Evolution of cancer transmission

新出现的传染病日益威胁着人类、野生动物和牲畜的健康。魔鬼面部肿瘤疾病(DFTD)是一种可传播的癌症，是开斋节导致标志性塔斯马尼亚魔鬼数量急剧下降的一个典型例子。自发现以来的20年里，DFTD已经在塔斯马尼亚州传播了95%，导致受影响时间最长的种群数量下降了90%以上，总种群数量减少了80%。值得注意的是，魔鬼对这种几乎总是致命的感染细胞株表现出高度的敏感性。由于传播的频率依赖性，流行病学模型预测其灭绝。然而，魔鬼在所有人群中持续存在，甚至在最长的患病地点也是如此。模型预测和经验观测之间的差异很可能是由塔斯马尼亚魔鬼和DFTD的进化反应驱动的。魔鬼们迅速进化出与癌症和免疫反应有关的候选基因，出现了抗体产生的初步迹象，甚至肿瘤完全缓解。结合贝叶斯状态空间模型和积分投影模型，通过整合接触网络中个体层面的魔鬼角色，以及魔鬼和肿瘤基因组特性的变化，来研究传播的进化。这些模型将利用对魔鬼的长期标记再捕获研究，这些研究有14,000多条陷阱记录，以及在DFTD出现之前、期间和之后采集的1,000个肿瘤分离株和10,000个魔鬼DNA样本的档案。基于疾病的可预测传播，DFTD-DEVER系统提供了前所未有的机会来测试关于新感染人群以及不同世代感染人群中疾病传播演变的模型预测。以下三个具体目标推动了拟议的研究：1)宿主(魔鬼)进化如何影响疾病传播？2)病原体(DFTD)进化如何影响传播？3)我们能否预测塔斯马尼亚魔鬼-DFTD系统中的进化动力学？

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?