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Critical Reviews in Clinical Laboratory Sciences
ISSN: 1040-8363 (Print) 1549-781X (Online) Journal homepage: http://www.tandfonline.com/loi/ilab20
Using circulating cell-free DNA to monitor
personalized cancer therapy
Michael Oellerich, Ekkehard Schütz, Julia Beck, Philipp Kanzow, Piers N.
Plowman, Glen J. Weiss & Philip D. Walson
To cite this article: Michael Oellerich, Ekkehard Schütz, Julia Beck, Philipp Kanzow, Piers
N. Plowman, Glen J. Weiss & Philip D. Walson (2017): Using circulating cell-free DNA to
monitor personalized cancer therapy, Critical Reviews in Clinical Laboratory Sciences, DOI:
10.1080/10408363.2017.1299683
To link to this article: http://dx.doi.org/10.1080/10408363.2017.1299683
Published online: 10 Apr 2017.
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Date: 10 April 2017, At: 05:35
CRITICAL REVIEWS IN CLINICAL LABORATORY SCIENCES, 2017
http://dx.doi.org/10.1080/10408363.2017.1299683
REVIEW ARTICLE
Using circulating cell-free DNA to monitor personalized cancer therapy
€tzb, Julia Beckb, Philipp Kanzowa
Michael Oellericha , Ekkehard Schu
a
and Philip D. Walson
, Piers N. Plowmanc, Glen J. Weissd
a
Department of Clinical Pharmacology, University Medical Center Go€ttingen, G€
ottingen, Germany; bChronix Biomedical GmbH,
G€ottingen, Germany; cDepartment of Clinical Oncology, St. Bartholomew’s Hospital, West Smithfield, London, UK; dCancer Treatment
Centers of America, Goodyear, AZ, USA
ABSTRACT
High-quality genomic analysis is critical for personalized pharmacotherapy in patients with cancer.
Tumor-specific genomic alterations can be identified in cell-free DNA (cfDNA) from patient blood
samples and can complement biopsies for real-time molecular monitoring of treatment, detection
of recurrence, and tracking resistance. cfDNA can be especially useful when tumor tissue is
unavailable or insufficient for testing. For blood-based genomic profiling, next-generation
sequencing (NGS) and droplet digital PCR (ddPCR) have been successfully applied. The US Food
and Drug Administration (FDA) recently approved the first such “liquid biopsy” test for EGFR
mutations in patients with non-small cell lung cancer (NSCLC). Such non-invasive methods allow
for the identification of specific resistance mutations selected by treatment, such as EGFR T790M,
in patients with NSCLC treated with gefitinib. Chromosomal aberration pattern analysis by low
coverage whole genome sequencing is a more universal approach based on genomic instability.
Gains and losses of chromosomal regions have been detected in plasma tumor-specific cfDNA as
copy number aberrations and can be used to compute a genomic copy number instability (CNI)
score of cfDNA. A specific CNI index obtained by massive parallel sequencing discriminated those
patients with prostate cancer from both healthy controls and men with benign prostatic disease.
Furthermore, androgen receptor gene aberrations in cfDNA were associated with therapeutic
resistance in metastatic castration resistant prostate cancer. Change in CNI score has been shown
to serve as an early predictor of response to standard chemotherapy for various other cancer
types (e.g. NSCLC, colorectal cancer, pancreatic ductal adenocarcinomas). CNI scores have also
been shown to predict therapeutic responses to immunotherapy. Serial genomic profiling can
detect resistance mutations up to 16 weeks before radiographic progression. There is a potential
for cost savings when ineffective use of expensive new anticancer drugs is avoided or halted.
Challenges for routine implementation of liquid biopsy tests include the necessity of specialized
personnel, instrumentation, and software, as well as further development of quality management
(e.g. external quality control). Validation of blood-based tumor genomic profiling in additional
multicenter outcome studies is necessary; however, cfDNA monitoring can provide clinically
important actionable information for precision oncology approaches.
Introduction
Progress in understanding the molecular pathways in
tumors has encouraged attempts to move away from
protocol-based approaches and toward more personalized cancer therapies. These new treatment concepts
use information about a person’s genes, proteins, and
environment to help diagnose, plan treatment, monitor
treatment efficacy, or to prognosticate (National Cancer
Institute 2016). Personalized cancer therapy allows
more targeted treatment, which has been shown to be
more effective for example in non-small cell lung cancer
(NSCLC) harboring EGFR and ALK mutations as well as
ARTICLE HISTORY
Received 5 December 2016
Revised 15 February 2017
Accepted 22 February 2017
Published online 5 April 2017
KEYWORDS
Genotype-directed cancer
care; liquid biopsy; ctDNA
tumor genomic profiling;
cfDNA; chromosomal
aberration pattern analysis;
immunotherapy
melanomas with BRAF mutations. KRAS mutations allow
identification of cancers that will not respond to EGFR
antibodies and EGFR kinase inhibitors (Oxnard et al.
2014). Identification of non-responders is helpful to
avoid unsuccessful, unnecessary treatment and costs.
A prerequisite for the successful application of such
personalized approaches to cancer care is the availability of practical diagnostic tools for identifying subsets of
patients with solid tumors sensitive to targeted therapies, real-time molecular monitoring of treatment, the
detection of recurrence, and tracking resistance (Oxnard
et al. 2014). Advances in genome technologies within
CONTACT Michael Oellerich
[email protected]
Department of Clinical Pharmacology, University Medical Center Go€ttingen,
Kreuzbergring 36, 37075 G€ottingen, Germany
Referees: Dr. David S Wilkinson, Transfusion Medicine, Department of Pathology, Virginia Commonwealth University, Richmond, Virginia; Dr. Karin
Trajcevski, Clinical Biochemistry, Laboratory Medicine & Pathobiology, University of Toronto, Toronto, Canada.
! 2017 Informa UK Limited, trading as Taylor & Francis Group
2
M. OELLERICH ET AL.
the past decade have been essential for monitoring
genotype-directed cancer care. Next-generation
sequencing (NGS) platforms have been developed that
allow for the simultaneous sequencing of multiple areas
of the genome (Gagan & Van Allen 2015). This technology is useful to develop more universal approaches for
cancer detection. Droplet digital PCR (ddPCR) has been
shown to be especially useful and practical for the
quantification of target nucleic acids (Oxnard et al.
2014).
Comparative genomic hybridization, and more
recently, NGS genomic profiling of tumor tissue have
been used to identify cancer associated somatic genomic alterations (Gagan & Van Allen 2015). Genomic
information about cancer is listed in several national
and international cancer genome resources, including
The Cancer Genome Atlas (Grade et al. 2015) and the
International Cancer Genome Consortium (ICGC). The
ICGC has mapped genomic, transcriptomic, and epigenetic changes in numerous types of tumors, which have
been used to develop more precise clinical laboratory
tests to detect and treat cancers (ICGC 2016). Figure 1
shows patterns of chromosomal aberrations in solid
tumors (Grade et al. 2015). It shows the most common
gains and losses in colon, rectal, cervical, bladder,
NSCLC, and breast cancer. The prevalence of specific
genomic imbalances is unique to each tumor type.
Plasma DNA tissue mapping has become possible using
genome-wide methylation sequencing. This general
approach is useful to assess the tissue contribution to
the circulating cell-free DNA (cfDNA) pool (Sun et al.
2015).
Cancer genomics data have facilitated a revolution in
oncology drug discovery by identifying candidate drug
targets for use in trials that target clinically relevant
driver mutations or molecular features. This has allowed
the development of modern oncology treatments,
which focus on identifying the therapy most appropriately matched to a particular patient’s genetic profile.
So far, however, the success and clinical benefit of personalized cancer care have been limited (Tannock &
Hickman 2016). A major challenge is the fact that there
is only partial inhibition of signaling pathways by
molecular-targeted agents. In addition, combinations of
such agents may be too toxic (Tannock & Hickman
2016). An alternative promising approach is immunotherapy, particularly with checkpoint inhibitors (Maus
et al. 2014). Some such immunotherapies can be combined with other anticancer agents (Zugazagoitia et al.
2016). Personalized combination strategies can be
envisaged.
For routine application, non-invasive molecular monitoring tools, such as circulating cell-free tumor DNA
(ctDNA), seem to be useful to assess the effectiveness
of these new precision cancer treatment strategies.
Blood-based tumor genomic profiling was therefore
chosen to demonstrate the potential of these emerging
technologies to support personalized cancer care.
Genotype-directed cancer care
Pharmacogenomics facilitates the identification of biomarkers that are useful to optimize drug selection,
dose, and treatment duration and avoid adverse drug
reactions (Wang et al. 2011).
Table 1 lists some pharmacogenomic biomarkers in
US Food and Drug Administration (FDA) approved
oncology drug labeling (FDA 2016). Two genomes are
involved: the somatic genome of the tumor and the
germline genome of the patient. The tumor genome
plays a critical role in the variation in response to antineoplastic therapy. Biomarkers from the tumor genome
include EGFR, KRAS, BRAF, and others that are already
being routinely determined in biopsy specimens. There
are also biomarkers, which are related to drug metabolism. For example, germline single nucleotide polymorphisms (SNPs) in the gene encoding the enzyme TPMT
can result in increased sensitivity to mercaptopurines
€tz et al. 1993). These pharmacogenetic tests are
(Schu
already considered part of routine oncologic care.
The first example of a targeted therapy, imatinib, is a
tyrosine kinase inhibitor (TKI) that has been successfully
used for the treatment of patients with chronic myeloid
leukemia (CML) and gastrointestinal stromal tumors
(GIST). CML presents an estimated incidence of
1/100,000 cases per year, which accounts for 15–20% of
leukemias (Koshiyama et al. 2013). The annual ageadjusted incidence of GIST averaged 6.8 per 1,000,000
(Coe et al. 2016). Imatinib is a potent selective inhibitor
of the BCR-ABL tyrosine kinase present in CML. BCR-ABL
tyrosine kinase is constitutively activated in the oncogenic fusion protein BCR-ABL (BCR ¼ “Breakpoint Cluster
Region”), causes anti-apoptotic effects and stimulates
proliferation (McDermott et al. 2011). BCR-ABL is a clonal
driver mutation, expressed at high levels only in leukemic cells. While pre-imatinib therapy was associated
with a poor prognosis, the current overall five-year survival rate for newly diagnosed chronic-phase CML
patients treated with imatinib is 89% (McDermott et al.
2011). For imatinib, the therapeutic target is BCR-ABL
tyrosine kinase. A biomarker of major molecular
response (MMR) is the BCR-ABL transcript concentration
measured in peripheral blood cells to predict clinical
response. A MMR is defined as a three or more log
reduction of BCR-ABL1 transcript levels of a standardized baseline (<0.1 in the International Scale), which is
CRITICAL REVIEWS IN CLINICAL LABORATORY SCIENCES
3
Figure 1. Patterns of chromosomal aberrations in solid tumors. (Grade et al. 2015. # Springer International Publishing
Switzerland 2015. With permission of Springer.).
associated with a favorable progression-free survival
(PFS) (Machado et al. 2011). Another biomarker of
response is the complete cytogenetic response, which
is defined as absence of Philadelphia-positive marrow
cell metaphases (Baccarani et al. 2009). The Philadelphia
chromosome is a changed chromosome 22, due to
fusion of BCR region of chromosome 22 and ABL1
proto-oncogene of chromosome 9. In more than 90% of
CML cases, the presence of the Philadelphia chromosome can be detected (Koshiyama et al. 2013). With
4
M. OELLERICH ET AL.
Table 1. Anticancer drugs and their pharmacogenomic biomarkers.
Biomarker with pharmacodynamic effect
(drug target)
Somatic genome of the tumor
EGFR
ALK
ROS-1
HER2 (ERBB2)
ESR1
AR
BRAF
BCR-ABL1
c-KIT
Germline genome of the patient
TPMT
UGT1A1
DPYD
Associated drug
Erlotinib, gefitinib, afatinib, osimertinib
Crizotinib, ceritinib, alectinib
Crizotinib
Lapatinib, trastuzumab, ado-trastuzumab
emtansine
Exemestane, anastrozole, letrozole, tamoxifen
Enzalutamide
Vemurafenib, dabrafenib, trametinib, cobimetinib,
pembrolizumab, nivolumab
Imatinib, dasatinib, nilotinib
Imatinib
Mercaptopurine, thioguanine
Irinotecan, nilotinib
Fluorouracil
Tumor type
NSCLC
NSCLC
NSCLC
Breast cancer
Breast cancer
Prostate cancer
Melanoma
Chronic myeloid leukemia
Gastrointestinal stromal tumor
Acute lymphatic leukemia (ALL)
Colorectal cancer
Colorectal, gastric, pancreatic, breast, esophageal,
head and neck cancer
From: McDermott et al. 2011; Zugazagoitia et al. 2016; FDA 2016.
imatinib, there is the particular advantage in that the
genetic biomarker is present in a high proportion of
CML patients and, therefore, allows for the treatment of
a group rather than only individual patients (Tannock &
Hickman 2016). Trough imatinib plasma concentrations
determined by liquid chromatography tandem mass
spectrometry (LC–MS/MS) can be used to rule out
pharmacokinetic causes of treatment failure (Picard
et al. 2007).
Another example of successful genotype-directed
cancer care is the use of gefitinib (another TKI) in
patients with NSCLC (Wang et al. 2011). Lung cancer
is a leading cause of cancer related death, with 1.6
million cases worldwide and 85% of all lung cancer
cases have NSCLC (Sandelin et al. 2015). The tumor
genome using biopsy specimens was shown to play
an important role in this differential response to
approved EGFR TKIs. Tumor EGFR encoding activating
mutations within the kinase domain result in
enhanced tumor sensitivity to gefitinib. The presence
of the EGFR sensitizing mutations (L858R or exon 19
deletion) is a selection criterion for the use of EGFR
TKIs including gefitinib, erlotinib, and afatinib. The initial patients treated with gefitinib and erlotinib identified with these mutations in their tumor biopsies
were found only retrospectively to have better clinical
responses than did patients without these mutations.
Studies involving afatinib in EGFR mutant NSCLC had
prospective tumor assessment for these sensitizing
mutations. Adenocarcinoma (ADC), which is among
the most common of the NSCLC histological subtypes,
has been shown to be associated with activating
mutations in the EGFR gene in 13% of European and
47% of Japanese patients (corresponding rates for
non-ADC are 5% and 7%, respectively) (Reck et al.
2016). Additionally, patients who had these mutations
but who more slowly metabolized gefitinib were
shown to likely have better PFS (Widmer et al. 2014).
The use of imatinib and EGFR TKI gefitinib is two
examples of successful genotype-directed cancer care.
Another example comes from a study by the Lung
Cancer Mutation Consortium testing for driver mutations in metastatic lung ADCs at 14 centers (Kris et al.
2014). In 64% of lung ADCs, actionable drivers were
detected. Individuals with oncologic drivers receiving a
matched targeted agent lived longer (median survival
3.5 years), compared to patients who did not receive
genotype-directed therapy (median survival 2.4 years).
Liquid biopsy tumor genomic profiling and tissue
biopsy-based approaches
While both fresh and archived biopsy material was and
still is commonly used for solid tumor genomic profiling, there are many limitations to biopsies including
their limited availability, repeatability, and high failure
rates (Mao et al. 2015); 10–50% of all biopsies fail to
obtain sufficient tumor tissue. One often underestimated problem is tumor heterogeneity. There are also
often real or perceived risks prohibiting patients from
undergoing biopsies. Tumors can be located in difficult
or dangerous locations to access, but even when in
accessible locations, biopsies are associated with risks,
inconvenience, and major costs; especially when they
need to be done repeatedly such as to monitor for the
development of resistance to targeted therapies.
Recently, less invasive, blood-based tumor genomic
profiling methods using either circulating tumor cells
(CTCs) or ctDNA are being investigated as a way to
overcome these limitations (Oxnard et al. 2014). For
example, in a systematic review of 25 studies it was
concluded that blood is a good substitute when tissue
CRITICAL REVIEWS IN CLINICAL LABORATORY SCIENCES
is insufficient for testing EGFR mutations to guide EGFR
TKIs treatment (Mao et al. 2015), where cfDNA seems
more sensitive compared to CTCs (Freidin et al. 2015).
Serial ctDNA measurements are being used as a form
of “liquid biopsy” to monitor responses and to detect
both relapses as well as drug resistance during treatment (McDermott et al. 2011). The methods involve as
the first step identification and quantification of the
specific somatic genomic alterations by sequencing
either tumor tissue or the ctDNA isolated from plasma.
Repeated measurement of these mutations in ctDNA
can then be used to monitor response and early detection of cancer relapse (Figure 2).
In an additional study, repeated ctDNA sampling was
used as a form of “liquid biopsy” to detect resistance
mutations up to 16 weeks before radiographic evidence
of tumor progression (Oxnard et al. 2014). Another indication of the potential value of ctDNA monitoring is the
fact that in May 2016 the US FDA approved the first
such “liquid biopsy” test (CobasV EGFR Mutation Test
v2) for patients with NSCLC.
R
Origin of ctDNA and quantification techniques
Various techniques that have been described for the
quantification of ctDNA (Diehl et al. 2005; Oxnard et al.
2014; Freidin et al. 2015; Sandelin et al. 2015; Zugazagoitia
et al. 2016) are summarized in Table 2. In the nucleus of a
cell, the DNA is wound around histones, forming nucleosomes (Jorde et al. 2010). As cells undergo apoptosis or
necrosis, these nucleosomes are released into the blood
stream and circulate freely in the plasma. The DNA seems
to be present in the circulation largely in the form of
nucleosomes, or in apoptotic vesicles (Mouliere et al.
2013). Because apoptosis leads to high inter-nucleosomal
DNA fragmentation, fragments as small as 158–200 base
pairs (the length of a mononucleosome DNA) may be
found following apoptosis. Necrosis on the other hand
results in larger ctDNA fragments, larger than 10,000 base
pairs (bp). Estimation of ctDNA fragmentation might be
able to provide evidence as to the cfDNA release mechanism involved. The half-life of ctDNA in plasma is very short,
less than 1.5 h (Lo et al. 1999). The liver, spleen, and kidney are presumably involved in this rapid cfDNA removal
(Lo et al. 1999). As tumors become more aggressive, the
degree of necrosis increases and the absolute amount of
circulating mutant DNA correspondingly increases.
Clinical studies on ctDNA tumor genomic
profiling
Detection of EGFR acquired resistance mutation
One of the most promising uses of ctDNA as a
liquid biopsy is monitoring for the development of
5
acquired resistance. Genetically acquired resistance
commonly occurs even with the most successful, personalized targeted therapies as a result of solid tumor
heterogeneity that selects for resistant tumor cells.
ctDNA has been shown to be especially useful for
detection of resistance because of the many previously
mentioned limitations of biopsies (Murtaza et al. 2013).
A schematic presentation of the methods used is shown
in Figure 3.
Non-invasive detection of acquired resistance to cancer therapy has been shown to be possible by repeated
sampling of plasma ctDNA, representing a non-invasive
“liquid biopsy”. In a study published by Murtaza et al.
(Murtaza et al. 2013), an analysis of mutations in circulating plasma cfDNA over time using exome sequencing
allowed for the identification of specific resistance
mutations. For example, the mutant allele frequency
significantly increased following treatment in a NSCLC
patient. Of particular interest was a resistance conferring mutation in EGFR (T790M) that had an increase of
13% in allele frequency following treatment with gefitinib. This mutation inhibits binding of gefitinib to EGFR;
causing resistance to gefitinib (Murtaza et al. 2013).
Now, in such cases, the patient can be switched to an
alternative therapy with osimertinib (AZD 9291). This is
a newer oral, irreversible, mutant-selective EGFR TKI
with potency against NSCLC cells harboring the EGFR
T790M resistance mutation (Thress et al. 2015).
Such serial analysis of plasma ctDNA can complement or even replace the invasive biopsy approaches
currently being used to identify acquired drug resistance mutations in patients with advanced cancers. This
would have major implications both for patients’ survival and quality of life, as well as for the costs of care
(Tie & Gibbs 2016). In Germany, TKI treatment costs per
day are 96 EUR for erlotinib and 150 EUR for gefitinib.
The costs per plasma ctEGFR PCR test is about 200 EUR
and the costs per tumor biopsy tissue EGFR testing
varies between 200 and 400 EUR, depending on the
method used. It is evident that the diagnostic costs are
comparatively small compared to the treatment costs.
Ineffective use of these expensive TKIs can be avoided
by ctDNA testing, resulting in substantial cost savings.
Being able to identify non-responders would avoid
unnecessary further treatment of such patients, thereby
avoiding treatment-related toxicity, unnecessary costs,
and potentially allowing a switch to an alternative
effective therapy.
The use of ctDNA to sequentially monitor specific
tumor SNP mutations associated with resistance has
been described in a study of patients with EGFR mutant
NSCLC receiving erlotinib (Oxnard et al. 2014). An
increase in plasma ctDNA containing both the L858R
6
M. OELLERICH ET AL.
Figure 2. ctDNA as a form of liquid biopsy. (From McDermott et al. 2011. Copyright # 2011 Massachusetts Medical Society.
Reprinted with permission from Massachusetts Medical Society.).
and T790M mutations was already observed in one
patient before new brain metastases were detected
(Oxnard et al. 2014). Later, decreased plasma ctDNA levels were seen when treatment was initiated with a new
medication as part of a clinical trial. A simultaneous
decrease in the plasma tumor genotype was associated
with objective tumor shrinkage. In a second patient, the
plasma L858R mutation decreased when the patient’s
pleural drainage resolved and a computed tomography
(CT) scan indicated stable disease.
CRITICAL REVIEWS IN CLINICAL LABORATORY SCIENCES
7
Table 2. Techniques for quantification of ctDNA.
Next-generation sequencing (NGS)
– NGS gene panels (e.g. hybrid capture-based)
– Whole genome sequencing (low coverage)
Droplet digital PCR (ddPCR)
Quantitative allele-specific, real-time
PCR (Idylla)
Competitive allele-specific TaqMan PCR
(cast-PCR)
Allele-specific PCR
Coamplification at lower denaturation
temperature (COLD)-PCR
BEAMing assay
Murtaza et al. 2013
Zugazagoitia et al. 2016
Sch€
utz et al. 2015
Oxnard et al. 2014
L"opez et al. 2016
Thress et al. 2015
Gao et al. 2010
Janku et al. 2016
Ashida et al. 2016
Sandelin et al. 2015
Freidin et al. 2015
Diehl et al. 2005
Figure 3. Schematic description of resistance monitoring to detect mutations associated with resistance. (Reprinted by permission
from Macmillan Publishers Ltd: Nature, Murtaza et al. 2013, copyright 2013).
Another two patients from this study (Oxnard et al.
2014) exhibited a plasma response on first-line erlotinib,
but later increasing plasma levels of the EGFR sensitizing mutation were detected; about 12–25 weeks before
progression was assessed using the Response
Evaluation Criteria in Solid Tumors (RECIST). In each of
these two patients, the plasma T790M mutation could
also be identified at progression, generally at somewhat
lower levels than the EGFR sensitizing mutation.
Targeted NGS and ddPCR have also been successfully used for the analysis of acquired resistance
to newer EGFR TKIs. Osimertinib is an oral, irreversible, mutant selective EGFR TKI with potency against
NSCLC cells harboring the EGFR T790M resistance
mutation (Thress et al. 2015). The estimated PFS
after use of this drug is about 10 months in
patients with the T790M mutation. Patients may,
however, acquire the EGFR C797S mutation which
8
M. OELLERICH ET AL.
mediates resistance to osimertinib (Thress et al.
2015).
Another example of the ability of targeted plasma
NGS to detect resistance mutations at the time of systemic progression is illustrated by results obtained in a
patient who acquired resistance to osimertinib mediated by the EGFR C797S mutation (Figure 4) (Thress
et al. 2015). In this patient targeted NGS identified
an acquired mutation (in 1.3% of reads) encoding EGFR
C797S at the time of progression. The T790M mutation
had decreased from 3.3% baseline to 1.8% during
progression.
In this study of 15 patients treated with osimertinib,
who were all positive for the T790M mutation, three
molecular subtypes emerged: 6 patients acquired the
C797S mutation, 5 maintained the T790M mutation but
did not acquire the C797S mutation, and 4 lost the
T790M mutation despite the presence of the underlying
EGFR activating mutation (Thress et al. 2015). This tumor
genome monitoring study illustrates both the diversity
of resistance mechanisms and the potential of ctDNA
serial analysis to identify and monitor for the presence
of such mechanisms.
denaturation temperature (COLD)-PCR assays, highresolution melt analysis (HRM), and commercial assays
including the Cobas KRAS mutation test and the
Therascreen pyrosequencing KRAS kit. The diagnostic
sensitivity and specificity of KRAS mutation detection
achieved with ctDNA was 0.96 and 0.95, respectively,
which was higher than for CTC DNA (0.52 for sensitivity
and 0.88 for specificity).
Plasma ctDNA monitoring has also been studied in
colorectal cancer patients with the KRAS G12V mutation
"pez et al. 2016). Measurement of ctDNA using ddPCR
(Lo
was used to look for the KRAS G12V mutation in 10
colorectal cancer patients and 6 healthy controls. The
mutation was detected in 9 of 10 patients and the
median number of copies per ml was significantly elevated in the colorectal cancer patients; with the highest
values seen in patients with metastatic disease. While
demonstrating that the KRAS G12V mutation was
detectable in the plasma of the majority (9/10) of these
colorectal cancer patients using ddPCR, the one false
negative raises the possibility that there may not be
sufficient cfDNA to be detected in some colorectal
cancer patients; possibly those at the earliest stages of
the disease.
Pancreatic ductal adenocarcinoma (PDAC) has one of
the lowest survival rates of all cancers and there is a
lack of personalized treatment options because biopsies
are often inadequate for molecular characterization. Zill
et al. (2015) studied ctDNA by sequencing in 17 patients
with PDAC or biliary carcinoma and compared matched
sequencing tests from tumor biopsies and plasma
cfDNA. These authors showed that 90.3% of mutations
detected in biopsies were also detected in ctDNA.
Across five informative genes (KRAS, TP53, APC, FBxW7,
SMAD4), the diagnostic accuracy of ctDNA was 97.7%
with a sensitivity of 92.3% and a specificity of 100%.
They concluded that ctDNA sequencing reliably
detected tumor-derived mutations and could pave the
way for precision oncology approaches to the treatment
of PDAC.
ctDNA monitoring in cancer patients with KRAS
mutation
ctDNA monitoring in melanoma patients with
BRAF mutations
KRAS mutations are responsible for resistance to EGFRtargeted antibody therapy with cetuximab or panitumu"pez et al. 2016). A recent study (Freidin et al.
mab (Lo
2015) reported that ctDNA outperformed the use of
CTCs for the detection of the KRAS mutation in patients
with thoracic malignancies. This study included 82
patients with lung cancer, and 11 with benign diseases
of the lung. Various molecular tests were used, including custom designed co-amplification at lower
The prognostic value of BRAF mutation-positive cfDNA
was also investigated in patients with melanoma
(Santiago-Walker et al. 2016). Although it comprises less
than 2% of skin cancers, melanoma is responsible for
the largest number of skin cancer-related deaths (9940
annually in the USA). BRAF mutations are observed in
approximately 50% of melanoma tumor tissue samples.
In this study (Santiago-Walker et al. 2016), 732 patients
with BRAF V600 mutation-positive melanoma, most
Figure 4. Acquired resistance to osimertinib (AZD 9291) mediated by EGFR C797S mutation. (Reprinted by permission from
Macmillan Publishers Ltd: Nature Medicine, Thress et al. 2015,
copyright 2015).
CRITICAL REVIEWS IN CLINICAL LABORATORY SCIENCES
treated with dabrafenib were evaluated. A comparison
between plasma ctDNA determined by BEAMing (Beads,
Emulsion, Amplification, and Magnetic) technology and
analysis of tumor PCR BRAF mutation status showed
that the BRAF mutation was detectable using ctDNA in
76% and 81% of late-stage patients with BRAF V600Eand V600K-positive tumors, respectively. Also, patients
with BRAF mutation-positive tumors, but negative for
BRAF-mutant ctDNA at baseline, had longer PFS and
overall survival compared to patients with a positive
ctDNA result. These results suggest that ctDNA alone,
while of some prognostic value, may not be suitable as
the principal screening method for patients with
unknown BRAF mutation status.
Another recent study (Ashida et al. 2016) investigated the relationship between BRAF V600E ctDNA and
melanoma progression in a 46-year old patient who
had no recurrence for five years after radical surgery. In
order to quantify small amounts of the mutant allele,
both BRAF V600E ctDNA copies per ml and the ctDNA
fraction were determined using competitive allele-specific TaqMan PCR with allele-specific blockers added to
suppress amplification of the wild type (WT) allele.
Between day 0 and day 91 of the study period, ctDNA
was not detected and a CT scan on day 54 revealed no
metastases. After day 91, there was a major increase of
ctDNA. Multiple metastases were detected in the pleural
cavity at day 180 and the patient died on day 343. The
increase in BRAF V600E ctDNA preceded the CT diagnosis, suggesting that ctDNA may be useful for monitoring
such patients.
ctDNA monitoring in patients with metastatic
breast cancer
A trial at the Cambridge Cancer Research Center compared the use of ctDNA, CA 15–3 (Cancer-Antigen 15–3)
and CTCs to monitor 30 metastatic breast cancer patients
(Dawson et al. 2013). Detection rates in women with
somatic genomic alterations were 97% with ctDNA, 78%
with CA 15–3, and 87% with CTCs. The ctDNA also
showed a greater correlation with tumor burden and
was the earliest measure of treatment response.
In this same study (Dawson et al. 2013), these
authors sequentially measured six separate point mutations; all of which showed similar but somewhat different dynamic patterns. There was a decrease in
mutations detected in patients with stable disease on
epirubicin treatment, but with disease progression there
was a strong increase in mutations that persisted after
the patient was switched to paclitaxel.
The comparison of the ctDNA, CA 15–3, and CTCs
results in one patient from this study (Figure 5)
9
Figure 5. Comparison of biomarkers to monitor metastatic
breast cancer tumor dynamics. (From Dawson et al. 2013.
Copyright # 2013 Massachusetts Medical Society. Reprinted
with permission from Massachusetts Medical Society.).
illustrates the ability of these three methods to monitor
individual tumor dynamics. The patient was treated
with capecitabine, vinorelbine, and epirubicin. The
ctDNA changes reflected partial response, progressive
disease, and stable disease very well. The number of
CTCs also decreased significantly during stable disease
and both ctDNA and CTCs had significant increases
with disease progression. On the other hand, CA 15–3
showed no consistent serial changes and had only a
low correlation (r2 ¼ .36) with ctDNA. Finally, increasing
ctDNA levels were significantly associated with poor
overall survival in this study (Dawson et al. 2013).
One potential benefit of using CTCs is their DNA
integrity; their DNA can be extracted from viable intact
cells, whereas ctDNA is fragmented and partially
degraded. However, tumor heterogeneity may be a
major drawback to the use of CTCs because the CTCs
isolated may not adequately represent the entire tumor
population. The higher sensitivity and specificity of the
ctDNA found in this study suggests that it may be more
representative of primary tumor tissue than DNA
extracted from CTCs. If so, ctDNA would be the preferred substrate for “liquid biopsy” tumor monitoring.
While not yet a conventional clinical practice, many
completed and ongoing trials have and are examining
this possibility.
Garcia-Murillas et al. (Garcia-Murillas et al. 2015)
speculated in a recent article that monitoring ctDNA
serially, over multiple time-points, may be superior to a
single time-point at judging risk of relapse. This possibility may have an impact on how future ctDNA studies
are designed. Overall, given the high likelihood of
relapse when ctDNA is detected, these findings lay the
groundwork for future clinical studies that can be
designed to test the intensification of adjuvant therapy
options in breast cancer with detectable ctDNA at the
10
M. OELLERICH ET AL.
completion of definitive treatment for non-metastatic
disease. This may be complementary to other prognostic features, such as residual cancer in the resected specimen following neoadjuvant chemotherapy.
Acquired ESR1 mutations are a major mechanism of
resistance to aromatase inhibitors (AIs). Schiavon et al.
(Schiavon et al. 2015) developed ultra-high sensitivity
multiplex digital PCR assays for the detection of ESR1
mutations in ctDNA and investigated the clinical relevance of these mutations in 171 women with advanced
breast cancer. ESR1 mutations were found only in estrogen receptor-positive breast cancer patients previously
exposed to AIs. Patients with ESR1 mutations had a substantially shorter PFS on subsequent AI-based therapy.
ESR1 mutations can be identified with ctDNA analysis
and predict resistance to subsequent AI therapy
(Schiavon et al. 2015).
Chromosomal aberration pattern analysis by low
coverage whole genome sequencing
In contrast to SNP-based applications discussed so far,
chromosomal aberration pattern analysis is a more uni€tz
versal approach based on genomic instability (Schu
et al. 2015). With the availability of NGS, it was recently
shown for the first time that this technology can be
applied to cfDNA for quantitative analyses of genomic
patterns (Beck et al. 2009). After having defined the
cfDNA genomic profile in healthy individuals, the same
group showed for the first time that the method can be
used to detect differences between the cfDNA profile in
cancer patients compared to apparently healthy individuals (Beck et al. 2010). The first step in this method is to
construct a whole genome sequencing library from
ctDNA. After sequencing, the mapped reads are
counted in windows along the chromosomes (25,000
reads per window, 700 windows total). The copy number instability (CNI) score is generated by statistical
comparisons to the normal population and is a general
measure of genomic instability directly related to the
regional chromosomal DNA ploidy. Genomic instabilities reflected as CNI often occur in malignant tumors.
€tz et al. 2015), it was shown
In a recent study (Schu
that ctDNA can be used as a diagnostic tool in prostate
cancer. Patients with prostate cancer could be discriminated with a diagnostic accuracy of 83% from controls
and 90% from patients with benign hyperplasia or prostatitis. Prostate cancer patients showed significantly
more regional copy number imbalances (DNA ploidy
heterogeneity) compared to healthy controls. Figure 6
shows a genome wheel with regions of genomic
instability of cfDNA identified in prostate cancer. The
outer circle depicts all preselected regions. The inner
circle depicts the 20 regions selected for calculating the
CNI index. The authors recommended adjusting CNI for
copy number variations of the individual patient’s white
blood cells. The CNI index (determined in cfDNA by
ploidy heterogeneity) in this study discriminated well
between 204 patients with prostate cancer (Gleason
score 2–10), 207 male controls, 10 patients with benign
hyperplasia, and 10 patients with prostatitis. However,
perhaps surprisingly, no separation was observed in the
CNI index on the basis of the Gleason score, which
would be required to allow differentiation between
aggressive and indolent prostate cancer. It appears that
cfDNA sequencing may better reflect the genomes of
all cancer sub-clones present in a patient. While these
are still preliminary results, it appears that the CNI index
using liquid biopsy analysis could provide information
of substantial value in the future for the selection of
therapeutic regimens. One hypothesis that needs to be
examined further is whether repeated CNI determinations or sequencing would improve the diagnostic discrimination of such testing.
Azad et al. (2015), in a study in 62 patients with
metastatic castration-resistant prostate cancer (mCRPC)
progressing on abiraterone and enzalutamide treatment, demonstrated that androgen receptor (AR) gene
aberrations in cfDNA were associated with therapeutic
resistance. Chromosome copy number analysis and AR
exon 8 sequencing was performed on cfDNA. AR gene
aberrations were seen in 50% of patients. Enzalutamide
resistance was linked to AR amplification and pretreatment AR aberration was predictive of adverse
outcomes.
In addition to AR gene copy gains, point mutations
occur and recently it was recognized that exon deletions during transcription (splice variants) lead to various truncated isoforms of AR. Notably and most
importantly: defective transcription of the C-terminal
ligand binding domain of AR resulted in a constitutive
AR activation. Variant 7 or AR-V7 were detectable by the
presence of their plasma-derived exosomal RNA using
ddPCR. The truncated AR is resistant to all AR inhibitors,
and its occurrence can be detected in patients’ plasma
(Del Re et al. 2017).
Changes in CNI score were also found to predict
therapeutic response in 24 patients with a number of
metastatic cancers (Figure 7) including advanced
esophageal cancer (N ¼ 2), colorectal cancer (N ¼ 3),
non-Hodgkin lymphoma (N ¼ 3), PDAC (N ¼ 4), and
NSCLC (N ¼ 12). Treatment response to chemotherapy
was recorded by RECIST 1.1 (Eisenhauer et al. 2009) or
EORTC (European Organization for Research and
Treatment of Cancer) PET/CT criteria. CNI changes were
considered predictive of either response or stable
CRITICAL REVIEWS IN CLINICAL LABORATORY SCIENCES
11
Figure 6. Genome wheel showing regions of genomic instability as basis of cfDNA prostate cancer biomarkers. Outer circle: all
regions, inner circle: selected regions for copy number instability index. Copy-number loss (red), gains (green). (Republished with
permission of American Association for Clinical Chemistry Inc., from Schu€tz et al. 2015; permission conveyed through Copyright
Clearance Center, Inc.) (refer online version for color figure).
disease when there was a reduction of CNI score "50%
relative to baseline. For at least 15 patients, CNI change
predicted response about 3–8 weeks prior to scan
results demonstrating response or progressive disease.
In responders, significantly lower CNI values were
observed compared to patients with disease progression. It was concluded that CNI change may serve as a
predictor (potentially early predictor) of therapeutic
response to standard chemotherapy for the investigated cancer types (Weiss et al. 2016).
Immunotherapy is an especially exciting new area for
personalized therapy and diagnostics (Maus et al. 2014;
Zugazagoitia et al. 2016). Immune checkpoint antibodies targeting negative regulatory molecules such as
Programmed Cell Death Protein 1 (PD1) and Cytotoxic
T-cell Lymphocyte/associate antigen 4 (CTL4) can be
used to “release the brakes on natural T-cells responsive
to tumor” (Maus et al. 2014). In a recent study (Weiss
et al. 2016), it was shown that CNI scores predicted
therapeutic responses to immunotherapy in 24 patients
with various types of cancer. Patients were treated with
either interleukin-2 alone or with a PD-1 inhibitor with
or without chemotherapy. The CNI change from baseline is shown in Figure 8. Patients with stable disease or
partial response by RECIST 1.1 showed a decreased CNI
score, whereas the CNI score was distinctly increased in
patients with disease progression. Meanwhile, other
independent studies have used a similar approach of
exploring copy number alteration in plasma (Chan et al.
2013; Heitzer et al. 2013; Heitzer et al. 2013).
Remaining challenges for routine clinical
application of ctDNA monitoring
For the routine use of ctDNA, specialized personnel and
specific instrumentation (NGS, ddPCR) is necessary.
External quality control programs also have to be established for quality management and specific laboratory
software and bioinformatics are necessary for the use of
NGS. For SNP-based assays, recent findings indicate that
the output from genetic testing can differ markedly,
depending on which genetic test is applied (Kuderer
12
M. OELLERICH ET AL.
Conclusions
Figure 7. Changes in copy number instability score (CNI) predict therapeutic response in metastatic cancers. 24 patients:
esophageal cancer (n ¼ 2); colorectal cancer (n ¼ 3), nonHodgkin lymphoma (n ¼ 3), pancreatic ductal adenocarcinoma
(PDAC; n ¼ 4); non-small cell lung cancer (n ¼ 12). SD: stable
disease; PR: partial response; CR: complete response.
Advances in both the understanding of tumor biology
and the availability of advanced but practical technology
have made it possible to use tumor genomic information
to rapidly and reliably identify effective treatment targets. The recent progress in this field also allows for both
prediction and monitoring of individual responses to
specific treatments or drug concentrations, as well as to
detect and even target some of the causes of drug resistance. The initial proof of concept studies used tumor
biopsy material, but the many limitations of biopsies
prompted the successful, and in some ways superior, use
of less invasively obtained sources of tumor DNA including ctDNA. The use of ctDNA has been validated as a
useful, non-invasive source of genetic material that can
be used as a diagnostic tool for guiding personalized
“precision” cancer therapy. Both specific SNP-based and
a more universal approach, chromosomal aberration pattern analysis, have been shown to be predictive of treatment response, tumor recurrence, and the development
of resistance. It is to be expected that ctDNA-based
assays will be helpful to develop new diagnostic strategies to overcome some of the current limitations of personalized cancer medicine.
Disclosure statement
Figure 8. Copy number instability scores (CNI) to predict
therapeutic response to immunotherapy. Diagnosis: PDAC
(n ¼ 3), ovarian cancer (n ¼ 1), lung ADC (n ¼ 2), small cell
lung cancer (n ¼ 2), renal cell carcinoma (n ¼ 2), melanoma
(n ¼ 4), colorectal ADC (n ¼ 3), sarcoma (n ¼ 1), breast cancer
(n ¼ 3), gastric ADC (n ¼ 1), adeno-gastro-esophageal junction
ADC (n ¼ 1). Interleukin-2 or PD-1 inhibitor with or without
chemotherapy. SD: stable disease; PR: partial response; CR:
complete response.
et al. 2016). Significant discordance has also been noted
between reports comparing tissue-based NGS tests.
Further in-depth comparisons of NGS tests across larger
numbers of patients with cancer are warranted to
improve concordance and clinical utility. For proper
interpretation of genomic results and their use to guide
clinical decisions, expert multidisciplinary cooperation is
essential. Further validation in multicenter outcome
studies is important as the clinical benefit of ctDNA testing regarding better patient outcomes remains to be
proven (Tie & Gibbs 2016).
In accordance with Taylor & Francis policy and our ethical
obligations as researchers, we are reporting all financial or
business interests and all funding from any company that
may be affected by the research reported in the enclosed
paper. We have disclosed those interests fully to Taylor &
Francis, and we have in place an approved plan for managing any potential conflicts arising from that involvement.
M.O. has declared Scientific Advisory Board participation and
consultancy fees from Chronix Biomedical, San Jos"
e, USA, a
research and development company. Chronix Biomedical was
involved in cfDNA measurements (CNI score). E.S. has
declared employment by Chronix Biomedical GmbH, a
research and development company that was involved in
cfDNA measurements (CNI score). J.B. has declared employment by Chronix Biomedical GmbH, a research and development company that was involved in cfDNA measurements
(CNI score). P.K. has no conflicts of interest. N.P.P. has financial interest in Chronix Biomedical. G.J.W. has been a consultant for Pharmatech, Paradigm, Blend Therapeutics, and
Viomics. He has been on the Speaker’s bureau for Medscape,
Novartis, and Merck and received travel/accommodations
from NantWorks. P.D.W. was previously a paid consultant to
Chronix Biomedical GmbH, which owns patents on some of
the technology mentioned.
Funding
Chronix Biomedical [cfDNA measurements].
CRITICAL REVIEWS IN CLINICAL LABORATORY SCIENCES
ORCID
Michael Oellerich
Philipp Kanzow
Philip D. Walson
http://orcid.org/0000-0002-9255-2261
http://orcid.org/0000-0002-2169-561X
http://orcid.org/0000-0002-9566-8024
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