Evidence map›Paper›PMID 39434198›Full record

ArticleJournal of cellular and molecular medicine2024

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

Abstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mariam Abdulaziz AlkhateebDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Nada H AljarbaDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Qudsia YousafiDepartment of Biosciences, COMSATS University Islamabad, Sahiwal Campus, Sahiwal, Pakistan.
Fatima AnwarDepartment of Biosciences, COMSATS University Islamabad, Sahiwal Campus, Sahiwal, Pakistan.
Partha BiswasLaboratory of Pharmaceutical Biotechnology and Bioinformatics, Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh.ORCID 0000-0002-9766-756X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Drug DesignErbB ReceptorsGene Expression Regulation, NeoplasticMicroRNAsProtein Interaction MapsStomach NeoplasmsAntineoplastic AgentsComputational BiologyComputer-Aided DesignGene Expression ProfilingGene OntologyGene Regulatory NetworksGenomicsHumansMolecular Docking SimulationAntineoplastic AgentsEGFR protein, humanErbB ReceptorsMicroRNAsCMNPDhub genesmiRNAmolecular dockingsurvival analysis

Identifiers

PMID39434198
PMCPMC11493557

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.