妇儿健康导刊2025，Vol.4Issue(10)：186-193,8.DOI:10.3969/j.issn.2097-115X.2025.10.041
借助生物信息学筛选卵巢癌预后的关键基因
Screening key prognostic genes for ovarian cancer using bioinformatics
摘要
Abstract
Objective To screen key prognostic genes for ovarian cancer using bioinformatics and provide new targets for ovarian cancer treatment.Methods The ovarian cancer-related data from the GSE26712,GSE6008,and GSE18520 datasets in the Gene Expression Omnibus database were downloaded,R software limma package was used for normalization and differential expression genes(DEGs)analysis,and Venn diagrams were used to take the DEGs overlapping of the 3 datasets.Gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)analysis were performed on DEGs using the Metascape database,the protein-protein interaction network of DEGs was constructed on the STRING database,the key genes ranked in the top ten were screened by Cytoscape software,and the key genes were validated by Gene Expression Profiling Interactive Analysis database in ovarian cancer and different staged ovarian cancer tissues.Survival analysis of key genes was performed in the Kaplan-Meier Plotter database,and immunohistochemistry results from the Human Protein Atlas database were used to compare protein expression of key genes in normal ovarian and ovarian cancer samples.Results A total of 66 DEGs were obtained as a result.GO functional annotation was mainly related to response to hormone and gland development,etc.The KEGG pathway was mainly enriched in cell adhesion molecule pathway and tryptophan metabolism pathway,etc.In ovarian cancer tissues,decorin(DCN),osteomodulin(OMD),and extracellular matrix protein 2(ECM2)were lowly expressed,Claudin-7(CLDN7),Claudin-4(CLDN4),epithelial cell adhesion molecule(EPCAM),epithelial splicing regulatory protein 1(ESRP1),serine peptidase inhibitor,Kunitz type 1(SPINT1),and cluster of differentiation were highly expressed,and only OMD was associated with pathological staging of patients.High expression of SPINT1 was beneficial for patients'survival prognosis,while high expression of CLDN4,DCN,ECM2,ESRP1,and OMD was detrimental to patients'survival prognosis.The immunohistochemical results of CLDN7,CLDN4,DCN,and EPCAM were ideal,and all except EPCAM had prognostic significance.Conclusion CLDN7,CLDN4,and DCN are closely related to the prognosis of ovarian cancer,but further research is still needed.关键词
卵巢癌/生物信息学/预后/关键基因Key words
Ovarian cancer/Bioinformatics/Prognosis/Key gene分类
临床医学引用本文复制引用
徐春菊,徐冬梅,全露..借助生物信息学筛选卵巢癌预后的关键基因[J].妇儿健康导刊,2025,4(10):186-193,8.基金项目
国家临床重点专科(肿瘤科)"苗圃计划"科研项目(qjzxyympjh2024005). （肿瘤科）
