Sex differences in gastric cancer mutational burden reflect MLH1-associated epigenetic regulation
摘要
Tumor mutational burden (TMB) is widely used as a biomarker for predicting response to immune checkpoint inhibitors. Therefore, understanding its variability across patient groups, particularly between sexes, and its underlying biological determinants is of critical importance.
MethodsWe analyzed autosomal TMB and its association with DNA repair–related regulatory mechanisms in gastric cancer across TCGA-STAD and independent targeted sequencing cohorts. Sex-stratified analyses were integrated with gene expression, promoter methylation, and regression modeling.
ResultsFemale tumors exhibited significantly higher autosomal TMB compared with male tumors, with differences most pronounced in older female patients. Across tumors, TMB was strongly associated with reduced MLH1 expression and increased MLH1 promoter methylation, while female tumors exhibited significantly higher MLH1 methylation levels. These relationships are consistent with mismatch repair deficiency as a major driver of mutation accumulation. In multivariable regression models adjusting for MLH1 methylation and expression, the association between sex and TMB was attenuated, suggesting that MLH1-related processes contribute to the observed sex differences. Subtype-aware analyses further suggested that the female-associated TMB elevation was partly related to increased representation of MSI/MMR-deficient tumors among females, while female and male MSI tumors showed comparable TMB. Independent targeted sequencing cohorts showed consistent directional trends, although these did not reach statistical significance.
ConclusionsTogether, our findings indicate that sex differences in mutation burden are linked to MLH1-associated epigenetic regulation, mismatch repair deficiency, and MSI/MMR-deficient tumor biology. These results highlight the importance of incorporating sex-specific molecular context into the interpretation of genomic biomarkers and support a more refined, biologically informed approach to precision oncology.