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

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.