The Annals of Applied Statistics

Using somatic mutation data to test tumors for clonal relatedness

Irina Ostrovnaya, Venkatraman E. Seshan, and Colin B. Begg

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A major challenge for cancer pathologists is to determine whether a new tumor in a patient with cancer is a metastasis or an independent occurrence of the disease. In recent years numerous studies have evaluated pairs of tumor specimens to examine the similarity of the somatic characteristics of the tumors and to test for clonal relatedness. As the landscape of mutation testing has evolved, a number of statistical methods for determining clonality have developed, notably for comparing losses of heterozygosity at candidate markers, and for comparing copy number profiles. Increasingly tumors are being evaluated for point mutations in panels of candidate genes using gene sequencing technologies. Comparison of the mutational profiles of pairs of tumors presents unusual methodological challenges: mutations at some loci are much more common than others; knowledge of the marginal mutation probabilities is scanty for most loci at which mutations might occur; the sample space of potential mutational profiles is vast. We examine this problem and propose a test for clonal relatedness of a pair of tumors from a single patient. Using simulations, its properties are shown to be promising. The method is illustrated using several examples from the literature.

Article information

Ann. Appl. Stat., Volume 9, Number 3 (2015), 1533-1548.

Received: March 2014
Revised: May 2015
First available in Project Euclid: 2 November 2015

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Mutational testing cancer pathology


Ostrovnaya, Irina; Seshan, Venkatraman E.; Begg, Colin B. Using somatic mutation data to test tumors for clonal relatedness. Ann. Appl. Stat. 9 (2015), no. 3, 1533--1548. doi:10.1214/15-AOAS836.

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Supplemental materials

  • Supplementary appendix. Explanation of results of simulations with correlated markers. In the on-line supplementary appendix we provide additional calculations and graphs that provide an explanation of the power trends in the presence of correlated markers..