Tumor genomic sequencing has become part of routine oncology practice in many tumor types, in order to identify potentially targetable mutations and to personalize cancer care. Plasma genotyping via circulating tumor DNA analysis is a noninvasive and rapid alternative method of detecting and monitoring genomic alterations throughout the course of disease. Multiple assays have been developed to date, each with different test characteristics and degrees of clinical validation. Here we review the clinical data supporting these different plasma genotyping methodologies, and present a practical approach to the interpretation of the results of these tests. While the clinical application of plasma genotyping has been most extensively validated in the metastatic setting—for the detection of targetable alterations at the time of initial diagnosis or disease progression—this technology holds significant promise across many tumor types and stages of disease. We will also review emerging applications of plasma genotyping that are currently under clinical investigation.
Modern targeted therapies have greatly advanced the treatment of many solid tumors. The rational use of these agents requires optimal strategies for the rapid and accurate detection of targetable genomic alterations, both upon initial diagnosis and when acquired resistance to targeted therapies develops. While tissue genotyping has traditionally been considered the standard of care for identifying such genomic alterations, this methodology is limited by often inaccessible or insufficient tumor tissue, and by the risks associated with undergoing serial tumor biopsies. In non–small-cell lung cancer (NSCLC), for example, where molecular testing to guide initial treatment decision making is considered standard of care, clinical studies show that up to 10% to 20% of biopsies are inadequate for molecular testing due to insufficient tissue or amplifiable DNA.[1,2] Furthermore, tumor biopsies are limited by tumor heterogeneity, particularly in the setting of disease resistance, and thus may yield false-negative results.
Plasma genotyping is an emerging technology that can noninvasively and rapidly detect and monitor genomic alterations in cancer patients over time, and which has the potential to overcome some of the limitations associated with tissue genotyping. To date, multiple platforms for plasma genotyping have been tested and validated to various degrees; each has different advantages and limitations, complicating the interpretation and routine integration of these tests into clinical practice.
Biology of Cell-Free DNA
The presence of cell-free DNA (cfDNA) in the plasma was first described in 1948 by Mandel and Metais. It was not until years later that tumor-derived cfDNA—also called circulating tumor DNA (ctDNA)—was discovered, stemming from the finding that cancer patients had higher levels of plasma cfDNA than normal controls.[4,5] The exact mechanism by which DNA is released into the peripheral blood has not been well described; however, it is thought to occur through multiple mechanisms, including tumor cell apoptosis, necrosis, and extracellular vesicle secretion.[6-8] In contrast to genomic DNA, ctDNA is highly fragmented, with most DNA fragments measuring approximately 150 bp in length; this supports the hypothesis that cfDNA originates through cell necrosis or apoptosis.[9,10] Also, peripheral cfDNA exists in low concentrations, with the majority of studies reporting absolute cfDNA levels of less than 100 ng/mL—and only a fraction of this total cfDNA (< 1% of total cfDNA) is actually tumor-derived.[9,12] Thus, highly sensitive methodologies are required to detect ctDNA (Figure).
The concept of ctDNA “shed” is critical to the understanding and interpretation of plasma genotyping assay results, since even the most sensitive assays may not detect a mutation if a tumor is not shedding ctDNA. The degree to which a tumor releases DNA into the peripheral circulation determines the concentration of ctDNA that may be detected in the blood. Factors associated with increased ctDNA shed include mitotic rate, cell death, and tumor vascularization. The extent of metastatic disease burden and sites of metastasis have also been associated with detection of increased ctDNA.[6,7] In particular, the presence of metastasis to the liver or bone has been associated with higher levels of ctDNA in clinical studies.
Current Assays and Validation
A variety of potential testing platforms for plasma genotyping have been utilized in the past. Each platform has been validated to a different degree and exhibits unique capabilities and test characteristics. Traditional DNA detection methods, such as Sanger sequencing, have generally lacked the sensitivity needed to detect the low levels of ctDNA present in the peripheral blood. Thus, more recent assays have utilized an allele-specific quantitative polymerase chain reaction (PCR)-based platform to enrich for mutant DNA, or have used massive parallel sequencing with a next-generation sequencing (NGS) platform. Most currently validated ctDNA assays have been compared against tissue genotyping. The specificities reported for these tests are consistently high, ranging between 90% and 100%, but their sensitivities are more variable, ranging between 30% and 85%, depending on the testing methodology (Table 1). While few prospective validation studies have been carried out to date, retrospective analysis of samples collected from patients enrolled in prospective clinical trials is a reliable alternative.
The Roche cobas EGFR Mutation Test v2 is the only ctDNA assay that is currently approved by the US Food and Drug Administration (FDA) for the detection of EGFR-sensitizing and resistance mutations in NSCLC. This platform was originally approved by the FDA for the detection of EGFR-sensitizing mutations in tissue. Recently, this approval has been extended to include plasma genotyping for both EGFR-sensitizing mutations and the T790M resistance mutation. The approval of the plasma genotyping assay was based on data from the retrospective analysis of paired plasma and tissue samples from 517 NSCLC patients screened for the ENSURE study, which compared treatment with cisplatin/gemcitabine vs erlotinib in EGFR-mutant NSCLC patients. The cobas assay demonstrated moderate sensitivity and high specificity—76.7% (range, 70.5%–81.9%) and 98.2% (range, 95.4%–99.3%), respectively—for the detection of EGFR-sensitizing mutations. The approval for inclusion of EGFR T790M was based on a retrospective analysis of plasma samples from EGFR-mutant NSCLC patients with acquired resistance to initial kinase inhibitor therapy who were enrolled in the early-phase trials (AURA and AURA2) of the third-generation epidermal growth factor receptor (EGFR) kinase inhibitor osimertinib. When compared with an NGS plasma genotyping assay, the sensitivity and specificity of the cobas assay for detection of EGFR T790M were 91.5% and 91.1%, respectively; however, when compared with tissue genotyping, sensitivity and specificity were lower, at 61.4% and 78.6%, respectively.[15,16] The discordance of these results was hypothesized to be related to the heterogeneity of the presence of resistance mutations in tumor tissue.
Many of the earliest attempts at ctDNA genotyping utilized the Scorpion amplification refractory mutation system (Scorpion-ARMS) platform, which uses allele-specific primers with fluorescent probes to amplify target DNA alleles. Kimura et al evaluated the test characteristics of ctDNA analysis using a Scorpion-ARMS platform, comparing it against tissue genotyping in NSCLC patients treated with gefitinib. They demonstrated that cfDNA analysis had the ability to detect EGFR mutations with a sensitivity of 85.7% and a specificity of 94.3%. Similar results have been reported in several other retrospective validation studies that used Scorpion-ARMS technology to assess plasma EGFR mutations in the NSCLC population.[2,18]
Newer PCR methodologies, such as beads, emulsion, amplification, and magnetics (BEAMing) and digital droplet PCR (ddPCR), are characterized by higher sensitivity and specificity, and have the additional capability of quantitating mutant ctDNA levels. A recent prospective clinical study compared a ddPCR-based plasma assay against tissue genotyping for the detection of EGFR and KRAS mutations in patients with advanced NSCLC. This assay demonstrated 100% specificity for the detection of EGFR-sensitizing and KRAS mutations. The median turnaround time for ctDNA testing results was only 3 days (range, 1–7 days), highlighting another advantage of ddPCR technology. BEAMing is a highly specific and sensitive PCR methodology with quantitative capabilities. Bettegowda et al reported ctDNA test characteristics using a BEAMing platform in a cohort of 640 patients across all tumor types and stages, demonstrating variability based on stage and tumor type. Within the cohort of 206 patients with metastatic colorectal cancer, the sensitivity for detection of KRAS mutations was 87.2% and the specificity was 99.2%. ctDNA analysis using BEAMing technology has also been retrospectively validated in studies in NSCLC to detect both EGFR-sensitizing and EGFR resistance mutations.[20,21] One limitation of both ddPCR and BEAMing is their limited ability to assess for more complex alterations, such as translocations or copy number alterations.
NGS technologies are capable of sequencing millions of small DNA fragments in parallel, resulting in highly sensitive and specific detection capabilities. NGS platforms also have the ability to quantify allele frequency and can detect complex alterations such as translocations and copy number changes. Using a multiplex NGS PCR platform to investigate for a panel of 50 cancer-related genes, Couraud et al reported an assay specificity of 86% to 100% and a sensitivity of 58% for the detection of all 50 genes. The ability to detect complex alterations present at low allele frequencies using NGS technology was demonstrated in a study by Paweletz et al. Complex alterations—including rearrangements in ALK, ROS1, and RET; HER2 insertions; and MET amplifications—were detected with 100% specificity and 77% sensitivity. Several commercially available ctDNA assays, including Guardant360 (Guardant Health) and FoundationACT (Foundation Medicine), utilize NGS platforms to investigate for a panel of potentially actionable mutations. Lanman et al validated the Guardant360 platform in a study of 165 patients with advanced solid tumors and reported a sensitivity of 85% and a specificity of > 99%. A subsequent large retrospective analysis of ctDNA testing results from more than 15,000 patients in whom the Guardant360 platform was used reported an accuracy of 87% when plasma genotyping was compared with historical tissue genotyping data from the Cancer Genome Atlas.[25,26]
1. Arcila ME, Oxnard GR, Nafa K, et al. Rebiopsy of lung cancer patients with acquired resistance to EGFR inhibitors and enhanced detection of the T790M mutation using a locked nucleic acid-based assay. Clin Cancer Res. 2011;17:1169-80.
2. Douillard JY, Ostoros G, Cobo M, 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;9:1345-53.
3. Mandel P, Metais P. Les acides nucleiques du plasma sanguin chez l’ homme [The nucleic acids in blood plasma in humans]. C R Seances Soc Biol Fil. 1948;142:241-3.
4. Leon SA, Shapiro B, Sklaroff DM, Yaros MJ. Free DNA in the serum of cancer patients and the effect of therapy. Cancer Res. 1977;37:646-50.
5. Stroun M, Anker P, Maurice P, et al. Neoplastic characteristics of the DNA found in the plasma of cancer patients. Oncology. 1989;46:318-22.
6. Jahr S, Hentze H, Englisch S, et al. DNA fragments in the blood plasma of cancer patients: quantitations and evidence for their origin from apoptotic and necrotic cells. Cancer Res. 2001;61:1659-65.
7. Stroun M, Lyautey J, Lederrey C, et al. About the possible origin and mechanism of circulating DNA apoptosis and active DNA release. Clin Chim Acta. 2001;313:139-42.
8. Anker P, Stroun M, Maurice PA. Spontaneous extracellular synthesis of DNA released by human blood lymphocytes. Cancer Res. 1976;36:2832-9.
9. Diehl F, Li M, Dressman D, et al. Detection and quantification of mutations in the plasma of patients with colorectal tumors. Proc Natl Acad Sci USA. 2005;102:16368-73.
10. Mouliere F, Rosenfeld N. Circulating tumor-derived DNA is shorter than somatic DNA in plasma. Proc Natl Acad Sci USA. 2015;112:3178-9.
11. Fleischhacker M, Schmidt B. Circulating nucleic acids (CNAs) and cancer—a survey. Biochim Biophys Acta. 2007;1775:181-232.
12. Yong E. Cancer biomarkers: written in blood. Nature. 2014;511:524-6.
13. Sacher AG, Paweletz C, Dahlberg SE, et al. Prospective validation of rapid plasma genotyping for the detection of EGFR and KRAS mutations in advanced lung cancer. JAMA Oncol. 2016;2:1014-22.
14. US Food and Drug Administration. Cobas EGFR mutation test v2. https://www.fda.gov/Drugs/InformationOnDrugs/ApprovedDrugs/ucm504540.htm. Accessed July 17, 2017.
15. Jenkins S, Yang J, Ramalingam S, et al. 134O_PR: Plasma ctDNA analysis for detection of EGFR T790M mutation in patients (pts) with EGFR mutation-positive advanced non-small cell lung cancer (aNSCLC). J Thorac Oncol. 2016;11:S153-S154.
16. Jenkins S, Yang JC, Ramalingam SS, et al. Plasma ctDNA analysis for detection of the EGFR T790M mutation in patients with advanced non-small cell lung cancer. J Thorac Oncol. 2017;12:1061-70.
17. Kimura H, Suminoe M, Kasahara K, et al. Evaluation of epidermal growth factor receptor mutation status in serum DNA as a predictor of response to gefitinib (IRESSA). Br J Cancer. 2007;97:778-84.
18. Goto K, Ichinose Y, Ohe Y, et al. Epidermal growth factor receptor mutation status in circulating free DNA in serum: from IPASS, a phase III study of gefitinib or carboplatin/paclitaxel in non-small cell lung cancer. J Thorac Oncol. 2012;7:115-21.
19. Bettegowda C, Sausen M, Leary RJ, et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med. 2014;6:224ra24.
20. Oxnard GR, Thress KS, Alden RS, et al. Association between plasma genotyping and outcomes of treatment with osimertinib (AZD9291) in advanced non-small-cell lung cancer. J Clin Oncol. 2016;34:3375-82.
21. Karlovich C, Goldman JW, Sun JM, et al. Assessment of EGFR mutation status in matched plasma and tumor tissue of NSCLC patients from a phase I study of rociletinib (CO-1686). Clin Cancer Res. 2016;22:2386-95.
22. Couraud S, Vaca-Paniagua F, Villar S, et al. Noninvasive diagnosis of actionable mutations by deep sequencing of circulating free DNA in lung cancer from never-smokers: a proof-of-concept study from BioCAST/IFCT-1002. Clin Cancer Res. 2014;20:4613-24.
23. Paweletz CP, Sacher AG, Raymond CK, et al. Bias-corrected targeted next-generation sequencing for rapid, multiplexed detection of actionable alterations in cell-free DNA from advanced lung cancer patients. Clin Cancer Res. 2016;22:915-22.
24. Lanman RB, Mortimer SA, Zill OA, et al. Analytical and clinical validation of a digital sequencing panel for quantitative, highly accurate evaluation of cell-free circulating tumor DNA. PLoS One. 2015;10:e0140712.
25. Zill OA, Banks KC, Jackson C, et al. Comparison of over 10,000 clinical NGS circulating tumor DNA profiles to tissue-derived genomic compendia. Presented at the Annual Meeting of the American Association for Cancer Research; April 16-20, 2016; New Orleans, LA. Abstr 4343.
26. Zill OA, Mortimer S, Banks KC, et al. Somatic genomic landscape of over 15,000 patients with advanced-stage cancer from clinical next-generation sequencing analysis of circulating tumor DNA. J Clin Oncol. 2016;34(suppl):abstr LBA11501.
27. Thress KS, Brant R, Carr TH, et al. EGFR mutation detection in ctDNA from NSCLC patient plasma: a cross-platform comparison of leading technologies to support the clinical development of AZD9291. Lung Cancer. 2015;90:509-15.
28. Mok TS, Wu YL, Ahn MJ, et al. Osimertinib or platinum-pemetrexed in EGFR T790M-positive lung cancer. N Engl J Med. 2017;376:629-40.
29. Gormally E, Vineis P, Matullo G, et al. TP53 and KRAS2 mutations in plasma DNA of healthy subjects and subsequent cancer occurrence: a prospective study. Cancer Res. 2006;66:6871-6.
30. Martincorena I, Roshan A, Gerstung M, et al. Tumor evolution: high burden and pervasive positive selection of somatic mutations in normal human skin. Science. 2015;348:880-6.
31. Tie J, Wang Y, Tomasetti C, et al. Circulating tumor DNA analysis detects minimal residual disease and predicts recurrence in patients with stage II colon cancer. Sci Transl Med. 2016;8:346ra92.
32. Garcia-Murillas I, Schiavon G, Weigelt B, et al. Mutation tracking in circulating tumor DNA predicts relapse in early breast cancer. Sci Transl Med. 2015;7:302ra133.
33. Leary RJ, Kinde I, Diehl F, et al. Development of personalized tumor biomarkers using massively parallel sequencing. Sci Transl Med. 2010;2:20ra14.
34. McBride DJ, Orpana AK, Sotiriou C, et al. Use of cancer-specific genomic rearrangements to quantify disease burden in plasma from patients with solid tumors. Genes Chromosomes Cancer. 2010;49:1062-9.
35. Ng SB, Chua C, Ng M, et al. Individualised multiplexed circulating tumour DNA assays for monitoring of tumour presence in patients after colorectal cancer surgery. Sci Rep. 2017;7:40737.
36. Mok T, Wu YL, Lee JS, 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;21:3196-203.
37. Dawson SJ, Tsui DW, Murtaza M, et al. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N Engl J Med. 2013;368:1199-209.
38. Tie J, Kinde I, Wang Y, et al. Circulating tumor DNA as an early marker of therapeutic response in patients with metastatic colorectal cancer. Ann Oncol. 2015;26:1715-22.
39. Frenel JS, Carreira S, Goodall J, et al. Serial next-generation sequencing of circulating cell-free DNA evaluating tumor clone response to molecularly targeted drug administration. Clin Cancer Res. 2015;21:4586-96.
40. Thress KS, Paweletz CP, Felip E, et al. Acquired EGFR C797S mutation mediates resistance to AZD9291 in non-small cell lung cancer harboring EGFR T790M. Nat Med. 2015;21:560-2.
41. Reckamp KL, Melnikova VO, Karlovich C, et al. A highly sensitive and quantitative test platform for detection of NSCLC EGFR mutations in urine and plasma. J Thorac Oncol. 2016;11:1690-700.
42. Wei F, Lin CC, Joon A, et al. Noninvasive saliva-based EGFR gene mutation detection in patients with lung cancer. Am J Respir Crit Care Med. 2014;190:1117-26.
43. Pu D, Liang H, Wei F, et al. Evaluation of a novel saliva-based epidermal growth factor receptor mutation detection for lung cancer: a pilot study. Thorac Cancer. 2016;7:428-36.
44. Momtaz P, Pentsova E, Abdel-Wahab O, et al. Quantification of tumor-derived cell free DNA (cfDNA) by digital PCR (DigPCR) in cerebrospinal fluid of patients with BRAFV600 mutated malignancies. Oncotarget. 2016;7:85430-6.
45. Zhao J, Ye X, Xu Y, et al. EGFR mutation status of paired cerebrospinal fluid and plasma samples in EGFR mutant non-small cell lung cancer with leptomeningeal metastases. Cancer Chemother Pharmacol. 2016;78:1305-10.
46. Yang H, Cai L, Zhang Y, et al. Sensitive detection of EGFR mutations in cerebrospinal fluid from lung adenocarcinoma patients with brain metastases. J Mol Diagn. 2014;16:558-63.
47. Pentsova EI, Shah RH, Tang J, et al. Evaluating cancer of the central nervous system through next-generation sequencing of cerebrospinal fluid. J Clin Oncol. 2016;34:2404-15.