Identification of a novel necroptosis-related classifier to predict prognosis and guide immunotherapy in breast invasive carcinoma

BackgroundNecroptosis plays a crucial function in the progression of breast invasive carcinoma (BRCA). It may be triggered in cancer therapy to enhance anti-tumor immunity. However, the functions of necroptosis in tumors and its relationship with the tumor microenvironment (TME) remain largely unclear. MethodsNecroptosis-related genes (NRGs) were collated from high-quality literature reviews. A robust risk model was constructed to systematically evaluate the clinical value, functional status, effects exerted by the risk model on the TME, and the genomic variations based on the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) meta-cohorts. ResultsA risk model was constructed which comprised of six NRGs, including TNF receptor-associated factor 5 (TRAF5), Toll-like receptor 3 (TLR3), a riboflavin kinase (RFK), Fas ligand (FASLG), Fas-associated protein with death domain (FADD), and baculoviral IAP repeat-containing 3 (BIRC3). The stability and accuracy of the risk model were demonstrated for both the training and validation cohorts and its utility as an independent prognostic model for BRCA was verified. Patients in the low-risk group exhibited "hot" tumors having active immune and cell killing functions, while those in the high-risk group showed "cold" tumors having active tumor proliferation and immunosuppression. Moreover, patients in the high-risk group had a greater number of CNV events in their genome, while the somatic mutations were fewer. Furthermore, patients in the low-risk group showed high sensitivity toward immunotherapy and chemotherapy. ConclusionA reliable risk model based on NRGs to assess patient prognoses and guide clinical decision-making was constructed and validated. Our findings may contribute to the understanding of necroptosis and aid clinical management, along with precision treatment in BRCA.