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

Mariam Abdulaziz Alkhateeb; Nada H Aljarba; Qudsia Yousafi; Fatima Anwar; Partha Biswas

doi:10.1111/jcmm.70133

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

J Cell Mol Med. 2024 Oct;28(20):e70133. doi: 10.1111/jcmm.70133.

Authors

Mariam Abdulaziz Alkhateeb¹, Nada H Aljarba¹, Qudsia Yousafi², Fatima Anwar², Partha Biswas³

Affiliations

¹ Department of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
² Department of Biosciences, COMSATS University Islamabad, Sahiwal Campus, Sahiwal, Pakistan.
³ Laboratory of Pharmaceutical Biotechnology and Bioinformatics, Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh.

Abstract

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.

Keywords: CMNPD; hub genes; miRNA; molecular docking; survival analysis.

MeSH terms

Antineoplastic Agents / pharmacology
Antineoplastic Agents / therapeutic use
Computational Biology / methods
Computer-Aided Design
Drug Design*
ErbB Receptors* / genetics
ErbB Receptors* / metabolism
Gene Expression Profiling / methods
Gene Expression Regulation, Neoplastic* / drug effects
Gene Ontology
Gene Regulatory Networks / drug effects
Genomics / methods
Humans
MicroRNAs* / genetics
Molecular Docking Simulation
Protein Interaction Maps* / drug effects
Protein Interaction Maps* / genetics
Stomach Neoplasms* / drug therapy
Stomach Neoplasms* / genetics
Stomach Neoplasms* / pathology

Substances

ErbB Receptors
MicroRNAs
EGFR protein, human
Antineoplastic Agents