Sensitive Detection of Somatic Point Mutations in Impure and Heterogeneous Cancer Samples

Overview

Journal Nat Biotechnol

Specialty Biotechnology

Date 2013 Feb 12

PMID 23396013

Citations 2794

Authors

Kristian Cibulskis

Michael S Lawrence

Scott L Carter

Andrey Sivachenko

David Jaffe

Carrie Sougnez

Stacey Gabriel

Matthew Meyerson

Eric S Lander

Gad Getz

Affiliations

Soon will be listed here.

Abstract

Detection of somatic point substitutions is a key step in characterizing the cancer genome. However, existing methods typically miss low-allelic-fraction mutations that occur in only a subset of the sequenced cells owing to either tumor heterogeneity or contamination by normal cells. Here we present MuTect, a method that applies a Bayesian classifier to detect somatic mutations with very low allele fractions, requiring only a few supporting reads, followed by carefully tuned filters that ensure high specificity. We also describe benchmarking approaches that use real, rather than simulated, sequencing data to evaluate the sensitivity and specificity as a function of sequencing depth, base quality and allelic fraction. Compared with other methods, MuTect has higher sensitivity with similar specificity, especially for mutations with allelic fractions as low as 0.1 and below, making MuTect particularly useful for studying cancer subclones and their evolution in standard exome and genome sequencing data.

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