胃癌以腺癌为主，占胃癌诊断的85%以上。目前的治疗选择有限，需要发现新的药物靶点和有效的治疗方法。 Affymetrix 基因表达微阵列数据集 (GSE64951) 从 NCBI-GEO 数据标准化中检索，并使用 R-Bioconductor 软件包进行 DEG 识别。使用 DAVID 进行 DEG 的基因本体 (GO) 分析。蛋白质-蛋白质相互作用网络是通过Cytoscape中的STRING数据库插件构建的。使用MCODE提取主网络中重要相互作用基因的子簇/模块。使用 Cytohubba 识别网络中的枢纽基因。 miRNet工具构建了中心基因/mRNA-miRNA网络，Kaplan-Meier-Plotter进行了生存分析。 AutoDock Vina 和 GROMACS MD 模拟用于海洋化合物与 5CNN 蛋白的对接和稳定性分析。总共鉴定出 734 个 DEG（507 个上调和 228 个下调）。差异表达基因 (DEG) 在细胞间粘附和 ATP 结合等过程中富集。选择八个中心基因（EGFR、HSPA90AA1、MAPK1、HSPA4、PPP2CA、CDKN2A、CDC20 和 ATM）进行进一步分析。总共鉴定出 23 个与 hub 基因相关的 miRNA，其中 12 个针对 PPP2CA。 EGFR 在生存分析中表现出最高的表达和危险率。选择 EGFR 的激酶结构域（PDBID：5CNN）作为药物靶点。来自 Petrosia alfiani 的 Adociaquinone A 与 5CNN 对接，在 50 ns MD 模拟中显示出最低的结合能和稳定的相互作用，突显了其作为针对 EGFR 的先导分子的潜力。这项研究确定了胃癌中的关键DEG和枢纽基因，提出了新的治疗靶点。具体而言，Adociaquinone A 作为针对胃癌中 EGFR 的生物活性药物表现出巨大的潜力，值得进一步研究。针对中心基因/蛋白质的预测 miRNA 也可用作潜在的治疗靶点。© 2024 作者。细胞与分子医学基金会和约翰·威利出版的《细胞与分子医学杂志》

Gastric cancer predominantly adenocarcinoma, accounts for over 85% of gastric cancer diagnoses. Current therapeutic options are limited, necessitating the discovery of novel drug targets and effective treatments. The Affymetrix gene expression microarray dataset (GSE64951) was retrieved from NCBI-GEO data normalization and DEGs identification was done by using R-Bioconductor package. Gene Ontology (GO) analysis of DEGs was performed using DAVID. The protein-protein interaction network was constructed by STRING database plugin in Cytoscape. Subclusters/modules of important interacting genes in main network were extracted by using MCODE. The hub genes from in the network were identified by using Cytohubba. The miRNet tool built a hub gene/mRNA-miRNA network and Kaplan-Meier-Plotter conducted survival analysis. AutoDock Vina and GROMACS MD simulations were used for docking and stability analysis of marine compounds against the 5CNN protein. Total 734 DEGs (507 up-regulated and 228 down-regulated) were identified. Differentially expressed genes (DEGs) were enriched in processes like cell-cell adhesion and ATP binding. Eight hub genes (EGFR, HSPA90AA1, MAPK1, HSPA4, PPP2CA, CDKN2A, CDC20, and ATM) were selected for further analysis. A total of 23 miRNAs associated with hub genes were identified, with 12 of them targeting PPP2CA. EGFR displayed the highest expression and hazard rate in survival analyses. The kinase domain of EGFR (PDBID: 5CNN) was chosen as the drug target. Adociaquinone A from Petrosia alfiani, docked with 5CNN, showed the lowest binding energy with stable interactions across a 50 ns MD simulation, highlighting its potential as a lead molecule against EGFR. This study has identified crucial DEGs and hub genes in gastric cancer, proposing novel therapeutic targets. Specifically, Adociaquinone A demonstrates promising potential as a bioactive drug against EGFR in gastric cancer, warranting further investigation. The predicted miRNA against the hub gene/proteins can also be used as potential therapeutic targets.© 2024 The Author(s). Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.