Search

Highlights • Three signal pathway inhibitors show higher toxicities than cisplatin: verteporfin, defactinib and NSC668394. • Verteporfin sensitivity is related to molecular classification in subgroups. • Verteporfin inhibits cell viability independently of YAP. • Defactinib sensitivity is related to FAK protein kinase activation. • Predictive biomarkers of inhibitors response were defined based on gene expression. Abstract Objectives Malignant pleural mesothelioma (MPM) is an aggressive tumor with limited therapeutic options, requiring the development of efficient targeted therapies based on molecular phenotype of the tumor and to identify predictive biomarkers of the response. Materials and methods The effect of inhibitors was investigated by cell viability assessment on primary MPM cell lines established in our laboratory from patient tumors, well characterized at the molecular level. Effects on apoptosis, cell proliferation and viability on MPM growing in multicellular spheroid were also assessed for verteporfin. Gene and protein expression, and gene knockdown by RNA interference were used to define mechanism of inhibition and specific predictive biomarkers. Results Anti-tumor effect of eight major signaling pathways inhibitors involved in mesothelial carcinogenesis was investigated. Three inhibitors were more efficient than cisplatin, the drug used as first-line chemotherapy in patients with MPM: verteporfin, a putative YAP inhibitor, defactinib, a FAK inhibitor and NSC668394, an Ezrin inhibitor. Verteporfin, the most efficient inhibitor, induced cell proliferation arrest and cell death, and is effective on 3D spheroid multicellular model. Verteporfin sensitivity was YAP-independent and related to molecular classification of the tumors. Biomarkers based on gene expression were identified to predict accurately sensitivity to these three inhibitors. Conclusion Our study shows that drug screening on well-characterized MPM cells allows for the identification of novel potential therapeutic strategies and defining specific biomarkers predictive of the drug response. [ABSTRACT FROM AUTHOR]