Machine learning, molecular docking, and experimental validation identify shared molecular signatures between idiopathic pulmonary arterial hypertension and malignant pleural mesothelioma: a retrospective study.
4 affiliations
- 1Department of General Medicine, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
- 2Department of Emergency, Peking University People's Hospital, Beijing, China.
- 3College of Pharmacy, Xinjiang Medical University, Urumqi, China.
- 4Department of Pharmacy, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Abstract
Background
Idiopathic pulmonary arterial hypertension (IPAH) exhibits cancer-like features, yet its pathogenesis remains unclear. Given molecular similarities between IPAH and malignant pleural mesothelioma (MPM), this study aimed to uncover shared transcriptomic patterns.Methods
GEO datasets for IPAH and MPM were analyzed. Overlapping DEGs and WGCNA modules were identified. PPI network analysis combined with LASSO, random forest, and SVM-RFE was used to identify candidate biomarker genes. A classification model was constructed and evaluated using leave-one-out cross-validation and bootstrap optimism correction. Immune infiltration was evaluated by ssGSEA. Molecular docking and MD simulations assessed drug binding to candidate target proteins. qRT-PCR validated candidate biomarker gene expression.Results
Six concordantly upregulated and eleven concordantly downregulated DEGs were shared between IPAH and MPM. Upregulated genes were enriched in cell cycle regulation, while downregulated genes were enriched in neutrophil chemotaxis. WGCNA identified 58 overlapping genes. CXCR2, S100A9, and LCN2 were identified as candidate biomarker genes. A ROTS sensitivity analysis confirmed that all 1710 MPM DEGs were reproducible and directionally concordant at the matching FDR <0.05 threshold despite the imbalanced case-control ratio. The classification model achieved AUCs of 0.909 and 0.875 in training and external validation sets, with a LOOCV AUC of 0.879 and an optimism-corrected AUC of 0.896. Immune infiltration revealed increased Th17 cells but decreased neutrophils in IPAH. CXCR2 and S100A9 expression correlated with neutrophil infiltration; LCN2 expression correlated with metabolic reprogramming. Navarixin showed the strongest binding affinity to CXCR2 (-10.1 kcal/mol). MD simulations confirmed stable binding of the CXCR2-Navarixin complex. qRT-PCR confirmed significant downregulation of all three genes in IPAH patients.Conclusion
This hypothesis-generating study identifies shared transcriptomic signatures between IPAH and MPM, highlighting CXCR2, S100A9, and LCN2 as candidate biomarkers linked to immune dysregulation and metabolic reprogramming. The computational and correlative nature of these findings, together with the limited size of the external validation cohort, requires confirmation through functional experiments and validation in larger, independent, and multicentre cohorts before clinical translation can be considered.
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BibTeX
@article{zhang2026machine,
title = {{Machine learning, molecular docking, and experimental validation identify shared molecular signatures between idiopathic pulmonary arterial hypertension and malignant pleural mesothelioma: a retrospective study.}},
author = {Neng Zhang and Chunyu Wang and Rui Wang and Xue Guo and Jing Yu and Jie Wang and Qin Luo and Yun Wu},
journal = {Frontiers in genetics},
year = {2026},
month = oct,
doi = {10.3389/fgene.2026.1894027},
url = {https://europepmc.org/article/MED/42948525},
note = {CC BY},
}
RIS
TY - JOUR
TI - Machine learning, molecular docking, and experimental validation identify shared molecular signatures between idiopathic pulmonary arterial hypertension and malignant pleural mesothelioma: a retrospective study.
AU - Neng Zhang
AU - Chunyu Wang
AU - Rui Wang
AU - Xue Guo
AU - Jing Yu
AU - Jie Wang
AU - Qin Luo
AU - Yun Wu
PY - 2026
DA - 2026/10/14
JO - Frontiers in genetics
DO - 10.3389/fgene.2026.1894027
UR - https://europepmc.org/article/MED/42948525
AB - Background Idiopathic pulmonary arterial hypertension (IPAH) exhibits cancer-like features, yet its pathogenesis remains unclear. Given molecular similarities between IPAH and malignant pleural mesothelioma (MPM), this study aimed to uncover shared transcriptomic patterns.Methods GEO datasets for IPAH and MPM were analyzed. Overlapping DEGs and WGCNA modules were identified. PPI network analysis combined with LASSO, random forest, and SVM-RFE was used to identify candidate biomarker genes. A classification model was constructed and evaluated using leave-one-out cross-validation and bootstrap optimism correction. Immune infiltration was evaluated by ssGSEA. Molecular docking and MD simulations assessed drug binding to candidate target proteins. qRT-PCR validated candidate biomarker gene expression.Results Six concordantly upregulated and eleven concordantly downregulated DEGs were shared between IPAH and MPM. Upregulated genes were enriched in cell cycle regulation, while downregulated genes were enriched in neutrophil chemotaxis. WGCNA identified 58 overlapping genes. CXCR2, S100A9, and LCN2 were identified as candidate biomarker genes. A ROTS sensitivity analysis confirmed that all 1710 MPM DEGs were reproducible and directionally concordant at the matching FDR <0.05 threshold despite the imbalanced case-control ratio. The classification model achieved AUCs of 0.909 and 0.875 in training and external validation sets, with a LOOCV AUC of 0.879 and an optimism-corrected AUC of 0.896. Immune infiltration revealed increased Th17 cells but decreased neutrophils in IPAH. CXCR2 and S100A9 expression correlated with neutrophil infiltration; LCN2 expression correlated with metabolic reprogramming. Navarixin showed the strongest binding affinity to CXCR2 (-10.1 kcal/mol). MD simulations confirmed stable binding of the CXCR2-Navarixin complex. qRT-PCR confirmed significant downregulation of all three genes in IPAH patients.Conclusion This hypothesis-generating study identifies shared transcriptomic signatures between IPAH and MPM, highlighting CXCR2, S100A9, and LCN2 as candidate biomarkers linked to immune dysregulation and metabolic reprogramming. The computational and correlative nature of these findings, together with the limited size of the external validation cohort, requires confirmation through functional experiments and validation in larger, independent, and multicentre cohorts before clinical translation can be considered.
SN - 1664-8021
ER -