Development of an Eight-gene Prognostic Model for Overall Survival Prediction in Patients with Hepatocellular Carcinoma

Background and Aims:The overall survival(OS)of hepatocellular carcinoma(HCC)remains dismal.Bioinformatic analysis of transcriptome data could identify patients with poor OS and may facilitate clinical decision.This study aimed to develop a prognostic gene model for HCC.Methods:GSE14520 was retrieved as a training set to identify differential expressed genes(DEGs)between tumor and adjacent liver tissues in HCC patients with different OS.A DEG-based prognostic model was then constructed and the TCGA-LIHC and ICGC-LIRI datasets were used to validate the model.The area under the receiver operating characteristic curve(AUC)and hazard ratio(HR)of the model for OS were calculated.A model-based nomogram was estab-lished and verified.Results:In the training set,differential expression analysis identified 80 genes dysregulated in oxidation-reduction and metabolism regulation.After univariate Cox and LASSO regression,eight genes(LPCAT1,DHRS1,SORBS2,ALDH5A1,SULT1C2,SPP1,HEY1 and GOLM1)were selected to build the prognostic model.The AUC for 1-,3-and 5-year OS were 0.779,0.736,0.754 in training set and 0.693,0.689,0.693 in the TCGA-LIHC validation set,respectively.The AUC for 1-and 3-year OS were 0.767 and 0.705 in the ICGC-LIRI validation set.Multivariate analysis confirmed the model was an independent prognostic factor(training set:HR=4.422,p<0.001;TCGA-LIHC validation set:HR=2.561,p<0.001;ICGC-LIRI validation set:HR=3.931,p<0.001).Furthermore,a nomogram combining the model and AJCC stage was established and validated,showing increased OS predictive efficacy compared with the prognostic model(p=0.035)or AJCC stage(p<0.001).Conclusions:Our eight-gene prognostic model and the related nomogram represent as reliable prognostic tools for OS prediction in HCC patients.