Decisions to continue or suspend therapy with immune checkpoint inhibitors are commonly guided by tumor dynamics seen on serial imaging. However, immunotherapy responses are uniquely challenging to interpret because tumors often shrink slowly or can appear transiently enlarged due to inflammation. We hypothesized that monitoring tumor cell death in real time by quantifying changes in circulating tumor DNA (ctDNA) levels could enable early assessment of immunotherapy efficacy. We compared longitudinal changes in ctDNA levels with changes in radiographic tumor size and with survival outcomes in 28 patients with metastatic non-small cell lung cancer (NSCLC) receiving immune checkpoint inhibitor therapy. CtDNA was quantified by determining the allele fraction of cancer-associated somatic mutations in plasma using a multigene next-generation sequencing assay. We defined a ctDNA response as a >50% decrease in mutant allele fraction from baseline, with a second confirmatory measurement. Strong agreement was observed between ctDNA response and radiographic response (Cohen's kappa, 0.753). Median time to initial response among patients who achieved responses in both categories was 24.5 days by ctDNA versus 72.5 days by imaging. Time on treatment was significantly longer for ctDNA responders versus nonresponders (median, 205.5 vs. 69 days; < 0.001). A ctDNA response was associated with superior progression-free survival [hazard ratio (HR), 0.29; 95% CI, 0.09-0.89; = 0.03], and superior overall survival (HR, 0.17; 95% CI, 0.05-0.62; = 0.007). A drop in ctDNA level is an early marker of therapeutic efficacy and predicts prolonged survival in patients treated with immune checkpoint inhibitors for NSCLC. .
Detection of cell-free tumor DNA in the blood has offered promise as a cancer biomarker, but practical clinical implementations have been impeded by the lack of a sensitive and accurate method for quantitation that is also simple, inexpensive, and readily scalable. Here we present an approach that uses next-generation sequencing to quantify the small fraction of DNA molecules that contain tumor-specific mutations within a background of normal DNA in plasma. Using layers of sequence redundancy designed to distinguish true mutations from sequencer misreads and PCR misincorporations, we achieved a detection sensitivity of approximately 1 variant in 5,000 molecules. In addition, the attachment of modular barcode tags to the DNA fragments to be sequenced facilitated the simultaneous analysis of more than a hundred patient samples. As proof of principle, we demonstrated the successful use of this method to follow treatment-associated changes in circulating tumor DNA levels in patients with non-small cell lung cancer. Our findings suggest that the deep sequencing approach described here may be applied to the development of a practical diagnostic test that measures tumor-derived DNA levels in blood.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with đź’™ for researchers
Part of the Research Solutions Family.