Obesity-associated gene mutations across cancer types: a pan-cancer analysis of TCGA data

TL;DR

This study explores how obesity affects cancer mutations by analyzing data from 14 cancer types, finding that higher BMI is linked to specific gene mutations in bladder cancer.

Contribution

The study identifies obesity-associated gene mutations in bladder cancer and suggests that BMI influences tumor genomic profiles.

Findings

Bladder urothelial cancer (BLCA) showed the strongest association with higher BMI-related mutations.

Ten genes in BLCA were prioritized as significantly associated with BMI, including BRCA2 and SF3B1.

Obese patients exhibited distinct mutational patterns and loss-of-function mechanisms in key genes.

Abstract

Obesity is a recognized risk factor for numerous cancers. Although several biological mechanisms have been proposed to explain obesity-associated carcinogenesis, the extent to which excess adiposity influences tumor genomic profiles remains incompletely understood. In particular, whether obesity-related selective pressures shape cancer-specific mutational landscapes is still underexplored.

A pan-cancer analysis of non-synonymous somatic mutations across 14 tumor types using data from The Cancer Genome Atlas (TCGA) has been conducted. Body mass index (BMI) at diagnosis was analyzed as a continuous variable. Associations between gene mutations and BMI were assessed using logistic regression models adjusted for age, sex, and tumor mutational burden, with false discovery rate correction. Genes were prioritized using a two-step ranking strategy based on mutation frequency and regression strength. Functional inactivation, exon-level mutation distribution, and Gene Ontology enrichment analyses were performed for significantly BMI-associated genes.

In particular, bladder urothelial cancer (BLCA) resulted as the most frequently mutated neoplasia in association with higher body mass index. Among Eighty-six genes significantly associated with BMI in BLCA, a prioritized set of ten genes (BRCA2, DNAH9, GRIA4, PLXNA4, UNC13C, FCGBP, SF3B1, ELP1, NES, TRERF1) has been selected for further analyses. Overweight and obese patients exhibited distinct BMI-specific exon-level mutational patterns and concurrent deleterious mutations across multiple candidate genes. Functional inactivation analysis suggested loss-of-function mechanisms in most top-ranked genes, while Gene Ontology (GO) analysis highlighted deregulation of extracellular matrix–related pathways.

These findings support a role for obesity in shaping the genomic landscape of tumors, highlighting the importance of integrating clinical parameters such as BMI into genomic studies to determine the potential impact of obesity on tumor evolution, heterogeneity, and treatment response.

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