Amplicon-based next-generation sequencing of plasma cell-free DNA for detection of driver and resistance mutations in advanced non-small cell lung cancer

Abstract

Background

Genomic analysis of plasma cell-free DNA is transforming lung cancer care, however available assays are limited by cost, turnaround time, and imperfect accuracy. Here we study amplicon-based plasma next-generation sequencing (NGS), rather than hybrid-capture-based plasma NGS, hypothesizing this would allow sensitive detection and monitoring of driver and resistance mutations in advanced non-small cell lung cancer (NSCLC).

Methods

Plasma samples from patients with NSCLC and a known targetable genotype (EGFR, ALK/ROS1 and other rare genotypes) were collected while on therapy and analyzed, blinded to tumor genotype. Plasma NGS was performed using enhanced tagged amplicon sequencing of hotspots and coding regions from 36 genes, as well as intronic coverage for detection of ALK/ROS1 fusions. Diagnostic accuracy was compared to plasma ddPCR and tumor genotype.

Results

A total of 168 specimens from 46 patients were studied. Matched plasma NGS and ddPCR across 120 variants from 80 samples revealed high concordance of allelic fraction (R²=0.95). Pretreatment, sensitivity of plasma NGS for the detection of EGFR driver mutations was 100% (30/30), compared to 87% for ddPCR (26/30). A full spectrum of rare driver oncogenic mutations could be detected including sensitive detection of ALK/ROS1 fusions (8/9 detected, 89%). Studying 25 patients positive for EGFR T790M that developed resistance to osimertinib, 15 resistance mechanisms could be detected including tertiary EGFR mutations (C797S, Q791P) and mutations or amplifications of non-EGFR genes, some of which could be detected pre-treatment or months before progression.

Conclusions

This blinded analysis demonstrates the ability of amplicon-based plasma NGS to detect a full range of targetable genotypes in NSCLC, including fusion genes, with high accuracy. The ability of plasma NGS to detect a range of pre-existing and acquired resistance mechanisms highlights its potential value as an alternative to single mutation digital PCR-based plasma assays for personalizing treatment of TKI resistance in lung cancer.