Sex differences in oncogenic mutational processes

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.

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 presence or absence of TERT promoter mutations. d The proportion of polyclonal samples and e the proportion of truncal structural variants in biliary cancer. 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. Error bars show the 95% confidence interval for the difference in proportions or medians between the sexes.

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 shows direction of bias, with blue indicating higher instability in male-derived tumours and pink indicating higher instability in female-derived tumours. Background shading shows q-values from multivariate linear regression. Sex differences in CNAs for b pan-cancer, c kidney renal cell cancer, and d hepatocellular cancer. Each plot shows, from top to bottom: the q-value showing significance of sex from multivariate linear modelling with yellow/green points corresponding to 0.1 < q < 0.05, deep blue/red points corresponding to q < 0.05, and grey points indicating hits that were attributed to covariate sample size imbalances and rejected; the proportion of samples with aberration; the difference in proportion between male and female groups for copy number gain events; the same repeated for copy number loss events; and the copy number aberration (CNA) profile heatmap. The columns represent genes ordered by chromosome. Light blue and pink points represent data for male- and female-derived tumours respectively.

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. 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 exclusively from exome sequencing data (n = 7131), un-starred indicate findings from PCAWG data (n = 1983), and double-starred indicate findings also described in other studies.