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`Clinical Chemistry 59:1
`6–8 (2013)
`
`Editorials
`
`Plasma-Derived Tumor DNA Analysis at Whole-Genome
`Resolution
`Charles Swanton1,2*
`
`The last 2 years have witnessed an extraordinary
`change in our understanding of the somatic mutational
`landscape of solid tumors, driven by the impressive
`large-scale sequencing efforts from such groups as the
`Cancer Genome Atlas and the Cancer Genome Project.
`As is so often the case with such ambitious scientific
`endeavors, the complexities these efforts have revealed
`raise even greater questions for the future. These stud-
`ies have exposed the scale of diversity in the mutational
`landscape among tumors of the same histopathologic
`subtype. For example, between 1 and 3 genes in high-
`grade serous ovarian cancer or triple-negative breast
`cancer are subject to somatic mutations in ⬎10% of
`patients with the same histopathologic subtype of dis-
`ease (1, 2 ). The remainder of the somatic mutational
`landscape is dominated by genes subject to mutations
`at much lower frequencies. Low-frequency but poten-
`tially targetable events challenge conventional ap-
`proaches to personalized medicine, both in terms of
`the health-economic costs in developing therapeutics
`for such small numbers of patients and in terms of
`tumor screening to identify such low-frequency so-
`matic events.
`Adding to this layer of complexity is the increasing
`evidence for profound heterogeneity in DNA copy
`number states, somatic mutational and ploidy profiles
`that may be distinguished within a single tumor sample
`(3–5 ) or between primary and metastatic sites (6 –9 ).
`Indeed, such subclonal diversity is thought to contrib-
`ute to adaptation for tumor growth at distant sites of
`disease (10 ). Increasing evidence suggests that the
`emergence of drug resistance in solid tumors may be
`predetermined by the presence of low-frequency het-
`erogeneous tumor subclones harboring somatic muta-
`tions that confer resistance to the targeting anticancer
`agent (11 ). Finally, also emerging is clear evidence that
`the subclonal dynamics of both hematologic and solid
`tumors change over time [reviewed in (10 )] to such an
`
`1 Translational Cancer Therapeutics Laboratory, Cancer Research UK London
`Research Institute, London, UK; 2 UCL Cancer Institute, London, UK.
`* Address correspondence to the author at: Translational Cancer Therapeutics
`Laboratory, Cancer Research UK London Research Institute, 44 Lincoln’s Inn
`Fields, London WC2A 3LY, UK. Fax ⫹44-20-7269-3094; e-mail Charles.
`swanton@cancer.org.uk.
`Received October 2, 2012; accepted October 4, 2012.
`Previously published online at DOI: 10.1373/clinchem.2012.197053
`
`6
`
`extent that the subclone that ultimately determines dis-
`ease outcome may barely be detectable at diagnosis
`(12 ).
`Such findings have begun to raise profound ques-
`tions regarding how mutational and DNA copy num-
`ber profiles can be defined rapidly in individual pa-
`tients and how future personalized cancer therapeutics
`can be designed to limit disease progression, predict
`the early emergence of drug resistance, and resolve the
`changing nature of a tumor’s subclonal dynamics over
`time (13 ). Given this emerging evidence for intratu-
`mor heterogeneity in somatic mutational status be-
`tween sites of disease and for the risks associated with
`biopsying multiple sites of disease (6, 14 ), it is critical
`to determine how less-invasive techniques can be es-
`tablished to profile a tumor’s somatic mutational load
`more rapidly and to track its evolution over time. Ar-
`guably, the future of oncologic care will rely on more
`accurate and less invasive diagnostic and predictive
`tools. Progress in our understanding of drug resistance
`and tumor metastases will undoubtedly depend on our
`ability to monitor a tumor’s subclonal dynamics and
`the Darwinian selection of tumor subclones, preferably
`with just a blood sample rather than multiple sequen-
`tial biopsies of metastatic sites.
`The analysis of circulating free tumor DNA
`(ctDNA)3 has been primed for some time to overcome
`the hurdle of invasive biopsies by identifying predeter-
`mined somatic mutations via a “liquid biopsy” (15 ).
`Until now, however, ctDNA analysis has not been able
`to resolve distinct copy number events in tumors or
`to resolve single-nucleotide variants (SNVs) on a
`genomewide scale. In this cancer-themed issue of Clin-
`ical Chemistry, Lo and colleagues provide long-awaited
`evidence that massively parallel sequencing (MPS)
`analysis of ctDNA can resolve DNA structural aberra-
`tions across the entire genome at 1-Mb resolution (16 ).
`These authors demonstrate, with 4 patients with hepa-
`tocellular carcinoma, the striking representation of
`copy number events detected in a tumor in events de-
`tected in ctDNA, and the almost complete loss of these
`events from the plasma after tumor resection. In con-
`
`3 Nonstandard abbreviations: ctDNA, circulating free tumor DNA; SNV, single-
`nucleotide variant; MPS, massively parallel sequencing.
`
`Personalis EX2003.001
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`trast, only 1% of the sequencing bins for ctDNA iso-
`lated from 4 carriers of the hepatitis B virus with no
`detectable tumor revealed abnormal copy number ab-
`errations, a finding that emphasizes the potential for
`ctDNA assessment as a screening tool for this disease.
`Intriguingly, the authors detected ctDNA aberrations
`that were not present in the single biopsy obtained
`from an individual’s hepatocellular carcinoma. Al-
`though Lo and colleagues reflect that such ctDNA ab-
`errations represent reduced specificity for the use of
`ctDNA analysis for hepatocellular carcinoma, an alter-
`native explanation is that a single biopsy of a tumor
`may underrepresent the copy number landscape, as has
`been shown for renal cancer (6 ). It would therefore be
`important to assess an equally plausible explanation—
`that ctDNA analysis may in fact be superior to a single
`tumor biopsy for resolving the majority of copy num-
`ber aberrations present in a single tumor.
`Remarkably, Lo and colleagues demonstrated
`through their study of a patient with synchronous
`breast and ovarian primaries that the structural DNA
`copy number aberrations detectable in plasma ctDNA
`were a hybrid of the ovarian and breast primaries. They
`elegantly demonstrate that the attenuation of DNA
`copy number signals in ctDNA after sequential, same-
`day surgical resection of the breast primary and bi-
`lateral ovarian cancers directly mirrors the single-
`nucleotide polymorphism/comparative
`genomic
`hybridization copy number profiles derived from the
`surgically resected tumors. Although the breast pri-
`mary was only 3 cm in size and contributed an estimated
`2.1% of the total ctDNA, the authors showed that this
`analytically sensitive technique was still able to detect
`breast cancer–specific copy number aberrations—such as
`a deletion in chromosome 6p and amplifications on
`chromosomes 1q, 7p, and 15q—that were present only
`in the breast primary and disappeared soon after breast
`surgery.
`These data provide conclusive evidence that the
`use of plasma-derived ctDNA for unbiased analysis
`of the structural genomic landscape of tumors over
`time is now fit for implementation in the research
`setting. Given the clinical risks of repeat tumor bi-
`opsies and the challenges associated with inter- and
`intratumor heterogeneity, this landmark study will
`enable rapid progress in our understanding of tumor
`evolution over time.
`Perhaps most importantly, the authors have used
`ctDNA analysis to explore the phenomenon of intratu-
`moral heterogeneity in ovarian cancer. Although 4 re-
`gions of the bilateral ovarian tumors had almost iden-
`tical copy number profiles, the authors found SNVs
`specific to a single region, shared SNVs within a single
`ovarian cancer, and ubiquitous SNVs present bilater-
`ally. Using a mass spectrometry– based iPLEX analyti-
`
`Editorials
`
`cal method, the authors conclusively identified 95% of
`the 67 SNVs selected for validation in the tumor DNA.
`The authors then leveraged this analysis to define the
`presence of these SNVs in the MPS data from ctDNA
`before and after surgery. In their analysis of the ubiq-
`uitous SNVs, the authors estimated that these SNVs
`accounted for 46% of the ctDNA before surgery and
`0.18% after bilateral oophorectomy. When the authors
`focused their attention on the SNVs shared by one or
`the other of the ovarian tumors, they found that the
`degree of a tumor’s SNV representation in the ctDNA
`mirrored the size of the ovarian tumor mass on the side
`from which these SNVs derived, suggesting that ctDNA
`may be a useful surrogate of residual disease.
`These data have important implications. First, it is
`apparent that tumor heterogeneity poses a substantial
`problem to the use of ctDNA focused on tumor-
`specific mutations as a tool to predict early relapse or to
`monitor the emergence of drug resistance, if the focus
`is on somatic events that may not be ubiquitous
`throughout the tumor mass. Second, these data sup-
`port the use of unbiased shotgun MPS approaches to
`ctDNA analysis—particularly in the context of study-
`ing the subclonal dynamics of the disease through
`therapy—for attempting to resolve the emergence of
`distinct tumor subclones harboring low-frequency so-
`matic events conferring drug resistance. With the fu-
`ture acceleration of DNA sequencing and data analysis,
`the shotgun MPS approach to ctDNA analysis has the
`potential to provide a powerful tool for deciphering the
`Darwinian mechanisms of tumor evolution and to
`keep pace with tumor subclonal dynamics through the
`disease course.
`
`Author Contributions: All authors confirmed they have contributed to
`the intellectual content of this paper and have met the following 3 re-
`quirements: (a) significant contributions to the conception and design,
`acquisition of data, or analysis and interpretation of data; (b) drafting
`or revising the article for intellectual content; and (c) final approval of
`the published article.
`
`Authors’ Disclosures or Potential Conflicts of Interest: No authors
`declared any potential conflicts of interest.
`
`References
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`Editorials
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