Accuracy and content-enhanced exome and transcriptome sequencing to guide therapeutic decision making in cancer treatment.

e22107 Background: With the advent of next-generation sequencing techniques, tumor mutations that guide therapeutic decisions can be identified on a large scale. The ability to accurately detect these mutations is crucial but often impaired by obstacles such as sequencing coverage gaps, small sample size, low cellularity, and tumor heterogeneity. Before sequencing can help direct personalized cancer therapies, these obstacles must be overcome. Methods: We developed a unique targeted exome sequencing assay to augment and improve detection of major cancer mutations. We compared our enhanced exome to standard exome using a set of ten cell lines from the NCI-60 panel. To gauge assay performance on cancer-related genes, we curated a comprehensive set of cancer genes that have previously been implicated in a range of tumor types and annotated them with clinically relevant information. Bioinformatics pipelines were developed to accurately call somatic point mutations and indels, amplifications, and deletions. Finally, we performed transcriptome sequencing to determine mRNA expression, allelic expression, alternative splicing, and gene fusion events in these samples. Results: We define a “finished” gene as a gene sequenced at 20x depth or higher across at least 99% of its bases. By this definition, our enhanced exome finishes 828 of 883 cancer genes (94%), compared with standard exome, which finishes just 577 cancer genes (65%) with the same amount of sequencing (12G). Within this set of genes, we report several known clinically-actionable driver mutations. We also annotate current clinical trials and FDA-approved therapies for the mutated genes. Finally, we combine RNA-seq evidence to validate expressed mutations discovered in the exome, as well as quantify transcript isoform expression, and identify known gene fusions in these cell lines. Conclusions: For cancer exome and transcriptome analysis to effectively guide clinical decisions, accuracy across cancer genes is of paramount importance. The enhanced exome plus transcriptome analysis presented here will lead to increased patient-therapy matching and, it is our hope, to improved patient outcomes.