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Circulating Tumour Cells and Cell-free DNA in Pancreatic Ductal Adenocarcinoma
Tamara M. Gall; Samuel Belete; Esha Khanderia;
Adam E. Frampton; Long R. Jiao
HPB Surgical Unit, Dept. of Surgery & Cancer, Imperial College, Hammersmith
Hospital campus, Du Cane Road, London, W12 0HS, United Kingdom.
Correspondence to: Tamara Gall, Email: [email protected]
Financial & competing interests:The authors have no other relevant affiliations or financial involvement with any
organization or entity with a financial interest in or financial conflict with the subject
matter or materials discussed in the manuscript.
No writing assistance was utilized in the production of this manuscript.
Disclosures: None declared
Running Title: CTCs and cfDNA in pancreatic cancer
Keywords: cell-free DNA; circulating tumour cells, pancreatic ductal
adenocarcinoma; cfDNA; CTC; PDAC
Word count: Abstract: 168
Manuscript: 4303
Tables: 2
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Abstract:
Pancreatic cancer is detected late in the disease process and has an extremely poor
prognosis. A blood-based biomarker that can enable early detection of disease,
monitor response to treatment, and potentially allow for personalised treatment,
would be of great benefit. This review analyses the literature regarding two potential
biomarkers: circulating tumour cells (CTCs) and cell-free DNA (cfDNA) with regards
to pancreatic ductal adenocarcinoma (PDAC). The origin of CTCs and the methods
of detection are discussed and a decade of research examining CTCs in pancreatic
cancer is summarized, including both levels of CTCs and analyzing their molecular
characteristics, and how this may affect survival in both advanced and early disease
and allow for treatment monitoring. The origin of cfDNA is discussed and the
literature over the past 15 years is summarized. This includes analyzing cfDNA for
genetic mutations and methylation abnormalities which has the potential to be used
for PDAC detection and prognosis. However, the research certainly remains in the
experimental stage warranting future large trials in these areas.
Introduction:
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with a 5 year
survival rate of only 2-9%. An estimated 279,000 people worldwide are diagnosed
with PDAC each year, and it is the 5 th most common cause of cancer death in the
UK. The onset of symptoms and diagnosis is often late and the majority of patients
have metastatic disease at diagnosis. However, genomic sequencing of PDAC
suggests that it takes at least 15 years between the initiating mutations and
metastatic potential 1. Those who are suitable for pancreatic resection have a much
longer overall survival (OS), and in this group, smaller tumour size and lymph-node
negative disease are associated with a further improvement in survival. The disease
recurrence rate post-surgical resection is high, with almost half developing disease
within 18 months. These findings suggest that earlier identification of initial disease
and disease recurrence would improve outcomes. Currently, the only non-invasive
blood-based biomarker routinely used in clinical practice is CA 19-9. However,
issues remain surrounding its sensitivity and specificity and thus this has led
researchers to search for novel biomarkers. In this review, we have focused on two
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of these potential biomarkers: circulating tumour cells (CTCs); and cell-free DNA
(cfDNA).
Circulating Tumour Cells:
Discovery:
In 1869, Thomas Ashworth reported that in a gentleman with multiple subcutaneous
tumours of his thorax and abdomen, cells identical to those of the tumour were seen
in the blood. This is the first written report suggesting that tumour cells in the blood
may be responsible for metastases. Almost 90 years later in 1955, a more detailed
study showed that cancer cells are present in the blood of patients with colorectal
cancer 2. Over the last decade there has been renewed research interest in these
circulating tumour cells (CTCs), both as a liquid biopsy, and as a prognostic marker
for a variety of cancers. They are likely to play a key role in metastatic progression, a
process known as the ‘invasion-metastasis cascade’ comprising invasion,
intravasation, migration, extravasation and colonisation 3.
Origin:
CTCs are cells which circulate through the bloodstream and are thought to derive
from the primary lesion. This blood-borne dissemination of cells from the primary
tumour to distant organs may lead to metastatic disease. The origin of CTCs can be
debated and it is unclear whether they occur as a result of passive shedding of the
tumour or due to active migration. Shedding could occur due to the detachment of
clusters of connecting cells during tumour invasion into local vessels 4. Further,
tumour induced angiogenesis leads to abundant blood vessels and an erosion-type
mechanism with cells from the tumour separating from the mass lesion 5. Active
vascular intravasation of cells may involve macrophages, with the resultant
interaction inducing movement of tumour cells along collagen fibres towards blood
vessels. Certainly, epidermal growth factor receptor (EGFR) and colony-stimulating
factor 1 (CSF-1), expressed by cancer cells, attract macrophages 6.
Methods of detection:
Levels of CTCs in the peripheral blood however are low, with around one cell per
105-107 mononuclear cells. Their detection is therefore extremely challenging.
3
There are 40-50 different methods which have been used to detect circulating
tumour cells in the literature 7, 8. Essentially, CTCs can be positively or negatively
enriched based on their biological properties or physical properties. Biological
technologies depend on specific antibodies that bind to cell-surface markers on the
CTCs 9. Methods for capturing CTCs based on their physical properties use
enrichment methods based on the size, density and electric charge of the CTCs 10.
Filtration-based systems and microfluidic cell sorting assume that tumour cells are
larger than haematopoietic cells and trap these cells based on their size. Those
using biological methods may have a high false-negative rate, missing tumour cells
which do not have the specific cell-surface markers. However, those identifying
CTCs by their physical properties are likely to have a higher false-positive rate,
trapping some blood cells 8. Furthermore, researchers are looking at the individual
properties of the CTCs, analysing mutations within the DNA of the CTCs captured,
enabling prediction of those that will respond to certain oncological therapies 11, 12.
The first FDA approved biological methodology was an automated detection system
‘CellSearch’ (Veridex, NJ, USA) validated in 2007 13. This kit is intended for the
enumeration of CTCs of epithelial origin. Using ferrofluid nanoparticles with
antibodies that target epithelial cell adhesion molecules (EpCAM), CTCs are
separated from the bulk of other cells. The CTCs are then stained with antibodies to
cytokeratins 8, 18+ and/or 19+, specific to epithelial cells. Leukocytes which may
have contaminated the sample are stained with their specific antibody marker CD45.
Finally, DAPI, a DNA stain is used to highlight the nuclei of the cells. A fluorescent
microscope is used to identify the CTCs, which are EpCAM, cytokeratin and DAPI
positive but negative for CD45. Clinical studies conducted with this system have
demonstrated that CTCs are an independent predictor of progression-free (PFS)
survival and OS in metastatic breast cancer 14 15, colorectal cancer 16, castrate-
resistant prostate cancer 17, small-cell-lung-cancer 18 and non-small cell lung cancer 19. Some CTCs however undergo epithelial-mesenchymal transition (EMT) with
down-regulated expression of cytokeratins and would not be detected by this
system. Others have developed micro-fluidic systems using multiple antibody
mixtures and alternate staining methods to try to capture more CTCs than anti-
EpCAM alone and to detect those that have undergone EMT and are CK-negative 20 21 22. Some systems, such as the newer ‘Screencell’ system (Caltag Medsytems Ltd,
Buckingham UK) rely on the larger size of the CTC rather than on the presence of
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surface antigens and have shown higher CTC detection rates 23, 24. Certainly, in
PDAC, Khoja et al. 25 captured CTCs in 40% (n=54) of patients using the CellSearch
system compared to 93% using ISET (isolation by size of epithelial tumour cells). In
essence, there is much heterogeneity in the methods used to detect CTCs, which
leads to varying results in the literature. The concept of analysing genetic and
epigenetic mutations within the individual CTCs captured is novel and may enable us
to predict those CTCs which are biologically active and more likely to cause
metastatic disease.
CTC detection in pancreatic cancer:
Despite an abundance of research into CTC numbers and their relationship with
oncological outcomes in many other cancers, particularly breast cancer, there has
been less in the literature regarding CTCs and PDAC. A literature search for
relevant studies using the search terms ‘CTC’ OR ‘circulating tumour cells’ AND
‘pancreatic adenocarcinoma’ OR ‘PDAC’ was conducted on PubMed, Embase, Web
of Science and Cochrane Library databases. Case reports and research looking at
non-blood CTCs (e.g. peritoneal and bone marrow samples) were excluded. We
identified 20 studies investigating CTCs in PDAC over the last 10 years (Table 1).
Kurihara et al. 45 found at least one CTC in the blood of 42% (n=26) of those with
PDAC, whereas no patients with chronic pancreatitis (n=11) or healthy controls
(n=10) had any CTCs detected. Interestingly, the median survival was 110.5 days for
those who were CTC positive compared to 375.8 days for those who were CTC
negative (p<0.001). This is despite 87% of the CTC negative patients having stage
IV disease. The survival difference persisted when analysing only those with stage
IV PDAC, 52.5 days for CTC positive patients compared to 308.3 days for CTC
negative patients (p<0.01). Similarly, De Alburquerque et al. 43 detected CTCs in
47.1% (n=34) of PDAC patients, compared to none in healthy controls (n=40). A
shorter PFS (66 days compared to 138 days; p=0.01) was observed for patients who
had at least one CTC detected compared to those who were CTC negative. Earl et
al.35 also found poorer OS (88 days compared to 393 days) in the 20% of PDAC
patients who were CTC positive. A meta-analysis was conducted of 9 cohort studies
analysing CTCs in PDAC patients 38. This showed that 43% (n=603) had positive
CTCs from peripheral blood samples. These CTC-positive patients had significantly
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worse PFS than CTC-negative patients (HR 1.89, 95% CI 1.25-4.00, p<0.001) and
also had worse OS (HR 1.23, 95% CI 0.88-2.08, p<0.001).
The suggestion that CTCs could be used as a prognostic marker for PDAC led Ren
et al. 44 to examine CTC numbers following chemotherapy treatment in patients with
PDAC. Two or more CTCs were detected in 80.5% (n=41) of patients, and again
none were seen in healthy donors (n=20). This high percentage of patients with
CTCs may be because all patients had advanced disease at the time of blood
sampling. Following one cycle of 5-FU only 29.3% had more than two CTCs
identified, suggesting that CTCs could be used as an assessment of response to
treatment, although this has not been reproduced 42. This limited evidence indicates
that CTCs may have a future role in assessment of prognosis and treatment
response in those with advanced PDAC.
Whether CTCs could also be of value as a prognostic marker in those with earlier
disease would be of interest. However, Bidard et al. 42 only identified CTCs in 5%
(n=75) of patients with borderline resectable disease. Furthermore, in contrast to
previous studies, more patients (9%; n=59) had CTCs detected after 2 months of
chemotherapy, and there was no difference in PFS between those who were CTC
positive or negative. Our own group examined CTCs in patients with resectable
disease and identified CTCs in 50% of patients using the CellSearch system. We
failed to demonstrate a difference in survival (unpublished data). We also examined
CTCs in the portal circulation of those with resectable disease and found CTC
positivity in 92% of patients 40. It is possible that many of these CTCs fail to enter the
peripheral circulation. However, Bissolati et al. 34 reported a higher rate of liver
metastases after 3 years follow-up in those with CTCs identified in portal venous
blood. Similarly, Tien et al. 32 found 85% of patients with portal venous CTCs
developed liver metastases, compared to 13% with no portal venous CTCs.
Compared to other epithelial cancers, a much smaller number of CTCs are seen in
PDAC, and in fewer patients. For this reason, CTCs do not currently have a high
enough sensitivity to be used for diagnosis, as a liquid biopsy. Certainly, only a
sensitivity of 67% was found when distinguishing PDAC from other malignant
pancreatic tumours 26; and 68% for distinguishing between PDAC and other
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pancreatic disease or healthy patients including: pancreatic pseudocysts; pancreatic
serous cystadenomas; and solid pseudopapillary tumours 37. Indeed, CTCs have
also been identified in 63% of those with benign disease 28, 33% of patients with
benign cystic lesions 41, 64% with neuroendocrine tumours, 62% with intraductal
papillary mucinous neoplasms (IPMN) and 46% with chronic pancreatitis 36, implying
a low specificity.
More recently, an exciting addition to CTC research has been to analyse the specific
molecular characteristics of the CTCs. This may lead to an understanding of the
malignant potential of CTCs captured, and add to the benefit of using CTCs as
prognostic biomarkers. Dotan et al. 30 were able to measure MUC-1 from the CTCs
captured by the CellSearch system. Increased MUC-1 tumour expression is
associated with a poorer outcome in PDAC 46 and the presence of anti-MUC-1 IgG
antibodies correlates with improved survival 47. They were able to demonstrate that
patients with MUC-1 expressing CTCs (n=10) had a shorter median OS (2.7
months), compared to those with MUC-1 negative CTCs (n=13; 9.6 months).
Kulemann et al. 29 looked at KRAS mutation subtypes in CTCs from 58 PDAC
patients. Those with a KRASG12V mutation (n=14) had a better OS (24.5 months)
compared to those with other (10 months) or no detectable KRAS mutations (8
months; p=0.04). Poruk et al. 33 identified CTCs that expressed Vimentin, a
mesenchymal marker, as well as the
epithelial cytokeratin markers. These CTCs have a strong association with
metastatic potential in breast cancer, and evidence suggests that CTCs undergoing
epithelial-
mesenchymal transition (EMT) may have more malignant potential 48. Seventy-eight
percent (n=50) of patients with resectable or borderline resectable PDAC had CTCs
expressing cytokeratins detected. Of these, 67% also expressed Vimentin, and had
a shorter disease free survival (9.5 months compared to 13.5 months; p=0.02). Yu et
al. 39 analysed the gene expression profile of CTC RNA in 50 patients with advanced
or locally advanced PDAC. They compared this to a model validated to predict
chemotherapy sensitivity. Those predicted to be sensitive to chemotherapy had a
longer disease free survival (10.4 months) than those predicted to be resistant to
chemotherapy (3.6 months; p=0.0001). Overall survival was also significantly
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different, 17.2 months in the sensitive group compared to 8.3 months in the resistant
group (p<0.0304).
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Cell-Free DNA:
Discovery:
Mandel and Metais published an article in 1948 with the first description of circulating
nucleic acids in human plasma 49. Following this in 1977 it was observed that 173
patients with cancer had elevated levels of DNA in their serum compared to 55
healthy controls. This level was higher in those with metastatic disease and was
found to be reduced after radiotherapy 50. In 1989, the DNA extracted from the
plasma of cancer patients was seen to be identical to the corresponding cancer cells 51. Subsequently, several DNA mutations and microsatellite alterations associated
with varying cancer subtypes have now been identified in plasma DNA. With huge
improvements in DNA extraction and the advent of widespread PCR techniques, the
oncological importance of cell-free DNA (cfDNA) has been established. There is
increasing evidence to suggest that specific genetic and epigenetic mutations in
cfDNA may be diagnostic for certain tumours and may be useful to monitor treatment
response. Furthermore, these specific mutations in cfDNA could have the potential to
establish personalised oncological therapies all from a simple blood test.
Origin:
CfDNA is mostly a double-stranded molecule, consisting of small fragments (70-200
base pairs) and also larger fragments with molecular weights of up to 21kb, and
occurs in both plasma and serum 52. Although cfDNA is actively released from cells
as a part of normal metabolism, 4-40 times greater levels are seen in cancer patients 53. Indeed, in colorectal cancer, an estimated 3.3% of tumour DNA is released into
the circulation daily 54. In healthy individuals, the cfDNA concentration ranges from 0-
100 ng/ml of blood, which compares to concentrations of 0 to over 1000 ng/ml of
blood in cancer patients 55. There is debate as to the origin of cfDNA, but it is thought
to be released from apoptosis, necrosis, direct release from viable cells and from the
lysis of CTCs. In cancer, there is a high cell turnover and hence increased
programmed apoptosis, which may explain higher plasma levels of cfDNA compared
to other physiological states 52. Further suggestion that apoptosis leads to the
presence of plasma DNA is that a large proportion of cfDNA has a size of 180-
720bp, a character of cell death fragments 56. In addition, chloroquine, which induces
apoptosis, also increases the concentration of cfDNA 57. Necrosis is commonly seen
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in cancer cells due to a higher growth rate of tumour tissue than angiogenesis,
resulting in hypoxia. Phagocytosis of the necrotic cells by macrophages leads to
release of cell components including tumour DNA fragments 54. There may also be
active release of DNA by tumour cells independent of apoptosis and necrosis. This
has been previously demonstrated on lymphocytes 58. Finally, the lysis of circulating
tumour cells (CTCs) may also contribute towards cfDNA.
cfDNA in Pancreatic Cancer:
As discussed above, healthy patients may have cfDNA detected in their circulation.
Further, as well as in neoplastic disease, increased levels may be seen in other
physiological and pathological conditions including exercise, smoking, inflammatory
disease, critical illness, sepsis and trauma 59 60 61. Therefore, measuring total cfDNA
levels is not thought to be clinically useful as a diagnostic marker for malignancy, as
its sensitivity is generally low 53. However, there is a possibility of using cfDNA in
cancer diagnosis and monitoring, by detecting tumour-specific genetic and
epigenetic mutations. New developments in techniques for these analyses have
enabled an accumulation of research in many malignancies over the last 2 decades.
Specifically, cfDNA has been analysed for gene mutations, loss of heterozygosity
(LOH), methylation alterations and microsatellite alterations. These changes may be
some of the earliest events in malignant transformation and therefore their detection
could lead to early clinical biomarkers.
There is some limited research on cfDNA in PDAC. A literature search for relevant
studies using the search terms ‘cfDNA’ OR ‘cell free DNA’ OR ‘circulating DNA’ AND
‘pancreatic adenocarcinoma’ OR ‘PDAC’ was conducted on PubMed, Embase, Web
of Science and Cochrane Library databases. We identified 23 studies investigating
CTCs in PDAC over the past 15 years (Table 2).
There are four main driver genes which are most frequently mutated in PDAC.
These are KRAS, CDKN2A, SMAD4 and TP53 and their association with PDAC has
been established for many years. More recently, exome sequencing of PDAC
ascertained KRAS to be the most commonly mutated, seen in 90-95% of cases 84.
Therefore, this gene has been the focus of much of the cfDNA research. Maire et al 83. investigated for G12D mutations in codon 12 of KRAS, from the cfDNA of 47
10
patients with PDAC, the majority with stage IV disease, and found these in 47%.
Interestingly, they also identified this mutation in 13% of those with chronic
pancreatitis. Similarly, Dabritz et al. 79 used peptic nucleic acid (PNA)-mediated PCR
clamping and real-time PCR with mutant-specific hybridization probes, to find codon
12 KRAS mutations in 36% of PDAC patients (n=56) and also in 14% (n=13) of
patients with chronic pancreatitis. Dai et al. used PCR techniques to find KRAS
mutations in 73% of PDAC patients (n=15) but again, in 20% of chronic pancreatitis
patients (n=10) 82. Combining the detection of these mutations, with a raised CA 19-
9, distinguishes PDAC from chronic pancreatitis with a sensitivity of 67-98%, and a
specificity of 77-97% 83 79 82. Levels of cfDNA have also been detected in patients
with IPMN, although at a lower level than in PDAC 70. Further, mutant KRAS has also
been detected in 14.8% of healthy controls 64. This evidence suggests limited use of
cfDNA KRAS mutations as a diagnostic biomarker.
Interestingly, cfDNA KRAS mutations may be of more value as a prognostic
biomarker. Chen et al. 78 analysed 91 patients with inoperable PDAC. Those with
detectable cfDNA codon 12 KRAS mutations had a significantly shorter survival (3.9
months) compared to those with wild type KRAS (10.2 months; p<0.001). In addition,
Earl et al. 35 determined that 26% of patients (n=31) with PDAC had cfDNA codon 12
mutations of KRAS. These patients had a shorter survival (60 days) compared to
those without the KRAS mutation (772 days; p=0.001). Hadano et al. 66 also
demonstrated a shorter survival, 13.6 months, in 31% of patients (n=105) with
mutant KRAS in cfDNA compared to 27.6 months in those with wild-type KRAS
(p<0.0001). In the largest study conducted 73 with 259 PDAC patients, mutant KRAS
was detected in cfDNA of 47% of patients with inoperable disease and 8.3% of those
with resectable disease. The presence of the mutation was an independent
prognostic factor for OS (HR 3.04; p<0.0001). In an analysis of cfDNA from 66 PDAC
patients, a shorter survival was seen in those with mutant KRAS compared to wild-
type KRAS. In contrast, the mutational status of the tumour DNA did not correlate
with survival 69. A further link to cfDNA KRAS mutations and prognosis was
established by Dabritz et al. 75 who correlated the presence of KRAS mutations and
CT findings. Thirty-nine percent (n=38) of patients had cfDNA KRAS mutations
however on further analysis, only 9% of those with disease remission on CT had
11
cfDNA KRAS mutations, compared to 75% of those with progressive disease on CT.
KRAS mutations in cfDNA may also be
beneficial for predicting disease recurrence. PCR analyses performed at various time
points after surgical resection determined that patients with detectable mutations in
their plasma were more likely to relapse than those with undetectable alterations
(p=0.02). Further, disease progression was detected 3.1 months after surgery,
compared to 9.6 months using CT imaging (p=0.0004) 68. However, others have
failed to correlate the presence of KRAS mutation in cfDNA and survival. Uemura et
al 81. analysed KRAS in plasma DNA in 28 patients with resectable PDAC, and were
able to identify mutations in 35%. No association was found between the presence of
the cfDNA mutation and the size of the tumour or stage of the disease. Brychta et al. 67 found no correlation between mutant KRAS in cfDNA, which was detected in only
35% of PDAC patients (n=50), and the stage or grade of the disease. Allenson et al. 64 and Singh et al. 71 were also unable to determine a significant difference in survival
when comparing patients with cfDNA mutant KRAS and those with cfDNA wild type
KRAS.
More recently, the development of next generation DNA sequencing analysers has
enabled rapid assessment of whole exome DNA, using probes to more than 50
genes covering thousands of COSMIC mutations. Chen et al. 63 used next generation
sequencing (NGS) from cfDNA in 188 patients with metastatic PDAC to identify at
least 1 mutation in 83% of patients and a KRAS mutation in 72.3%. Specifically, only
the KRAS G12V and ERBB2 exon 17 mutations were independently significantly
associated with shorter survival. The presence of the KRAS G12 mutation was
associated with tumour responses observed on CT images in 76.9% of patients and
provided the earliest measurement of treatment in 60%. Vietsch et al. 62 analysed
the plasma of 5 PDAC patients at initial diagnosis with NGS. An average of 8
mutations was detected per sample, but concordance with the tumour sample was
only 28%. Interestingly, after the development of disease metastases, 63% of
mutations in cfDNA had not been detected initially, demonstrating the heterogeneity
of the disease with progression. Our own group (unpublished data) used the ion
torrent next generation sequencer to analyse cfDNA in 16 patients with operable
PDAC. We identified a total of 256 single nucleotide polymorphisms, but only 2 gene
mutations (APC and STK11), and no KRAS mutations were detected.
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DNA methylation is an important physiological process active in all cells. It occurs at
CpG islands, found at the promoter region of genes. Abnormal methylation, such as
the hypermethylation of a promoter region of a tumour suppressor gene results in
gene silencing 55. Hypomethylation leads to increased mutation rates and
chromosome instability 85. Therefore, some research has examined methylation
abnormalities in cfDNA. Altered methylation was detected in the cfDNA of 81.3% of
PDAC patients, but also in 61.5% of those with chronic pancreatitis, and 3.5% of
healthy controls 74. Others were able to use methylation abnormalities in 17 promoter
regions of cfDNA to discriminate between PDAC and chronic pancreatitis with a
sensitivity of 91.2% and a specificity of 90.8% 77. Using a model of five promoter CpG
sites, and a large cohort of 240 patients with PDAC, malignancy could be
discriminated from healthy controls with a C-statistic of 0.76 76. Melnikov et al. also
developed a model of five promoters to discriminate between PDAC and healthy
controls with a sensitivity of 76% and specificity of 59% 80. Henrikson et al. analysed
the hypermethylation of 10 genes, and although cfDNA hypermethylation was
detectable in both malignant disease and chronic pancreatitis, a much higher level
was seen in PDAC. A diagnostic prediction model was able to differentiate between
PDAC and benign disease with a sensitivity of 76% and specificity of 83% 65.
Summary:
Pancreatic cancer has an aggressive and devastating biology. Insights into the
molecular characteristics of this disease will provide valuable information, leading to
earlier detection of the disease and the development of improved oncological
therapies. The continuing analysis of circulating biomarkers is an exciting area of
exploration, which may lead to personalised prognosis and treatment plans from a
simple blood test. CTCs and cfDNA are two such biomarkers at the forefront of
oncological research. There is promising published evidence that the presence of
CTCs in advanced PDAC leads to shorter PFS and OS, and as levels are reduced
after chemotherapy, they could be used to evaluate response to treatment. There is
less evidence regarding the presence of CTCs in resectable PDAC and outcomes.
However, in these patients, portal venous CTC detection could suggest a higher
likelihood to develop liver metastases. As yet, CTCs may not distinguish between
13
malignant and benign disease, reducing the potential benefit for disease diagnosis.
However, recent advances in CTC research have evaluated the biological properties
of captured CTCs, and this could be of future use in detection and prognostication.
There are many markers in proteomic and genomic research which may increase the
malignant potential of PDAC yet, in terms of CTCs, the analyses are in their infancy,
with only three investigated. Analysing cfDNA for genetic abnormalities is also a
promising area. Most research has examined KRAS mutations in plasma, and
although detected in benign disease at lower levels, combination with CA 19-9 may
increase diagnostic sensitivity and specificity. The majority of studies have also
found shorter survival outcomes in those with mutant KRAS and some evidence
would suggest that the development of cfDNA mutant KRAS is an early marker of
disease recurrence. With the advent of NGS we expect to see an expansion of
studies in the coming years. Panels of genes with methylation abnormalities may
also aid in the diagnosis of PDAC, however there is not yet an established panel with
potential clinical use. It must be noted that published research is very much at the
experimental stage and currently involves small numbers of patients, using a variety
of methodologies. Some of the encouraging results seen could partly be due to
publication bias. We hope that the future will bring larger trials leading to the
development of agreed protocols, and the clinical use of both CTCs and cfDNA as
markers of diagnosis, prognosis and response to oncological treatments.
14
15
Author Year Study size Methodology Main findingsSefrioui et al. 26
2017 PDAC – 52Other pancreatic malignancy - 10
Screencell Sensitivity and specificity for PDAC 67% and 80%
Liu et al. 27 2017 PDAC – 95Controls - 48
.
Immunostaining of CD45, DAPI and CEP8-FISH
CTC >2 sensitivity and specificity for PDAC 75.8% and 68.7%
CTC subtype-positive rates associated with tumor location.
Rosenbaum et al. 28
2017 PDAC – 8NET – 9Cholangiocarcinoma – 8!PMN – 16MCN – 1Pancreatitis – 12Controls - 9
Screencell Malignant: 51% CTC positive
Benign: 63% CTC positive
Kulemann et al. 29
2017 PDAC – 58Controls - 10
Screencell >3 CTCs shorter overall survival
CTC KRAS G12V mutation trend to better overall survival
Dotan et al. 30
2016 PDAC - 48 Cellsearch No difference in overall survival between CTC +ve and CTC-ve patients
Shorter overall survival in patients with CTC expressing MUC-1
Ankeny et al. 31
2016 PDAC – 72Controls - 39
Nanovelcro CTC sensitivity and specificity 75.0% and 95.7%
Tien et al. 32 2016 PDAC/ ampullary cancer - 60 CMx Platform More CTCs detected from portal (58.3%) compared to peripheral venous blood (40%)
85% of patients with portal vein CTCs developed liver metastases compared to 13% of those with no portal vein CTCs
Poruk et al. 33
2016 PDAC – 50 ISET 78% CTC positive for cytokeratins
67% of these also expressed vimentin.
Presence of cytokeratins and vimentin associated with shorter overall survival.
Bissolati et al. 34
2015 PDAC - 20 Cellsearch 45% with CTCs
Higher rate of liver metastases in patients with CTC positive from portal vein
Earl et al. 35 2015 PDAC - 45 Cellsearch 20% with CTCs
Shorter overall survival in CTC +ve (88 vs 393 days)
Cauley et al. 36
2015 PDAC – 105Other pancreatic lesions - 74Controls - 9
Screencell 49% PDAC with CTCs64% NET with CTCs62% IPMN with CTCs46% chronic pancreatitis with CTCs
Zhang et al. 37
2015 PDAC – 22Benign lesions – 6Controls - 30
EpCAM-independent method
Sensitivity and specificity for PDAC 68.18% and 94.87%
Han et al. 38 2014 PDAC – 603 Meta-analysis Shoter disease-free survival and overall survival in CTC +ve patients
Yu et al. 39 2014 PDAC - 50 Not stated Expression profiling of RNA from CTCs can predict chemotherapy response, disease-free and overall survival
Gall et al. 40 2014 PDAC - 12 Cellsearch 92% with portal vein CTCs
No difference in disease-free survivalRhim et al. 41
2013 PDAC – 11Cystic lesions – 21Controls - 19
GEDI 73% PDAC with CTCs33% cystic lesions with CTCs
Bidard et al. 42
2013 PDAC - 79 Cellsearch 5% PDAC with CTCs
Shorter overall survival with CTC +vede Albuquerque et al. 43
2012 PDAC – 34Controls - 40
BM7 and VU1D9 (targeting mucin 1 and EpCAM, respectively)
47% PDAC with CTCs
Shorter progression-free survival in CTC +ve
Ren et al. 44 2011 PDAC – 41Controls - 20
CA19-9-Alexa Fluor 488 and CK8/18-Alexa Fluor 594 immunofluorescence
>2 CTCs in 80.5% PDAC
>2 CTCs in 29.3% after first cycle 5-FU
Kurihara et al 45.
2008 PDAC – 26Chronic pancreatitis -11Controls - 10
Cellsearch 42% PDAC with CTCs
Shorter overall survival in CTC +ve
Table 1: Studies evaluating circulating tumour cells in pancreatic ductal adenocarcinoma.
Glossary: PDAC (pancreatic ductal adenocarcinoma); CTC (circulating tumour cells); NET (neuroendocrine tumour); IPMN (intraductal papillary mucinous neoplasm); MCN (mucinous cystic neoplasm)
Author Year Study Size cfDNA analysis
Significant findings
Vietsch et al. 62
2017 PDAC - 5 56 gene screening panel
Concordance of mutations with tumour sample in 28%
New mutations with development of metastasesCheng et al. 63
2017 PDAC - 188 60 gene panel
KRAS G12V and ERBB2 exon 17 mutations were independently significantly associated with shorter survival
Presence of KRAS G12 mutation associated with tumour responses observed on CT images in 76.9%
Allenson et al.64
2017 PDAC – 68Controls - 54
KRAS mutation
KRAS mutations in 45.5% with localised disease and 57.9% with metastatic disease
No correlation with survival
KRAS mutations in 14.8% controlsHenriksen et al. 65
2016 PDAC – 95Chronic pancreatitis – 59Controls - 27
Methylation, 10 gene panel screened
Higher number of methylated genes in cancer
Prediction model differentiated between PDAC and benign disease with a sensitivity of 76% and specificity of 83%
Hadano et al. 66
2016 PDAC - 105 KRAS mutation
KRAS mutation in 31%.
Overall survival was 13.6 months in patients with mutant KRAS cfDNA and 27.6 months in wild-type KRAS
Brychta et al. 67
2016 PDAC – 50Controls - 20
KRAS mutation
KRAS mutations in 35% PDAC
No KRAS mutations detected in controls
No correlation seen between tumour stage, size, tumour content and tumour cell load with the concentration of cfDNA in plasma
Sausen et al. 68
2015 PDAC - 77 KRAS mutation
KRAS mutations in 43%
Disease progression using cfDNA was detected at an average of 3.1 months after surgery compared with 9.6 months using standard CT imaging
Kinugasa et al. 69
2016 PDAC - 75 KRAS mutation
KRAS mutation in 62.6%
No correlation with survival
Berger et al. 70
2016 PDAC – 24IPMN – 21Controls - 38
KRAS and GNAS mutations
Higher level of cfDNA in PDAC compared to IPMN
Earl et al. 35
2015 PDAC - 31 KRAS mutation
No significant difference in total cfDNA and survival
Codon 12 KRAS mutant cfDNA detected in 26% of patients
cfDNA concentration increases with advanced disease stages. Survival was 60 days in patients with the KRAS mutant cfDNA and 772 days in patients without
Singh et al. 71
2015 PDAC – 127Controls - 25
KRAS mutation
Higher levels of plasma cfDNA (>62ng/ml) was associated with lower overall median survival time of 3 months as compared to 11 months
Presence of the KRAS gene was not found to be associated with any difference in survival
Sikora et al. 72
2015 PDAC – 50NET – 23Chronic pancreatitis – 20Controls - 23
Alu83, Alu44 nucleotides
Higher levels of cfDNA in PDAC
16
Takai et al. 73
2015 PDAC - 259 KRAS mutation
KRAS mutations in 47% inoperable PDAC and 8.3% resectable
Park et al. 74
2012 PDAC – 16Chronic pancreatitis – 13Controls - 29
Methylation
Altered methylation in PDAC compared with CP and compared with controls
Dabritz et al. 75
2012 PDAC - 38 KRAS mutation
KRAS mutations in 39% of PDAC patients.
Mutations associated with signs of progressive disease
Pederson et al. 76
2011 PDAC – 240Controls - 240
Methylation
Prediction model of 5 CpG sites discriminated PDAC from controls
Liggett et al. 77
2010 PDAC – 30Chronic pancreatitis – 30Controls - 30
Methylation
91.2% sensitivity and 90.8% specificity for PDAC vs CP differentiation
Chen et al. 78
2010 PDAC - 91 KRAS mutation
KRAS mutations in 33% of PDAC patients.
Worse survival in those with mutations Dabritz et al. 79
2009 PDAC – 56Chronic pancreatitis - 13
KRAS mutation
More KRAS mutations in PDAC vs chronic pancreatitis
The addition of CA 19-9 gave 91% sensitivity for cancer diagnosis
Melnikov et al.80
2009 PDAC – 30Controls - 30
Methylation
Prediction model of 5 promoters has 76% sensitivity and 59% specificity for PDAC detection
Uemura et al. 81
2004 PDAC - 28 KRAS mutation
KRAS mutations in 35%
Dai et al. 82
2003 PDAC- 15Chronic pancreatitis - 10
KRAS mutation
KRAS mutations in 73% of PDAC vs 20% of chronic pancreatitis
KRAS + CA 19-9 = 66.67% sensitivity and 97% specificity for cancer detection
Maire et al. 83
2002 PDAC – 47Chronic pancreatitis - 31
KRAS mutation
KRAS mutations in 47% of PDAC vs 13% of chronic pancreatitis
KRAS + CA 19-9 = 98% sensitivity and 77% specificity
Table 2: Studies evaluating cell-free DNA in pancreatic ductal adenocarcinoma.
Glossary: PDAC (pancreatic ductal adenocarcinoma); cfDNA (cell-free DNA); NET (neuroendocrine tumour); IPMN (intraductal papillary mucinous neoplasm)
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