Pan-cancer profiles of mesothelin (MSLN) unveil diagnostic potential and therapeutic targetability of pancreatic adenocarcinoma

Our plain-English summary of Pan-cancer profiles of mesothelin (MSLN) unveil diagnostic potential and therapeutic targetability of pancreatic adenocarcinoma, by M.R. Sheikh, B. Mistry, R.H. Shafin, et al (PloS One, 2026).

The study

• Authors: M.R. Sheikh, B. Mistry, R.H. Shafin, A. Apu, T.H. Sara, J. Tasnim, D. Dutta, A. Nandy, A. Rahman
• Journal: PloS One
• Published: 2026;21(8):e0354334
• Read it: PubMed · Publisher · Free full text

Abstract

Background: Mesothelin (MSLN) is a cell surface glycoprotein that is often over-expressed in various malignancies of humans and has been suggested as a potential therapeutic and diagnostic target. However, its expression profile, clinical implications and drug-targeting potential are not fully understood and needs to be investigated across various cancer types.

Objectives: The goal of this study was to systematically characterize the MSLN expression pattern, its prognostic value and functionality in different types of cancers, particularly in pancreatic adenocarcinoma (PAAD), as well as to identify viable therapeutic target opportunities.

Methods: Transcriptomic and clinical datasets from TCGA and GEO were used to evaluate the expression of the MSLN gene, diagnostic value, and its prognostic significance. To study the genomic alterations and functional pathways of MSLN, mutation, GO, and KEGG analyses were used. Drug sensitivity correlations were performed with GDSC and CTRP datasets. Structure-based drug discovery involved molecular docking (AutoDock Vina and Maestro Glide), 100 ns molecular dynamics simulations, and MMPBSA binding free energy analysis, followed by drug-likeness and toxicity assessment using SwissADME and ProTox-III.

Results: MSLN was found to be over expressed in several cancers, including PAAD, ovarian and mesothelioma, and this was confirmed in the independent GEO datasets. The analysis of ROC curves showed high accuracy for PAAD and stomach adenocarcinoma and moderate to low accuracy for the other cancers. Both survival and Cox regression analyses showed that MSLN was a cancer-type-specific prognostic factor. Analysis of mutations showed low frequencies of genetic changes, suggesting that the mechanism of dysregulation may be transcriptional or epigenetic. Enrichment analysis highlighted immune-related and tumor-microenvironment signaling pathways associated with MSLN. Drug sensitivity analysis suggested association of MSLN expression with response to targeted and selected chemotherapeutic drugs. Molecular docking revealed Withaferin A as the most potent protein binding compound with MSLN with stable protein-ligand interaction as evidenced by molecular dynamics simulations and binding energy analysis.

Conclusion: MSLN is a diagnosis and prognosis biomarker that is context dependent and has application in selected cancers, especially pancreatic adenocarcinoma. While Withaferin A shows promising in silico binding and stability against MSLN, predicted toxicity and pharmacokinetic limitations suggest the need for further optimization and experimental validation before therapeutic application.

Copyright: © 2026 Sheikh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

In plain English

This was an entirely computational (in silico) pan-cancer analysis of the mesothelin (MSLN) gene using public data. The authors used TCGA tumour and normal tissue data for pancreatic adenocarcinoma (179 tumour, 4 normal), cholangiocarcinoma, stomach and lung adenocarcinoma, breast carcinoma, and ovarian serous cystadenocarcinoma and mesothelioma (379 and 87 tumours, no normal samples for either), plus two pancreatic GEO datasets for validation. MSLN expression was significantly higher in tumour than normal tissue in PAAD, CHOL, STAD, LUAD and BRCA, and in both GEO sets (p = 7.42 x 10-8 and 1.98 x 10-9). Diagnostic ROC accuracy was highest for PAAD and STAD and near-random for BRCA. Kaplan-Meier analysis using a median split linked high MSLN expression to poorer overall survival in LUAD, MESO and OV but found no significant difference in PAAD, CHOL, STAD or BRCA, while multivariate Cox regression found MSLN an independent predictor in PAAD only. Gene mutations were uncommon. Docking ranked Withaferin A highest among the screened compounds, and 100 ns simulations of apo MSLN and the MSLN-Withaferin A complex supported predicted stability; respiratory, cardiac and immune toxicity were predicted. The authors presented the work as exploratory and requiring experimental validation.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: In silico bioinformatics and molecular modelling study using publicly available transcriptomic, clinical, mutation and pharmacogenomic databases; no new experiments
• Who was studied: Public tumour and normal tissue datasets: TCGA PAAD (179 tumour, 4 normal), CHOL (36 tumour, 9 normal), STAD (415, 35), LUAD (524, 59), OV (379, 0), MESO (87, 0), BRCA (1097, 113); GEO validation GSE62452 (69 tumour, 61 normal) and GSE15471 (39 tumour, 39 normal)
• Exposure: Not an exposure study. What was analysed was MSLN gene expression level (tumour versus normal, high versus low), MSLN mutations, and the docking of 31 phytochemical compounds with doxorubicin as control against the MSLN protein structure (PDB 7U9J)
• Main results:
  • In the TCGA data, MSLN expression was significantly higher in tumour than in normal tissue for PAAD, CHOL, STAD, LUAD and BRCA; OV and MESO had no normal samples for comparison
  • In the two independent pancreatic GEO datasets, MSLN was significantly upregulated in tumour tissue, with diagnostic AUCs of 0.836 (GSE15471) and 0.806 (GSE62452)
  • ROC analysis across TCGA cancers: AUC values listed in Table 1 were PAAD 0.821, CHOL 0.728, STAD 0.799, LUAD 0.554, BRCA 0.506 (the text states 0.822, 0.729 and 0.800 for PAAD, CHOL and STAD); MESO and OV could not be assessed for lack of normal samples
  • Kaplan-Meier overall survival by median split of MSLN expression: significantly poorer survival with high MSLN in LUAD, MESO and OV; no significant difference in PAAD, CHOL, STAD or BRCA
  • Multivariate Cox regression found higher MSLN expression an independent predictor of mortality only in PAAD (HR 1.14, 95% CI 1.05-1.24, p = 0.0007)
  • MSLN genetic alterations were uncommon, mostly missense and clustered in the N-terminal domain, with overall frequencies below 5 per cent
  • In the GDSC and CTRP drug-sensitivity datasets, MSLN expression correlated with broad chemoresistance but with greater sensitivity to EGFR/MAPK-pathway inhibitors
  • In docking, Withaferin A had the best binding affinity to MSLN in AutoDock Vina (-8.0 kcal/mol) and remained top-ranked in Glide (-7.3 kcal/mol); doxorubicin control scored -7.1 and -6.4 kcal/mol
  • The 100 ns molecular dynamics simulations compared apo MSLN with the MSLN-Withaferin A complex only, and both systems stayed structurally stable (RMSD fluctuations about 1.5 to 3.5 Angstrom)
  • Predicted toxicity for Withaferin A: oral LD50 300 mg/kg, toxicity class III; no predicted hepatotoxicity, mutagenicity or carcinogenicity, but predicted respiratory toxicity, cardiotoxicity and immunotoxicity
• The authors' conclusion: The authors concluded that MSLN is a biologically relevant but context-dependent diagnostic and prognostic marker, of most use in pancreatic adenocarcinoma, and that Withaferin A is a promising but unvalidated MSLN-binding compound whose predicted toxicity means it cannot be translated clinically without further optimisation
• Limitations the authors state:
  • All transcriptomic analyses were computational and based on public data, requiring validation in cell and animal models
  • The MSLN binding pocket and the ligand interactions have not been experimentally validated
  • The 100 ns molecular dynamics simulation may not capture behaviour over longer time scales
  • ADMET and toxicity results are predictions only

Topics

Medical terms in this study, explained in our Lexicon: Mesothelin, Adenocarcinoma, Glycoprotein, Discovery, Mesothelioma, Prognosis, Biomarker.

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