局解手术学杂志2025，Vol.34Issue(11)：955-959,5.DOI:10.11659/jjssx.10E024091
生物信息学分析结直肠癌预后不良相关的基因
Bioinformatics analysis of genes associated with poor prognosis in colorectal cancer
摘要
Abstract
Objective To screen genes associated with poor prognosis of colorectal cancer(CRC)through bioinformatics analysis.Methods The gene expression profiles of GSE74602,GSE110223,GSE113513 and GSE141174 were obtained from Gene Expression Omnibus(GEO)database,including samples from 65 CRC tissues and 65 normal tissues.Differentially expressed genes(DEGs)between CRC tissues and normal tissues were screened out by GEO2R tool and Venn software,and the consistent genes were extracted from DEGs by Venn software.A protein-protein interaction(PPI)network was constructed by the STRING database to identify key genes,which were analyzed by Kaplan-Meier Plotter and GEPIA.Kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analysis was conducted on the 13 selected genes.Results There were 171 DEGs obtained from the four datasets,including 148 up-regulated genes and 23 down-regulated genes.Up-regulated DEGs were enriched in the redox processes,bicarbonate transport,digestion,ion trans-membrane transport,and one-carbon metabolism;and down-regulated DEGs were enriched in the positive regulation of cell proliferation.The survival curve analysis showed that 30 of the 87 genes were significantly associated with poor survival prognosis.GEPIA showed that 13 of the 30 genes were highly expressed in CRC tissues compared to normal tissues,among which MYC and FGFR3 markedly enriched in the CRC pathway.Conclusion This study identifies that MYC and FGFR3 are significantly up-regulated in CRC and closely associated with poor prognosis,suggesting that they may serve as potential prognostic markers and therapeutic targets for CRC patients.关键词
结直肠癌/差异表达基因/蛋白质/预后/生物信息学分析Key words
colorectal cancer/differentially expressed genes/protein/prognosis/bioinformatical analysis分类
临床医学引用本文复制引用
王立杰,陈思,常程,高凯月,张海佳..生物信息学分析结直肠癌预后不良相关的基因[J].局解手术学杂志,2025,34(11):955-959,5.基金项目
吉林省科技厅资助项目(20240304063SF) （20240304063SF）
