Elucidating gastric cancer mechanisms and therapeutic potential of Adociaquinone A targeting EGFR: A genomic analysis and Computer Aided Drug Design (CADD) approach.

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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.", "claims": [{"id": "claim-method", "statement": "The thresholds were set as, adjusted p <0.05 and |log2 fold change (log2FC)| ≥1 for identification of DEGs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39434198", "locator": "sections[4] \"Collection normalization and statistical analysis of dataset for identification of differentially expressed genes (DEGs)\" paragraph 2", "quote": "The thresholds were set as, adjusted p <0.05 and |log2 fold change (log2FC)| ≥1 for identification of DEGs."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All the related to the study data have been included in the study.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39434198", "locator": "sections[32] \"DATA AVAILABILITY STATEMENT\" paragraph 2", "quote": "All the related to the study data have been included in the study."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Total of 734 DEGs retrieved from Affymetrix gene expression microarray dataset (GSE64951) contained 507 upregulated and 228 downregulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39434198", "locator": "sections[17] \"Collection normalization and statistical analysis of dataset for identification of differentially expressed genes\" paragraph 2", "quote": "Total of 734 DEGs retrieved from Affymetrix gene expression microarray dataset (GSE64951) contained 507 upregulated and 228 downregulated genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Total of 734 DEGs retrieved from Affymetrix gene expression microarray dataset (GSE64951) contained 507 upregulated and 228 downregulated genes.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:39434198"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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