Abstract

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. 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. 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. 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.

Highlights

  • Generation sequencing (NGS) can significantly facilitate personalized cancer therapy approaches by identifying actionable somatic events in tumor samples [1]

  • Our study revealed the critical importance of acquiring and utilizing high depth in profiling clinical tumor samples and presented a very useful platform for implementing routine sequencing in a cancer care institution

  • We aimed to determine a minimum sequencing depth at which we were confident in detecting very low-frequency mutations

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Summary

Introduction

Generation sequencing (NGS) can significantly facilitate personalized cancer therapy approaches by identifying actionable somatic events in tumor samples [1]. The relatively low coverage of WGS and WES, as currently implemented in most of the sequencing laboratories (100–250x), may have limited ability to cost-effectively detect aberrations that are present in a subpopulation of tumor cells while identifying a myriad of aberrations of unknown clinical significance [2]. 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. It is unclear to what extent such intra-tumor heterogeneity is present and whether it may affect clinical decision making. To unravel this challenge, we established a deep targeted sequencing platform to identify potentially actionable DNA alterations in tumor samples

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