Clinical actionability enhanced through deep targeted sequencing of solid tumors.

BACKGROUND: Further advances of targeted cancer therapy require comprehensive in-depth profiling of somatic mutations that are present in subpopulations of tumor cells in a clinical tumor sample. However, it is unclear to what extent such intratumor heterogeneity is present and whether it may affect clinical decision-making. To study this question, we established a deep targeted sequencing platform to identify potentially actionable DNA alterations in tumor samples. METHODS: We assayed 515 formalin-fixed paraffin-embedded (FFPE) tumor samples and matched germline DNA (475 patients) from 11 disease sites by capturing and sequencing all the exons in 201 cancer-related genes. Mutations, indels, and copy number data were reported. RESULTS: We obtained a 1000-fold mean sequencing depth and identified 4794 nonsynonymous mutations in the samples analyzed, of which 15.2% were present at <10% allele frequency. Most of these low level mutations occurred at known oncogenic hotspots and are likely functional. Identifying low level mutations improved identification of mutations in actionable genes in 118 (24.84%) patients, among which 47 (9.8%) otherwise would have been unactionable. In addition, acquiring ultrahigh depth also ensured a low false discovery rate (<2.2%) from FFPE samples. CONCLUSIONS: Our results were as accurate as a commercially available CLIA-compliant hotspot panel but allowed the detection of a higher number of mutations in actionable genes. Our study reveals the critical importance of acquiring and utilizing high sequencing depth in profiling clinical tumor samples and presents a very useful platform for implementing routine sequencing in a cancer care institution.

Precision Oncology Decision Support: Current Approaches and Strategies for the Future.

With the increasing availability of genomics, routine analysis of advanced cancers is now feasible. Treatment selection is frequently guided by the molecular characteristics of a patient's tumor, and an increasing number of trials are genomically selected. Furthermore, multiple studies have demonstrated the benefit of therapies that are chosen based upon the molecular profile of a tumor. However, the rapid evolution of genomic testing platforms and emergence of new technologies make interpreting molecular testing reports more challenging. More sophisticated precision oncology decision support services are essential. This review outlines existing tools available for health care providers and precision oncology teams and highlights strategies for optimizing decision support. Specific attention is given to the assays currently available for molecular testing, as well as considerations for interpreting alteration information. This article also discusses strategies for identifying and matching patients to clinical trials, current challenges, and proposals for future development of precision oncology decision support. Clin Cancer Res; 24(12); 2719-31. ©2018 AACR.