A Novel Model Based on Necroptosis-Related Genes for Predicting Prognosis of Patients With Prostate Adenocarcinoma - Li, Xin-yu; You, Jian-xiong; Zhang, Lu-yu; Su, Li-xin; Yang, Xi-tao (Frontiers in Bioengineering and Biotechnology, 2022)
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 database, and construct a nomogram model for prognosis of patients with prostate cancer. Methods: RNA‐seq expression and clinical information of Prostate adenocarcinoma (PRAD) patients were obtained from TCGA data portal(http://tcga-data.nci.nih.gov/tcga/). Identification of hub genes as potential prognostic biomarkers in PRAD using comprehensive bioinformatics analysis and validation studies. We assessed the overall prediction performance in terms of the receiver operating characteristic (ROC) curves and the area under the ROC curve(AUC). Results: A total of 5 necroptosis -related genes (ALOX15, BCL2, IFNA1, PYGL and TLR3) were used to construct a survival prognostic model. The model performed well in the TCGAand validation group and had good prediction accuracy and could screen out high-risk prostate cancer patients. Conclusions: In summary, we identified and constructed a prognostic model that could be used to predict overall survival of PRAD patients. The model can accurately and conveniently predict the 1- 3-and 5-year OS of PRAD patients.