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Systematic analysis of differentially expressed genes in gastric cancer based on GEO database and targeted screening of potential traditional Chinese medicines
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Chinese Traditional and Herbal Drugs | 2026, 57(8) : 3099 - 3109
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Chinese Traditional and Herbal Drugs | 2026, 57(8): 3099-3109
Systematic analysis of differentially expressed genes in gastric cancer based on GEO database and targeted screening of potential traditional Chinese medicines
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SHEN Yikang, PANG Huaxin, LIU Mingrui, LIU Haiyu, Ma Pengzhen, LI Yaning, WANG Qihao, XIE Xiaoxia, ZHANG Xiaoping, ZHAO Yufeng
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doi: 10.7501/j.issn.0253-2670.2026.08.022
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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.
gastric cancer  /  differentially expressed genes  /  SULF1  /  THY1  /  DNER  /  SPINK7  /  heat-clearing and detoxifying  /  yin-nourishing and blood-activating
SHEN Yikang, PANG Huaxin, LIU Mingrui, LIU Haiyu, Ma Pengzhen, LI Yaning, WANG Qihao, XIE Xiaoxia, ZHANG Xiaoping, ZHAO Yufeng. Systematic analysis of differentially expressed genes in gastric cancer based on GEO database and targeted screening of potential traditional Chinese medicines[J]. Chinese Traditional and Herbal Drugs, 2026 , 57 (8) : 3099 -3109 . DOI: 10.7501/j.issn.0253-2670.2026.08.022
Year 2026 volume 57 Issue 8
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doi: 10.7501/j.issn.0253-2670.2026.08.022
  • Receive Date:2025-11-13
  • Online Date:2026-09-09
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  • Received:2025-11-13
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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