Abstract
OBJECTIVE: Among breast cancer subtypes, triple-negative breast cancer (TNBC) is associated with the poorest prognosis and currently lacks effective targeted therapies. While gene mutation profiling provides valuable insights into recurrent mutations and genomic heterogeneity, the comparative mutational characteristics distinguishing TNBC from non-TNBC tumors have not been comprehensively investigated. This study aims to elucidate these differences through a systematic comparative analysis. METHODS: We retrieved clinical data and somatic mutation profiles of 704 breast cancer patients from The Cancer Genome Atlas (TCGA) database. Based on hormone receptor expression status, the breast cancer samples were stratified into TNBC cohort (n = 109) and non-TNBC cohort (n = 595). Comprehensive genomic analysis was performed to compare differences in mutational profiles between the two cohorts, including differential frequencies of recurrent mutations, interaction patterns of co-occurring and mutually exclusive mutations, driver genes, decomposition of mutational signatures using the Catalogue of Somatic Mutations in Cancer (COSMIC) database, and pathway enrichment of significantly altered genes. RESULTS: Compared to the non-TNBC cohort, the TNBC patients had a younger age at onset. Significant differences were observed in the mutation rate of TP53 (81% vs. 27%, p < 2.2 × 10(- 16)), PIK3CA (11% vs. 38%, p = 5.4 × 10(- 9)) and GATA3 (1% vs. 16%, p = 1.0 × 10(- 6)) between TNBC and non-TNBC cohorts. TNBC also exhibited a higher tumor mutation burden (TMB) than non-TNBC (1.2 vs. 0.6 mutations/Mb). Genes in TNBC predominantly exhibited a co-mutation pattern, whereas non-TNBC showed either co-occurring or mutually exclusive mutational relationships. TTN and PIK3CA were identified as key driver genes in TNBC, while non-TNBC exhibited greater diversity in driver alterations, including MAP3K1 and KMT2C. Mutational signature analysis revealed that Single-Base Substitution2 (SBS2) and SBS6 were common to both cohorts, while SBS3 and SBS26 were predominantly enriched in TNBC, and SBS10b was more frequent in non-TNBC. Pathway enrichment analysis showed that the most affected oncogenic pathways in TNBC were TP53, TGF-Beta, RTK-RAS, and Hippo pathways, whereas non-TNBC involved TP53, TGF-Beta, NRF2, PI3K, and RTK-RAS pathways. CONCLUSIONS: Our study delineates the distinct genomic mutational landscapes between TNBC and non-TNBC cohorts, and reveals somatic interactions, driver genes, mutational signatures and pathway enrichment. These findings highlight the distinct molecular features of TNBC, which may contribute to its aggressive clinical behavior.