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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

1

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

2

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

4

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

5

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

6

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

7

different, 17.2 months in the sensitive group compared to 8.3 months in the resistant

group (p<0.0304).

8

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

9

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.

12

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


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


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


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


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


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


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


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


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


KRAS mutations in 47% inoperable PDAC and 8.3% resectable

Park et al. 74


Methylation

Altered methylation in PDAC compared with CP and compared with controls

Dabritz et al. 75


KRAS mutations in 39% of PDAC patients.

Mutations associated with signs of progressive disease

Pederson et al. 76


Methylation

Prediction model of 5 CpG sites discriminated PDAC from controls

Liggett et al. 77


Methylation

91.2% sensitivity and 90.8% specificity for PDAC vs CP differentiation

Chen et al. 78


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


Methylation

Prediction model of 5 promoters has 76% sensitivity and 59% specificity for PDAC detection

Uemura et al. 81


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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