Construction of prognostic model for hypoxia-related lncRNA in uveal melanoma based on bioinformatics
Aim To construct a prognostic model for hypoxia-related long non-coding RNA(lncRNA)in uveal melanoma(UM)based on bioinformatics.Methods The lncRNA expression profiles and clinical information data of uveal melanoma were selected from the TCGA database.Lasso regression,univariate and multivariate Cox were used to identify prognostic markers of hypoxia-related lncRNA in UM,and a prognostic model was constructed.ROC curves were used to evaluate the sensitivity and specificity of the prognostic model,and a nomogram was estab-lished.According to the median risk score,UM was divided into high-risk and low-risk group.Kaplan-Meier analysis was used to compare the overall survival of patients in high-and low-risk groups.The functional enrich-ment analysis of differential genes of hypoxia-related lncRNAs was based on KEGG.Results 983 hypoxia-related lncRNAs were obtained.7 hypoxia-related lncRNA prognostic markers in UM(AC100791.3,SOS1-IT1,LHFPL3-AS1,AP005121.1,AL121820.2,LINC01006,AC104825.1)with independent prognostic significance were screened and a prognostic model was constructed.The risk score of the prognostic model is an independent prognostic factor for UM patients(P＜0.001).The ROC curve indicates that the prognostic model has high accuracy.The high risk group had a lower overall survival time than the low risk group(P＜0.001).KEGG enrichment analysis showed that oxidative phosphorylation pathway,glyoxylic acid and dicarboxylic acid metabolism,systemic lupus erythematosus,antigen processing and presentation,P53 signaling pathway were enriched in the high-risk group.Conclusion The prognostic model based on 7 hypoxia-related lncRNAs can predict the prognostic value of UM patients.
万方数据
维普
