Review Article
Personalized Therapy for Pancreatic Cancer: Challenges and Opportunities
Thomas Hanna and William Greenhalf*
Department of Molecular and Clinical Cancer Medicine, The University of Liverpool, UK
*Corresponding author: William Greenhalf, Department of Molecular and Clinical Cancer Medicine, The University of Liverpool, 5th Floor, UCD Building, Royal Liverpool University Hospital, Daulby Street, Liverpool, L69 3GA, United Kingdom
Published: 22 Mar, 2017
Cite this article as: Hanna T, Greenhalf W. Personalized
Therapy for Pancreatic Cancer:
Challenges and Opportunities. Clin
Oncol. 2017; 2: 1242.
Abstract
Pancreatic Ductal Adenocarcinoma (PDAC) has one of the lowest 5-year survival rates of all cancers.
Early metastatic spread and failure of standard chemotherapeutics both contribute to this statistic.
Over the last decade many other cancer types have benefited from the targeted therapy revolution
in which signalling networks found to be altered in cancer cells are specifically targeted. Despite an
ever-growing understanding of the mutation profiles in PDAC, the vast majority of these approaches
have failed for this form of malignancy. Chemotherapy, which simply targets dividing cells, remains
the most effective available treatment option alongside surgery. Although targeting a broad range of
tyrosine kinase receptors with erlotinib has been shown to offer a modest improvement in the 5-year
survival when combined with the pyrimidine-based chemotherapeutic gemcitabine, this suggests
that targeted approaches may be of benefit in at least some patients. PDAC is characterised by a
long genomic tail of potentially actionable mutations but each appearing in only a small number
of patients, making it difficult to show a survival benefit of a targeted therapy in an unselected
group of patients. Identifying specific subpopulations based on molecular characterisation of the
tumour is particularly difficult in PDAC because of problems in biospecimen acquisition; only a
small proportion of patients undergo surgery and the organ is difficult to biopsy due to its location.
Furthermore, PDAC is characterised by cellular heterogeneity within primary tumours and their
metastases, meaning that targeted therapies may have only a transient effect, killing dominant
cellular populations but leaving behind potentially even more aggressive forms of cancer cells that
have unidentified (and so unexploited) molecular targets. In this review, consideration is given to
overcoming the barriers of personalised medicine specific to PDAC with the aim of improving the
5-year survival rates.
Keywords: PDAC; Targeted therapy; Chemotherapy; Circulating tumour cells; Next generation sequencing
Introduction
In the USA, death rates are stable or decreasing for most forms of cancer, largely due to advances
in treatment. However, for Pancreatic Ductal Adenocarcinoma (PDAC) increasing incidence more
than compensates for any tiny improvement in survival and so despite accounting for less than 5%
of all newly diagnosed cancers, PDAC has grown to become the 4th largest cancer killer [1]. The
median survival for patients after a diagnosis with PDAC is less than 5 months [2]. Chemotherapy
with 5-Fluorouracil (5FU) or gemcitabine following surgical resection of primary tumours
improves prognosis [3,4], but only less than 20% of patients are suitable for surgical resection of
their tumour [5]. Gemcitabine became the standard of treatment for advanced PDAC due to slight
superiority over 5FU in patients with advanced cancer [6]. FOLFIRINOX (oxaliplatin, irinotecan,
leucovorin, and 5FU) is the only non-gemcitabine regime shown to be superior to gemcitabine in
patients with metastatic pancreatic cancer [7] but its toxicity and side effect profile limit its use to
patients with a high performance indicator. Targeting cell division by interfering with microtubule
depolymerisation using albumin-bound paclitaxel (nab-paclitaxel) combined with gemcitabine
gave modest improvement in Overall Survival (OS) in advanced PDAC [8]. The addition of an
orally administered precursor of 5FU (capecitabine) to gemcitabine significantly improved response
rates and Progression Free Survival (PFS) but only showed a trend towards increasing OS in patients
with advanced cancer [9]. A severely limited repertoire of effective chemotherapeutics in a disease
characterised by treatment resistance is a major factor contributing to the poor 5-year survival of
PDAC.
Targeted therapy in PDAC
Targeted therapies have shown significant survival benefit in many different cancer types. It was hoped that similar outcomes would follow for PDAC but most
trials have failed to demonstrate a survival benefit. For example,
bevacizumab (a recombinant humanized anti-VEGF monoclonal
antibody) gave improved Overall Survival (OS) in phase III trials in
advanced colorectal [10], non-small cell lung [11], renal cell [12],
and breast cancer [13]. Despite strong pancreas specific pre-clinical
evidence [14] and an encouraging phase II study [15] no improvement
in OS was seen in a phase III study in advanced PDAC [16]. Lack
of response may be due to the pattern of VEGF isoforms present in
the PDAC patients on the trial. Bevacizumab inhibits angiogenesis
via VEGF-A but the majority of pancreatic cancer patients have
high levels of expression of the VEGF-D which can compensate for
reduced VEGF-A activity. There is evidence that for a small subset of
patients with low levels of VEGF-D bevacizumab does have efficacy
[17], unfortunately this is too few patients to allow the benefit to be
observed in an unselected population.
Conceptually aflibercept offers an advantage over bevacizumab in
treatment of PDAC because as well as targeting VEGF-A it also acts
against at least two other members of the VEGF family (VEGF-B, and
PLGF) [18]. However, aflibercept again gave no survival advantage
when combined with gemcitabine over gemcitabine alone for
advanced PDAC patients [19].
An alternative would be to inhibit the receptors rather than
VEGF itself. Axitinib is a fairly broad range kinase inhibitor but is
best characterised in terms of its inhibition of VEGF Receptors 1,
2 and 3 [20], it has also received approval for use in treatment of
renal cell carcinoma, nevertheless it proved ineffective when used
in combination with gemcitabine in a phase III trial with advanced
PDAC [21].
Other targeted therapies with proven effectiveness in several
cancer types and strong pre-clinical evidence have also failed to show
improved OS. The following are examples, all of which were used in
combination with gemcitabine and all of which showed no survival
benefit:
Tipifarnib targets RAS by inhibiting farnesyl transferases, as
stated above nearly all PDAC tumours have K-Ras mutations, but
despite this targeting K-Ras in the clinic has not yet proved successful
[22]. Including a clinical trial of tipifarnib with gemcitabine [23].
Possibly because K-Ras unlike other forms of Ras protein does not
absolutely require farnesyl transferases to become active (using
geranyl transferases instead) and perhaps because of the ability of
cancer cells to survive having lost K-Ras [24].
Marimastat targets Matrix Metalloproteinases (MMPs). MMPs
are important in the metastatic process that is so characteristic of
PDAC and so they would appear to be a very suitable target, but
in combination with gemcitabine marimastat had little or no effect
on survival [25]. This may be because by the time of treatment the
cancer had already metastasised and the MMPs were not necessary
for cancer cell survival.
Cetuximab targets Epidermal Growth Factor Receptors (EGFRs);
in other cancers, EGFR inhibitors have been shown to be most
effective in patients with EGFR mutations [26] and without K-Ras
mutations [27]. In PDAC EGFR is rarely mutated (less than 5% of
cases) and K-Ras is mutated in over 90% of cases [28,29]. On this
basis, it seems unlikely that Cetuximab would be effective in PDAC,
which was confirmed in clinical trials [30].
Sorafenib is a broad-spectrum kinase inhibitor, targeting not only
tyrosine kinases (e.g. EGFR and VEGF receptors) but also serine/
threonine kinases (e.g. RAF kinase), it could therefore be considered
as a more likely prospect for PDAC than cetuximab. Nevertheless, it
was not successful when tested in a clinical trial [31].
Of all the targeted therapy tested to date against PDAC only the
addition of the tyrosine kinase inhibitor erlotinib to gemcitabine
provided a significant survival advantage [32]. Like cetuximab and
sorafenib, erlotinib targets EGFR. Therefore, it is perhaps surprising
that erlotinib should be effective. Sorafenib and erlotinib are both
small molecule kinase inhibitors but they have a different spectrum
of affinities to specific targets: for example sorafenib is more effective
at inhibiting VEGF receptors than erlotinib but less effective at
inhibiting EGFR [33]. However, erlotinib does not seem to be any
more effective in PDAC patients with wild type K-Ras than in patients
with mutations [34], in marked contrast to the K-Ras dependence
seen in other tumour types [27,35], suggesting that the efficacy of
erlotinib seen in PDAC may be due to inhibition of targets other than
EGFR. It could be that although the kinases inhibited by erlotinib
cover a narrower spectrum than those inhibited by Sorafenib this
spectrum matches more closely the profile of kinases driving tumour
growth and development in PDAC.
The problem is that all the targeted agents described above
might be effective against PDAC in some patients, none of them is
effective against the majority of patients and this means it is difficult
to establish efficacy in a clinical trial.
Clinical trial design
The Randomised Controlled Trial (RCT) was developed nearly
70 years ago to investigate the treatment of a relatively simple disease
(pulmonary tuberculosis) with a single treatment (Streptomycin)
[36]. This was a population-based approach; if more people benefit
from a drug than are harmed by it then it is a good drug. It was always
apparent that a simplistic use of RCTs would miss many beneficial
agents if the benefit was restricted to only a subset of the population,
similarly there is an ethical issue in licensing an agent for use because
the majority will benefit when it is possible that a minority will be
seriously harmed. Statistical methods such as multivariate assessment
of proportional hazards can be used to mitigate this problem [37],
but use of such approaches requires recruitment of large numbers
of patients to give each subgroup an adequate representation. This
approach also requires identification of the relevant parameters
defining the subgroups, for example, subgroups could be defined by
the genotype of the tumour. Unfortunately, the more parameters (e.g.
clinical features or mutations) considered the greater the number
of subgroups and so the greater the number of patients that need
to be recruited. Clinical trials are expensive and so recruitment is
restricted, if 1,000 patients are recruited to a trial and only 1% have a
genotype that interacts positively with the treatment then the effect is
likely to be missed. The solution is to selectively recruit patients who
are predicted to benefit from the treatment.
The problem is exemplified by the failure of early trials with
the EGFR inhibitor gefitinib in unselected cohorts with Non-Small
Cell Lung Cancer (NSCLC) [38-40]. A later phase III study, which
restricted trial entry to patients harbouring an EGFR mutation, was
required to uncover the survival benefit [41].
In NSCLC EGFR mutations are relatively common and so in the
successful trial described above only 337 patients had to be screened in order to recruit 118 patients [41]. Conducting a comparable study
restricting entry to patients harbouring a mutation with a prevalence
of less than 5% (e.g. EGFR in PDAC) would require over 2,000
patients to be screened: this would be expensive and time consuming.
Basket trials recruit patients with different histological cancers but
identical actionable mutations to allow completion of trials with
statistical power in a feasible timeframe [42-44]. PDAC with its long
tail of low frequency actionable mutations has the most to gain from
such a strategy. The first basket trial including PDAC examined the
effect of vemurafenib in non-melanoma cancers with BRAF V600
mutations, it recruited 2 PDAC patients and has now been published
[45]. The National Cancer Institute’s Molecular Analysis for Therapy
Choice (MATCH) study is a large basket trial open to all patients with
solid tumours who have progressed on first line chemotherapy. The
trial includes 10 separate targeted therapies matched to actionable
mutations. The likelihood of PDAC recruitment is significantly
diminished by the inclusion criteria which requires four core biopsies
of primary tumour with >70% tumour content [46].
Basket trials offer an elegant solution to overcome some statistical
challenges with standard RCTs. However, in reality acquired resistance
to monotherapy typically seen in PDAC demands a methodology that
can evaluate multi-drug therapy according to a plethora of actionable
mutations, which evolve throughout a patient's treatment (see later
section). Neither RCTs nor basket trials can accommodate these vast
permutations. Single-patient or n-of-1 trials use multiple time points
and crossover two or more treatments using individual patients as a
control. They may be the method of choice to re-evaluate previously
dismissed treatments [47,48].
Genomics of PDAC
Obviously targeted therapy requires the target to be present. The
key to success therefore lies in proper characterisation of tumours, to
this end the International Cancer Genome Consortium (ICGC) has
set up large-scale cancer genome studies to generate a comprehensive
catalogue of somatic mutations from a variety of cancer types
including PDAC [49]. Such studies offer new insights into the
genomic landscape of PDAC [28,50,51] and provide the platform
from which new approaches to PDAC treatment can be developed.
A classification of the PDAC based on genomic structural variation
has been proposed [28]. Two of these groups have direct therapeutic
relevance and will be considered below.
Locally rearranged
This subgroup accounts for 30% of PDAC patients, one third
harbour a focal amplification in an oncogene (ERBB2, CDK6,
PIK3CA, MET and FGFR1) which can be targeted therapeutically.
ERBB2 (HER2) has been found to be over expressed in 2% of
PDACs, it is suggested that this is associated with absence of liver
metastasis and propensity for lung and brain metastasis [52]. ERBB2
is well known to be over expressed in up to 30% of breast cancers [53]
and has long been effectively targeted with the monoclonal antibody
trastuzumab [54], which has also been shown to have antitumor
effects in PDAC [55]. As well as directly targeting cells dependent on
ERBB2, trastuzumab can also be used to target cytotoxins to ERBB2
positive tumour cells by conjugating the cytotoxin to the antibody.
For example, a derivative of the tubulin inhibitor maitansine has
been conjugated to trastuzumab to give ado-trastuzumab emtansine
(Kadcyla) [56]. Kadcycla is one of the drugs that is being assessed in
the NCI MATCH trial in patients with proven ERBB2 over expression
[46].
One of the most frequently mutated genes in PDAC is CDKN2A
gene which encodes the p16ink4a protein, an inhibitor of Cyclin
Dependent Kinases 4 and 6 (CDK4/6) [57], taken together with the
frequency of focal amplifications involving CDK6 [28], this suggests
an exquisitely significant role for CDK4/6 in pancreatic cancer.
Palbociclib is an oral and selective inhibitor of CDK4/6 and studies in
PDAC animal models suggest palbociclib may be effective in PDAC
treatment [58].
The PIK3CA gene encodes for the p110 subunit of
phosphatidylinositol 3-kinase (PI3K), which activates the
mammalian target of rapamycin (mTOR) pathway [59]. mTOR
inhibitors such as afinitor (everolimus) have improved PFS in
pancreatic neuro endocrine tumours [60] advanced breast [61] and
renal cell carcinoma [62]. In pre-clinical studies, inhibition of the
mTOR pathway has shown anti-tumour effect in PDAC models [63-
66]. Although treatment with everolimus in an unselected group of
patients with metastatic PDAC who had progressed on gemcitabine
showed minimal clinical advantage [67], sub-groups defined by
mutations in the PIK3CA gene may benefit.
MET can be targeted using tivantinib [68], early phase I trials have
found tivantinib to be safe and tolerable in patients with advanced
PDAC [69].
Ponatinib is an inhibitor of FGFR1 (amongst other receptors)
and may be effective in FGFR1 mutated cancers [70] although this
has not yet been tested in a clinical trial with PDAC patients.
Unstable
This subgroup accounts for 14% of PDAC (in the Wadell et al.
[28] study) and is defined by a large number of structural variations,
implicating defects in DNA maintenance and association with both
germline and somatic mutations in the BRCA2 and/or the PALB2
genes. Though numbers were small combined patient and patientderived
xenograft data indicated that these patients respond better
to platinum based chemotherapy than other groups (P = 0.007).
In vitro [71] and phase II studies [72] suggest that patients with
recombination repair defects (e.g. with BRCA2 mutations) respond
better to Poly (ADP-ribose) polymerase (PARP) inhibitors, it is
therefore reasonable to assume that PARP inhibitors would be more
effective in the Unstable subgroup than in others. In a prospective
phase II non-randomised study Kaufman et al. [72] investigated the
PARP inhibitor olaparib in 23 patients with advanced PDAC and a
known deleterious germline mutation in BRCA1/2 who had already
progressed on gemcitabine and platinum based chemotherapy. The
response rate of 22% in this population is encouraging.
The emerging picture from whole genome sequencing studies is
that PDAC tumours are very heterogeneous. Positively, many of the
driver mutations are dominant focal mutation in oncogenes which
have matching targeted therapies which in many cases are tried and
tested in more homogeneous cancers types; where the prevalence of
mutation is over 5%. The challenge of extending this strategy to low
prevalence mutations is multi-faceted. New methods of evaluating
treatments in very small sub-groups have been discussed above. The
next section will consider how such subgroups can be identified.
PDAC tumour sample
The availability of high quality bio-specimens is a prerequisite
for entry of patients into clinical trials of personalized medicine
and ultimately will be required to apply personalized medicine
in clinical practice. An ideal bio-specimen accurately reflects the contemporaneous molecular composition of the tumour; is adequate
for the analysis (e.g. offers enough DNA of good enough quality for
sequencing); and allows minimally invasive acquisition to permit
serial sampling to track clonal evolution.
Incisional biopsies
In breast, colorectal and ovarian cancer the majority of patients
undergo surgical resection, but in prostate, lung and pancreas cancer
patients undergoing resection are in the minority: for example,
resection rates for colon cancer is 85.5% compared to 16.6% for
PDAC [73]. As a result, molecular profiling of primary PDAC is
more dependent on incisional rather than excisional biopsies, which
is also true of other cancer types such as prostate. The anatomical
position of the prostate allows easy access to transrectal core biopsies
which are widely used for molecular profiling in prostate cancer [74].
The pancreas however, occupies a retroperitoneal position, in close
proximity to major vascular structures such that only an endoscopic
approach to biopsy is possible.
Endoscopic Ultrasound-Guided Fine-Needle Aspiration (EUSFNA)
is the most common modality for obtaining a tissue diagnosis
of PDAC but the aspirate is often of limited or no cellularity and
allows at most very limited histological analysis [75]. EUS-FNA
will often be inadequate for diagnosis let alone Next Generation
Sequencing (NGS). Whilst successful NGS on pancreas FNA has been
reported and in fact shown good concordance with paired Formalin
Fixed Paraffin Embedded (FFPE) samples from the primary tumour,
this approach has not been widely replicated [76]. A core tissue
biopsy is the gold standard incisional biopsy and often is a minimum
requirement for clinical trials enrolment. EUS-guided Tru-Cut
biopsies (EUS-TCB) of the pancreas was first reported in 2002 [77],
however, this is a technically difficult procedure and as a consequence
improvement in diagnostic accuracy (over FNA) proved marginal in
early studies [78] and EUS-TCB has not yet been adopted into routine
clinical practice [79]. Without core biopsies entry into basket trials,
such as the MATCH trial which stipulates four core biopsies each
with minimum tumour content >70%, will be limited to the small
percentage of PDAC patients undergoing resection.
Excisional biopsies
Less than 20% of PDAC patients undergo surgical resection of
their tumours [73]. FFPE sections from tumour excision biopsy
are by far the most commonly used material in routine diagnostic
laboratories due to difficulties in collection and storage of fresh or
fresh-frozen samples. The formalin fixation process however, damages
DNA through a number of mechanisms including fragmentation and
cross-linking to proteins [80]. It is fortunate that the fragmented
nucleic acids typically extracted from FFPE specimens are ideally
suited, in length at least, to NGS platforms which are restricted to
reading short length nucleic acids sequences also of around 200-225
base pairs [81]. Despite the DNA damage accrued during the fixation
process, studies have shown comparable sequencing quality with
FFPE derived DNA compared to the gold standard of fresh or freshfrozen
samples [81,82]. A more significant problem of using FFPE for
NGS is the tumour cellularity of the sample. Large scale sequencing
studies using conventional approaches requires at least 80% tumour
cellularity [74]. Dense desmoplastic stroma is a universal feature in
PDAC [83] which dilutes the mean tumour cellularity to between 38-
44% [51]. To some extent this can be overcome by coring out areas of
high tumour cell content [84], either on the basis of gross histology
[85] or using histological guided laser capture microscopy [86], but
this is operator dependant and adds time to the workflow which
may threaten clinical utility. These difficulties are illustrated in the
first trial investigating personalised therapy in PDAC, the IMPACT
study [87]. The plan was that patients would be randomised between
standard chemotherapy or personalised chemotherapy based on 4
sub-groups of actionable mutations. However, a pilot study although
identifying some patients, only served to emphasise the difficulties:
indicating that poor quality, inaccessible, untimely, heterogeneous
bio-specimens would make molecular characterisation of the primary
tumour to guide therapy impractical in an adequately powered trial.
Intra-tumour heterogeneity
During oncogenesis, genomic instability contributes to the
formation of multiple clonal subpopulations with distinct molecular
profiles, which can be demonstrated experimentally by NGS from
multiple topographical sites within the same primary [88]. This
intra tumour heterogeneity is particularly high in PDAC which,
combined with low tumour cellularity, results in the potential for
considerable sampling bias undermining personalised therapy efforts
[89]. The problem is compounded by the apparent tendency for
low frequency sub-clones in the primary PDAC to be enriched in
metastatic lesions [90,91], perhaps reflecting the greater metastatic
potential of relatively slow growing cancer stem cells [92]. Clonal
diversity is driven by branched tumour evolution, responding to
selective pressure from the local microenvironment and potentially
by chemotherapy [93,94]. Studies in breast cancer have revealed that
metastatic sites can acquire HER2 mutations even when the primary
tumour is HER2 negative, which has obvious treatment implications
[95-97]. These findings highlight the inadequacy of directing therapy
based on a single primary or even metastatic tumour sample: serial
sampling, which can track clonal diversity as it develops is required.
Liquid biopsy has recently emerged as a potential successor to the
standard tumour biopsy and has the potential to overcome many of
the issues described above.
Liquid biopsy
Circulating free DNA (cfDNA) and circulating Tumour Cells
(CTCs) obtained from blood have the potential to molecularly
characterise the tumour to meet the aims described in the previous
section.
Circulating free DNA
A number of studies have described the use of cfDNA to screen
for cancer [98-100], recurrence [101-103] and response [104-109].
Plasma contains approximately 1μg/ml of free DNA [110], most
comes from leukocytes and endothelial cells, but in cancer patients
the levels can rise by as much as 10 fold; even more during chemo
and radio therapy [111]. Some of this increase may be due to release
of DNA from lysed apoptotic or necrotic tumour cells but the largest
proportion results from active secretion from macrophages; work in
mouse models suggests that this cancer induced increase includes
nucleosomes that have not come from cancer cells [112]. This means
that in order to detect a specific mutation in circulating DNA a
highly robust technique is required that can cope with vast excess of
wild type sequences. For example, Garcia-Murillas et al. [113] used
mutation specific digital PCR to identify what they referred to as
minimal residual disease in patients with breast cancer. This could
only work if a specific mutant allele was known. In this work the
specific mutations were first identified in primary tumours using
conventional NGS. Douillard et al. [114] demonstrated that cfDNA
is as effective a biospecimen as primary tumour in determining the presence of a specific EGFR mutation when used in the setting of
selecting patients for a targeted therapy trial. In both instances, a
priori knowledge of the specific mutation is required, and thus cfDNA
cannot be used with current methodology to uncover the molecular
heterogeneity of PDAC in real time.
Circulating tumour cells
CTCs are cells shed from the primary tumour and found
circulating in the vasculature, a sub-population of which may
be capable of seeding distant metastasis [115]. Because of the
methods used for detection, CTCs have come to be defined as cells
isolated from blood with an intact nucleus, which stain positive
for cytokeratin, Epithelial Cell Adhesion Molecule (EpCAM) and
are negative for CD45 [116]. The most widely used and only FDA
approved technology for identification of CTCs is CellSearchTM
(Veridex). Using the definition above and Cell Search technology,
CTCs are very rare (1-10 CTCs/ml blood). It has been over 10
years since this system first demonstrated that enumeration of
CTCs, despite their reported scarcity, has prognostic significance in
metastatic breast cancer [117] and this has since been confirmed in
many other cancer types. More recently, CTCs have been evaluated
as a means of directing personalised chemotherapy by overcoming
the issue of genetic discordance between primary and secondary
molecular profile [96,97]. The DETECT study for example, aimed
to determine whether treatment intervention guided by the HER2
status of CTCs in HER negative metastatic breast cancer patients
(determined by primary tumour assessment) is superior to physician
assessment [118].
The benefits of CTC analysis in targeting PDAC seem intuitive
given all the obstacles precluding solid tumour tissue as a biospecimen.
With its propensity for early haematogenous metastasis
CTCs should be more abundant and identification easier in PDAC
than in other cancer types. Unfortunately, it has proven more difficult
to identify CTCs in PDAC than in other cancer types, indeed there
seems to be an inverse relationship between five-year survival and
EpCAM-based CTC recovery rates. A low number of CTCs identified
in patients even with locally advanced or metastatic disease has
been consistently explained by the assumption that CTCs must be
exceptionally rare in PDAC [119,120]. A more plausible explanation
is that they are exceptionally abundant, just not identifiable with
current Ep-CAM based methods [121].
This paradox that less CTCs are observed in a more metastatic
tumour type may be explained by the process of Epithelial
Mesenchymal Transition (EMT): a process that could make tumour
cells more likely to metastasise while simultaneously making them
less likely to be detected. EMT plays an essential role in physiological
processes such as embryology and tissue repair but also pathological
ones such as fibrosis [122] and cancer progression [123]. In cancer,
polarised epithelial cells adhered to the basement membrane and
must transit through a number of biological changes to assume a
mesenchymal phenotype before they can invade the vasculature
[124]. In the process cells shed their epithelial antigens including
EpCAM and cytokeratin (CK) and acquire mesenchymal markers
such as COL5A2, EGFR, MSN, PDGFRB and Twist. A degree of
phenotypic plasticity has been observed whereby cells may transition
between epithelial and mesenchymal state with CTCs existing in both
forms [125]. The process has been implicated in the rapid formation
of primary tumours [126,127], metastasis [128,129], acquisition of
therapeutic resistance [130] and poor survival [131] associated with
PDAC. The most widely used CTC enrichment systems including
CellSearch™, Adna Test [132], Magnetic Activated Cell Sorting
System (MACS®) [133] and microfluidic technologies [120] all require
cell surface expression of EpCAM for CTC capture and will therefore
miss mesenchymal sub-populations of CTCs which are known to be
responsible for the aggressive characteristics of the tumour. This is
supported by evidence suggesting a purely mesenchymal phenotype
predominate in the metastatic stages of cancer [134].
Protein and DNA based methods have been proposed to extend
the utility of CTC analysis to mesenchymal tumour cells. Gorges et al.
[121] have described the use of new mesenchymal cell surface markers
which select for different mesenchymal sub-populations of CTCs.
This approach is currently being pursued by Adna [135], Cellsearch
[135] and CanPatrol CTC [134]. The use of surface markers requires
a priori selection of the markers or markers and will therefore be
vulnerable to missing CTC sub-populations in a heterogeneous
population: significant genetic disparity between CTCs, so called
‘micro heterogeneity’, has been demonstrated in cancer patients
[136]. Another approach is to use the genomic signature of the CTCs,
independent of cell surface markings, to deliver an unbiased analysis
of all CTC sub-populations. This approach offers the possibility
to detect any type of cell in a lineage based on founder mutations.
However, it is limited by the contamination of vast numbers of wild
type leucocytes (~7 x106/mL blood) [137] which drown out the
mutant signal from CTC derived DNA. Several negative depletion
strategies, which remove leucocytes, thereby enriching the CTC
populations are available to overcome this [138]. Developments in
NGS now permit sequencing to a much greater depth and PCR errors
have been reduced to a level that now permit identification of mutant
signal amongst considerable contaminating wild type DNA.
Next generation sequencing
As discussed previously, multiple actionable mutations have
been identified at low frequency in the PDAC genome [28,50,51].
Sequencing approaches therefore will need to interrogate multiple
candidate genes to provide a meaningful attempt at personalised
therapy encompassing all of the targetable oncogenes and genetic
biomarkers. Oncology consortiums have recently developed custom
gene panels using multiplex PCR combined with amplicon-based
NGS from as little as 10 ng of DNA derived from FFPE [139]. The
composition of the gene panels reflects both the frequency of mutated
genes and oncogenes with potentially actionable mutations. Emphasis
remains on validating diagnostic tests across multiple clinical
laboratories [139,140], allowing in-house downstream bioinformatic
analysis within the budget and turnaround time required by clinical
oncologists. For trials such as the NCI MATCH trial, larger custom
panels including up to 200 genes are used on easily accessible
platforms (such as the Ion Torrent PGM). Though these panels
are designed for sequencing of the primary tumour, application to
alternative biospecimens such as enriched CTCs should be considered
in PDAC where access to primary tumour is limited and may not
properly reflect the clinically important metastatic deposits. In this
way treatment can be adapted to the changing cancer burden. The
initial treatment based on the primary tumour, possibly requiring a
combination of therapies targeting dominant cancer cell populations;
a modified treatment on relapse with further modification as resistant
cancer cell populations are selected.
Conclusion
Improved 5-year survival rates in many cancer types has resulted from a deeper understanding of cancer genomics, pharmaceutical development of targeted therapies and a personalised approach to therapy; these improvements have not been realised in PDAC. Recent insights into the PDAC genome not only explain these failures but point to new approaches to tackle them. Advances in treatment are limited by the weakest link in the chain. The genetic revolution is driving a paradigm shift from histological classification of PDAC according to organ, to considering PDAC as a disparate groups of rare diseases, and finally to truly personalized medicine on an individual basis. The pharmaceutical industry has duly kept pace manufacturing targeted treatments soon after molecular targets are identified. NGS developments have also kept pace and are now capable of identifying all molecular targets on a population level. Improvements in PDAC survival will come from addressing the weakest links in the chain: treatment evaluation and biospecimen acquisition.
References
- Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin. 2015;65(1):5-29.
- Yuan C, Rubinson DA, Qian ZR, Wu C, Kraft P, Bao Y, et al. Survival among patients with pancreatic cancer and long-standing or recent-onset diabetes mellitus. J Clin Oncol. 2015;33(1):29-35.
- Neoptolemos JP, Stocken DD, Friess H, Bassi C, Dunn JA, Hickey H, et al. A randomized trial of chemoradiotherapy and chemotherapy after resection of pancreatic cancer. N Engl J Med. 2004;350(12):1200-10.
- Neoptolemos JP, Stocken DD, Bassi C, Ghaneh P, Cunningham D, Goldstein D, et al. Adjuvant chemotherapy with fluorouracil plus folinic acid vs gemcitabine following pancreatic cancer resection: a randomized controlled trial. JAMA. 2010;304(10):1073-81.
- Hackert T, Schneider L, Büchler MW. Current State of Vascular Resections in Pancreatic Cancer Surgery. Gastroenterol Res Pract. 2015;2015:120207.
- Burris HA, Moore MJ, Andersen J, Green MR, Rothenberg ML, Modiano MR, et al. Improvements in survival and clinical benefit with gemcitabine as first-line therapy for patients with advanced pancreas cancer: a randomized trial. J Clin Oncol. 1997;15(6):2403-13.
- Conroy T, Desseigne F, Ychou M, Bouche O, Guimbaud R, Becouarn Y, et al. FOLFIRINOX versus Gemcitabine for Metastatic Pancreatic Cancer. N Engl J Med. 2011;364:1817-25.
- Von Hoff DD, Ervin T, Arena FP, Chiorean EG, Infante J, Moore M, et al. Increased Survival in Pancreatic Cancer with nab-Paclitaxel plus Gemcitabine. N Engl J Med. 2013;369:1691-703.
- Cunningham D, Chau I, Stocken DD, Valle JW, Smith D, Steward W, et al. Phase III randomized comparison of gemcitabine versus gemcitabine plus capecitabine in patients with advanced pancreatic cancer. J Clin Oncol. 2009;27(33):5513-8.
- Hurwitz H, Fehrenbacher L, Novotny W, Cartwright T, Hainsworth J, Heim W, et al. Bevacizumab plus irinotecan, fluorouracil, and leucovorin for metastatic colorectal cancer. N Engl J Med. 2004;350(23):2335-42.
- Sandler A, Gray R, Perry MC, Brahmer J, Schiller JH, Dowlati A, et al. Paclitaxel-carboplatin alone or with bevacizumab for non-small-cell lung cancer. N Engl J Med. 2006;355(24):2542-50.
- Escudier B, Pluzanska A, Koralewski P, Ravaud A, Bracarda S, Szczylik C, et al. Bevacizumab plus interferon alfa-2a for treatment of metastatic renal cell carcinoma: a randomised, double-blind phase III trial. Lancet. 2007;370(9605):2103-11.
- Miller K, Wang M, Gralow J, Dickler M, Cobleigh M, Perez EA, et al. Paclitaxel plus bevacizumab versus paclitaxel alone for metastatic breast cancer. N Engl J Med. 2007;357(26):2666-76.
- Bockhorn M, Tsuzuki Y, Xu L, Frilling A, Broelsch CE, Fukumura D. Differential vascular and transcriptional responses to anti-vascular endothelial growth factor antibody in orthotopic human pancreatic cancer xenografts. Clin Cancer Res. 2003;9(11):4221-6.
- Kindler HL, Friberg G, Singh DA, Locker G, Nattam S, Kozloff M, et al. Phase II trial of bevacizumab plus gemcitabine in patients with advanced pancreatic cancer. J Clin Oncol. 2005;23(31):8033-40.
- Kindler HL, Niedzwiecki D, Hollis D, Sutherland S, Schrag D, Hurwitz H, et al. Gemcitabine plus bevacizumab compared with gemcitabine plus placebo in patients with advanced pancreatic cancer: phase III trial of the Cancer and Leukemia Group B (CALGB 80303). J Clin Oncol. 2010;28(22):3617-22.
- Weickhardt AJ, Williams DS, Lee CK, Chionh F, Simes J, Murone C, et al. Vascular endothelial growth factor D expression is a potential biomarker of bevacizumab benefit in colorectal cancer. Br J Cancer. 2015;113(1):37-45.
- Sun W. Angiogenesis in metastatic colorectal cancer and the benefits of targeted therapy. J Hematol Oncol. 2012;5:63.
- Rougier P, Riess H, Manges R, Karasek P, Humblet Y, Barone C, et al. Randomised, placebo-controlled, double-blind, parallel-group phase III study evaluating aflibercept in patients receiving first-line treatment with gemcitabine for metastatic pancreatic cancer. Eur J Cancer. 2013;49(12):2633-42.
- McTigue M, Murray BW, Chen JH, Deng YL, Solowiej J, Kania RS. Molecular conformations, interactions, and properties associated with drug efficiency and clinical performance among VEGFR TK inhibitors. Proc Natl Acad Sci U S A. 2012;109(45):18281-9.
- Kindler HL, Ioka T, Richel DJ, Bennouna J, Létourneau R, Okusaka T, et al. Axitinib plus gemcitabine versus placebo plus gemcitabine in patients with advanced pancreatic adenocarcinoma: a double-blind randomised phase 3 study. Lancet Oncol. 2011;12(3):256-62.
- Macdonald JS, McCoy S, Whitehead RP, Iqbal S, Wade JLd, Giguere JK, et al. A phase II study of farnesyl transferase inhibitor R115777 in pancreatic cancer: a Southwest oncology group (SWOG 9924) study. Invest New Drugs. 2005;23(5):485-7.
- Van Cutsem E, van de Velde H, Karasek P, Oettle H, Vervenne WL, Szawlowski A, et al. Phase III trial of gemcitabine plus tipifarnib compared with gemcitabine plus placebo in advanced pancreatic cancer. J Clin Oncol. 2004;22(8):1430-8.
- Viale A, Pettazzoni P, Lyssiotis CA, Ying H, Sánchez N, Marchesini M, et al. Oncogene ablation-resistant pancreatic cancer cells depend on mitochondrial function. Nature. 2014;514(7524):628-32.
- Bramhall SR, Schulz J, Nemunaitis J, Brown PD, Baillet M, Buckels JA. A double-blind placebo-controlled, randomised study comparing gemcitabine and marimastat with gemcitabine and placebo as first line therapy in patients with advanced pancreatic cancer. Br J Cancer. 2002;87(2):161-7.
- Pao W, Miller V, Zakowski M, Doherty J, Politi K, Sarkaria I, et al. EGF receptor gene mutations are common in lung cancers from "never smokers" and are associated with sensitivity of tumors to gefitinib and erlotinib. Proc Natl Acad Sci U S A. 2004;101(36):13306-11.
- Allegra CJ, Jessup JM, Somerfield MR, Hamilton SR, Hammond EH, Hayes DF, et al. American Society of Clinical Oncology provisional clinical opinion: testing for KRAS gene mutations in patients with metastatic colorectal carcinoma to predict response to anti-epidermal growth factor receptor monoclonal antibody therapy. J Clin Oncol. 2009;27(12):2091-6.
- Waddell N, Pajic M, Patch AM, Chang DK, Kassahn KS, Bailey P, et al. Whole genomes redefine the mutational landscape of pancreatic cancer. Nature. 2015;518,495-501.
- Witkiewicz AK, McMillan EA, Balaji U, Baek G, Lin WC, Mansour J, et al. Whole-exome sequencing of pancreatic cancer defines genetic diversity and therapeutic targets. Nat Commun. 2015;6:6744.
- Philip PA, Benedetti J, Corless CL, Wong R, O'Reilly EM, Flynn PJ, et al. Phase III study comparing gemcitabine plus cetuximab versus gemcitabine in patients with advanced pancreatic adenocarcinoma: Southwest Oncology Group-directed intergroup trial S0205. J Clin Oncol. 2010;28(22):3605-10.
- Gonçalves A, Gilabert M, François E, Dahan L, Perrier H, Lamy R, et al. BAYPAN study: a double-blind phase III randomized trial comparing gemcitabine plus sorafenib and gemcitabine plus placebo in patients with advanced pancreatic cancer. Ann Oncol. 2012;23(11):2799-805.
- Moore MJ, Goldstein D, Hamm J, Figer A, Hecht JR, Gallinger S, et al. Erlotinib plus gemcitabine compared with gemcitabine alone in patients with advanced pancreatic cancer: a phase III trial of the National Cancer Institute of Canada Clinical Trials Group. J Clin Oncol. 2007;25(15):1960-6.
- Uitdehaag JC, de Roos JA, van Doornmalen AM, Prinsen MB, de Man J, Tanizawa Y, et al. Comparison of the cancer gene targeting and biochemical selectivities of all targeted kinase inhibitors approved for clinical use. PLoS One. 2014;9(3):e92146.
- Boeck S, Jung A, Laubender RP, Neumann J, Egg R, Goritschan C, et al. KRAS mutation status is not predictive for objective response to anti-EGFR treatment with erlotinib in patients with advanced pancreatic cancer. J Gastroenterol. 2013;48(4):544-8.
- Pao W, Wang TY, Riely GJ, Miller VA, Pan Q, Ladanyi M, et al. KRAS mutations and primary resistance of lung adenocarcinomas to gefitinib or erlotinib. PLoS Med. 2005;2(1):e17.
- [No authors listed]. STREPTOMYCIN treatment of pulmonary tuberculosis. Br Med J. 1948;2(4582):769-82.
- Cox, D. Regression Models and Life-Tables. J Royal Statist Society. 1972;34:187-220.
- Kim ES, Hirsh V, Mok T, Socinski MA, Gervais R, Wu YL, et al. Gefitinib versus docetaxel in previously treated non-small-cell lung cancer (INTEREST): a randomised phase III trial. Lancet. 2008;372(9652):1809-18.
- Maruyama R, Nishiwaki Y, Tamura T, Yamamoto N, Tsuboi M, Nakagawa K, et al. Phase III study, V-15-32, of gefitinib versus docetaxel in previously treated Japanese patients with non-small-cell lung cancer. J Clin Oncol. 2008;26(26):4244-52.
- Thatcher N, Chang A, Parikh P, Rodrigues Pereira J, Ciuleanu T, von Pawel J, et al. Gefitinib plus best supportive care in previously treated patients with refractory advanced non-small-cell lung cancer: results from a randomised, placebo-controlled, multicentre study (Iressa Survival Evaluation in Lung Cancer). Lancet. 2005;366(9496):1527-37.
- Mitsudomi T, Morita S, Yatabe Y, Negoro S, Okamoto I, Tsurutani J, et al. Gefitinib versus cisplatin plus docetaxel in patients with non-small-cell lung cancer harbouring mutations of the epidermal growth factor receptor (WJTOG3405): an open label, randomised phase 3 trial. Lancet Oncol. 2010;11(2):121-8.
- Mehta C, Schäfer H, Daniel H, Irle S. Biomarker driven population enrichment for adaptive oncology trials with time to event endpoints. Stat Med. 2014;33(26):4515-31.
- Berry DA. The Brave New World of clinical cancer research: Adaptive biomarker-driven trials integrating clinical practice with clinical research. Mol Oncol. 2015;9(5):951-9.
- Redig AJ, Jänne PA. Basket trials and the evolution of clinical trial design in an era of genomic medicine. J Clin Oncol. 2015;33(9):975-7.
- Hyman DM, Puzanov I, Subbiah V, Faris JE, Chau I, Blay JY, et al. Vemurafenib in Multiple Nonmelanoma Cancers with BRAF V600 Mutations. N Engl J Med. 2015;373(8):726-36.
- Do K, O'Sullivan Coyne G, Chen AP. An overview of the NCI precision medicine trials-NCI MATCH and MPACT. Chin Clin Oncol. 2015;4(3):31.
- Schork NJ. Personalized medicine: Time for one-person trials. Nature. 2015;520(7549):609-11.
- Duan N, Kravitz RL, Schmid CH. Single-patient (n-of-1) trials: a pragmatic clinical decision methodology for patient-centered comparative effectiveness research. J Clin Epidemiol. 2013;66(8 Suppl):S21-8.
- International Cancer Genome Consortium, Hudson TJ, Anderson W, Artez A, Barker AD, Bell C, Bernabe RR, et al. International network of cancer genome projects. Nature. 2010;464:993-8.
- Nones K, Waddell N, Song S, Patch AM, Miller D, Johns A, et al. Genome-wide DNA methylation patterns in pancreatic ductal adenocarcinoma reveal epigenetic deregulation of SLIT-ROBO, ITGA2 and MET signaling. Int J Cancer. 2014;135:1110-8.
- Biankin AV, Waddell N, Kassahn KS, Gingras MC, Muthuswamy LB, Johns AL, et al. Genomic alterations in pancreatic cancer and their relevance to therapy. Nature. 2012;491:399-405.
- Chou A, Waddell N, Cowley MJ, Gill AJ, Chang DK, Patch AM, et al. Clinical and molecular characterization of HER2 amplified-pancreatic cancer. Genome Med. 2013;5:78.
- Slamon DJ, Clark GM, Wong SG, Levin WJ, Ullrich A, McGuire WL. Human breast cancer: correlation of relapse and survival with amplification of the HER-2/neu oncogene. Science. 1987;235(4785):177-82.
- Slamon DJ, Leyland-Jones B, Shak S, Fuchs H, Paton V, Bajamonde A, et al. Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N Engl J Med. 2001;344(11):783-92.
- Kimura K, Sawada T, Komatsu M, Inoue M, Muguruma K, Nishihara T, et al. Antitumor effect of trastuzumab for pancreatic cancer with high HER-2 expression and enhancement of effect by combined therapy with gemcitabine. Clin Cancer Res. 2006;12(16):4925-32.
- Lewis Phillips GD, Li G, Dugger DL, Crocker LM, Parsons KL, Mai E, et al. Targeting HER2-positive breast cancer with trastuzumab-DM1, an antibody-cytotoxic drug conjugate. Cancer Res. 2008;68:9280-90.
- Schutte M, Hruban RH, Geradts J, Maynard R, Hilgers W, Rabindran SK, et al. Abrogation of the Rb/p16 tumor-suppressive pathway in virtually all pancreatic carcinomas. Cancer Res. 1997;57(15):3126-30.
- Franco J, Witkiewicz AK, Knudsen ES. CDK4/6 inhibitors have potent activity in combination with pathway selective therapeutic agents in models of pancreatic cancer. Oncotarget. 2014;5(15):6512-25.
- Bjornsti MA, Houghton PJ. The TOR pathway: a target for cancer therapy. Nat Rev Cancer. 2004;4(5):335-48.
- Yao JC, Shah MH, Ito T, Bohas CL, Wolin EM, Van Cutsem E, et al. Everolimus for advanced pancreatic neuroendocrine tumors. N Engl J Med. 2011;364:514-23.
- Baselga J, Campone M, Piccart M, Burris HA, Rugo HS, Sahmoud T, et al. Everolimus in postmenopausal hormone-receptor-positive advanced breast cancer. N Engl J Med. 2012;366(6):520-9.
- Motzer RJ, Escudier B, Oudard S, Hutson TE, Porta C, Bracarda S, et al. Efficacy of everolimus in advanced renal cell carcinoma: a double-blind, randomised, placebo-controlled phase III trial. Lancet. 2008;372(9637):449-56.
- Bondar VM, Sweeney-Gotsch B, Andreeff M, Mills GB, McConkey DJ. Inhibition of the phosphatidylinositol 3'-kinase-AKT pathway induces apoptosis in pancreatic carcinoma cells In vitro and in vivo. Mol Cancer Ther. 2002;1(12):989-97.
- Bruns CJ, Koehl GE, Guba M, Yezhelyev M, Steinbauer M, Seeliger H, et al. Rapamycin-induced endothelial cell death and tumor vessel thrombosis potentiate cytotoxic therapy against pancreatic cancer. Clin Cancer Res. 2004;10(6):2109-19.
- Asano T, Yao Y, Zhu J, Li D, Abbruzzese JL, Reddy SA. The rapamycin analog CCI-779 is a potent inhibitor of pancreatic cancer cell proliferation. Biochem Biophys Res Commun. 2005;331(1):295-302.
- Ito D, Fujimoto K, Mori T, Kami K, Koizumi M, Toyoda E, et al. In vivo antitumor effect of the mTOR inhibitor CCI-779 and gemcitabine in xenograft models of human pancreatic cancer. Int J Cancer. 2006;118(9):2337-43.
- Wolpin BM, Hezel AF, Abrams T, Blaszkowsky LS, Meyerhardt JA, Chan JA, et al. Oral mTOR inhibitor everolimus in patients with gemcitabine-refractory metastatic pancreatic cancer. J Clin Oncol. 2009;27:193-8.
- Pérez-Ramírez C, Cañadas-Garre M, Jiménez-Varo E, Faus-Dáder MJ, Calleja-Hernández MÁ. MET: a new promising biomarker in non-small-cell lung carcinoma. Pharmacogenomics. 2015;16(6):631-47.
- Pant S, Saleh M, Bendell J, Infante JR, Jones S, Kurkjian CD, et al. A phase I dose escalation study of oral c-MET inhibitor tivantinib (ARQ 197) in combination with gemcitabine in patients with solid tumors. Ann Oncol. 2014;25(7):1416-21.
- Gozgit JM, Wong MJ, Moran L, Wardwell S, Mohemmad QK, Narasimhan NI, et al. Ponatinib (AP24534), a multitargeted pan-FGFR inhibitor with activity in multiple FGFR-amplified or mutated cancer models. Mol Cancer Ther. 2012;11(3):690-9.
- van der Heijden MS, Brody JR, Dezentje DA, Gallmeier E, Cunningham SC, Swartz MJ, et al. In vivo therapeutic responses contingent on Fanconi anemia/BRCA2 status of the tumor. Clin Cancer Res. 2005;11(20):7508-15.
- Kaufman B, Shapira-Frommer R, Schmutzler RK, Audeh MW, Friedlander M, Balmaña J, et al. Olaparib monotherapy in patients with advanced cancer and a germline BRCA1/2 mutation. J Clin Oncol. 2015;33(3):244-50.
- Speelman AD, van Gestel YR, Rutten HJ, de Hingh IH, Lemmens VE, et al. Changes in gastrointestinal cancer resection rates. Br J Surg. 2015;102(9):1114-22.
- Yadav SS, Li J, Lavery HJ, Yadav KK, Tewari AK. Next-generation sequencing technology in prostate cancer diagnosis, prognosis, and personalized treatment. Urol Oncol. 2015;33(6):267.
- Varadarajulu S, Fockens P, Hawes RH. Best practices in endoscopic ultrasound-guided fine-needle aspiration. Clin Gastroenterol Hepatol. 2012;10(7):697-703.
- Young G, Wang K, He J, Otto G, Hawryluk M, Zwirco Z, et al. Clinical next-generation sequencing successfully applied to fine-needle aspirations of pulmonary and pancreatic neoplasms. Cancer Cytopathol. 2013;121(12):688-94.
- Wiersema MJ, Levy MJ, Harewood GC, Vazquez-Sequeiros E, Jondal ML, Wiersema LM. Initial experience with EUS-guided trucut needle biopsies of perigastric organs. Gastrointestinal endoscopy. 2002;56:275-8.
- Shah SM, Ribeiro A, Levi J, Jorda M, Rocha-Lima C, Sleeman D, et al. EUS-guided fine needle aspiration with and without trucut biopsy of pancreatic masses. JOP. 2008;9(4):422-30.
- Fuccio L, Larghi A. Endoscopic ultrasound-guided fine needle aspiration: How to obtain a core biopsy? Endosc Ultrasound. 2014;3(2):71-81.
- Auerbach C, Moutschen-Dahmen M, Moutschen J. Genetic and cytogenetical effects of formaldehyde and related compounds. Mutat Res. 1977;39(3-4):317-61.
- Shaw V, Bullock K, Greenhalf W. Single-Nucleotide Polymorphism to Associate Cancer Risk. Methods Mol Biol. 2016;1381:93-110.
- Spencer DH, Sehn JK, Abel HJ, Watson MA, Pfeifer JD, Duncavage EJ. Comparison of clinical targeted next-generation sequence data from formalin-fixed and fresh-frozen tissue specimens. J Mol Diagn. 2013;15(5):623-33.
- Mahadevan D, Von Hoff DD. Tumor-stroma interactions in pancreatic ductal adenocarcinoma. Mol Cancer Ther. 2007;6(4):1186-97.
- Weng L, Wu X, Gao H, Mu B, Li X, Wang JH, et al. MicroRNA profiling of clear cell renal cell carcinoma by whole-genome small RNA deep sequencing of paired frozen and formalin-fixed, paraffin-embedded tissue specimens. J Pathol. 2010;222(1):41-51.
- Wagle N, Berger MF, Davis MJ, Blumenstiel B, Defelice M, Pochanard P, et al. High-throughput detection of actionable genomic alterations in clinical tumor samples by targeted, massively parallel sequencing. Cancer Discov. 2012;2(1):82-93.
- Shen K, Luk S, Hicks DF, Elman JS, Bohr S, Iwamoto Y, et al. Resolving cancer-stroma interfacial signalling and interventions with micropatterned tumour-stromal assays. Nat Commun. 2014;5:5662.
- Chantrill LA, Nagrial AM, Watson C, Johns AL, Martyn-Smith M, Simpson S, et al. Precision Medicine for Advanced Pancreas Cancer: The Individualized Molecular Pancreatic Cancer Therapy (IMPaCT) Trial. Clin Cancer Res. 2015;21:2029-37.
- Gerlinger M, Rowan AJ, Horswell S, Larkin J, Endesfelder D, Gronroos E, et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med. 2012;366(10):883-92.
- Marusyk A, Almendro V, Polyak K. Intra-tumour heterogeneity: a looking glass for cancer? Nat Rev Cancer. 2012;12(5):323-34.
- Yachida S, Jones S, Bozic I, Antal T, Leary R, Fu B, et al. Distant metastasis occurs late during the genetic evolution of pancreatic cancer. Nature. 2010;467:1114-7.
- Campbell PJ, Yachida S, Mudie LJ, Stephens PJ, Pleasance ED, Stebbings LA, et al. The patterns and dynamics of genomic instability in metastatic pancreatic cancer. Nature. 2010;467(7319):1109-13.
- Niess H, Camaj P, Renner A, Ischenko I, Zhao Y, Krebs S, et al. Side population cells of pancreatic cancer show characteristics of cancer stem cells responsible for resistance and metastasis. Target Oncol. 2015; 10(2):215-27.
- Greaves M, Maley CC. Clonal evolution in cancer. Nature. 2012;481(7381):306-13.
- Burrell RA, McGranahan N, Bartek J, Swanton C. The causes and consequences of genetic heterogeneity in cancer evolution. Nature. 2013;501(7467):338-45.
- Curtit E, Nerich V, Mansi L, Chaigneau L, Cals L, Villanueva C, et al. Discordances in estrogen receptor status, progesterone receptor status, and HER2 status between primary breast cancer and metastasis. Oncologist. 2013;18(6):667-74.
- Rossi S, Basso M, Strippoli A, Dadduzio V, Cerchiaro E, Barile R, et al. Hormone Receptor Status and HER2 Expression in Primary Breast Cancer Compared With Synchronous Axillary Metastases or Recurrent Metastatic Disease. Clin Breast Cancer. 2015;15(5):307-12.
- Santinelli A, Pisa E, Stramazzotti D, Fabris G. HER-2 status discrepancy between primary breast cancer and metastatic sites. Impact on target therapy. Int J Cancer. 2008;122(5):999-1004.
- Szpechcinski A, Chorostowska-Wynimko J1, Struniawski R1, Kupis W2, Rudzinski P2, Langfort R3, et al. Cell-free DNA levels in plasma of patients with non-small-cell lung cancer and inflammatory lung disease. Br J Cancer. 2015;113(3):476-83.
- Heitzer E, Ulz P, Geigl JB. Circulating tumor DNA as a liquid biopsy for cancer. Clin Chem. 2015;61(1):112-23.
- Bianchi DW, Chudova D, Sehnert AJ, Bhatt S, Murray K, Prosen TL, et al. Noninvasive Prenatal Testing and Incidental Detection of Occult Maternal Malignancies. JAMA. 2015;314(2):162-9.
- Bratman SV, Newman AM, Alizadeh AA, Diehn M. Potential clinical utility of ultrasensitive circulating tumor DNA detection with CAPP-Seq. Expert Rev Mol Diagn. 2015;15(6):715-9.
- Stremitzer S, Zhang W, Yang D, Ning Y, Stintzing S, Sebio A, et al. Genetic Variations in Angiopoietin and Pericyte Pathways and Clinical Outcome in Patients With Resected Colorectal Liver Metastases. Cancer. 2015;121:1898-905.
- Olsson E, Winter C, George A, Chen Y, Howlin J, Tang MH, et al. Serial monitoring of circulating tumor DNA in patients with primary breast cancer for detection of occult metastatic disease. EMBO Mol Med. 2015;7(8):1034-47.
- Mok T, Wu YL, Lee JS, Yu CJ, Sriuranpong V, Sandoval-Tan J, et al. Detection and Dynamic Changes of EGFR Mutations from Circulating Tumor DNA as a Predictor of Survival Outcomes in NSCLC Patients Treated with First-line Intercalated Erlotinib and Chemotherapy. Clin Cancer Res. 2015;21(14):3196-203.
- Gong C, Liu B, Yao Y, Qu S, Luo W, Tan W, et al. Potentiated DNA Damage Response in Circulating Breast Tumor Cells Confers Resistance to Chemotherapy. J Biol Chem. 2015;290(24):14811-25.
- Schwarzenbach H. The potential of circulating nucleic acids as components of companion diagnostics for predicting and monitoring chemotherapy response. Expert Rev Mol Diagn. 2015;15(2):267-75.
- Cappelletti V, Appierto V, Tiberio P, Fina E, Callari M, Daidone MG. MicroRNA Biomarkers in Neurodegenerative Diseases and Emerging NanoSensors Technology. J Natl Cancer Inst Monogr. 2015;2015:60-3.
- Neal JW, Gainor JF, Shaw AT. Developing biomarker-specific end points in lung cancer clinical trials. Nat Rev Clin Oncol. 2015;12(3):135-46.
- Tabernero J, Lenz HJ, Siena S, Sobrero A, Falcone A, Ychou M, et al. Serum VEGF-A and CCL5 levels as candidate biomarkers for efficacy and toxicity of regorafenib in patients with metastatic colorectal cancer. Lancet Oncol. 2015;16:937-48.
- Bagul A, Pushpakom S, Boylan J, Newman W, Siriwardena AK. Quantitative analysis of plasma DNA in severe acute pancreatitis. JOP. 2006;7(6):602-7.
- Holdenrieder S, Stieber P, Bodenmüller H, Busch M, Fertig G, Fürst H, et al. Nucleosomes in serum of patients with benign and malignant diseases. Int J Cancer. 2001;95(2):114-20.
- Pisetsky DS. The immune response to cell death in SLE. Autoimmun Rev. 2004;3(7-8):500-4.
- Garcia-Murillas I, Schiavon G, Weigelt B, Ng C, Hrebien S, Cutts RJ, et al. Mutation tracking in circulating tumor DNA predicts relapse in early breast cancer. Sci Transl Med. 2015;7(302):302ra133.
- Douillard JY, Ostoros G, Cobo M, Ciuleanu T, Cole R, McWalter G, et al. Gefitinib treatment in EGFR mutated caucasian NSCLC: circulating-free tumor DNA as a surrogate for determination of EGFR status. J Thorac Oncol. 2014;9(9):1345-53.
- Gupta GP, Massagué J. Cancer metastasis: building a framework. Cell. 2006;127(4):679-95.
- Andreopoulou E, Yang LY, Rangel KM, Reuben JM, Hsu L, Krishnamurthy S, et al. Comparison of assay methods for detection of circulating tumor cells in metastatic breast cancer: AdnaGen AdnaTest BreastCancer Select/Detectâ„¢ versus Veridex CellSearchâ„¢ system. Int J Cancer. 2012;130(7):1590-7.
- Cristofanilli M, Budd GT, Ellis MJ, Stopeck A, Matera J, Miller MC, et al. Circulating tumor cells, disease progression, and survival in metastatic breast cancer. N Engl J Med. 2004;351(8):781-91.
- Schramm A, Friedl TW, Schochter F, Scholz C, de Gregorio N, Huober J, et al. Real-time HER2 status detected on circulating tumor cells predicts different outcomes of anti-HER2 therapy in histologically HER2-positive metastatic breast cancer patients. BMC Cancer. 2016; 16: 526.
- Cristofanilli M, Hayes DF, Budd GT, Ellis MJ, Stopeck A, Reuben JM, et al. Circulating tumor cells: a novel prognostic factor for newly diagnosed metastatic breast cancer. J Clin Oncol. 2005;23(7):1420-30.
- Nagrath S, Sequist LV, Maheswaran S, Bell DW, Irimia D, Ulkus L, et al. Isolation of rare circulating tumour cells in cancer patients by microchip technology. Nature. 2007;450(7173):1235-9.
- Gorges TM, Tinhofer I, Drosch M, Röse L, Zollner TM, Krahn T, et al. Circulating tumour cells escape from EpCAM-based detection due to epithelial-to-mesenchymal transition. BMC Cancer. 2012;12:178.
- Kalluri R, Neilson EG. Epithelial-mesenchymal transition and its implications for fibrosis. J Clin Invest. 2003;112(12):1776-84.
- Thiery JP, Acloque H, Huang RY, Nieto MA. Epithelial-mesenchymal transitions in development and disease. Cell. 2009;139(5):871-90.
- Kalluri R, Weinberg RA. The basics of epithelial-mesenchymal transition. J Clin Invest. 2009;119(6):1420-8.
- Armstrong AJ, Marengo MS, Oltean S, Kemeny G, Bitting RL, Turnbull JD, et al. Circulating tumor cells from patients with advanced prostate and breast cancer display both epithelial and mesenchymal markers. Mol Cancer Res. 2011;9(8):997-1007.
- Castellanos JA, Merchant NB, Nagathihalli NS. Emerging targets in pancreatic cancer: epithelial-mesenchymal transition and cancer stem cells. Onco Targets Ther. 2013;6:1261-7.
- Mani SA, Guo W, Liao MJ, Eaton EN, Ayyanan A, Zhou AY, et al. The epithelial-mesenchymal transition generates cells with properties of stem cells. Cell. 2008;133(4):704-15.
- Tsuji T, Ibaragi S, Hu GF. Epithelial-mesenchymal transition and cell cooperativity in metastasis. Cancer Res. 2009;69(18):7135-9.
- von Burstin J, Eser S, Paul MC, Seidler B, Brandl M, Messer M, et al. E-cadherin regulates metastasis of pancreatic cancer in vivo and is suppressed by a SNAIL/HDAC1/HDAC2 repressor complex. Gastroenterology. 2009;137:361-71, 371.e1-5.
- Arumugam T, Ramachandran V, Fournier KF, Wang H, Marquis L, Abbruzzese JL, et al. Epithelial to mesenchymal transition contributes to drug resistance in pancreatic cancer. Cancer Res. 2009;69(14):5820-8.
- Yamada S, Fuchs BC, Fujii T, Shimoyama Y, Sugimoto H, Nomoto S, et al. Epithelial-to-mesenchymal transition predicts prognosis of pancreatic cancer. Surgery. 2013;154(5):946-54.
- Demel U, Tilz GP, Foeldes-Papp Z, Gutierrez B, Albert WH, Böcher O. Detection of tumour cells in the peripheral blood of patients with breast cancer. Development of a new sensitive and specific immunomolecular assay. J Exp Clin Cancer Res. 2004;23(3):465-8.
- Griwatz C, Brandt B, Assmann G, Zänker KS. An immunological enrichment method for epithelial cells from peripheral blood. J Immunol Methods. 1995;183(2):251-65.
- Wu S, Liu S, Liu Z, Huang J, Pu X, Li J, et al. Classification of Circulating Tumor Cells by Epithelial-Mesenchymal Transition Markers. PLoS One. 2015;10:e0123976.
- Kasimir-Bauer S, Hoffmann O, Wallwiener D, Kimmig R, Fehm T. Expression of stem cell and epithelial-mesenchymal transition markers in primary breast cancer patients with circulating tumor cells. Breast Cancer Res. 2012;14(1):R15.
- Polzer B, Medoro G, Pasch S, Fontana F, Zorzino L, Pestka A, et al. Molecular profiling of single circulating tumor cells with diagnostic intention. EMBO Mol Med. 2014;6(11):1371-86.
- SB M. Textbook of hematology. Baltimore, Williams and Wilkins. 1996.
- Lustberg M, Jatana KR, Zborowski M, Chalmers JJ. Emerging technologies for CTC detection based on depletion of normal cells. Recent Results Cancer Res. 2012;195:97-110.
- Tops BB, Normanno N, Kurth H, Amato E, Mafficini A, Rieber N, et al. Development of a semi-conductor sequencing-based panel for genotyping of colon and lung cancer by the Onconetwork consortium. BMC Cancer. 2015;15:26.
- Dijkstra JR, Tops BB, Nagtegaal ID, van Krieken JH, Ligtenberg MJ. The homogeneous mutation status of a 22 gene panel justifies the use of serial sections of colorectal cancer tissue for external quality assessment. Virchows Arch. 2015;467(3):273-8.