中草药2026，Vol.57Issue(8)：3099-3109,11.DOI:10.7501/j.issn.0253-2670.2026.08.022
基于GEO数据库的胃癌差异表达基因系统分析及潜在中药靶向筛选
Systematic analysis of differentially expressed genes in gastric cancer based on GEO database and targeted screening of potential traditional Chinese medicines
摘要
Abstract
Objective To integrate differentially expressed genes(DEGs)in gastric cancer(GC)from the Gene Expression Omnibus(GEO)database,systematically identify core targets associated with tumor progression,and predict therapeutic Chinese medicines via network distance,providing molecular evidence for integrated traditional Chinese and Western medicine precision intervention in GC.Methods A total of 21 GC datasets(2 125 GC,367 normal samples)were downloaded from GEO to construct an expression matrix.DEGs were screened using the limma package(|log2(FC)|＞1,FDR＜0.05),weighted gene co-expression network analysis(WGCNA)was performed to identify modules most correlated with disease phenotype,gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)enrichment analyses were conducted on key genes,seven machine learning models were built with SHapley additive exPlanations(SHAP)for feature importance interpretation;network distance between Chinese medicine target modules and GC key genes was calculated based on the human PPI network to screen topologically proximal medicines,with statistics on four properties,five flavors,meridian tropism,and efficacy.Results A total of 455 DEGs were obtained.WGCNA yielded 31 modules,with the light-yellow module(r=0.56,q＜0.01)containing 194 hub genes;intersection with DEGs produced 177 key genes.Enrichment analysis showed GO-biological processes(BP)focused on extracellular matrix organization and adhesion,GO-cell component(CC)on collagen-containing ECM and focal adhesion,GO-molecular function(MF)on integrin/growth factor binding,and KEGG on actin cytoskeleton regulation,phosphatidylinositol-3-hydroxykinase(PI3K)-protein kinase B(Akt),and interleukin-17(IL-17)signaling.The random forest(RF)model achieved 0.991 accuracy,with SHAP consistently ranking SULF1,THY1,DNER,and SPINK7 as top contributors.Network distance screening identified Arctii Fructus,Prunellae Spica,Atractylodis Rhizoma,Fritillariae Cirrhosae Bulbus,Ligustri Lucidi Fructus,Hypocreaceae,and Persicae Semen among the top 15 medicines,characterized by cool/cold properties,bitter flavor,liver/stomach/lung tropism,and primarily heat-clearing with deficiency-tonifying efficacy.Conclusion This study systematically elucidates GC molecular mechanisms,predicting multi-target anti-GC potential of heat-clearing,yin-nourishing,and blood-activating Chinese medicines,and provides novel strategies for GC precision diagnosis/treatment and modernization of traditional Chinese medicine.关键词
胃癌/差异基因/SULF1/THY1/DNER/SPINK7/清热解毒/滋阴活血Key words
gastric cancer/differentially expressed genes/SULF1/THY1/DNER/SPINK7/heat-clearing and detoxifying/yin-nourishing and blood-activating分类
生物科学引用本文复制引用
沈翊康,赵玉凤,庞华鑫,刘明睿,刘海煜,马鹏珍,李雅宁,王麒皓,谢晓霞,张小平..基于GEO数据库的胃癌差异表达基因系统分析及潜在中药靶向筛选[J].中草药,2026,57(8):3099-3109,11.基金项目
国家自然科学基金面上项目(82374621) （82374621）
中国中医科学院创新工程项目(CI2021A05042) （CI2021A05042）
国家自然科学基金面上项目(82575263) （82575263）
