Applying Molecular Phylogeny to Predict Clinical Outcomes in Cancer

描述（由申请人提供）：我们的目标是研究癌症分子遗传学（一种新的技术概念）预测临床结果的效用。我们建议使用癌症年龄的分子测量，而不是使用新的高通量技术来识别分子标记或签名来预测生存率。由于我们没有观察到初始转化和克隆扩增，因此癌症年龄的估计变得复杂。我们观察到的是一群细胞，它们是原始转化细胞的后代。我们能测量的是种群的分子多样性。群体遗传学决定了来自老年群体的细胞将比来自年轻群体的细胞表现出更多的多样性。因此，肿瘤多样性的分子测量应该捕获肿瘤年龄。我们建议肿瘤年龄将有助于预测患者的预后。因此，我们挑战目前的范式，寻找一个共同的途径，癌症的发展，导致生存率低。相反，我们提出，无论累积的突变序列如何，老年肿瘤都更加多样化，正是这种多样性使它们对化疗具有抗性并易于扩散，从而导致更差的结果。我们建议使用细胞系校准这种新技术，以表征大量（表）基因组区域的细胞分裂的多样性和传代次数之间的关联。我们假设，这种基本的，但目前尚未研究的肿瘤特征的老化，将预测临床结果。我们建议证明这一点的特殊情况下，癌症患者的第三阶段结肠癌。如果成功，该方法有望预测许多不同癌症部位（例如乳腺癌，肺癌，前列腺）实体瘤的临床结果。该应用程序有两个具体目标：目标1：表征70个体细胞癌分子钟以测量进展史;目标2：测试转移的时间是否与III期结直肠癌无病生存期相关。 公共卫生相关性：我们的假设是，老年癌症的细胞群比年轻癌症更多样化，对治疗的抵抗力更强。然而，这个简单的假设从未被验证过，因为我们没有观察到癌症的初始转化和克隆扩增，因此无法直接测量肿瘤年龄。我们通过应用群体遗传学领域的概念来推断肿瘤年龄来解决这一基本挑战。在这个项目中，我们应用分子生物学的工具来预测癌症研究的临床结果。

DESCRIPTION (provided by applicant): Our goal is to investigate the utility of cancer molecular phylogeny, a novel technological concept, to predict clinical outcomes. Rather than use novel high-throughput technologies to identify a molecular marker or signature to predict survival, we propose to use a molecular measure of cancer age. Estimation of cancer age is complicated by the fact that we do not observe the initial transformation and clonal expansion. What we do observe is a population of cells that are descendants of the original transformed cell. What we can measure is the molecular diversity of the population. Population genetics dictates that cells from an older population will show more diversity than cells from a younger population. Thus a molecular measure of tumor diversity should capture tumor age. We propose that tumor age will help predict patient outcomes. Thus, we challenge the current paradigm of finding a common pathway of cancer development that leads to poor survival. Instead we propose that older tumors are more diverse, regardless of the sequence of mutations accumulated, and that it is this diversity that makes them resistant to chemotherapy and prone to dissemination, thus leading to poorer outcomes. We propose to calibrate this novel technology using cell lines, in order to characterize the association between diversity and number of passages of cell division at a large number of (epi)genomic regions. We hypothesize that this basic, but presently unstudied, tumor characteristic of aging, will predict clinical outcome. We propose to demonstrate this for the special case of cancer patients with Stage III colon cancers. If successful, the approach has promise for predicting clinical outcome for solid tumors of many different cancer sites (e.g. breast, lung, prostate). This application has two Specific Aims: Aim 1: Characterize 70 somatic cell cancer molecular clocks to measure progression histories; Aim 2: Test whether the timing of metastases correlates with Stage III colorectal cancer disease-free survival. PUBLIC HEALTH RELEVANCE: Our hypothesis is that older cancers are more diverse cell populations and more resistant to treatment than younger cancers. However, this simple hypothesis has never been tested because we do not observe the initial transformation and clonal expansion of a cancer, and therefore cannot measure tumor age directly. We resolve this fundamental challenge by apply concepts from the field of population genetics to infer tumor age. In this project we apply tools for molecular phylogeny to predict clinical outcomes in cancer research.