Funding: icare Dust Disease Care NSW (2018-2020); US Department of Defense (2018-2021); NHMRC (2019-2022).
Synopsis: Mesothelioma is an incurable asbestos induced cancer. We think that a person’s genetic makeup plays a large part in their sensitivity to asbestos and this project aims to figure out which specific genes have this property. This two-part research program uses a systems genetics approach to understand how an individual’s genetic makeup influence disease development following asbestos exposure. The first part combines the power of two unique mouse models with computation biology to identify genes associated with asbestos related disease development. The Collaborative Cross (CC) is a powerful mouse genetic resource. The CC captures over 90% of common allelic diversity of the mouse species. Each CC strain’s genome is a mosaic of chromosomal segments inherited from eight founder strains. The CC has been used to identify genes relevant to the development of melanoma, with a resolution of less than 40 Kbp. We have combined 71 unique CC strains with our well-characterized asbestos-induced MexTAg mouse model of mesothelioma and collected data on latency and progression. We have identified and collected tumour from animals that are relatively resistant to AIC and from animals that are highly sensitive to AIC. The CC‑MexTAg program uses an established informatics pipeline (GeneMiner) to identify alleles associated with these traits. In addition, we will fully analyse the acquired genetic changes in these different strains to determine whether the path to mesothelioma is conserved. This project has the potential to lead to an improved understanding of the pathobiology of mesothelioma by identifying new targets, and also provide the necessary data for the development of diagnostic tests to assess individual risk of developing mesothelioma after asbestos exposure. Such tests would identify patients for further active monitoring and treatment, while reassuring others that their risk of mesothelioma is low.
The results will help us to identify which asbestos-exposed people and their families are most at risk of developing mesothelioma. But perhaps more importantly this work will help to identify new targets for the next generation of treatments for this cancer.