Abstract
Background: Necroptosis is a newly recognized form of cell death. Here, we applied bioinformatics tools to identify necroptosis-related genes using a dataset from The Cancer Genome Atlas (TCGA) database, then constructed a model for prognosis of patients with prostate cancer. Methods: RNA sequence (RNA‐seq) data and clinical information for Prostate adenocarcinoma (PRAD) patients were obtained from the TCGA portal (http://tcga-data.nci.nih.gov/tcga/). We performed comprehensive bioinformatics analyses to identify hub genes as potential prognostic biomarkers in PRAD u followed by establishment and validation of a prognostic model. Next, we assessed the overall prediction performance of the model using receiver operating characteristic (ROC) curves and the area under curve (AUC) of the ROC. Results: A total of 5 necroptosis-related genes, namely ALOX15, BCL2, IFNA1, PYGL and TLR3, were used to construct a survival prognostic model. The model exhibited excellent performance in the TCGA cohort and validation group and had good prediction accuracy in screening out high-risk prostate cancer patients. Conclusion: We successfully identified necroptosis-related genes and constructed a prognostic model that can accurately predict 1- 3-and 5-years overall survival (OS) rates of PRAD patients. Our riskscore model has provided novel strategy for the prediction of PRAD patients’ prognosis.
Highlights
Necroptosis is a newly recognized form of cell death
RNA sequence (RNA-seq) data and clinical information for Prostate adenocarcinoma (PRAD) patients were obtained from the The Cancer Genome Atlas (TCGA) portal
We evaluated the relationship between necroptosis-related genes and prognosis of PRAD patients
Summary
Necroptosis is a newly recognized form of cell death. Here, we applied bioinformatics tools to identify necroptosis-related genes using a dataset from The Cancer Genome Atlas (TCGA) database, constructed a model for prognosis of patients with prostate cancer. Prostate adenocarcinoma (PRAD) is a complex but common malignancy that accounts for about 1300000 new cases and 360,000 deaths every year worldwide. PRAD accounts for 15% of all new tumor-related cases, making it the second most common neoplasia in elderly males, and the fifth most frequent cause of cancer-related deaths worldwide (Bray et al, 2018; Siegel et al, 2020). Previous studies have shown that necroptosis, which was first identified and named in 2005, is regulated by intracellular signaling pathways (Degterev et al, 2005). This phenomenon can be unmediated by caspases, functioning upon inhibition of apoptotic pathways. We systematically analyzed differential expression profiles of necroptosis-related genes between normal and PRAD tissues, developed a novel risk-scorebased model for predicting prognosis of PRAD patients
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