利用TCGA数据库构建胃癌铁死亡相关LncRNA的预后模型OACSTPCD

Objective:The prognostic risk model was constructed to help evaluate the prognosis of patients with gastric cancer by screening long non-coding RNA(LncRNA)associated with ferroptosis in gastric cancer.Methods:The transcripts and clinical date of gastric cancer were downloaded from the Cancer Genome Atlas(TCGA)and 103 ferroptosis-related genes were downloaded from NC-BI.The expression matrix of LncRNA associated with ferroptosis in gatric cancer was obtained through data processing by R and Perl software.Combined that with survival time and then the key LncRNAs were screened out by KM and univariate Cox regression an analy-sis using R software.Randomly divided clinical samples into training and validation sets in a 7∶3 ratio.The prognostic prediction models of the Train and Test group were established by multivariate Cox regression model.Survival analysis,risk cure analysis,single-factor and multi-factor independent prognostic analysis,multi-ROC curve drawing,etc.,were performed for the two groups respectively.Finally,line chart and KEGG analysis of GSEA were performed for the train.Results:13 LncRNAs(LINC00106,TNFRSF10A-AS1,AC244153.1,AC005586.1,AP001318.2,MAGI2-AS3,AP001528.2,MSC-AS1,PVT1,AC037198.1,AC010719.1,HAGLR)were obtained by univariate Cox regression analysis,and five LncRNAs(AC005586.1,AP001318.2,AP001528.2,AC010719.1,HAGLR)related to ferroptosis were screened out by multivariate regression analysis.5 LncRNAs related toferroptosis in gastric cancer were screened through multiple regression analysis(AC005586.1,AP001318.2,AP001528.2,AC010719.1,HAGLR),the trend of the prognostic models constructed from the training and validation sets was consistent.The predictive power of ROC assessment risk model was greater than that of other clinical indicators.The constructed 5 lncRNA histograms showed that the 1-year,2-year and 3-year cali-bration curves coincided with the diagonal of 45°,indicating that the risk model had a good predictive ability.Conclusion:AC005586.1,AP001318.2,AP001528.2,AC010719.1 and HAGLR associated with iron death in gastric cancer can effectively predict the progno-sis of gastric cancer patients.