Abstract

BackgroundThe somatic mutations found in a tumor have in most cases been caused by multiple mutational processes such as those related to extrinsic carcinogens like cigarette smoke, and those related to intrinsic processes like age-related spontaneous deamination of 5-methylcytosine. The effect of such mutational processes can be modeled by mutational signatures, of which two different conceptualizations exist: the model introduced by Alexandrov et al., Nature 500:415–421, 2013, and the model introduced by Shiraishi et al., PLoS Genetics 11(12):e1005657, 2015. The initial identification and definition of mutational signatures requires large sets of tumor samples.ResultsHere, we present decompTumor2Sig, an easy to use R package that can decompose an individual tumor genome into a given set of Alexandrov-type or Shiraishi-type signatures, thus quantifying the contribution of the corresponding mutational processes to the somatic mutations identified in the tumor. Until now, such tools were available only for Alexandrov signatures. We demonstrate the correctness and usefulness of our approach with three test cases, using somatic mutations from 21 breast cancer genomes, from 435 tumor genomes of ten different tumor entities, and from simulated tumor genomes, respectively.ConclusionsThe decompTumor2Sig package is freely available and has been accepted for inclusion in Bioconductor.

Highlights

  • The somatic mutations found in a tumor have in most cases been caused by multiple mutational processes such as those related to extrinsic carcinogens like cigarette smoke, and those related to intrinsic processes like age-related spontaneous deamination of 5-methylcytosine

  • We present a user-friendly R package, called decompTumor2Sig, that can be used to evaluate the contribution of Shiraishi signatures to the somatic mutations found in an individual tumor, allowing larger sequence contexts to be taken into consideration than with Alexandrov signatures. (In addition, the package can just as well be used for Alexandrov signatures, but we will discuss mostly Shiraishi signatures here)

  • Contribution of signatures to individual tumor samples To derive the influence of a given set of Shiraishi signatures on the generation of the mutational catalog of an individual tumor sample, the decompTumor2Sig package takes the same quadratic programming approach used by Lynch for Alexandrov signatures [7]

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Summary

Introduction

The somatic mutations found in a tumor have in most cases been caused by multiple mutational processes such as those related to extrinsic carcinogens like cigarette smoke, and those related to intrinsic processes like age-related spontaneous deamination of 5-methylcytosine. The effect of such mutational processes can be modeled by mutational signatures, of which two different conceptualizations exist: the model introduced by Alexandrov et al, Nature 500:415–421, 2013, and the model introduced by Shiraishi et al, PLoS Genetics 11(12):e1005657, 2015. Krüger and Piro BMC Bioinformatics 2019, 20(Suppl 4):152

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