Discovery of a DNA repair-associated radiosensitivity index for predicting radiotherapy efficacy in breast cancer

Abstract

Purpose: Radiotherapy is a cornerstone of breast cancer (BRCA) treatment. Accurately predicting tumor radiosensitivity is critical for optimizing therapeutic outcomes and personalizing treatment strategies. DNA repair pathways are key determinants of radiotherapy response. Thus, we aimed to develop a novel DNA repair-related radiosensitivity model and to identify potential targets for enhancing radiotherapy efficacy. Methods: A retrospective study was conducted using data from 942 BRCA patients from TCGA database. A radiosensitivity model, comprising a radiosensitivity index, was developed using LASSO regression analysis. Patients were stratified into radiosensitive (RS) and radioresistant (RR) groups based on their radiosensitivity index (RSI). Associations between the RSI, clinicopathological parameters, and PD-L1 status were analyzed. The CIBERSORT and ESTIMATE algorithms were employed to characterize the immune landscape of the tumor microenvironment. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and pRRophetic platform were used to predict treatment responses. Key genes identified in the radiosensitivity model were further validated using in vitro qRT-PCR experiments. Results: We successfully constructed a radiosensitivity index incorporating 10 DNA repair-related genes. Patients in the RS group exhibited significantly better prognosis compared to the RR group, but this benefit was limited to those receiving radiotherapy. This survival benefit associated with the radiosensitivity signature was absent in patients who did not receive radiotherapy. The RS group displayed a distinct molecular profile characterized by enrichment of TGF-β signaling and protein secretion pathways, potentially contributing to enhanced radiosensitivity. Furthermore, the RS group exhibited increased infiltration of immune cells. Notably, the RS-PD-L1-high subgroup demonstrated the most favorable survival outcomes and highest immune cell infiltration, highlighting their potential responsiveness to immunotherapy. In addition, the RR group exhibited a distinct profile characterized by enrichment of DNA repair pathways and a heightened sensitivity to CDK and HER2 inhibitors. Conversely, this group displayed resistance to DNA-damaging drugs. These findings were supported by in vitro experiments using MCF-7 and radioresistant MCF-7/IR cell lines, confirming differential expression of key radiosensitivity index genes. Conclusion: In conclusion, we established a radiosensitivity model for predicting radiotherapy benefit in breast cancer. Our study reveals a strong association between radiosensitivity, enhanced antitumor immunity, and potential immunotherapy benefit, particularly within the RS-PD-L1-high subgroup.