Molecular profiling reveals primary mesothelioma cell lines recapitulate human disease

T Chernova, X M Sun, I R Powley, S Galavotti, S Grosso, F A Murphy, G J Miles, L Cresswell, A V Antonov, J Bennett, A Nakas, D Dinsdale, K Cain, M Bushell, A E Willis, M MacFarlane

Malignant mesothelioma (MM) is an aggressive, fatal tumor strongly associated with asbestos exposure. There is an urgent need to improve MM patient outcomes and this requires functionally validated pre-clinical models. Mesothelioma-derived cell lines provide an essential and relatively robust tool and remain among the most widely used systems for candidate drug evaluation. Although a number of cell lines are commercially available, a detailed comparison of these commercial lines with freshly derived primary tumor cells to validate their suitability as pre-clinical models is lacking. To address this, patient-derived primary mesothelioma cell lines were established and characterized using complementary multidisciplinary approaches and bioinformatic analysis. Clinical markers of mesothelioma, transcriptional and metabolic profiles, as well as the status of p53 and the tumor suppressor genes CDKN2A and NF2, were examined in primary cell lines and in two widely used commercial lines. Expression of MM-associated markers, as well as the status of CDKN2A, NF2, the 'gatekeeper' in MM development, and their products demonstrated that primary cell lines are more representative of the tumor close to its native state and show a degree of molecular diversity, thus capturing the disease heterogeneity in a patient cohort. Molecular profiling revealed a significantly different transcriptome and marked metabolic shift towards a greater glycolytic phenotype in commercial compared with primary cell lines. Our results highlight that multiple, appropriately characterised, patient-derived tumor cell lines are required to enable concurrent evaluation of molecular profiles versus drug response. Furthermore, application of this approach to other difficult-to-treat tumors would generate improved cellular models for pre-clinical evaluation of novel targeted therapies.Cell Death and Differentiation advance online publication, 19 February 2016; doi:10.1038/cdd.2015.165.