Statistical Models in Epigenomics

描述（由申请人提供）：主要目标是利用“分子钟假说”开发数学模型，使我们能够研究癌症如何生长和扩散。人类癌症的生长无法直接观察，总体目标是开发一种方法，通过“读取”复制错误秘密写入基因组中的祖先来回顾性重建肿瘤进展。序列通常用于重建物种和个体的谱系，我们建议将这种通用的分子系统发育方法转化为人类癌症。我们将使用 DMA 甲基化数据，这是一种在细胞分裂时复制的 DNA 表观遗传修饰。由于直接计算可能不切实际或不可行，因此我们建议使用拒绝算法，这是一种基于模拟的方法。这个总体框架将使我们能够估计肿瘤的年龄、转移的年龄、甲基化错误率以及转移是否源自原发癌症的细胞群。我们的目标源于南加州大学莫里斯综合癌症中心正在进行的研究。具体来说，我们建议： 1. 开发方法，使我们能够使用 5' 至 3' DNA 甲基化模式来估计表征癌症生长的参数。这些模型将解决以下生物学问题：根据甲基化模式推断的祖先树类型来测试癌症干细胞的存在 b．评估肿瘤异质性 C.估计肿瘤年龄和甲基化错误率 2. 扩展目标 1 中开发的模型来研究癌症的扩散。目标是比较两个细胞群（原发肿瘤和转移瘤）并确定它们是否年龄相同，或者其中一个细胞群是否更年轻并且源自另一个细胞群。 3. 扩展目标 1 和 2 中的模型，使每个 CpG 位点的甲基化概率取决于邻近 CpG 的甲基化状态，并评估其对感兴趣的生物学问题的影响。 4. 将这些方法应用于在人类和小鼠的结肠原发性肿瘤和远处转移肿瘤中观察到的 DNA 甲基化模式。

DESCRIPTION (provided by applicant): The primary objective is to utilize the 'molecular clock hypothesis' to develop mathematical models that will allow us to study how cancers grow and spread. Human cancer growth cannot be directly observed and the overall goal is to develop an approach that can retrospectively reconstruct tumor progression by "reading" the ancestry surreptitiously written within genomes by replication errors. Sequences are commonly used to reconstruct the genealogy of species and individuals, and we propose to translate this general molecular phylogeny approach to human cancers. We will use DMA methylation data, an epigenetic modification of DNA that is replicated at cell division. As direct calculation can be either impractical or infeasible, we propose to use rejection algorithms, a simulation-based approach. This general framework will allow us to estimate the age of a tumor, the age of a metastasis, the methylation error rate, and whether the metastasis is derived from a population of cells from the primary cancer. Our aims are motivated by ongoing studies at the Morris Comprehensive Cancer Center at the University of Southern California. Specifically, we propose to: 1. Develop methods that will allow us to estimate parameters characterizing the growth of cancer using 5' to 3' DNA methylation patterns. The models will address the following biological problems: a. To test for the existence of cancer stem cells based on the types of ancestral trees inferred from the methylation patterns b. To evaluate tumor heterogeneity c. To estimate tumor age and the rate of methylation errors 2. Extend models developed in Aim 1 to study the spread of cancer. The goal will be to compare two cell populations (primary tumor and metastasis) and determine if they are the same age, or if one is younger and derived from the other. 3. Extend the model in Aims 1 and 2 to allow the probability of methylation at each CpG site to depend on the methylation status of neighboring CpGs and evaluate its effect on the biological questions of interest. 4. Apply the methods to DNA methylation patterns observed in primary tumors of the colon and distant metastasis in humans and in mice.