Construction and Validation of Necroptosis Risk-Scoring Signature in Lung Adenocarcinoma
Department of Intensive Care Medicine, Emergency Department, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hankou, Wuhan 430030, China
Y. S. Li, Department of Intensive Care Medicine, Emergency Department, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hankou, Wuhan 430030, China, E-mail: firstname.lastname@example.org
Lung adenocarcinoma is one of the most common tumors in humans. By exploring the role of necroptosis in lung adenocarcinoma, we aimed to gather information which can be used to build a necroptosis-relatedgene- based diagnostic model that can play an auxiliary role in lung adenocarcinoma diagnosis and treatment. Necroptosis-related genes were selected from the Kyoto Encyclopedia of genes and genomes database. Differentially expressed genes in the tumor group and normal group were identified from The Cancer Genome Atlas/Genomic Data Commons database then analyzed by gene ontology, Kyoto Encyclopedia of genes and genomes and gene set enrichment analysis. Cox and Lasso regression analyses were used to screen out prognosis-related necroptosis-related genes from the differentially expressed genes and establish a necroptosis risk-scoring signature. The receiver operating characteristic curves were plotted and patients were divided into high-risk and low-risk groups according to the necroptosis risk-scoring signature. Kaplan- Meier survival curves were drawn and area under the curve, and decision curve analyses were calculated to evaluate the performance of the model. Then, internal and external dataset validations were performed. A total of 159 necroptosis-related genes were retrieved from the Kyoto Encyclopedia of genes and genomes database, 39 of which were differentially expressed in tumor tissues. Four necroptosis-related genes (interleukin-33, cytochrome B-245 beta chain, H2A.X variant histone and Readthrough (RNF103-CHMP3)) independently correlated with lung adenocarcinoma prognosis were screened by Lasso or Cox regression based on which prognostic model was established. The independent prognostic value of this model was verified by multivariate Cox regression analysis. In this model, the low-risk group showed significantly longer survival time than the high-risk group (p<0.01) and the model showed good predictive performance in both the internal and external validation sets. In this study, we explored the potential link between necroptosis and lung adenocarcinoma, established a necroptosis gene-based prognostic model and validated the independent prognostic value of the model.