The Role of the Microbiome in Cancer Suppression and Susceptibility Across Species

项目总结： 为什么有些物种特别容易患癌症，而另一些物种患癌症的几率却很小？ 我们发现，癌症患病率在不同物种之间存在很大差异。然而，我们可以 只解释这种变化的一小部分。我们假设物种的微生物群 可能解释了他们癌症流行的部分原因。具体地说，我们假设微生物群 多样性防止致病微生物占优势，因此应该与较低的 癌症在不同物种中的流行。我们还假设，已经被 与人类癌症有关的人将与更高的肿瘤和恶性肿瘤相关 在动物中流行。同样，与较低癌症相关的微生物种类 人类的患病率将与较低的肿瘤和恶性肿瘤患病率相关 在动物之间。我们还将测试癌症患病率与未感染的微生物的关系 之前被认为与癌症有关。我们将下载公开可用的微生物组16s 我们的比较肿瘤学数据库中164个物种的rRNA数据，我们至少有 50份尸检报告。如果缺乏这些物种的16S rRNA数据，我们将合作 与凤凰城和其他动物园一起获取粪便样本，我们将对这些样本进行测序，以分析 胃肠道微生物组。因为饮食和微生物群是更重要的因素 比许多其他可能解释癌症患病率的变量更容易修改，如基本 代谢率，我们的分析结果可能会转化为癌症预防 人类。

Project Summary: Why are some species particularly susceptible to cancer while others develop very little cancer? We have discovered wide variation in cancer prevalence across species. However, we can explain only a small fraction of that variation. We hypothesize that the microbiomes of species may explain part of their cancer prevalence. Specifically, we hypothesize that microbiome diversity prevents pathogenic microbes from dominating and so should be associated with lower cancer prevalence across species. We also hypothesize that microbial species that have been associated with cancer in humans will be associated with higher neoplasia and malignancy prevalence across animals. Likewise, microbial species associated with lower cancer prevalence in humans will be associated with lower neoplasia and malignancy prevalence across animals. We will also test for cancer prevalence associations with microbes that have not been previously connected to cancer. We will download publicly available microbiome 16S rRNA data for the 164 species in our comparative oncology database for which we have at least 50 necropsy reports. If 16S rRNA data is lacking for any of those species, we will collaborate with the Phoenix and other zoos to acquire stool samples that we will sequence to profile the gastrointestinal microbiome. Because diet and microbiome are factors that are much more easily modified than many other variables that may explain cancer prevalence, such as basal metabolic rate, the results of our analyses are potentially translatable to cancer prevention in humans.