A Prognostic Model Of Autophagy Gene In Hepatocellular Carcinoma Based On Multidatabase

ObjectiveTo construct a prognostic model of hepatocellular carcinoma(HCC)with differential expression of autophagy genes.MethodsAutophagy genes expression data of hepatocellular carcinoma and normal liver tissues were obtained from The Cancer Genome Atlas(TCGA)database and The Genotype-Tissue Expression(GTEx)database respectively.The gene expression data from different platforms is normalized into log2(FPKM value + 1).Differentially expressed autophagy-related genes of HCC were identified by using R program limma package from the TCGA-GTEx combined data set,the criteria of|log FC| > 1 and FDR < 0.05 was deemed to be of statistically significance.The Gene Ontology(GO)analyses and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analyses were performed by using R program cluster Profiler package,as criteria of P < 0.05.Univariate and Multivariate Cox proportional hazards regression analyses were performed by using R program survival package to identify the HCC potential prognostic differentially expressed autophagy-related genes.The prognostic model was constructed based on differentially expressed autophagy genes expression and the corresponding regression coefficient(coef).The Receiver Operating Characteristic(ROC)of the model is also predicted.ResultsThe genes expression data and clinical information of 374 hepatocellular carcinoma samples and 160 normal liver tissue samples were obtained from TCGA and GTEx databases.Total 205 autophagy genes expression data was obtained from the TCGA-GTEx combined sequence.Total 11 differentially expressed autophagy genes were identified between HCC and normal liver samples.GO analysis mainly enriched in “regulation of protein serine/threonine kinase activity”,“Erb B 2signaling pathway”,“protein kinase regulator activity” and “kinase regulator activity”;KEGG analysis enriched frequently in “EGFR tyrosine kinase inhibitor resistance”,“Erb B signaling pathway”.A significant prognosis index(PI)was established based on NRG1 and IKBKE(P < 0.05).PI =(0.44247 × NRG1 expression level)+(0.55977 × IKBKE expression level).The ROC of the prognosis model shows that the Area under Curve(AUC)of the overall seven-year survival is 0.711.ConclusionThe prognosis model of hepatocellular carcinoma based on NRG1 and IKBKE has high predictive value for the long-term survival rate of hepatocellular carcinoma patients.