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Detection of low prevalence somatic mutations in solid tumors with ultra-deep targeted sequencing

Olivier Harismendy12*, Richard B Schwab1, Lei Bao1, Jeff Olson3, Sophie Rozenzhak12, Steve K Kotsopoulos3, Stephanie Pond4, Brian Crain1, Mark S Chee4, Karen Messer1, Darren R Link3 and Kelly A Frazer125*

Author Affiliations

1 Moores UCSD Cancer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA

2 Department of Pediatrics and Rady Children's Hospital, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA

3 RainDance Technologies, 44 Hartwell Avenue, Lexington, MA 02421, USA

4 Prognosys Biosciences, 505 Coast Blvd, La Jolla, CA 92037, USA

5 Institute for Genomic Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA

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Genome Biology 2011, 12:R124  doi:10.1186/gb-2011-12-12-r124

Published: 20 December 2011

Abstract

Ultra-deep targeted sequencing (UDT-Seq) can identify subclonal somatic mutations in tumor samples. Early assays' limited breadth and depth restrict their clinical utility. Here, we target 71 kb of mutational hotspots in 42 cancer genes. We present novel methods enhancing both laboratory workflow and mutation detection. We evaluate UDT-Seq true sensitivity and specificity (> 94% and > 99%, respectively) for low prevalence mutations in a mixing experiment and demonstrate its utility using six tumor samples. With an improved performance when run on the Illumina Miseq, the UDT-Seq assay is well suited for clinical applications to guide therapy and study clonal selection in heterogeneous samples.