Abstract

BackgroundCircadian rhythm is an internal timing system generated by circadian-related genes (CRGs). Disruption in this rhythm has been associated with a heightened risk of breast cancer (BC) and regulation of the immune microenvironment of tumors. This study aimed to investigate the clinical significance of CRGs in BC and the immune microenvironment. MethodsCRGs were identified using the GeneCards and MSigDB databases. Through unsupervised clustering, we identified two circadian-related subtypes in patients with BC. We constructed a prognostic model and nomogram for circadian-related risk scores using LASSO and Cox regression analyses. Using multi-omics analysis, the mutation profile and immunological microenvironment of tumors were investigated, and the immunotherapy response in different groups of patients was predicted based on their risk strata. ResultsThe two circadian-related subtypes of BC that were identified differed significantly in their prognoses, clinical characteristics, and tumor immune microenvironments. Subsequently, we constructed a circadian-related risk score (CRRS) model containing eight signatures (SIAH2, EZR, GSN, TAGLN2, PRDX1, MCM4, EIF4EBP1, and CD248) and a nomogram. High-risk individuals had a greater burden of tumor mutations, richer immune cell infiltration, and higher expression of immune checkpoint genes, than low-risk individuals, indicating a “hot tumor" immune phenotype and a more favorable treatment outcome. ConclusionsTwo circadian-related subtypes of BC were identified and used to establish a CRRS prognostic model and nomogram. These will be valuable in providing guidance for forecasting prognosis and developing personalized treatment plans for BC.

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