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A Novel Model Based on Necroptosis-Related Genes for Predicting Prognosis of Patients With Prostate Adenocarcinoma

: 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. RNA sequence (RNA-seq) data and c...

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Bibliographic Details
Published in:Frontiers in bioengineering and biotechnology 2022-01, Vol.9, p.814813-814813
Main Authors: Li, Xin-Yu, You, Jian-Xiong, Zhang, Lu-Yu, Su, Li-Xin, Yang, Xi-Tao
Format: Article
Language:English
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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, then constructed a model for prognosis of patients with prostate cancer. 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. A total of 5 necroptosis-related genes, namely and , 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. 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.
ISSN:2296-4185
2296-4185
DOI:10.3389/fbioe.2021.814813