Evolution of cancer transmission

癌症传播的演变

• 批准号: 9765050
• 负责人: ANDREW T STORFER
• 金额: $ 57.95万
• 依托单位: WASHINGTON STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-10 至 2021-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9765050
• 关键词: Affect; Antibody Formation; Archives; Candidate Disease Gene; Cell Line; DNA; Disease; Disease remission; Drug Targeting; Emerging Communicable Diseases; Evolution; Extinction (Psychology); Face; Frequencies; Generations; Genes; Genomics; Health; Human; Immune response; Individual; Lead; Livestock; Malignant Neoplasms; Modeling; Mutation; Nature; Population; Population Sizes; Predisposition; Property; Records; Research; Role; Sampling; Site; Space Models; System; Techniques; Testing; Variant; Work; base; cancer therapy; disease transmission; epidemiological model; pathogen; predictive modeling; response; success; transmission process; tumor

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?

新出现的传染病日益威胁着人类、野生动物和牲畜的健康。魔鬼面部肿瘤病（DFTD）是一种传染性癌症，是EID的一个典型例子，它导致了标志性的塔斯马尼亚魔鬼的急剧减少。自发现以来的20年里，DFTD已经在塔斯马尼亚蔓延了95%，导致受影响时间最长的种群数量减少了90%以上，种群总数减少了80%。值得注意的是，魔鬼对这种传染性细胞系表现出高度敏感性，这种细胞系几乎总是致命的。由于传播的频率依赖性，流行病学模型预测灭绝。然而，恶魔在所有人群中都存在，即使是在患病时间最长的地区。模型预测和经验观察之间的差异可能是由袋獾和DFTD的进化反应驱动的。魔鬼在负责癌症和免疫反应的候选基因上迅速进化，有抗体产生的最初迹象，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，研究了传播的演变。这些模型将利用对魔鬼的长期标记再捕获研究，其中有超过14,000个陷阱记录，以及在DFTD出现之前，期间和之后采集的1,000个肿瘤分离物和10,000个魔鬼DNA样本的档案。基于可预测的疾病传播，DFTD-devil系统提供了前所未有的机会来测试关于新感染人群以及感染不同世代的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系统的进化动力学？