Stemness-related gene signatures as a predictive tool for breast cancer radiosensitivity

Understanding the role of cancer stemness in predicting breast cancer (BRCA) response to radiotherapy is crucial for optimizing treatment outcomes. This study developed a stemness-based signature to identify BRCA patients who are likely to benefit from radiotherapy.

Gene expression data for BRCA patients were obtained from the TCGA and METABRIC databases, including 920 TCGA-BRCA and 1980 METABRIC-BRCA patients. Univariate and multivariate Cox regression analyses were used to construct a radiosensitivity signature. Immune cell infiltration and pathway enrichment analyses were conducted using ESTIMATE and GSVA methods. The TIDE algorithm and the pRRophetic platform were employed to predict responses to radiotherapy. Radioresistant BRCA cells were examined using a colony formation assay. Key genes identified in the radiosensitivity signature were validated in vitro by qRT-PCR.

By analyzing gene expression data from 920 BRCA samples, we identified a set of 267 stemness-related genes between high and low mRNAsi groups. Based on these genes, a radiosensitivity signature comprising two stemness-related genes (EMILIN1 and CYP4Z1) was constructed, stratifying patients into radiosensitive (RS) and radioresistant (RR) groups. Radiotherapy within the RS group significantly improved prognosis compared to non-radiotherapy patients. This signature was further validated in the METABRIC dataset. Notably, patients in the RS group also exhibited a significantly better response to immunotherapy compared to the RR group. We established a radioresistant BRCA cell line using the MCF-7 breast cancer cell line. A radioresistant breast cancer cell line (MCF-7/IR) was established by progressive exposure to increasing radiation doses. Comparative clonogenic and CCK8 assays demonstrated a radioresistant phenotype in the MCF-7/IR compared to MCF-7. In vitro studies utilizing both the MCF-7/IR and MCF-7 cell lines validated the expression of two radiosensitivity genes.

This study identified a stemness-related gene signature predictive of radiosensitivity in breast cancer. This signature may guide personalized treatment strategies and inform the development of novel radiosensitizing agents.