Identification and validation of a prognostic signature of drug resistance and mitochondrial energy metabolism-related differentially expressed genes for breast cancer

作者：Tiankai Xu, Chu Chu, Shuyu Xue, Tongchao Jiang, Ying Wang, Wen Xia, Huan‐Xin Lin · 发表于：Journal of Translational Medicine · 年份：2025 · DOI：10.1186/s12967-025-06080-7 · 被引用次数：10 · 研究领域：Ferroptosis and cancer prognosis、Cancer, Hypoxia, and Metabolism、Mitochondrial Function and Pathology

BACKGROUND: Drug resistance constitutes one of the principal causes of poor prognosis in breast cancer patients. Although cancer cells can maintain viability independently of mitochondrial energy metabolism, they remain reliant on mitochondrial functions for the synthesis of new DNA strands. This dependency underscores a potential link between mitochondrial energy metabolism and drug resistance. Hence, drug resistance and mitochondrial energy metabolism-related differentially expressed genes (DMRDEGs) may emerge as candidates for novel cancer biomarkers. This study endeavors to assess the viability of DMRDEGs as biomarkers or therapeutic targets for breast cancer. METHODS: We utilized the DRESIS database and MSigDB to identify genes related to drug resistance. Additionally, we sourced genes associated with mitochondrial energy metabolism from GeneCards and extant literature. By merging these genes with differentially expressed genes observed in normal and tumor tissues from the TCGA-BRCA and GEO databases, we successfully identified the DMRDEGs. Employing unsupervised consensus clustering, we divided breast cancer patients into two distinct groups based on the DMRDEGs. Consequently, we identified four hub genes to formulate a prognostic model, applying Cox regression, LASSO regression, and Random Forest methods. Furthermore, we examined immune infiltration and tumor mutation burden of the genes within our model and scrutinized divergences in the immune microenvironment betwee...