Emerging infectious diseases (EIDs) increasingly threaten human, wildlife and livestock health. Devil facial tumor disease (DFTD), a transmissible cancer, is a marquee example of an EID that has caused dramatic declines of the iconic Tasmanian devil. In 20 years since its discovery, DFTD has spread 95% of the way across Tasmania, causing greater than 90% declines in populations affected the longest, and reducing the total population size by 80%. Remarkably, devils show high susceptibility to this infectious cell line, which is nearly always fatal. Due to the frequency-dependent nature of transmission, epidemiological models predict extinction. However, devils persist in all populations, even in the longest diseased sites. The discrepancy between model predictions empirical observations is likely driven by evolutionary responses in Tasmanian devils and DFTD. Devils have rapidly evolved at candidate genes responsible for cancer and immune response, with first signs of antibody production and even complete tumor remission. A combination of Bayesian state-space models and integral projection models are proposed to study the evolution of transmission by integrating individual-level devil roles in contact networks, as well as variation in devil and tumor genomic properties. These models will capitalize on long-term mark-recapture studies of devils with over 14,000 trap records, as well as an archive of 1,000 tumor isolates and 10,000 devil DNA samples taken before, during and after DFTD emergence. Based on the predictable spread of the disease, the DFTD-devil system affords the unprecedented opportunity to test model predictions regarding evolution of disease transmission in newly infected populations, as well as those infected for varying numbers of generations. The following three specific aims drive the proposed research: 1) How does host (devil) evolution influence disease transmission? 2) How does pathogen (DFTD) evolution influence transmission? 3) Can we predict evolutionary dynamics in the Tasmanian devil-DFTD system?
The proposed work entails predicting cancer evolution in Tasmanian devils. Using advanced genomic techniques, the study will reveal key mutations that lead to cancer success. Consequent gene editing techniques will help identify potential targets for drug-related therapies with possible implications for human cancer treatment.
| Storfer, Andrew; Hohenlohe, Paul A; Margres, Mark J et al. (2018) The devil is in the details: Genomics of transmissible cancers in Tasmanian devils. PLoS Pathog 14:e1007098 |
| Margres, Mark J; Ruiz-Aravena, Manuel; Hamede, Rodrigo et al. (2018) The Genomic Basis of Tumor Regression in Tasmanian Devils (Sarcophilus harrisii). Genome Biol Evol 10:3012-3025 |
| Lazenby, Billie T; Tobler, Mathias W; Brown, William E et al. (2018) Density trends and demographic signals uncover the long-term impact of transmissible cancer in Tasmanian devils. J Appl Ecol 55:1368-1379 |
