Development of prognostic index based on necroptosis-related genes in patient with hepatocellular carcinoma

Development of prognostic index based on necroptosis-related genes in patient with hepatocellular carcinoma. Methods: By analyzing the expression levels of 159 NRGs from The Cancer Genome Atlas (TCGA) database,36 differentially expressed NRGs were screened.Gene Ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to evaluate the underlying molecular mechanisms of differentially expressed NRGs in HCC.[1]The STRING online tool was used to establish a PPI network to evaluate the interactions among NRG-coded proteins. Results were observed using the Cytoscape software.The prognostic value of NRGs was established using COX regression, and a prognostic risk model for scoring patients was subsequently developed. Kaplan-Meier (KM) curves and receiver operating characteristic (ROC) curves were plotted to determine the prognostic value of the model. Finally, the performance of the model was successfully validated with the Gene Expression Omnibus (GEO) sub-dataset. Result: Compared with normal tissues,34 highly upregulated and 2 downregulated NRGs in HCC tissues were screened.GO analysis results revealed that these 36 genes are indeed related to necroptosis the function. KEGG analysis revealed that these 36 genes were correlated with Necroptosis,NLRs,Shigellosis,MAPK,andTNF signaling pathways.COX regression showed that these 4 NRGs (HSP90AA1, PPIA, SQSTM1, USP21) were associated with prognosis and developed a model.According to the high and low risk score, the patients were divided into high-risk groups and low-risk groups.The risk model had a better clinical potency than the other clinical characteristics, with the area under the ROC curve (AUC =0.806). Conclusion: Based on the differential expression of NRGs, we established a novel risk model for predicting HCC prognosis.It also provides a new basis for the study of necroptosis in hepatocellular carcinoma.