Screening of prognostic ferroptosis-related gene and construction of prognostic prediction model in colorectal cancer
Objective To screen and analyze ferroptosis-related genes(FRGs)associated with the prognosis of colorectal cancer(CRC)based on bioinformatics method,and to construct a clinical prognosis model.Methods Prognostic sample genes of CRC were obtained through The Cancer Genome Atlas(TCGA)database,prognostic related genes were obtained after univariate Cox regression analysis.FRGs were obtained from FerrDb database,and prognostic related FRGs were obtained after intersection.The prognosis model was constructed by LASSO-Cox regression analysis.With the median risk score of the prognostic model as the critical value,CRC patients were divided into high risk group and low risk group.Survival curves were plotted and receiver operating characteristic(ROC)curves were used to evaluate the diagnostic efficacy of the FRGs model.Univariate and multivariate Cox regression analysis were used to determine independent prognostic factors for overall survival(OS).GeneMANIA database was used for protein interaction network analysis of the genes in the prognostic model,while Metascap database was used for gene ontology(GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis.Results A total of 11 FRGs with prognostic value were selected and the prognostic model was constructed.The survival curve indicated that the high risk group had worse prognosis than the low risk group,and the difference in OS was statistically significant(P<0.05).The ROC curve suggested that the FRGs model had a good diagnositc effect.Univariate and multivariate Cox regression analysis showed that T stage,N stage,pathological stage,age,residual tumor and risk score were independent prognostic risk factors(P<0.05).The result of protein interaction network analysis suggested that it was mainly related to macroautophagy and iron ion transport.Functional enrichment analysis showed that the 11 prognostic related FRGs were significantly enriched in regulation of membrane potential,autophagy and retrograde endocannabinoid signaling pathways.Conclusion The prognostic model consisting of 11 prognostic related FRGs screened by bioinformatics method has good prognostic value for CRC patients,and may provide basis for treatment and prognostic evaluation for CRC patients.
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