Analysis of a new therapeutic target and construction of a prognostic model for breast cancer based on ferroptosis genes

• Published in: Computers in biology and medicine Vol. 165; p. 107370
• Main Authors: Li, Qi, Liu, Hengchen, Jin, Yun, Yu, Yuanquan, Wang, Yihang, Wu, Di, Guo, Yinghao, Xi, Longfu, Ye, Dan, Pan, Yanzhi, Zhang, Xiaoxiao, Li, Jiangtao
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.10.2023; Elsevier Limited
• Subjects: Adenomatous polyposis coli; Antigen-presenting cells; Apoptosis; Breast cancer; CD8 antigen; CD80 antigen; Cell death; Drug development; Drugs; Ferroptosis; Gene expression; Genes; Genomes; Immunosuppressive agents; Immunotherapy; Immunotherapy targets; LILRA2 protein; Lipid peroxidation; Lipids; Lymphocytes; Lymphocytes B; Lymphocytes T; Medical prognosis; Patients; Peroxidation; Prediction models; Prognosis; Prognostic model; Regression analysis; Statistical analysis; Survival; Therapeutic applications; Therapeutic targets; Tumors; Prognostic model; Ferroptosis; Breast cancer; Immunotherapy targets
• ISSN: 0010-4825; 1879-0534
• DOI: 10.1016/j.compbiomed.2023.107370

Breast cancer, which is the most common malignant tumor among women worldwide and an important cause of death in women. The existing prognostic model for patients with breast cancer is not accurate as breast cancer is resistant to commonly used antitumor drugs. Ferroptosis is a novel mechanism of programmed cell death that depends on iron accumulation and lipid peroxidation. Various studies have confirmed the role of ferroptosis in tumor regulation and ferroptosis is now considered to play an important role in breast cancer development. At present, the association between breast cancer prognosis and ferroptosis-related gene expression remains unclear. Further exploration of this research area may optimize the evaluation and prediction of prognosis of patients with breast cancer and finding of new therapeutic targets. In this study, clinical factors and the expression of multiple genes were evaluated in breast cancer samples from the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database database. Eleven prognostication-related genes (TP63, IFNG, MT3, ANO6, FLT3, PTGS2, SLC1A4, JUN, SLC7A5, CHAC1, and TF) were identified from differentially expressed genes to construct a survival prediction model, which showed a good prediction ability. KEGG pathway analysis revealed that immune-related pathways were the primary pathways. ssGSEA analysis showed significant differences in the distribution of certain immune-related cell subsets, such as CD8+T cells and B cells, and in the expression of multiple immune genes, including type II IFN response and APC coinhibition. In addition, 10 immune targets related to ferroptosis in breast cancer were found: CD276, CD80, HHLA2, LILRA2, NCR3LG1, NECTIN3, PVR, SLAMF9,TNFSF4, and BTN1A1. Using TCGA, new ferroptosis genes related to breast cancer prognosis were identified, a new reliable and accurate prognosis model was developed, and 10 new potential therapeutic targets different from the traditional targeted drugs were identified to provide a reference for improving the poor prognosis of patients with breast cancer. •Identified ferroptosis genes associated with prognosis in BC patients.•Built correlation networks based on ferroptosis genes related to survival.•Discovered the crucial role of JUN in ferroptosis in breast cancer.•Built an accurate prognostic survival model associated with ferroptosis in BC.•Identified immune therapy targets associated with prognosis in BC patients.