Molecular Characterization of Mesothelioma: Impact of Histologic Type and Site of Origin on Molecular Landscape.

PURPOSE: Mesothelioma is an aggressive malignancy with heterogeneous outcomes that are partly driven by the differential efficacy of existing therapies across histologic types and sites of origin. Large-scale molecular analysis of mesothelioma and its subtypes has the potential to inform future therapeutic strategies. MATERIALS AND METHODS: We analyzed 1,294 mesotheliomas {980 pleural (malignant pleural mesothelioma [MPM]) and 314 peritoneal (malignant peritoneal mesothelioma [MPeM])} using next-generation sequencing, determined programmed death ligand-1 (PD-L1) expression and histology in a subset of cases, and assessed MTAP/CDKN2A copy-number status by fluorescence in situ hybridization and T-cell infiltration in an independent cohort. RESULTS: The molecular landscape of MPM was characterized by inactivating alterations in CDKN2A (49%), BAP1 (44%), CDKN2B (42%), MTAP (34%), and NF2 (33%). Compared with epithelioid MPM, nonepithelioid (ie, biphasic and sarcomatoid) MPM had identical tumor mutational burden (median 1.25 mut/Mb, P = .63), more commonly expressed PD-L1 (74% v 51%, P = .02), and was more likely to harbor MTAP, CDKN2A, and CDKN2B copy loss (P < .05). Fluorescence in situ hybridization confirmed that homozygous MTAP loss was enriched in nonepithelioid MPM. Relative to MPM, MPeM had comparable tumor mutational burden and PD-L1 expression. The molecular profile of MPeM was similar to MPM, with the distinction that PBRM1 alterations occurred at higher frequency (16% v 7%, P < .01). ALK rearrangements were only observed in MPeM. CONCLUSION: Regardless of histology and location, the molecular landscape of mesothelioma primarily consists of inactivating alterations in tumor suppressor genes, with enrichment of certain alterations in distinct subsets (eg, MTAP loss in nonepithelioid tumors). Given the limited efficacy of current therapies for this disease, novel approaches targeting recurring alterations should be explored.

WHEN DOES IMPROVING HEALTH RAISE GDP?

We assess quantitatively the effect of exogenous health improvements on output per capita. Our simulation model allows for a direct effect of health on worker productivity, as well as indirect effects that run through schooling, the size and age-structure of the population, capital accumulation, and crowding of fixed natural resources. The model is parameterized using a combination of microeconomic estimates, data on demographics, disease burdens, and natural resource income in developing countries, and standard components of quantitative macroeconomic theory. We consider both changes in general health, proxied by improvements in life expectancy, and changes in the prevalence of two particular diseases: malaria and tuberculosis. We find that the effects of health improvements on income per capita are substantially lower than those that are often quoted by policy-makers, and may not emerge at all for three decades or more after the initial improvement in health. The results suggest that proponents of efforts to improve health in developing countries should rely on humanitarian rather than economic arguments.