Annals of Oncology · 2019 · 157 citations · 20 references
MedicineMolecular BiologyOncologyGenomicsMolecular DiagnosticsMolecular OncologyCancer GenomicsCancer Molecular DiagnosticsCirculating Tumor Dna AnalysisDna SequencingOncogene MutationsSequencing-based DiagnosticsEgfr Mutation TestingHybrid CaptureKras Mutation TestingOncogenic Driver MutationsOrthogonal Validation AssaysPlasma GenotypingResistance-associated MutationsUltra-deep Sequencing
Plasma cfDNA genotyping can replace invasive biopsies and reveal tumor heterogeneity. The study aimed to develop an ultra‑deep plasma NGS assay for NSCLC to detect actionable drivers and resistance mutations when tissue biopsies are inadequate. Plasma cfDNA and matched white blood cells were subjected to ultra‑deep NGS with a 37‑gene hybrid capture panel at 50,000× coverage, filtering clonal hematopoiesis, and validated by ddPCR. In 127 patients, plasma NGS detected driver mutations (0.14–52% VAF) with 75% sensitivity and 100% specificity versus tissue, identified additional KRAS mutations in tissue‑insufficient cases, and revealed resistance mechanisms (EGFR T790M, C797S, ERBB2 amplification) in EGFR‑mutant patients.
BackgroundNoninvasive genotyping using plasma cell-free DNA (cfDNA) has the potential to obviate the need for some invasive biopsies in cancer patients while also elucidating disease heterogeneity. We sought to develop an ultra-deep plasma next-generation sequencing (NGS) assay for patients with non-small-cell lung cancers (NSCLC) that could detect targetable oncogenic drivers and resistance mutations in patients where tissue biopsy failed to identify an actionable alteration.Patients and methodsPlasma was prospectively collected from patients with advanced, progressive NSCLC. We carried out ultra-deep NGS using cfDNA extracted from plasma and matched white blood cells using a hybrid capture panel covering 37 lung cancer-related genes sequenced to 50000× raw target coverage filtering somatic mutations attributable to clonal hematopoiesis. Clinical sensitivity and specificity for plasma detection of known oncogenic drivers were calculated and compared with tissue genotyping results. Orthogonal ddPCR validation was carried out in a subset of cases.ResultsIn 127 assessable patients, plasma NGS detected driver mutations with variant allele fractions ranging from 0.14% to 52%. Plasma ddPCR for EGFR or KRAS mutations revealed findings nearly identical to those of plasma NGS in 21 of 22 patients, with high concordance of variant allele fraction (r = 0.98). Blinded to tissue genotype, plasma NGS sensitivity for de novo plasma detection of known oncogenic drivers was 75% (68/91). Specificity of plasma NGS in those who were driver-negative by tissue NGS was 100% (19/19). In 17 patients with tumor tissue deemed insufficient for genotyping, plasma NGS identified four KRAS mutations. In 23 EGFR mutant cases with acquired resistance to targeted therapy, plasma NGS detected potential resistance mechanisms, including EGFR T790M and C797S mutations and ERBB2 amplification.ConclusionsUltra-deep plasma NGS with clonal hematopoiesis filtering resulted in de novo detection of targetable oncogenic drivers and resistance mechanisms in patients with NSCLC, including when tissue biopsy was inadequate for genotyping.
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