Gastric cancer (GC) remains a major global health burden with poor prognosis. Environmental pollutants such as mono(2-ethylhexyl) phthalate (MEHP), a primary metabolite of di(2-ethylhexyl) phthalate, have been implicated in gastrointestinal carcinogenesis, yet the underlying mechanisms remain elusive. We integrated chemoinformatics, transcriptomics, and computational biology to explore potential molecular mechanisms linking predicted MEHP-associated targets to gastric carcinogenesis. MEHP-associated protein targets were predicted from multiple databases and intersected with gene signatures identified by differential expression and weighted co-expression network analyses of GC transcriptome datasets. Protein-protein interaction network construction combined with machine learning algorithms (LASSO, SVM-RFE, and random forest) identified endothelin receptor type A (EDNRA) and BCL2-like 1 (BCL2L1) as hub genes. Both genes were significantly upregulated in GC across independent cohorts and demonstrated high diagnostic performance, with EDNRA additionally associated with poor prognosis. Gene set enrichment analysis revealed that EDNRA and BCL2L1 were predominantly enriched in pathways such as calcium signaling, cell adhesion, cell cycle, and lysosome. In parallel, immune infiltration profiling indicated that these genes were closely correlated with specific immune cells, including macrophage polarization and T-cell regulation. Molecular docking combined with molecular dynamics simulations provided computational support for the structural and energetic plausibility of MEHP interactions with both hub proteins, with van der Waals and electrostatic interactions contributing to binding stability. Collectively, our findings provide systems-level evidence suggesting that MEHP-associated molecular targets may intersect with EDNRA- and BCL2L1-related signaling and immune networks relevant to gastric carcinogenesis. These findings contribute to the understanding of potential toxicogenomic links between phthalate exposure and gastric cancer and highlight EDNRA and BCL2L1 as candidate biomarkers within MEHP-associated molecular networks.
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Renjie Duan
Wannan Medical College
Shanjun Tao
Wannan Medical College
Aichen Yang
Wannan Medical College
Discover Oncology
Wannan Medical College
First Affiliated Hospital of Wannan Medical College
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Duan et al. (Fri,) studied this question.
synapsesocial.com/papers/69b606ea83145bc643d1d757 — DOI: https://doi.org/10.1007/s12672-026-04829-0