), Chan et al. (2003)

ation of caspase-3 which are events Mandal et al. (2010)

e activity relationship are suggested to Sethi (1983)

ERT) and senescence induction was Noureini and Wink (2009)

Habermehl et al. (2006)

a cell line (HT 29) and less potent onto doxorubicin, and murine leukaemia

Colombo et al. (2001)

apoptotic stimuli Lamoral-Theys et al. (2010)production of the synthetic compound Jones et al. (2009), El Tahchy et al. (2010),

McNulty et al. (2009)

atory, neuroprotective and anti Esatbeyoglu et al. (2012)

Fig. 4. Chemical structures of some important natural products used in cancertherapy—include (1) berberine, (2) palmatine, (3) chelidonine, (4) chelerythrine,(5) sanguinarine, (6) coptisine, (7) lycopodine, (8) lycorine, (9) curcumin, (10)scopoletin, (11) camptothecins, (12) epothilones and (13) geldanamycin to use infuture anticancer agent.

S.K. Saha, A.R. Khuda-Bukhsh / European Journal of Pharmacology 714 (2013) 239–248 245

5. Role of some purified and structurally defined naturalproducts in targeted cancer therapy

Utilization of natural products as effective drugs for cancertherapy is still an elusive goal due to the lack of proper bio-targetidentification, specificity aspect, lack of understanding of themolecular mechanism of action, and the signalling pathwaysinvolved. We shall mention hereunder the functional role andthe suggested molecular mechanisms of action and different

signalling pathways of a few natural products in their purifiedform (Fig. 4) in cancer therapy as examples of how this kind ofapproach is possible (Table 1).

6. Outlook and future challenges—Application of innovativetechnologies in cancer therapy

A better understanding of the key patho-physiological differ-ences between differential interaction of natural compounds andtheir derivatives in cancer cells and their counterparts in non-malignant cells will undoubtedly be instrumental for increasingthe level of selectivity of targeted anticancer agents. The discoveryand development of potent anticancer agents has been greatlyhampered due to lack of suitable preclinical model to check theefficacy of candidate agents. To bridge the gap, innovation inxenografts models and genetically engineered models of humantumorigenesis would play an important role in developing cancertherapeutic strategy. Applications of a few incoming innovativetechnologies are mentioned below.

The importance of tumor microenvironment, three dimen-sional aspects of solid tumors and the response to therapy atthese conditions have pushed forward to build such models moreprecisely in vitro. In fact 3D cell cultures are believed to be analternative model of in vivo counterparts. Examples of 3D culturesystems include, multilayer cell systems, matrix embedded 3Dcultures, hollow fibre-based approaches, ex vivo tumor culturesand multi-cellular tumor spheroids (Yamada and Cukierman,2007). Similarly, one of the potential issues associated withxenografts as models of drug efficacy is inappropriate dosing.With the improvement of animal models for human tumors suchas orthotopic models, metastatic models, autochthonous modelsand genetically engineered cancer models, identification of clini-cally useful agents is likely to improve in future (Gopinathan andTuveson, 2008). Some tumor derived cell lines are remarkablysimilar to that of the primary tumors from which they originated,implying a valid genetic surrogate of tumors in vivo. Examplesinclude: 51 breast cancer cell lines (Neve et al., 2006); 101melanoma derived cell lines (Lin et al., 2008); and 84 non smallcell lung carcinoma cell lines (Sos et al., 2009). Another importantaspect is the selection and identification of biomarkers in cancertherapeutics. A huge amount of information on genomic, tran-scriptomic, proteomic and epigenomic data obtained from differ-ent ‘systems’ platform make the job as difficult as “finding a needlein bush”. System biology approaches help to find out a meaningfulcorrelation of drug sensitivity data to establish molecular signa-tures or cancer biomarkers; e.g. yielding an expression signature of13 genes that are associated with the sensitivity of 48 breastcancer cell lines to the polyamine analogue PG-11047 (an inves-tigational clinical compound).

A major limitation of drug formulation in cancer lies in its drugresistance property. Use of drug-sensitive cancer derived cell linesas models provides an alternative to solve this issue. Drug resistantclones are selected after a continuous exposure over a period oftime in vitro. Genetic information which include mutation datafrom re-sequencing studies, gene expression information frommicroarrays, identifying gene copy number variations etc. facilitatethe identification of drug sensitivity (Drexler et al., 2000). Multidrug resistance is one of the main reasons of treatment failure incancer. Multi drug resistance protein such as ATP binding cassettetransporter family mainly controls the multi drug resistancemechanism by cellular efflux and decreases the effectiveness ofchemotherapeutic agents. Inhibitors of multi drug resistancefamily proteins are developed but are toxic in nature. Chen(2010) evaluated the importance of nuclear receptor, named aspregene X receptor, in controlling drug metabolism and drug

S.K. Saha, A.R. Khuda-Bukhsh / European Journal of Pharmacology 714 (2013) 239–248246

clearance. On the other hand interferon family of peptides areplaying emerging role in cancer therapeutics but the anti tumoractivity of Interferon-α is limited due to activation of tumorresistance mechanism. Interferon-β is emerging as considerablymore potent therapeutic agents in cancer through induction ofapoptosis and cell cycle arrest to overcome tumor resistancemachinery (Caraglia et al., 2009). Recently, Troiani et al. (2013)described a number of antibody based therapeutic strategiesincluding development of nanotech devices, combinatorial agentsblocking alternative escape pathways, targeting epidermal growthfactor receptor and immune system to overcome drug resistantcancer cell populations. A recent research approach worth men-tioning in this context is on the development of nanoparticlesloaded drug delivery system. Kaur and Tikoo (2013) reported thatpoly lactic-co-glycolic acid encapsulated gefitinib exhibit enhancedanti-cancer effects. They also observed that the nano-particlecovered drug acted as a ‘histone acetyltransferase’ rather than‘tyrosine kinase inhibitor’ (gefitinib in its free form acts more astyrosine kinase inhibitor). Patra and Dasgupta (2012) describedimportant aspects of background theory of design parameters foroptimizing gold nanoparticles for cancer therapy. Bhattacharyyaet al. (2011) reported poly lactic-co-glycolic acid encapsulatedsynthetic coumarin to have enhanced anti-cancer effect as revealedfrom their studies on cellular toxicity and bio-distribution in cancercells, both in vitro and in vivo. Bisphosphonates, a syntheticanalogue of naturally occurring pyrophosphate compounds,reported to have ability to induce apoptosis in cancer cells, arecandidates which need to be tested in nano-form for possible abilityto deliver the drugs in bone tumors (De Rosa et al., 2013) moresuccessfully. Another novel cell delivery system which is emergingfor target specific gene therapy is by using peptide nucleic acid. Theantisense technology combined with reporter tag in duplex form orreporter tag-peptide nucleic acid in triplex form facilitates rapid,sensitive, selective detection technique as a bio-sensing platform fordetecting target molecule (Yildiz et al., 2012).

7. Methodological drawbacks

Establishment of a causal relationship between a particulartherapeutic application and cancer is difficult. The occurrence ofthis chronic disease might have been the outcome of any pointmutation (due to environmental/behavioural/food/lifestyle stress)in chromosomal DNA that successfully replicate generation aftergeneration in cell. Physiological diets of laboratory animals are toodifferent from humans that it needs to justify the translation ofresults obtained in these studies (Wicki and Hagmann, 2011).Controlled experiments conducted to find out the effects of anytherapeutic strategies are of two types: (a) observational studiesand (b) cohort studies. Both types of studies are flawed due tohidden biasness introduced in terms of self chosen groups(Ioannidis, 2005). Randomised controlled trials are more reliableapproach in this aspect of conducting hypothesis generatingexperiments because in this case, individuals are randomlyassigned to treatment groups (Martinez et al., 2008).

Although much of the phenomena and causes of cancer havenow been elucidated, and a lot of strategies have been made tofind out the foolproof remedy, unfortunately none has succeededso far to prevent cancer from occurring or curing it when it hasadvanced to a certain limit. Some of the major reasons for failurein cancer drugs development have been suggested as due to poorpharmacokinetics, insufficient therapeutic activity, toxicity, andpoor bioavailability (Kola and Landis, 2004).With all these diffi-culties and obstacles in way natural products as a source of newdrugs serving mankind for decades (Newman and Cragg, 2007).

8. Conclusion

Finally, one wonders if one may find clues from nature herself inform of some natural products that can successfully target the cancercells, and this implies that a systematic global screening approachaimed at specially identifying targeted cancer therapy from largelibraries of natural substances will most likely present a treasuretrove for motivating a renewed 2search for anticancer drug discovery.

Acknowledgements

The authors wish to thank Boiron laboratories, Lyon, France forfinancial support. Saha SK wishes to thank Sweta Sharma ofNational Institute of Biomedical Genomics, Kalyani and DhimanSantra, University of Kalyani, Department of Chemistry for theirsupport, co-operation and insightful comments on manuscript.

References

Abraham, R., Schafer, J., Rothe, M., Bange, J., Knyazev, P., Ullrich, A., 2005.Identification of MMP-15 as an anti-apoptotic factor in cancer cells. J. Biol.Chem. 280, 34123–34132.

Adams, J., 2001. Proteasome inhibition in cancer: development of PS-341. Semin.Oncol. 28, 613–619.

Adams, J., 2004. The proteasome: a suitable anti-neoplastic target. Nat. Rev. Cancer4, 349–360.

Adhami, V.M., Aziz, M.H., Mukhtar, H., Ahmad, N., 2003. Activation of pro death Bcl-2 family proteins and mitochondrial apoptosis pathway by sanguinarine inimmortalized human HaCaT keratinocytes. Clin. Cancer Res. 9, 3176–3182.

Ahmad, N., Gupta, S., Husain, M.M., Heiskanen, K.M., Mukhtar, H., 2000. Differentialantiproliferative and apoptotic response of sanguinarine for cancer cells versusnormal cells. Clin. Cancer Res. 6, 1524–1528.

Aplin, A.E., Howe, A., Alahari, S.K., Juliano, R.L., 1998. Signal transduction and signalmodulation by cell adhesion receptors: the role of integrins, cadherins,immunoglobulin-cell adhesion molecules, and selectins. Pharmacol. Rev. 50,197–263.

Baker, D.D., Chu, M., Oza, U, Rajgarhia, V., 2007. The value of natural products tofuture pharmaceutical discovery. Nat. Prod. Rep. 24, 1225–1244.

Benson, J.D., Chen, Y.N., Cornell-Kennon, S.A., Dorsch, M., Kim, S., Leszczyniecka, M.,Sellers, W.R., Lengauer, C., 2006. Validating cancer drug targets. Nature 441,451–456.

Bryan, T.M., Cech, T.R., 1999. Telomerase and the maintenance of chromosome ends.Curr. Opin. Cell Biol. 11, 318–324.

Bhattacharyya, S.S., Paul, S., De, A., Das, D., Samadder, A., Boujedaini, N., Khuda-Bukhsh, A.R., 2011. Poly (lactide-co-glycolide) acid nanoencapsulation of asynthetic coumarin: cytotoxicity and bio-distribution in mice, in cancer cell lineand interaction with calf thymus DNA as target. Toxicol. Appl. Pharmacol. 253,270–281.

Bryan, T.M., Englezou, A., Gupta, J., Bacchetti, S., Reddel, R.R., 1995. Telomereelongation in immortal human cells without detectable telomerase activity.EMBO. J. 14, 4240–4248.

Butler, M.S., 2008. Natural products to drugs: natural product-derived compoundsin clinical trials. Nat. Prod. Rep. 25, 475–516.

Card, G.L., Blasdel, L., England, B.P., Zhang, C., Suzuki, Y., Gillette, S., Fong, D.,Ibrahim, P.N., Artis, D.R., Bollag, G., Milburn, M.V., Kim, S.H., Schlessinger, J.,Zhang, K.Y., 2005. A family of phosphodiesterase inhibitors discovered by co-crystallography and scaffold-based drug design. Nat. Biotechnol. 23, 201–207.

Caraglia, M., Dicitore, A., Marra, M., Castiglioni, S., Persani, L., Sperlongano, P.,Tagliaferri, P., Abbruzzese, A., Vitale, G., 2013. Type I interferons: ancientpeptides with still under-discovered anti-cancer properties. Protein Pept. Lett.20, 412–423.

Caraglia, M., Marra, M., Tagliaferri, P., Lamberts, S.W., Zappavigna, S., Misso, G.,Cavagnini, F., Facchini, G., Abbruzzese, A., Hofland, L.J., Vitale, G., 2009.Emerging strategies to strengthen the anti-tumour activity of type I interfer-ons: overcoming survival pathways. Curr. Cancer Drug Targets 9, 690–704.

Chan, S.L., Lee, M.C., Tan, K.O., Yang, L.K., Lee, A.S., Flotow, H., Fu, N.Y., Butler, M.S.,Soejarto, D.D., Buss, A.D., Yu, V.C., 2003. Identification of chelerythrine as aninhibitor of Bcl XL function. J. Biol. Chem. 278, 20453–20456.

Chen, T., 2010. Overcoming drug resistance by regulating nuclear receptors. Adv.Drug Delivery Rev. 62, 1257–1264.

Clardy, J., Walsh, C., 2004. Lessons from natural molecules. Nature 432, 829–837.Clemons, P.A., 2004. Complex phenotypic assays in high-throughput screening.

Curr. Opin. Chem. Biol. 8, 334–338.Collins, I., Workman, P., 2006. New approaches to molecular cancer therapeutics.

Nat. Chem. Biol. 2, 689–700.Colombo, M.L., Bugatti, C., Mossa, A., Pescalli, N., Piazzoni, L., Pezzoni, G., Menta, E.,

Spinelli, S., Johnson, F., Gupta, R.C., Dasaradhi, L., 2001. Cytotoxicity evaluationof natural coptisine and synthesis of coptisine from berberine. Farmaco 56,403–409.

S.K. Saha, A.R. Khuda-Bukhsh / European Journal of Pharmacology 714 (2013) 239–248 247

De Rosa, G., Misso, G., Salzano, G., Caraglia, M., 2013. Bisphosphonates and cancer:what opportunities from nanotechnology? J. Drug Delivery 2013, 637976.

Ding, Z., Tang, S.C., Weerasinghe, P., Yang, X., Pater, A., Liepins, A., 2002. The alkaloidsanguinarine is effective against multidrug resistance in human cervical cellsvia bimodal cell death. Biochem. Pharmacol. 63, 1415–1421.

Drexler, H.G., Fombonne, S., Matsuo, Y., Hu, Z.B., Hamaguchi, H., Uphoff, C.C., 2000.p53 alterations in human leukemia–lymphoma cell lines: in vitro artifact orprerequisite for cell immortalization? Leukemia 14, 198–206.

El Tahchy, A., Boisbrun, M., Ptak, A., Dupire, F., Chrétien, F., Henry, M., Chapleur, Y.,Laurain-Mattar, D., 2010. New method for the study of Amaryllidaceae alkaloidbiosynthesis using biotransformation of deuterium-labeled precursor in tissuecultures. Acta Biochim. Pol. 57, 75–82.

Esposito, C.L., Passaro, D., Longobardo, I., Condorelli, G., Marotta, P., Affuso, A., deFranciscis, V., Cerchia, L., 2011. A neutralizing RNA aptamer against EGFR causesselective apoptotic cell death. PLoS One 6, e24071.

Esatbeyoglu, T., Huebbe, P, Ernst, I.M., Chin, D., Wagner, A.E., Rimbach, G., 2012.Curcumin–from molecule to biological function. Angew. Chem. Int. Ed. Engl. 51,5308–5332.

Feher, M., Schmidt, J.M., 2003. Property distributions: differences between drugs,natural products, and molecules from combinatorial chemistry. J. Chem. Inf.Comput. Sci. 43, 218–227.

Futreal, P.A., Coin, L., Marshall, M., Down, T., Hubbard, T., Wooster, R., Rahman, N,Stratton, M.R., 2004. A census of human cancer genes. Nat. Rev. Cancer 3,177–183.

Garnett, M.J., Edelman, E.J., Heidorn, S.J., Greenman, C.D., Dastur, A., Lau, K.W.,Greninger, P., Thompson, I.R., Luo, X., Soares, J., Liu, Q., Iorio, F., Surdez, D., Chen,L., Milano, R.J., Bignell, G.R., Tam, A.T., Davies, H., Stevenson, J.A., Barthorpe, S.,Lutz, S.R., Kogera, F., Lawrence, K., McLaren-Douglas, A., Mitropoulos, X.,Mironenko, T., Thi, H., Richardson, L., Zhou, W., Jewitt, F., Zhang, T., O'Brien, P.,Boisvert, J.L., Price, S., Hur Yang, W., Deng, X., Butler, A., Choi, H.G., Chang, J.W.,Baselga, J., Stamenkovic, I., Engelman, J.A., Sharma, S.V., Delattre, O., Saez-Rodriguez, J., Gray, N.S., Settleman, J., Futreal, P.A., Haber, D.A., Stratton, M.R.,Ramaswamy, S., McDermott, U., Benes, C.H., 2012. Systematic identification ofgenomic markers of drug sensitivity in cancer cells. Nature 483, 570–575.

Gill, A.L., Frederickson, M., Cleasby, A., Woodhead, S.J., Carr, M.G., Woodhead, A.J.,Walker, M.T., Congreve, M.S., Devine, L.A., Tisi, D., O'Reilly, M., Seavers, L.C.,Davis, D.J., Curry, J., Anthony, R., Padova, A., Murray, C.W., Carr, R.A., Jhoti, H.,2005. Identification of novel p38alpha MAP kinase inhibitors using fragment-based lead generation. J. Med. Chem. 48, 414–426.

Gopinathan, A., Tuveson, D.A., 2008. The use of GEM models for experimentalcancer therapeutics. Dis. Model. Mech. 1, 83–86.

Graham, J.C., Zarbl, H., 2012. Use of cell-SELEX to generate DNA aptamersas molecular probes of HPV-associated cervical cancer cells. PLoS One 7, e36103.

Habermehl, D., Kammerer, B., Handrick, R., Eldh, T., Gruber, C., Cordes, N., Daniel, P.T., Plasswilm, L, Bamberg, M., Belka, C, Jendrossek, V., 2006. Pro apoptoticactivity of Ukrain is based on Chelidonium majus L. alkaloids and mediated via amitochondrial death pathway. BMC Cancer 17, 6–14.

Hanahan, D., Weinberg, R.A., 2011. Hallmarks of cancer: the next generation. Cell144, 646–674.

Henkel, T., Brunne, R., Muller, H., Reichel, F., 1999. Statistical investigation ofstructural complementarity of natural products and synthetic compounds.Angew. Chem. Int. Ed. Engl. 38, 643–647.

Howlader, N., Noone, A.M., Krapcho, M., Neyman, N., Aminou, R., Altekruse, S.F.,Kosary, C.L., Ruhl, J., Tatalovich, Z., Cho, H., Mariotto, A., Eisner, M.P., Lewis, D.R.,Chen, H.S., Feuer, E.J., Cronin, K.A., 2012. SEER Cancer Statistics Review.

Iizuka, N., Miyamoto, K., Okita, K., Tangoku, A., Hayashi, H., Yosino, S., Abe, T.,Morioka, T., Hazama, S., Oka, M., 2000. Inhibitory effect of Coptidis Rhizomaand berberine on the proliferation of human esophageal cancer cell lines.Cancer Lett. 148, 19–25.

Ioannidis, J.P., 2005. Why most published research findings are false. PLoS Med. 2, e124.Jones, M.T., Schwartz, B.D., Willis, A.C., Banwell, M.G., 2009. Rapid and enantiose-

lective assembly of the lycorine framework using chemo-enzymatic techniques.Org. Lett. 11, 3506–3509.

Kaur, J., Tikoo, K., 2013. p300/CBP dependent hyperacetylation of histone potenti-ates anticancer activity of gefitinib nanoparticles. Biochim. Biophys. Acta 1833,1028–1040.

Koehn, F.E., Carter, G.T., 2005. The evolving role of natural products in drugdiscovery. Nat. Rev. Drug Discovery 4, 206–220.

Kola, I., Landis, J., 2004. Can the pharmaceutical industry reduce attrition rates? Nat.Rev. Drug Discovery 3, 711–715.

Kuo, C.L., Chou, C.C., Yung, B.Y., 1995. Berberine complexes with DNA in theberberine-induced apoptosis in human leukemic HL-60 cells. Cancer Lett. 93,193–200.

Lamberti, A, Longo, O, Marra, M, Tagliaferri, P, Bismuto, E, Fiengo, A, Viscomi, C,Budillon, A, Rapp, UR, Wang, E, Venuta, S, Abbruzzese, A, Arcari, P, Caraglia, M.,2007. C-Raf antagonizes apoptosis induced by IFN-alpha in human lung cancercells by phosphorylation and increase of the intracellular content of elongationfactor 1A. Cell Death. Differ. 14, 952–962.

Lamoral-Theys, D., Decaestecker, C., Mathieu, V., Dubois, J., Kornienko, A., Kiss, R.,Evidente, A., Pottier, L., 2010. Lycorine and its derivatives for anticancer drugdesign. Mini-Rev. Med. Chem. 10, 41–50.

Lamy, L., Ngo, V.N., Emre, N.C.T., Shaffer III, A.L., Yang, Y., Tian, E., Nair, V., Kruhlak,M.J., Zingone, A., Landgren, O., Staudt, L.M., 2013. Control of autophagic celldeath by caspase-10 in multiple myeloma. Cancer Cell 23, 435–449.

Letasiova, S., Jantova, S., Cipak, L., Muckova, M., 2006. Berberine-antiproliferativeactivity in vitro and induction of apoptosis/necrosis of the U937 and B16 cells.Cancer Lett. 239, 254–262.

Li, N., Nguyen, H.H., Byrom, M., Ellington, A.D., 2011. Inhibition of cell proliferationby an Anti-EGFR aptamer. PLoS One 6, e20299.

Lin, W.M., Baker, A.C., Beroukhim, R., Winckler, W., Feng, W., Marmion, J.M., Laine,E., Greulich, H., Tseng, H., Gates, C., Hodi, F.S., Dranoff, G., Sellers, W.R., Thomas,R.K., Meyerson, M., Golub, T.R., Dummer, R., Herlyn, M., Getz, G., Garraway, L.A.,2008. Modeling genomic diversity and tumor dependency in malignantmelanoma. Cancer Res. 68, 664–673.

Lin, J.P., Yang, J.S., Lee, J.H., Hsieh, W.T., Chung, J.G., 2006. Berberine induces cellcycle arrest and apoptosis in human gastric carcinoma SNU-5 cell line. World J.Gastroenterol. 12, 21–28.

Lipinski, C.A., Lombardo, F., Dominy, B.W., Feeney, P.J., 1997. Experimental andcomputational approaches to estimate solubility and permeability in drugdiscovery and developmental settings. Adv. Drug Delivery Rev. 23, 3–25.

Lu, K., Chakroborty, D., Sarkar, C., Lu, T., Xie, Z., Liu, Z., Basu, S., 2012. Triphala and itsactive constituent chebulinic acid are natural inhibitors of vascular endothelialgrowth factor-a mediated angiogenesis. PLoS One 7, e43934, http://dx.doi.org/10.1371/journal.pone.0043934.

Lundholt, B.K., Linde, V., Loechel, F., Pedersen, H.C., Moller, S., Praestegaard, M.,Mikkelsen, I., Scudder, K., Bjorn, S.P., Heide, M., Arkhammar, P.O., Terry, R., Nielsen,S.J., 2005. Identification of Akt pathway inhibitors using redistribution screening onthe FLIPR and the IN Cell 3000 analyzer. J. Biomol. Screening 10, 20–29.

Malikova, J., Zdarilova, A., Hlobilkova, A., Ulrichova, J., 2006. The effect ofchelerythrine on cell growth, apoptosis, and cell cycle in human normal andcancer cells in comparison with sanguinarine. Cell Biol. Toxicol. 22, 439–453.

Mandal, S.K., Biswas, R., Bhattacharyya, S.S., Paul, S., Dutta, S., Pathak, S., Khuda-Bukhsh, A.R., 2010. Lycopodine from Lycopodium clavatum extract inhibitsproliferation of HeLa cells through induction of apoptosis via caspase-3activation. Eur. J. Pharmacol. 626, 115–122.

Mann, J., 2002. Natural products in cancer chemotherapy: past, present and future.Nat. Rev. Cancer 2, 143–148.

Mantena, S.K., Sharma, S.D., Katiyar, S.K., 2006. Berberine, a natural product,induces G1-phase cell cycle arrest and caspase-3-dependent apoptosis inhuman prostate carcinoma cells. Mol. Cancer Ther. 5, 296–308.

Martinez, M.E., Marshall, J.R., Giovannucci, E., 2008. Diet and cancer prevention: theroles of observation and experimentation. Nat. Rev. Cancer 8, 694–703.

Massague, J., 2004. G1 cell-cycle control and cancer. Nature 432, 298–306.McDermott, U., Sharma, S.V., Dowell, L., Greninger, P., Montagut, C., Lamb, J.,

Archibald, H., Raudales, R., Tam, A., Lee, D., Rothenberg, S.M., Supko, J.G.,Sordella, R., Ulkus, L.E., Iafrate, A.J., Maheswaran, S., Njauw, C.N., Tsao, H., Drew,L., Hanke, J.H., Ma, X.J., Erlander, M.G., Gray, N.S., Haber, D.A., Settleman, J.,2007. Identification of genotype-correlated sensitivity to selective kinaseinhibitors by using high-throughput tumor cell line profiling. Proc. Nat. Acad.Sci. U.S.A. 104, 19936–19941.

McDonald, E., Workman, P., Jones, K., 2006. Inhibitors of the HSP90 molecularchaperone: attacking the master regulator in cancer. Curr. Top. Med. Chem. 6,1091–1107.

McNulty, J., Nair, J.J., Bastida, J., Pandey, S., Griffin, C., 2009. Structure activity studieson the crinane alkaloid apoptosis-inducing pharmacophore. Nat. Prod. Com-mun. 4, 483–488.

Medema, R.H., Bos, J.L., 1993. The role of p21ras in receptor tyrosine kinasesignaling. Crit. Rev. Oncog. 4, 615–661.

Minucci, S., Pelicci, P.G., 2006. Histone deacetylase inhibitors and the promise ofepigenetic (and more) treatments for cancer. Nat. Rev. Cancer 6, 38–51.

Mitani, N., Murakami, K., Yamaura, T., Ikeda, T., Saiki, I., 2001. Inhibitory effect ofberberine on the mediastinal lymph node metastasis produced by orthotopicimplantation of Lewis lung carcinoma. Cancer Lett. 165, 35–42.

Neve, R.M., Chin, K., Fridlyand, J., Yeh, J., Baehner, F.L., Fevr, T., Clark, L., Bayani, N.,Coppe, J.P., Tong, F., Speed, T., Spellman, P.T., DeVries, S., Lapuk, A., Wang, N.J.,Kuo, W.L., Stilwell, J.L., Pinkel, D., Albertson, D.G., Waldman, F.M., McCormick, F.,Dickson, R.B., Johnson, M.D., Lippman, M., Ethier, S., Gazdar, A., Gray, J.W., 2006.A collection of breast cancer cell lines for the study of functionally distinctcancer subtypes. Cancer Cell 10, 515–527.

Newman, D.J., Cragg, G.M., 2007. Natural products as sources of new drugs over thelast 25 years. J. Nat. Prod. 70, 461–477.

Noureini, S.K., Wink, M., 2009. Transcriptional down regulation of hTERT andsenescence induction in HepG2 cells by chelidonine. World J. Gastroenterol. 15,3603–3610.

Pan, M.H., Ho, C.T., 2008. Chemopreventive effects of natural dietary compounds oncancer development. Chem. Soc. Rev. 37, 2558–2574.

Pandey, M.K., Sung, B., Kunnumakkara, A.B., Sethi, G., Chaturvedi, M.M., Aggarwal,B.B., 2008. Berberine modifies cysteine 179 of IkappaBalpha kinase, suppressesnuclear factor-kappaB-regulated anti-apoptotic gene products, and potentiatesapoptosis. Cancer Res. 68, 5370–5379.

Patra, H.K., Dasgupta, A.K., 2012. Cancer cell response to nanoparticles: criticalityand optimality. Nanomedicine 8, 842–852.

Peczuh, M.W., Hamilton, A.D., 2000. Peptide and protein recognition by designedmolecules. Chem. Rev. 100, 2479–2494.

Perera, F.P., 1996. Molecular epidemiology: insights into cancer susceptibility, riskassessment, and prevention. J. Natl. Cancer Inst. 88, 496–509.

Roe, S.M., Prodromou, C., O'Brien, R., Ladbury, J.E., Piper, P.W., Pearl, L.H., 1999.Structural basis for inhibition of the Hsp90 molecular chaperone by theantitumor antibiotics radicicol and geldanamycin. J. Med. Chem. 42, 260–266.

S.K. Saha, A.R. Khuda-Bukhsh / European Journal of Pharmacology 714 (2013) 239–248248

Rosen, J.M., Jordan, C.T., 2009. The increasing complexity of the cancer stem cellparadigm. Science 324, 1670–1673.

Salvador, J.A., Carvalho, J.F., Neves, M.A., Silvestre, S.M., Leitao, A.J., Silva, M.M.,Melo, M.L., Sa E, 2012. Anticancer steroids: linking natural and semi-syntheticcompounds. Nat. Prod. Rep. , http://dx.doi.org/10.1039/c2np20082a.

Sebastian, C., Zwaans, B.M.M., Silberman, D.M., Gymrek, M., Goren, A., Oren Ram, L.Z., Truelove, J., Guimaraes, A.R., Toiber, D., Cosentino, C., Greenson, J.K.,MacDonald, A.I., McGlynn, L., Maxwell, F., Edwards, J., Giacosa, S., Guccione,E., Weissleder, R., Bernstein, B.E., Regev, A., Shiels, P.G., Lombard, D.B.,Mostoslavsky, R., 2012. The histone deacetylase SIRT6 Is a tumor suppressorthat controls cancer metabolism. Cell 151, 1185–1199.

Sethi, M.L., 1983. Enzyme inhibition VI: inhibition of reverse transcriptase activityby protoberberine alkaloids and structure–activity relationships. J. Pharm. Sci.72, 538–541.

Sharma, S.V., Haber, D.A., Settleman, J., 2010. Cell line-based platforms to evaluatethe therapeutic efficacy of candidate anticancer agents. Nat. Rev. Cancer 10,241–253.

Shay, J.W., Bacchetti, S., 1997. A survey of telomerase activity in human cancer. Eur.J. Cancer 33, 787–791.

Shiwa, M., Nishimura, Y., Wakatabe, R., Fukawa, A., Arikuni, H., Ota, H., Kato, Y.,Yamori, T., 2003. Rapid discovery and identification of a tissue-specific tumorbiomarker from 39 human cancer cell lines using the SELDI protein chipplatform. Biochem. Biophys. Res. Commun. 309, 18–25.

Sos, M.L., Michel, K., Zander, T., Weiss, J., Frommolt, P., Peifer, M., Li, D., Ullrich, R.,Koker, M., Fischer, F., Shimamura, T., Rauh, D., Mermel, C., Fischer, S., Stückrath,I., Heynck, S., Beroukhim, R., Lin, W., Winckler, W., Shah, K., LaFramboise, T.,Moriarty, W.F., Hanna, M., Tolosi, L., Rahnenführer, J., Verhaak, R., Chiang, D.,Getz, G., Hellmich, M., Wolf, J., Girard, L., Peyton, M., Weir, B.A., Chen, T.H.,Greulich, H., Barretina, J., Shapiro, G.I., Garraway, L.A., Gazdar, A.F., Minna, J.D.,Meyerson, M., Wong, K.K., Thomas, R.K., 2009. Predicting drug susceptibility ofnon-small cell lung cancers based on genetic lesions. J. Clin. Invest. 119,1727–1740.

Strege, M.A., 1999. High-performance liquid chromatographic–electrospray ioniza-tion mass spectrometric analyses for the integration of natural products withmodern high-throughput screening. J. Chromatogr. B 725, 67–68.

Sun, H., Wang, Z., Yakisich, J.S., 2012. Natural products targeting autophagy via thePI3K/Akt/mTOR pathway as anticancer agents. Anticancer Agents Med. Chem.Decis. 24.

Tang, F., Wang, D., Duan, C., Huang, D., Wu, Y., Chen, Y., Wang, W., Xie, C., Meng, J.,Wang, L., Wu, B., Liu, S., Tian, D., Zhu, F., He, Z., Deng, F., Cao, Y., 2009. Berberineinhibits metastasis of nasopharyngeal carcinoma 5–8F cells by targeting Rhokinase-mediated Ezrin phosphorylation at threonine 567. J. Biol. Chem. 284,27456–27466.

Thornberry, N.A., Lazebnik, Y., 1998. Caspases: enemies within. Science 281,1312–1316.

Troiani, T., Zappavigna, S., Martinelli, E., Addeo, S.R., Stiuso, P., Ciardiello, F., Caraglia,M., 2013. Optimizing treatment of metastatic colorectal cancer patients withanti—EGFR antibodies: overcoming the mechanisms of cancer cell resistance.Expert Opin. Biol. Ther. 13, 241–255.

Veikkola, T., Alitalo, K., 1999. VEGFs, receptors and angiogenesis. Sem. Cancer Biol.9, 211–220.

Vieth, M., Siegel, M.G., Higgs, R.E., Watson, I.A., Robertson, D.H., Savin, K.A., Durst, G.L., Hipskind, P.A., 2004. Characteristic physical properties and structuralfragments of marketed oral drugs. J. Med. Chem. 47, 224–232.

Weinstein, J.N., Myers, T.G., O'Connor, P.M., Friend, S.H., Fornacer Jr., A.J., Kohn, K.M.,Fojo, T., Bates, S.E., Rubinstein, L.V., Anderson, N.L., Buolamwini, J.K., Osdol, W.W., van, Monks, A.P., Scudiero, D.A., Sausville, E.A., Zaharevitz, D.W., Bunow, B.,Viswanadhan, V.N., Johnson, G.S., Wittes, R.E., Paull, K.D., 1997. An information-intensive approach to the molecular pharmacology of cancer. Science 275,343–349.

Wicki, A., Hagmann, J., 2011. Diet and cancer. Swiss Med. Wkly. 141, w13250.Wu, Y., Sefah, K., Liu, H., Wang, R., Tan, W., 2010. DNA aptamer–micelle as an

efficient detection/delivery vehicle toward cancer cells. Proc. Nat. Acad. Sci. U.S.A. 107, 5–10.

Yamada, K.M., Cukierman, E., 2007. Modelling tissue morphogenesis and cancer in3D. Cell 130, 601–610.

Yildiz, U.H., Alagappan, P., Liedberg, B., 2012. Naked eye detection of lung cancerassociated miRNA by paper based biosensing platform. Anal. Chem. 85, 820–824.

Zhang, X., Chen, L.X., Ouyang, L., Cheng, Y., Liu, B., 2012. Natural compounds:targeting pathways of autophagy as anti-cancer therapeutic agents. Cell Prolif.45, 466–476.