| Summary: | Necroptosis is a genetically regulated form of necrotic cell death that has emerged as an important pathway in cancers. Long non-coding RNAs (lncRNAs) are key regulators of breast cancer development. Nevertheless, few studies are reporting the effect of lncRNAs in necroptosis processes and the role of necroptosis-related lncRNAs (NRLs). The present study aimed to construct a prognostic model based on NRLs in breast cancer. NRLs were identified by combining expression profiling data from The Cancer Genome Atlas (TCGA) with necroptosis-related genes. The non-negative matrix factorization (NMF) clustering analysis was conducted to identify molecular subtypes of BC, and the clinical outcome and tumor-infiltrating immune cells (TIICs) in the different molecular subtypes were analyzed. Four molecular subtypes based on NRLs were identified, and these four molecular subtypes could predict clinical features, prognosis, and tumor-infiltrating immune cells (TIICs). A 4-NRLs signature and nomogram were established and validated its predictive capability of overall survival (OS) in breast cancer patients. Analyses of clinicopathological features, prognosis, TIICs, tumor microenvironment (TME), somatic mutations, and drug response revealed significant differences between the two risk groups. In addition, we found that low-risk patients exhibited higher levels of immune checkpoints and showed higher immunogenicity in immunophenoscore (IPS) analysis. In conclusion, we constructed a prognostic model based on the expression profile of NRLs, which may facilitate the assessment of patient prognosis, immunotherapeutic responses, and maybe a promising therapeutic target in clinical practice. © 2022, The Author(s).
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