ABSTRACT
Gene mutation detection and the resulted precision-medicine therapy is transforming clinical practice. Here, we report the use of a custom-developed, medium-sized, pan-cancer probe panel for the detection of somatic and germline mutations. We used a hybridization capture-based NGS assay for targeted deep sequencing of all exons and selected introns of 181 key cancer driver genes, covering both inherited risks and somatic mutations. We performed paired-variant calling on tumor samples and their matched normal samples. We processed clinical patient samples of formalin-fixed, paraffin embedded tumors (FFPE samples) and cell-free peripheral blood (cfDNA samples). We found germline mutations of inherited cancer risk at 9%; and discovered a novel germline mutation in BRCA1. Somatic mutation rate in driver genes is at 73.1%, much higher than previously reported. On recommending precision-medicine therapeutics, we achieved 91.6% for patients with FFPE samples.
Subject(s)
High-Throughput Nucleotide Sequencing , Neoplasms , Germ Cells , Germ-Line Mutation , High-Throughput Nucleotide Sequencing/methods , Humans , Mutation , Neoplasms/genetics , Paraffin EmbeddingABSTRACT
FD-180 and FD-600 are two next-generation sequencing panels developed by First Dimension Biosciences Co. for detecting mutations in cancer tissues and providing therapeutics guidance in precision medicine applications. FD-180 includes the coding exons of about 180 genes, including all the known drug target genes and some important driver genes; whereas FD-600 includes the coding exons of 578 cancer driver genes in the COSMIC database as of year 2016 when the panels are developed. Additional noncoding regions in the selected genes are included if they are reported as clinically meaningful in ClinVar. Tumor mutation burden (TMB) is a statistical index calculated from genomic sequencing for immunotherapeutic treatments, especially for PD1/PD-L1 antibodies. We used our computational algorithm on 81 patients and provided their classifications. TMB can be estimated quite accurately for the FD-180 and FD-600 panels, both for The Cancer Genome Atlas data and in clinical practice.
