Circulating Tumor DNA Analysis Allows Rapid Therapy Matching in Lung Cancer

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Among patients who tested plasma NGS positive for oncogenic driver alterations recognized by the National Comprehensive Cancer Network guidelines (EGFR, KRAS, ALK, ROS1, RET, BRAF, MET, HER2), 96.1 percent were concordant on tissue NGS.
Bob T. Li Physician Ambassador to China and Asia-Pacific, Bobst International Center

Our recent prospective study data provide support for the incorporation of plasma next-generation sequencing (NGS) assays into lung cancer practice guidelines.

Analyzing circulating tumor DNA (ctDNA) could allow for rapid and noninvasive genotyping that immediately guides precision therapy, providing an important supplement to tissue NGS, as well as an alternative when a tissue biopsy is not feasible.

Our study, which included 210 patients with advanced non-small cell lung cancer, identified a variety of oncogenic drivers with statistically shorter turnaround times compared to tissue NGS and matched patients to targeted therapies with clinical benefits. The median turnaround time for plasma NGS was nine days, significantly shorter than the 20 days for tissue NGS (p < 0.001). (1)

Plasma NGS detected somatic mutations in almost 65 percent of patients with advanced non-small cell lung cancer who had no known oncogenic drivers or resistance to current targeted therapies. Nearly all patients who tested positive for oncogenic drivers with plasma NGS (49 of 51, 95% CI = 86.5 to 99.5%) also tested positive with tissue NGS. Overall, 22 percent of all patients studied were matched to a targeted therapy based on their plasma NGS results, and the vast majority responded. (1)

As a narrower panel, plasma NGS identified fewer mutations than tissue NGS. Therefore, negative findings may still require further testing with tissue NGS. However, the high concordance with tissue NGS and the shorter turnaround time suggest that plasma NGS should be incorporated into lung cancer practice guidelines for guiding immediate treatment. (1)

Identifying Oncogenic Drivers with Next-Generation Sequencing

Plasma-based NGS assays that provide rapid and noninvasive genotyping of tumors have been increasingly adopted in clinical practice. However, there is little prospective evidence regarding their utility in matching patients to targeted therapy or the ideal timing for performing the tests. The American Society of Clinical Oncology and the College of American Pathologists recently concluded that there is little evidence of clinical utility and validity to support the widespread use of ctDNA NGS in most patients with advanced cancer.

Genetic sequencing is particularly crucial in patients with advanced non-small cell lung cancer because their tumors may harbor actionable somatic mutations. Cell-free genetic material from a primary tumor or metastases can be identified in plasma and may serve as a useful surrogate of tumor burden, intratumor heterogeneity, and response to therapy. Plasma-based genotyping may also address some of the limitations of tissue genotyping, including the risks of repeat invasive procedures, insufficient biopsy tissue, intratumor heterogeneity, and slow turnaround time with conventional tissue processing.

To determine the utility of plasma NGS compared to tissue NGS in this patient population, a group of researchers from Memorial Sloan Kettering Cancer Center, the University of Sydney, and Resolution Bioscience, an NGS technology company, collaborated to prospectively analyze genotyping results for 210 lung cancer patients (176 from MSK and 34 from Sydney). All patients in the study were tested with plasma ctDNA NGS using the ctDx lung cancer assay, a 21-gene assay developed by Resolution Bioscience. Tissue NGS was also performed for all MSK patients using MSK-IMPACT™, a 468-gene assay.

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Study Results

Somatic mutations were detected with plasma NGS in 64.3 percent of patients. Interestingly, detection was lower, at 42.9 percent, for patients who were on systemic therapy at the time of plasma collection compared to 75.0 percent for those who were not (OR = 0.26, 95 percent CI = 0.1 to 0.5, p < 0.001). This difference suggests that the optimal time to perform plasma genotyping is at initial diagnosis or at the time of disease progression. (1) The ctDNA yield might be highest at those times based on the correlation with tumor volume. (4)

Overall concordance, defined as the percentage of patients for whom at least one genetic alteration was found in both tissue and plasma, was 56.6 percent (60 of 106, 95% CI = 46% to 66.2%). We analyzed concordance in both directions: Among patients who tested positive with plasma NGS, 89.6 percent were also concordant on tissue NGS, and 60.6 percent of patients who tested positive with tissue NGS were concordant on plasma NGS. (1)

Plasma NGS genotyping identified a driver alteration in 45.7 percent of patients (96 of 210) and a broad range of actionable alterations overall, including EGFR mutations, secondary EGFR resistance mechanisms (T790M, C797S, and MET amplification), ALK fusions, MET exon 14 skipping alterations, BRAF alterations, and nonactionable mutations, such as KRAS and P1K3CA. Identification of actionable mutations led to matching targeted therapies for 21.9 percent of patients, which included standard therapies approved by the US Food and Drug Administration and investigational treatments. (1)

Among patients who tested positive on plasma NGS for oncogenic driver alterations recognized by the National Comprehensive Cancer Network guidelines (EGFR, KRAS, ALK, ROS1, RET, BRAF, MET, and HER2), 96.1 percent were concordant on tissue NGS. (1)

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Implications

Plasma genotyping identified oncogenic drivers with a fast turnaround time, and positive findings could immediately guide treatment without the need to wait for tissue genotyping. However, plasma genotyping has some notable limitations, including the low concentration of ctDNA shed into peripheral blood. (3) We observed a lower rate of driver detection for plasma NGS compared to tissue NGS, as demonstrated in other studies. (5) Therefore, a negative finding on plasma ctDNA does not exclude the presence of a targeted driver that may be found on tissue NGS genotyping.

Overall, our prospective evidence provides support for including plasma NGS in lung cancer practice guidelines. The technology can successfully assess the systemic genomic landscape and incorporate tumor heterogeneity, especially for patients with multiple metastases that may be distinct from the primary site that was biopsied at the time of initial diagnosis. Successful integration of plasma NGS into clinical practice will require universal guidelines that span multiple institutions and companies.

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MSK-IMPACT

MSK-IMPACT was developed by bioinformaticians, molecular pathologists, and genome scientists at MSK and has been employed to analyze tumors in patients with advanced cancer since January 2014. Originally used to detect gene mutations in melanoma, lung, and colon cancers, its use was expanded with the November 2017 authorization for the detection of mutations in any solid tumors regardless of origin.

MSK-IMPACT is currently available only at MSK. International patients can request MSK-IMPACT as a remote service. At present, the panel covers 468 genes, and we are expanding the panel as our knowledge base grows.

At MSK, we continue to pioneer the translation of molecular insights into clinical research. Close collaboration among teams of physician-scientists with diverse clinical and scientific training has led to internationally recognized advances in the treatment of lung cancer, melanoma, thyroid cancer, prostate cancer, and endometrial cancer.

We are currently conducting more than 80 clinical trials for adults with lung cancer to investigate new treatment approaches that may improve patient outcomes.

 

Other MSK authors of this study were Michael Offin, Dennis Stephens, Andy Ni, Sutirtha Datta, Nidhi Tandon, Mackenzie Myers, Alex Makhnin, Andres Martinez, Ysleni Leger, Helena Yu, Laetitia Borsu, Maria Arcila, Jeong Jeon, Valerie Rusch, Paul Paik, Jamie Chaft, Mark Kris, Marc Ladanyi, Matthew Hellmann, Alexander Drilon, Gregory Riely, David Jones, Andreas Rimner, Charles Rudin, and James Isbell.

MSK, the University of Sydney, and Resolution Bioscience collaborated on this study. There was no exchange of funds between the academic partners. Resolution Bioscience paid for the tests for all enrolled patients, and neither MSK nor the University of Sydney charged Resolution Bioscience for access to patients’ blood. Patients who consented to participate in the study received liquid biopsy testing free of charge. 

This research was supported in part by the National Institutes of Health and the National Cancer Institute (T32 CA009207 and P30 GA008748) and the Nussbaum/Kuhn Foundation. Dr. Li received travel support from Resolution Bioscience for an academic conference presentation, and he has served as a consultant for Genentech Roche, Thermo Fisher Scientific, and Guardant Health.

Part of this study was presented as a poster and abstract at the annual meeting of the American Society of Clinical Oncology in June 2017, and a portion was presented as an oral abstract at the International Association for the Study of Lung Cancer’s conference in October 2017.

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  1. Sabari JK, Offin M, Stephens D, et al. A prospective study of circulating tumor DNA to guide matched targeted therapy in lung cancers. J Natl Cancer Inst. 2019;111(6):djy156. 

  2. Merker JD, Oxnard GR, Compton C, et al. Circulating tumor DNA analysis in patients with cancer: American Society of Clinical Oncology and College of American Pathologists joint review. J Clin Oncol. 2018: 36(16):1631–1641.

  3. Diehl F, Schmidt K, Choti MA, et al. Circulating mutant DNA to assess tumor dynamics. Nat Med. 2008;14(9):985–990.

  4. Abbosh C, Birkbak NJ, Wilson GA, et al. Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature. 2017;545(7655):446–451.

  5. Schwaederle M, Husain H, Fanta PT, et al. Detection rate of actionable mutations in diverse cancers using a biopsy-free (blood) circulating tumor cell DNA assay. Oncotarget. 2016;7(9):9707–9717.