Metabolic determinants of metastatic heterogeneity: quantitative experiments and mathematical models

转移异质性的代谢决定因素：定量实验和数学模型

• 批准号: 10231357
• 负责人: Deepti Mathur
• 金额: $ 7.05万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-31 至 2024-07-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10231357
• 关键词: Affect; Area; Biological Assay; Breast Cancer Cell; Cancer Biology; Cancer Etiology; Cancer Patient; Cell Line; Cells; Cessation of life; Complex; Computational Biology; Computer Models; Custom; Data; Data Analyses; Disease; Disseminated Malignant Neoplasm; Distal; Education; Educational process of instructing; Ensure; Environment; Equilibrium; Foundations; Freedom; Future; Genes; Genetic Transcription; Goals; Heterogeneity; Home; Hypoxia; Intervention; Knowledge; Lead; Malignant Neoplasms; Measurement; Mediating; Memorial Sloan-Kettering Cancer Center; Mentorship; Metabolic; Metabolic Pathway; Metabolism; Metastatic breast cancer; Modeling; Neoplasm Metastasis; Nutrient; Organ; Pathway interactions; Patients; Play; Population; Prevention; Primary Neoplasm; Probability; Process; Property; Publishing; Research; Resources; Risk; Role; Seeds; Shapes; Site; Soil; System; Systems Biology; Testing; Time; Tissues; Training; Tropism; base; cancer therapy; career; career development; drug discovery; experimental study; extracellular; in vivo; knock-down; malignant breast neoplasm; mathematical model; meetings; metabolic phenotype; metabolomics; mimetics; neoplastic cell; overexpression; potential biomarker; programs; segregation; success; tumor; tumor metabolism; tumor progression

Project Summary/Abstract It is critically important to establish the causes of organ-specific metastasis; without this knowledge, prevention and timely treatment of metastatic cancer progression will likely remain limited. The proposed project aims to identify how metabolic gradients in the primary tumor can maintain diverse lineages with specific metabolic adaptations, and how these adaptations contribute to organ-specific metastasis in breast cancer. The central hypothesis is 1) that metabolic adaptations are key to the match between the seed (the disseminated cell) and the soil (the distal site) in metastatic breast cancer, and 2) that the metabolic microenvironment in a primary tumor drives metabolically diverse subpopulations. The hypothesis has been formulated based on 1) published data detailing metabolic heterogeneity and that metabolic adaptations can promote metastasis, 2) preliminary data and analysis of RNA expression, metabolomics, and flux measurements, revealing different metabolic adaptations in breast tumor cells that home to different tissues, and 3) preliminary data showing that metastatic lineages respond differently to hypoxia and nutrient gradients, indicating a role for the metabolic microenvironment in maintaining diverse subpopulations within the same heterogeneous primary tumor. The proposed aims will be accomplished using a combination of experimental and computational biology. Integrated flux balance models of metastatic lineages will identify perturbed metabolic pathways in each lineage. Knocking down or overexpressing key nodes in these pathways and assessing tropism in vivo will determine the role of metabolic adaptations in organ-specific metastatic selection. The ability of spontaneous nutrient gradients in the primary tumor to affect spatial segregation of lineages with distinct metabolic adaptations will be investigated using custom MEMIC tissue mimetic plates. Mathematical models will be used to study the ecological interactions between cell lines and their microenvironment that lead to coexistence of metabolically distinct pre-metastatic subpopulations in the primary tumor. Joao Xavier will provide excellent mentorship for this project and the candidate’s career goals of leading an independent research program, with a combination of hands-on teaching and freedom for independent discovery. The current project will form the foundation of the candidate’s future independent research. The training plan also includes meetings with a co-sponsor and collaborators, facilitating a comprehensive education and ensuring a high probability of success for the project. The environment at MSKCC provides further resources important for the completion of the proposed project, as well as career development support as the candidate transitions to an independent career.

项目总结/摘要 确定器官特异性转移的原因至关重要;如果没有这些知识， 转移性癌症进展的预防和及时治疗可能仍然有限。拟议 该项目旨在确定原发性肿瘤中的代谢梯度如何维持不同的谱系， 特定的代谢适应，以及这些适应如何有助于乳腺癌的器官特异性转移 癌核心假设是1）代谢适应是种子（种子）之间匹配的关键。 扩散的细胞）和土壤（远端部位）在转移性乳腺癌，和2），代谢 原发性肿瘤中的微环境驱动代谢多样化的亚群。这个假设是 根据1）详细说明代谢异质性的已发表数据制定，代谢适应可以 促进转移，2）RNA表达、代谢组学和通量的初步数据和分析 测量，揭示了不同的代谢适应乳腺肿瘤细胞的家园不同的组织， 和3）初步数据显示转移谱系对缺氧和营养梯度的反应不同， 这表明代谢微环境在维持同一细胞内的不同亚群中的作用， 异质性原发性肿瘤 所提出的目标将通过实验和计算相结合来实现 生物学转移性谱系的综合通量平衡模型将确定受干扰的代谢途径， 每一个血统。敲除或过表达这些通路中的关键节点并评估体内向性 将决定器官特异性转移选择中代谢适应的作用。的能力 原发性肿瘤中自发的营养梯度影响具有不同分化的谱系的空间分离 将使用定制的MEMIC组织模拟板研究代谢适应。数学模型 将用于研究细胞系与其微环境之间的生态相互作用， 原发性肿瘤中代谢不同的转移前亚群共存。 Joao Xavier将为该项目和候选人的职业目标提供出色的指导， 领导一个独立的研究计划，与实践教学和自由的组合， 独立发现。目前的项目将形成候选人未来独立的基础 research.培训计划还包括与共同赞助者和合作者的会议， 全面的教育，确保项目成功的可能性很高。的环境 MSKCC提供了进一步的资源，对完成拟议的项目以及职业生涯非常重要。 在候选人向独立职业过渡时提供发展支持。