Topology of Cancer Evolution and Heterogeneity

癌症进化和异质性的拓扑

基本信息

批准号：
8866149
负责人：
Antonio Iavarone
金额：
$ 199.09万
依托单位：
COLUMBIA UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-05-19 至 2020-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8866149
关键词：
Address Architecture Area Biological Biological Sciences Cancer Biology Cells Chronic Myeloid Leukemia Clinical Clonal Evolution Collaborations Communities Complex Computer Analysis Consensus Data Data Set Development Diagnosis Drug resistance Education and Outreach Educational workshop Event Evolution Experimental Models Foundations Future Genetic Genomic approach Genomics Goals Hematologic Neoplasms Heterogeneity Human Institution Logic Machine Learning Malignant Neoplasms Mathematics Measurement Methods Modeling Molecular Profiling Mutation New York Operative Surgical Procedures Organoids Penetrance Physics Pilot Projects Primary Neoplasm Protocols documentation Radiation therapy Recurrence Research Research Personnel Research Project Grants Resistance Resources Role Route Scientist Solid Neoplasm Structure System Techniques Technology Theoretical model Therapeutic Time Training Universities Work anticancer research base bcr-abl Fusion Proteins chemotherapy clinically relevant computerized tools design drug sensitivity effective therapy imprint improved in vivo interdisciplinary approach leukemia mathematical methods metropolitan novel novel therapeutic intervention oncology outcome forecast patient population physical science pressure prognostic programs public health relevance single cell sequencing success targeted treatment tool traditional therapy treatment planning tumor tumor progression

项目摘要

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.

描述（通过应用程序提供）：在实体瘤中，我们识别出来源细胞的能力的当前局限性，跟踪时间和时间上肿瘤亚克隆建筑的动力学，并预测机械方式中的药物敏感性对我们开发有效治疗的能力构成了重大挑战，并破坏了可用疗法的实用性，尤其是在具有抵抗力的玻璃疗法中。在此提案中，我们认为基于数学和物理学的方法非常适合解决这些关键问题。从历史上看，物理科学通过生产还原主义模型来成功解决基本科学问题，从而能够开发概念前提，技术突破，从而实现新型的测量以及可以准确代表和预测未来活动的数学工具。在这个新哥伦比亚大学的癌症进化与异质性拓扑拓扑中心（CUPS-OC）中，我们的目标是开发，验证和提供一系列互补的数学，技术和计算方法，这些方法将为癌症研究社区提供框架，以在实体瘤中散发出复杂性，并具有长期的临床诊断和治疗方法。更具体地说，该中心的主要研究重点是通过开发谱系跟踪来研究单细胞水平实体瘤的进化和异质性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基于基因组学的新方法，用于鉴定靶向疗法。这些实验方法将通过基于拓扑领域的新颖，健壮和有效的数学和计算方法的开发来支持，该方法为解释最先进的基因组技术生成的高维数据集提供了独特而有力的方法。此外，我们将通过培训新研究人员和参与物理科学与癌症生物学交集的既定研究人员的培训，从而促进物理科学方法与癌症研究的融合。每个项目和核心都将应对技术，数学和生物学挑战，从而为癌症研究的全球企业做出贡献，并促进更广泛的跨学科研究人员网络的发展，该网络致力于推进该领域。如果成功的话，我们将能够为科学界提供经过实验验证的几何和拓扑结构，这些结构和拓扑结构是克隆进化的因果推理，单细胞基因组协议，用于快速且可靠地揭示克隆异质性，实验验证的机器学习方法，用于预测药物敏感性的机器敏感性，以及强大的多型技术，纯粹的互联网互联网互联网，以构成互构成的技术，以构成互联网的互联网，以构成互构成的互联网互助。部门和癌症研究。