ArticleIranian journal of basic medical sciences2026
Identification of key genes and pathways involved in trastuzumab resistance in HER2-positive gastric cancer through integrative bioinformatics analysis.
Article in Iranian journal of basic medical sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objectives: Trastuzumab resistance limits therapeutic efficacy in HER2-positive gastric cancer, and its systems-level regulatory architecture remains poorly characterized. This study aimed to identify key regulatory modules, biomarkers, and candidate therapeutic targets associated with trastuzumab resistance. Materials and Methods: Gene expression profiles from trastuzumab-sensitive and -resistant gastric cancer cell lines (GSE77346) were analyzed to identify differentially expressed genes (DEGs). Protein-protein interaction (PPI) networks were constructed, and hub genes were identified using topology-based methods and clustering. Functional enrichment analysis was performed using Gene Ontology and KEGG pathways. Prognostic relevance was evaluated using TCGA-STAD data via UALCAN. Drug-gene interactions were explored using DrugBank and PHAROS, followed by structural modeling and molecular docking. Results: Trastuzumab resistance was linked to transcription factor-driven reprogramming, cytoskeletal and adhesion remodeling, and receptor tyrosine kinase (RTK) bypass signaling. Eleven hub genes were identified across four functional modules potentially associated with FGFR signaling, epithelial-mesenchymal transition (EMT), and lineage plasticity. Elevated PXDN and CDH2 expression was significantly associated with poor overall survival in TCGA-STAD. Molecular docking provided preliminary in silico evidence for potential interactions between selected compounds, including ADH-1, AGX51, artenimol, and phenethyl isothiocyanate, and candidate targets, including N-cadherin/CDH2, ID3, and vimentin. Conclusion: Trastuzumab resistance may involve networks related to transcriptional plasticity, adhesion dynamics, and RTK redundancy. This study provides a hypothesis-generating framework for future biomarker-guided combination strategies, which requires validation in HER2-positive cohorts and experimental models.
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