Integrative analysis of homologous recombination repair patterns unveils prognostic signatures and immunotherapeutic insights in breast cancer

Abstract

Globally, breast cancer (BC) is the leading cause of female death and morbidity. Homologous recombination repair (HRR) is critical in BC. However, the prognostic role and immunotherapy response of HRR in BC remains to be clarified. Firstly, we identified HRR types in BC samples from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset (GSE42568) based on 65 HRR genes (HRRGs). A differentially expressed gene (DEG) list for different HRR types was generated. Then, the influences of gene sets composed of these DEGs on biological pathways and BC prognosis were explored. Next, we identified gene clusters based on gene sets composed of DEGs. Genes associated with prognosis for DEGs were identified using univariate Cox regression. Finally, the HRR score was constructed based on genes associated with prognosis. We analyzed how HRR score correlates with tumor mutation burden (TMB), immune cell infiltration (ICI), and immunotherapy response. Three HRR clusters were discovered. HRR subtype A demonstrated decreased infiltration and a high number of immunosuppressive cells with a poor prognosis. DEGs among various HRR types were predominantly enriched in cell cycle and genomic stability-related pathways. The prognostic model based on sixteen DEGs accurately predicted BC prognosis. The HRRGs were differentially expressed in three DEG clusters. TMB, ICI, and immunotherapy responses differed significantly between the high and low HRR groups (HSG, LSG). The HSG was distinguished by a high degree of ICI and low TMB. LSG had a better response to anti-PD-1 or anti-PD-1 and anti-CTLA4 combination therapy. This work revealed that HRR patterns would contribute to predicting prognosis and immunotherapy response in BC, which may benefit patients.