Editorial
`
`Potential clinical utility of ultrasensitive
`circulating tumor DNA detection with
`CAPP-Seq
`
`Expert Rev. Mol. Diagn. 15(6), 715–719 (2015)
`
`Scott V Bratman
`
`Department of Radiation
`Oncology, University of Toronto,
`Toronto, Ontario, Canada
`
`Aaron M Newman
`
`Division of Oncology,
`Department of Medicine and
`Institute for Stem Cell Biology
`and Regenerative Medicine,
`Stanford University, Stanford,
`California, USA
`
`Ash A Alizadeh
`
`Author for correspondence:
`Division of Oncology,
`Department of Medicine and
`Institute for Stem Cell Biology
`and Regenerative Medicine,
`Stanford University, Stanford,
`California, USA
`arasha@stanford.edu
`
`Maximilian Diehn
`
`Author for correspondence:
`Department of Radiation
`Oncology, Stanford Cancer
`Institute, and Institute for Stem
`Cell Biology and Regenerative
`Medicine, Stanford University,
`Stanford, California, USA
`diehn@stanford.edu
`
`Tumors continually shed DNA into the circulation, where it can be noninvasively
`accessed. The ability to accurately detect circulating tumor DNA (ctDNA) could
`significantly impact the management of patients with nearly every cancer type.
`Quantitation of ctDNA could allow objective response assessment, detection of
`minimal residual disease and noninvasive tumor genotyping. The latter application
`overcomes the barriers currently limiting repeated tumor tissue sampling during
`therapy. Recent technical advancements have improved upon the sensitivity,
`specificity and feasibility of ctDNA detection and promise to enable innovative
`clinical applications. Here, we focus on the potential clinical utility of ctDNA
`analysis using CAncer Personalized Profiling by deep Sequencing (CAPP-Seq), a
`novel next-generation sequencing-based approach for ultrasensitive ctDNA
`detection. Applications of CAPP-Seq for the personalization of cancer detection
`and therapy are discussed.
`
`We are in the middle of a revolution in
`molecular oncology that is allowing for
`increasingly personalized management of
`cancer patients. The individualization of
`cancer care will rely on the development
`of effective targeted therapeutics as well
`as biomarkers for selecting the appropri-
`ate treatments and evaluating their effec-
`tiveness. To aid with complex decision
`making in clinics,
`improved tools are
`needed to accurately measure disease
`burden, assess prognosis and predict
`response to targeted therapies.
`Circulating tumor DNA (ctDNA) has
`emerged as a promising cancer biomarker
`because it provides noninvasive access to
`cancer DNA. Distinct from circulating
`tumor cells (CTCs), ctDNA is cell-free
`and can be collected from peripheral
`blood plasma, urine or other bodily flu-
`ids. Although more
`comprehensive,
`head-to-head comparisons across a larger
`number of tumor types are needed, sev-
`eral recent studies have suggested that
`ctDNA may be detectable by deep
`sequencing-based approaches in a greater
`proportion of patients than CTCs [1–4].
`
`A major technical challenge in the analy-
`sis of ctDNA is that the vast majority of
`the cell-free DNA found in plasma origi-
`from a patient’s healthy cells.
`nates
`Therefore, highly sensitive techniques are
`necessary for reliable detection and quan-
`titation of
`the tumor-derived fraction.
`For example, in patients with stage IV
`non-small cell
`lung cancer, the percent
`of circulating DNA that is tumor-derived
`has been shown to vary between median
`values of approximately 0.1–5% and is
`affected by factors such as disease burden
`and treatment status [5–7].
`ctDNA
`Early
`efforts
`at detecting
`mostly focused on the application of
`allele-specific real-time quantitative PCR
`assays [8]. These assays, which utilized
`technologies
`such as TaqMan, PNA
`clamps,
`and Scorpion Amplification
`Refractory Mutation System, were lim-
`ited in their applicability to patients
`with high tumor burden due to their
`analytical
`sensitivity
`and
`specificity.
`However, within the past decade, several
`methods have been developed that allow
`for ultrasensitive detection of ctDNA.
`
`KEYWORDS: biomarker . circulating tumor DNA . next-generation sequencing . noninvasive
`. ultrasensitive
`
`informahealthcare.com
`
`10.1586/14737159.2015.1019476
`
`Ó 2015 Informa UK Ltd
`
`ISSN 1473-7159
`
`715
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`Editorial
`
`Bratman, Newman, Alizadeh & Diehn
`
`These methods have detection thresholds between 0.01 and
`0.1% for mutant allele abundance and fall into two main cate-
`gories – digital PCR (dPCR) [9,10] and next-generation sequenc-
`ing (NGS) [1,5,11]. The dPCR-based methods have very high
`analytical sensitivity for minor alleles (~0.01%) with improved
`specificity and reproducibility compared with real-time quanti-
`tative PCR [12] but generally can only interrogate one or a few
`genomic positions simultaneously. In addition, assays must be
`optimized for each mutation of
`interest, which complicates
`clinical implementation.
`NGS-based methods for ctDNA detection can detect multi-
`ple somatic alterations simultaneously. Although early NGS-
`based ctDNA detection platforms had insufficient sensitivity
`[13,14],
`several groups,
`for most clinical applications
`(>1%)
`including ours, have recently developed NGS-based methods
`that permit ultrasensitive ctDNA detection [1,5,11]. Two of these
`utilized deep sequencing of a limited number of amplicons tar-
`geting commonly mutated cancer genes [1,2,11,15,16]. Although
`low detection thresholds are achievable with such methods,
`technical limitations related to multiplexing of PCR assays have
`to date limited the number of genomic positions that can be
`interrogated. This complicates potential clinical applications
`because a given small combination of amplicons will not iden-
`tify a mutation in the majority of patients with most cancers.
`Moreover, amplicon-based methods are not able to detect most
`rearrangements and translocations if the exact breakpoints are
`not known a priori.
`To overcome these issues, we developed a capture-based
`NGS ctDNA detection method called CAncer Personalized
`Profiling by deep Sequencing (CAPP-Seq), which is applicable
`‘off the shelf’ to the vast majority of patients with a given can-
`cer type and which can detect all major classes of mutations
`including single nucleotide variants, indels, rearrangements, and
`[5]. Capture-based NGS methods
`copy number alterations
`enrich for genomic regions before sequencing by hybridization
`of target regions to antisense oligonucleotides. Such methods
`are scalable such that large portions of the genome can be
`examined. As a result, CAPP-Seq can usually identify multiple
`mutations in any given patient’s tumor, which increases its sen-
`sitivity and facilitates assessment of intratumoral heterogeneity.
`These properties make CAPP-Seq an effective tool with which
`to investigate the potential clinical utility of ctDNA analysis in
`a variety of contexts.
`
`Measurement of disease burden
`For a patient diagnosed with cancer, precise measurements of
`the total body disease burden may have prognostic significance
`and may be useful for assessing treatment response. Currently,
`the workhorse for such measurements
`is medical
`imaging,
`including computed tomography, PET, and MRI. Medical
`imaging consumes up to 6% of the total cost of cancer care in
`the USA [17], and both computed tomography and PET expose
`patients to ionizing radiation. Furthermore, response assessment
`on scans is subjective, imaging has suboptimal resolution for
`identifying small tumor deposits (<~1 cm diameter), and it can
`
`often be difficult to distinguish local treatment effects from
`recurrent cancer [18]. Despite these limitations, the use of high-
`cost medical imaging studies has been on the rise among cancer
`patients [17].
`Quantitation of ctDNA by CAPP-Seq could potentially over-
`come many of the shortcomings of imaging for measurement of
`disease burden. Multiple
`studies have demonstrated that
`changes in ctDNA levels can reflect
`treatment response in
`patients with advanced disease [1,2,5,9,11,14,15]. CAPP-Seq is
`designed to limit
`sequencing costs by targeting recurrently
`mutated genomic regions; current reagents and sequencing costs
`are approximately US$200–US$300 per assay, and costs will
`continue to decrease as NGS technologies mature. Still, there
`are a number of caveats to consider regarding the potential util-
`ity of monitoring disease burden using ctDNA. First, it is not
`known whether ctDNA is released at the same rate from pri-
`mary, nodal and distant metastatic sites. Some variation is likely
`to be present, based on differences in both tumor cell biology
`as well as access to the circulation [1]. For example, the blood–
`brain barrier may limit the passage of ctDNA from the central
`system into the peripheral circulation [1]. Second,
`nervous
`tumor histology likely impacts ctDNA release in ways that are
`not yet completely understood. Third, although there exists
`promising data suggesting that ctDNA analysis will be more
`sensitive than medical imaging [5,9], this will need to be explored
`in much larger patient cohorts. Fourth, ctDNA analysis by itself
`cannot reveal where tumor deposits are located within the body.
`We therefore envision that ctDNA analysis will be complimen-
`tary to standard imaging for disease monitoring.
`
`Prognostic indicator
`There is hope that ctDNA levels could provide added prog-
`nostic information beyond standard clinical indices. The cor-
`relation between ctDNA levels and traditional stage groupings
`is imperfect [1]; rather, it appears that total tumor volume bet-
`ter predicts ctDNA levels [5]. Tumor volume measurements
`derived from medical
`imaging are frequently found to be
`strongly prognostic [19,20], but in patients with metastatic dis-
`ease precise measurements of tumor volume can be challeng-
`ing. For
`these patients, quantitation of
`ctDNA could
`potentially be used to identify individuals with worse long-
`term survival [2,9].
`One particularly exciting application of ctDNA analysis was
`illustrated by Diehl et al. [9]. In their report, the absence of
`detectable ctDNA following surgery for advanced colorectal
`cancer
`identified individuals
`that
`remained disease-free for
`extended periods [9]. In the context of early stage malignancies,
`detection of minimal
`residual disease (MRD) post-surgery
`using ctDNA analysis could distinguish between patients with
`micrometastases who may derive a significant benefit
`from
`aggressive adjuvant systemic therapy and patients without resid-
`ual disease who could be spared the toxicity of such treatments.
`For example, the use of adjuvant chemotherapy is controversial
`in patients with stage I lung cancer or stage II colon cancer
`because prospective randomized trials have failed to show a
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`Expert Rev. Mol. Diagn. 15(6), (2015)
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`Potential clinical utility of ultrasensitive ctDNA detection with CAPP-Seq Editorial
`
`survival advantage in unselected populations [21,22]. By incorpo-
`rating CAPP-Seq into future clinical trials, patient selection
`could potentially be optimized when testing adjuvant therapies.
`The notion that detection of MRD following treatment can
`affect prognosis and aid clinical decision making is not new.
`MRD analysis is a vital component of post-treatment monitor-
`ing in hematologic malignancies and can identify individuals at
`high risk for relapse despite otherwise displaying complete
`response to therapy. In this context, MRD analysis involves
`PCR or multiparameter flow cytometry on cellular material
`from bone marrow biopsies or peripheral blood. We envision
`that CAPP-Seq will extend the applications of MRD analysis
`to solid malignancies for which no similar tests currently exist.
`CAPP-Seq can detect disease burden below the resolution of
`medical imaging [5], demonstrating its potential utility in MRD
`monitoring. Although secreted protein biomarkers can serve
`this function in a subset of patients with a few cancer types,
`poor specificity limits their utility in many instances. In con-
`trast, patient-specific genetic markers detected by CAPP-Seq
`are by nature specific to the tumor of interest. Future studies
`will compare the clinical utility of CAPP-Seq to other available
`biomarkers for MRD monitoring.
`
`Noninvasive genotyping & detection of resistance
`mutations
`In the age of personalized medicine, an ever-increasing number
`of targeted cancer therapies are available to specifically kill
`tumor cells with defined genetic aberrations. Thus, accurate
`tumor genotyping has become an essential component of opti-
`mal patient selection for these treatments. Unfortunately, there
`are often practical barriers to adequate tumor tissue acquisition,
`including risk from invasive procedures,
`inadequate sample
`retrieval through needle biopsies and difficulties of performing
`repeated invasive procedures over the course of therapy. Nonin-
`vasive access to tumor DNA could therefore enable more fre-
`quent and reliable tumor genotyping without the risks and
`discomfort that accompany biopsies. A growing number of
`companies are now offering or developing ctDNA-based tests
`to address the demand for such analyses.
`Currently, only a handful of cancer mutations are important
`for therapeutic decisions. However, this list will continue to
`grow as more targeted cancer therapies are developed and as
`the mechanisms of resistance to these agents are elucidated. As
`a capture-based NGS method, CAPP-Seq has the capability to
`interrogate thousands of genomic loci in parallel for the pur-
`pose of noninvasive genotyping. This differentiates it
`from
`other methods such as dPCR or amplicon-based NGS, which
`have limited abilities to simultaneously interrogate multiple
`mutations and thus require splitting of a blood sample into
`separate aliquots. Such subdividing of blood samples is prob-
`lematic because given the low concentrations of ctDNA that
`are present in most patients, a particular mutation will only be
`represented by a handful of molecules in a blood sample. Fur-
`thermore, CAPP-Seq has the advantage that in addition to
`point mutations, it can detect indels, rearrangements and copy
`
`number changes, which are also important determinants of
`response to certain targeted agents [23,24].
`Analysis of ctDNA also offers a strategy for monitoring
`evolving tumor heterogeneity over
`the course of
`therapy,
`because it simultaneously integrates contributions from cells
`within a primary tumor as well as from different tumor depos-
`its throughout the body. This is particularly relevant in regards
`to the emergence of mutations that confer resistance to targeted
`therapies, which can be readily detected using CAPP-Seq [5].
`Ultimately, early detection of such mutations could facilitate
`modification of therapy at a time when the burden of resistant
`cells is still low.
`
`Cancer screening
`The application of ctDNA analysis that could have the largest
`impact on patient survival is cancer screening. Many cancers
`are curable when detected early in their development, and
`screening programs that identify early stage tumors have dem-
`onstrated important survival benefits [25,26]. However, screening
`programs produce large numbers of false-positive results, which
`can cause significant stress and lead to unnecessary invasive
`procedures [27,28], possibly degrading survival gains while adding
`costs to health care systems.
`Detection of ctDNA could potentially improve upon the
`diagnostic accuracy of screening tests by reducing false-positive
`results. However, ctDNA analysis in this context is complicated
`by the facts that: tumors are small and therefore ctDNA con-
`centrations are very low; the specific mutations present in a
`given patient’s tumor are not known; and somatic mutations
`within circulating DNA may also be present as a result of
`mosaicism or benign/precancerous lesions [29,30]. Due to its
`high analytical sensitivity and specificity as well as ability to
`simultaneously interrogate thousands of possible mutations,
`CAPP-Seq could overcome some of these obstacles. In explor-
`atory analyses, we found that CAPP-Seq can be tuned to have
`a high positive predictive value for lung cancer detection with-
`out prior knowledge of tumor genotype. We expect ongoing
`technological
`improvements to enable even greater gains in
`diagnostic accuracy, which ultimately may make ctDNA-based
`cancer screening feasible. Much like existing screening tests,
`such ctDNA-based screening would need to be applied to high
`risk populations to limit the impact of false positives and may
`be best used in conjunction with medical imaging to limit the
`number of false-positive results from both modalities.
`
`Conclusions & future directions
`Over the past few years, considerable enthusiasm has developed
`for the clinical implementation of ctDNA detection technolo-
`gies. Because ctDNA reflects the genomic changes that occur
`within cancer cells,
`these technologies provide noninvasive
`access to biomarkers for diagnosis, prognosis and treatment
`response assessment. With CAPP-Seq,
`the possible clinical
`applications of ctDNA analysis continue to expand, and addi-
`tional innovations can be expected. Once thought to be appli-
`cable primarily in advanced stage cancers, NGS analysis of
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`Editorial
`
`Bratman, Newman, Alizadeh & Diehn
`
`ctDNA is now technically feasible in earlier stages as well. As
`with every new biomarker, the clinical utility of ctDNA analy-
`sis will need to be proven through well-designed clinical trials.
`However, based on the large amounts of promising data pub-
`lished in this field over the past few years, we anticipate that
`ctDNA analysis will revolutionize detection and management
`of cancer in the near future.
`
`Acknowledgements
`SV Bratman is
`supported by a grant from the Radiological Society of
`North America (RR1221) and has a translational cancer research fellow-
`ship with the Association of American Cancer Institutes. M Diehn is sup-
`ported by a grant from the US National Institutes of Health Director’ s
`New Innovator Award Program (1-DP2-CA186596). M Diehn and
`
`AA Alizadeh are supported by a grant from the Ludwig Institute for
`Cancer Research and a grant from the Doris Duke Clinical Scientist
`Development awards. AM Newman is
`supported by a grant from the
`Siebel Stem Cell Institute and the Thomas and Stacey Siebel Foundation.
`
`Financial & competing interests disclosure
`SV Bratman, AM Newman, AA Alizadeh, and M Diehn are co-inventors
`on patent applications related to the CAPP-Seq technology. AA Alizadeh
`and M Diehn are co-founders and consultants for CAPP Medical. The
`authors have no other relevant affiliations or financial involvement with
`any organization or entity with a financial interest in or financial conflict
`with the subject matter or materials discussed in the manuscript apart
`from those disclosed.
`No writing assistance was utilized in the production of this manuscript.
`
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