Sex differences in oncogenic mutational processes

Li, Constance H.; Prokopec, Stephenie D.; Sun, Ren X.; Yousif, Fouad; Schmitz, Nathaniel; PCAWG Tumour Subtypes and Clinical Translation; Boutros, Paul C.; PCAWG Consortium

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Date

28/08/2020

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Abstract

Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research.

Citation

Li , C H , Prokopec , S D , Sun , R X , Yousif , F , Schmitz , N , PCAWG Tumour Subtypes and Clinical Translation , Boutros , P C & PCAWG Consortium 2020 , ' Sex differences in oncogenic mutational processes ' , Nature Communications , vol. 11 , 4330 . https://doi.org/10.1038/s41467-020-17359-2

Publication

Nature Communications

Status

Peer reviewed

DOI

https://doi.org/10.1038/s41467-020-17359-2

ISSN

2041-1723

Type

Journal article

Rights

Copyright © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Description

This study was conducted with the support of the Ontario Institute for Cancer Research to P.C.B. through funding provided by the Government of Ontario. This work was supported by the Discovery Frontiers: Advancing Big Data Science in Genomics Research program, which is jointly funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada, the Canadian Institutes of Health Research (CIHR), Genome Canada and the Canada Foundation for Innovation (CFI). P.C.B. was supported by a Terry Fox Research Institute New Investigator Award and a CIHR New Investigator Award. This work was supported by an NSERC Discovery grant and by Canadian Institutes of Health Research, grant #SVB-145586, to P.C.B. This work was supported by the NIH/NCI under award number P30CA016042 and an operating grant from the National Cancer Institute Early Detection Research Network (1U01CA214194-01).

Collections

University of St Andrews Research

URI

http://hdl.handle.net/10023/20993