Deciphering Circadian Rhythm-Related Molecular Subtypes in Breast Cancer and Establishing a Prognostic Prediction Model.

Background: Recent evidence suggests that alterations in circadian rhythm genes may lead to circadian rhythm disruption (CRD), which is a key mechanism in the progression of breast cancer. Therefore, investigating the role of circadian rhythm genes in the prognosis of breast cancer holds significant clinical value. Materials and Methods: We utilized expression profile data from the Gene Expression Omnibus (GEO) database to identify cancer features closely associated with CRD in breast cancer. Then, we analyzed publicly available datasets (including GEO, TCGA, and METABRIC) to identify alterations in core circadian genes significantly associated with patient survival across breast cancer and constructed a circadian-related gene signature (CGS) based on these prognostic cancer features. Results: Circadian rhythm-related genes (CRGs) were selected to construct a risk gene signature associated with individual prognosis, which was validated in six independent cohorts and demonstrated good predictive ability. We identified three circadian rhythm-associated subtypes with distinct prognoses, which exhibited significant differences in immune checkpoint molecules, drug sensitivity, and molecular features. Additionally, the gene signature and clinicopathologic features were integrated to develop a risk model with enhanced predictive accuracy. To validate the functional role of signature genes, BMAL1 knockdown in SKBR3 cells disrupted circadian rhythms, with qPCR confirming altered risk gene expression. We found that the nomogram exhibited superior discriminative ability compared to the traditional breast cancer staging system. Conclusion: We developed a nomogram that can accurately predict the prognosis of breast cancer, and conclude that the expression of CRGs is crucial in breast cancer treatment decisions.