医学信息2024，Vol.37Issue(19)：10-18,9.DOI:10.3969/j.issn.1006-1959.2024.19.002
胶质母细胞瘤耐药性基因筛选及治疗药物预测
Drug Resistance Gene Screening and Therapeutic Drug Prediction of Glioblastoma
摘要
Abstract
Objective To screen differentially expressed genes(DEGs)of temozolomide(TMZ)resistance in glioblastoma cells(GBM)by bioinformatics technology,explore the key drug resistance genes and pathogenesis,and predict the related traditional Chinese medicine.Methods Based on GBM,GEO2R,GPEIA and other databases,biological function and pathway enrichment analysis were carried out,and protein interaction network was constructed to screen key genes.The effects of key genes on mRNA expression and survival rate in normal human and glioma patients were searched.The COREMINE platform was further used to construct a drug-active ingredient-target network for key drug resistance genes,and the active ingredients of related Chinese medicines were screened.Results A total of 293 DEGs were screened,involving key targets such as FN1,CD44,CTGF,and FOS.The expression was significantly higher than that of normal people,affecting the overall survival rate of patients,and was a harmful prognostic factor for GBM,but it did not affect the recurrence-free survival rate.While it affected biological functions such as cell adhesion,nervous system development,transforming growth factor β receptor signal transduction and gene positive regulation.It was predicted by COREMINE that the intervention drugs closely related to FN1 were mostly attributed to the liver meridian,and the nature and flavor were mainly heat-clearing and deficiency-tonifying.Conclusion Twelve key genes related to TMZ resistance in GBM were screened out.FN1 plays an important role in the occurrence and development of TMZ resistance.The active components of Muxiang,Qingyedan and Bimazi may be used as the source of TMZ resistance drugs.关键词
胶质母细胞瘤/替莫唑胺/耐药基因/生物信息学/中药预测Key words
Glioblastoma/Temozolomide/Drug resistance genes/Bioinformatics/Traditional Chinese medicine prediction分类
医药卫生引用本文复制引用
初晓玲,吴波,蓝晓红,易剑峰,李薛梅,陈旭青..胶质母细胞瘤耐药性基因筛选及治疗药物预测[J].医学信息,2024,37(19):10-18,9.基金项目
国家自然科学基金项目(编号:82060739) （编号:82060739）
