Sex Differences in Mutational Processes
Constance H. Li,Stephenie D. Prokopec,Ren X. Sun,Fouad Yousif,Nathaniel Schmitz,Paul C. Boutros,Pcawg Molecular Subtypes,Icgc +7 more
TL;DR: The first pan-cancer analysis of sex differences in whole genomes of 1,983 tumours of 28 subtypes from the ICGC Pan-Cancer Analysis of Whole Genomes project is described, confirming the results of exome studies, and uncover previously undescribed sex differences.
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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 describe the first pan-cancer analysis of sex differences in whole genomes of 1,983 tumours of 28 subtypes from the ICGC Pan-Cancer Analysis of Whole Genomes project. 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 cancer research.
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Figures
Fig. 3 Sex differences in mutational signatures related to mutational processes. Comparisons between proportions of signature-positive samples (top) and signature activity (bottom) for a pan-cancer comparisons, b liver hepatocellular cancer, and c B-cell non-Hodgkin lymphoma. FDR-adjusted q-values for multivariate logistic regression (top) and multivariate linear regression (bottom) shown only for significant comparisons. Blue shows male- and pink shows female-derived tumours. Tukey boxplots are shown with the box indicating quartiles and the whiskers drawn at the lowest and highest points within 1.5 interquartile range of the lower and upper quartiles, respectively. 
Fig. 1 Sex-biases in mutation frequency of driver genes, SNV density and tumour evolution. a From top to bottom, each plot shows the logistic regression q-value for the sex effect; difference in proportion of mutated samples between the sexes with blue denoting male-dominated bias; and mutation proportion for each gene. Covariate bars indicate mutation context and tumour subtype of interest. b The burden of somatic SNVs for coding, non-coding and overall mutation load. Linear regression q-values are shown. c Coding mutation load for thyroid adenocarcinoma samples compared by sex and 
Fig. 4 The landscape of sex differences in cancer genomics. Summary of genomic features found to be sex-biased in pan-cancer analysis or in specific tumour subtypes. Results from both PCAWG and TCGA analyses are shown. Direction of sex-bias is shown in coloration denoting which sex has higher or more frequent aberration of the genomic feature. Top plot shows union of genes found to be involved in sex-biased CNAs. Starred indicate findings 
Fig. 2 Sex-biases in percent chromosome altered are reflected in gene-specific events. a A summary of associations between sex and genome instability across tumour subtypes. Dot size shows difference in median percent genome altered or percent chromosome altered between the sexes. Dot colour
Citations
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Divergent mutational processes distinguish hypoxic and normoxic tumours.
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Sex disparities in the incidence of 21 cancer types: Quantification of the contribution of risk factors
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Sex Differences in Mutational Processes
Constance H. Li,Stephenie D. Prokopec,Ren X. Sun,Fouad Yousif,Nathaniel Schmitz,Paul C. Boutros,Pcawg Molecular Subtypes,Icgc +7 more
TL;DR: The first pan-cancer analysis of sex differences in whole genomes of 1,983 tumours of 28 subtypes from the ICGC Pan-Cancer Analysis of Whole Genomes project is described, confirming the results of exome studies, and uncover previously undescribed sex differences.
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TL;DR: It is shown that hypermutation localized to small genomic regions, ‘kataegis’, is found in many cancer types, and this results reveal the diversity of mutational processes underlying the development of cancer.
Fast model-based estimation of ancestry in unrelated individuals
TL;DR: The results show that ADMIXTURE's computational speed opens up the possibility of using a much larger set of markers in model-based ancestry estimation and that its estimates are suitable for use in correcting for population stratification in association studies.
The Repertoire of Mutational Signatures in Human Cancer
Ludmil B. Alexandrov,Jaegil Kim,Nicholas J. Haradhvala,Nicholas J. Haradhvala,Mi Ni Huang,Alvin Wei Tian Ng,Yang Wu,Arnoud Boot,Kyle R. Covington,Dmitry A. Gordenin,Erik N. Bergstrom,S M Ashiqul Islam,Nuria Lopez-Bigas,Nuria Lopez-Bigas,Leszek J. Klimczak,John R. McPherson,Sandro Morganella,Radhakrishnan Sabarinathan,Radhakrishnan Sabarinathan,David A. Wheeler,Ville Mustonen,Gad Getz,Steven G. Rozen,Michael R. Stratton +23 more
TL;DR: The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet- base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.
Mutational Processes Molding the Genomes of 21 Breast Cancers
Serena Nik-Zainal,Ludmil B. Alexandrov,David C. Wedge,Peter Van Loo,Peter Van Loo,Peter Van Loo,Christopher Greenman,Christopher Greenman,Christopher Greenman,Keiran Raine,David T. Jones,Jonathan Hinton,John D Marshall,Lucy Stebbings,Andrew Menzies,Sancha Martin,Kenric Leung,Lina Chen,Catherine Leroy,Manasa Ramakrishna,Richard Rance,King Wai Lau,Laura Mudie,Ignacio Varela,David J. McBride,Graham R. Bignell,Susanna L. Cooke,Adam Shlien,John Gamble,Ian Whitmore,Mark Maddison,Patrick S. Tarpey,Helen Davies,Elli Papaemmanuil,Philip J. Stephens,Stuart McLaren,Adam Butler,Jon W. Teague,Göran Jönsson,Judy Garber,Daniel P. Silver,Penelope Miron,Aquila Fatima,Sandrine Boyault,Anita Langerød,Andrew Tutt,John W.M. Martens,Samuel Aparicio,Åke Borg,Anne Vincent Salomon,Gilles Thomas,Anne Lise Børresen-Dale,Anne Lise Børresen-Dale,Andrea L. Richardson,Michael S. Neuberger,P. Andrew Futreal,Peter J. Campbell,Peter J. Campbell,Peter J. Campbell,Michael R. Stratton +59 more
TL;DR: This work generated catalogs of somatic mutation from 21 breast cancers and applied mathematical methods to extract mutational signatures of the underlying processes, finding a remarkable phenomenon of localized hypermutation, termed “kataegis,” was observed.
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