Identification of the prognostic value of ferroptosis-related gene signature in breast cancer patients

作者：Ding Wang, Guodong Wei, Ju Ma, Shuai Cheng, Longyuan Jia, Xinyue Song, Ming Zhang, Mingyi Ju, Lin Wang, Lin Zhao, Shijie Xin · 发表于：BMC Cancer · 年份：2021 · DOI：10.1186/s12885-021-08341-2 · 被引用次数：136 · 研究领域：Ferroptosis and cancer prognosis、Immune cells in cancer、Cancer, Stress, Anesthesia, and Immune Response

BACKGROUND: Breast cancer (BRCA) is a malignant tumor with high morbidity and mortality, which is a threat to women's health worldwide. Ferroptosis is closely related to the occurrence and development of breast cancer. Here, we aimed to establish a ferroptosis-related prognostic gene signature for predicting patients' survival. METHODS: Gene expression profile and corresponding clinical information of patients from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database. The Least absolute shrinkage and selection operator (LASSO)-penalized Cox regression analysis model was utilized to construct a multigene signature. The Kaplan-Meier (K-M) and Receiver Operating Characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes, Genomes (KEGG) pathway and single-sample gene set enrichment analysis (ssGSEA) were performed for patients between the high-risk and low-risk groups divided by the median value of risk score. RESULTS: We constructed a prognostic signature consisted of nine ferroptosis-related genes (ALOX15, CISD1, CS, GCLC, GPX4, SLC7A11, EMC2, G6PD and ACSF2). The Kaplan-Meier curves validated the fine predictive accuracy of the prognostic signature (p < 0.001). The area under the curve (AUC) of the ROC curves manifested that the ferroptosis-related signature had moderate predictive power. GO and KEGG functional analysis revealed that immune-related resp...