Topology of Cancer Evolution and Heterogeneity

 描述（由申请人提供）：在实体瘤中，目前我们在识别起源细胞、跟踪肿瘤亚克隆结构随时间和空间的动态以及以机械方式预测药物敏感性方面的能力有限，这对我们开发有效治疗的能力构成了重大挑战，并破坏了现有疗法的效用，特别是在耐药肿瘤中。在这个建议中，我们认为，基于数学和物理的方法非常适合解决这些关键问题。从历史上看，物理科学已经成功地解决了基本的科学问题，通过生产简化模型，使概念前提的发展，技术突破，使新的测量，数学工具，可以准确地表示和预测未来的活动。在这个新的哥伦比亚大学物理科学-肿瘤学中心癌症演变和异质结的拓扑结构（CUPS-OC），我们的目标是开发，验证和提供一套互补的数学，技术和计算方法，将为癌症研究界提供一个框架，解开实体瘤的复杂性，长期目标是改善诊断和治疗。更具体地说，该中心的主要研究重点将是通过发展谱系追踪，在单细胞水平上研究实体瘤的进化和异质性。 类器官和体内系统中的技术，原发性肿瘤中的单细胞测序，以及用于鉴定靶向疗法的新兴基因组学方法。这些实验方法将得到基于拓扑学领域的新颖，稳健和有效的数学和计算方法的发展的支持，这些方法提供了独特而强大的方法，用于解决解释最先进的基因组学技术产生的高维数据集的基本挑战。此外，我们将通过培训新的研究人员和从事物理科学和癌症生物学交叉领域的研究人员，促进物理科学方法与癌症研究的整合。每个项目和核心将解决技术，数学和生物学挑战，为癌症研究的全球企业做出贡献，并致力于发展更广泛的跨学科研究人员网络，以推进该领域的发展。如果成功，我们将能够为科学界提供实验验证的克隆进化因果推理的几何和拓扑结构，快速可靠地揭示克隆异质性的单细胞基因组协议，实验验证的机器学习方法用于预测药物敏感性，以及一个强大的多机构，跨学科计划，在纯数学研究人员之间建立桥梁，技术部门和癌症研究。

 DESCRIPTION (provided by applicant): In solid tumors, current limitations in our ability to identify the cell(s) of origin, track the dynamics of tumor subclonal architecture over space and time, and predict drug sensitivities in a mechanistic fashion pose significant challenges to our ability to develop effective treatments and undermine the utility of available therapies, particularly in tumors that become resistant. In this proposal, we argue that approaches based in mathematics and physics are well suited for addressing these critical problems. Historically, the physical sciences have been successful in solving fundamental scientific problems by producing reductionist models that enable the development of conceptual premises, technological breakthroughs that enable new kinds of measurements, and mathematical tools that can accurately represent and predict future activity. In this new Columbia University Physical Sciences-Oncology Center for Topology of Cancer Evolution and Heterogeneity (CUPS-OC), our goal is to develop, validate, and deliver a set of complementary mathematical, technological, and computational approaches that will provide the cancer research community with a framework for unraveling complexity in solid tumors, with the long-term aim of improving diagnosis and treatment. More specifically, the Center's primary research focus will be to study evolution and heterogeneity of solid tumors at the single cell level, by developing lineage tracing techniques in organoid and in vivo systems, single cell sequencing in primary tumors, and emerging genomics-based approaches for identifying targeted therapies. These experimental approaches will be supported by the development of novel, robust, and effective mathematical and computational approaches based in the field of topology, which offers unique and powerful methods for addressing the essential challenge of interpreting the high-dimensional data sets that state-of-the- art genomics technologies generate. In addition, we will promote the integration of physical science approaches into cancer research by both training new researchers and engaging established researchers working at the intersection of the physical sciences and cancer biology. Each of the projects and cores will address technical, mathematical, and biological challenges, contributing to the global enterprise of cancer research and to the development of a broader network of interdisciplinary researchers committed to advancing the field. If successful, we will be able to provide the scientific community with experimentally validated geometric and topological structures of causal inference of clonal evolution, single cell genomic protocols for fast and reliable uncovering of clonal heterogeneity, experimentally validated machine learning approaches for predicting drug sensitivities, and a strong multi-institutional, interdisciplinary program that creates bridges between researchers in pure mathematics, the technology sector, and cancer research.