Core 2: Ecological Core

核心2：生态核心

• 批准号: 10730409
• 负责人: Joel Brown
• 金额: $ 33.79万
• 依托单位: H. LEE MOFFITT CANCER CTR & RES INST
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10730409
• 关键词: 3-Dimensional; Behavior; Biological Markers; Calibration; Cataloging; Cells; Clinical; Complex; Computer software; Data; Development; Dimensions; Ecological Change; Ecology; Ecosystem; Environment; Feedback; Generations; Genotype; Heterogeneity; Histology; Image; Immune; Immunofluorescence Immunologic; Investigation; Maintenance; Malignant Neoplasms; Malignant neoplasm of lung; Methods; Modeling; Non-Small-Cell Lung Carcinoma; Pattern; Recording of previous events; Resolution; Sampling; Shelter facility; Slice; Speed; Stains; Techniques; Testing; Thinking; Time; Tissues; Visualization; cancer therapy; computational pipelines; data pipeline; high dimensionality; histological specimens; image registration; imaging modality; improved; insight; interest; mathematical model; multimodality; multiplexed imaging; novel therapeutic intervention; spatiotemporal; three dimensional structure; tissue reconstruction; tool; treatment response; tumor; tumor behavior; tumor heterogeneity; tumor microenvironment; tumor progression; tumor-immune system interactions; whole slide imaging

Summary – Ecological Core Recent advances in spatial ‘omics’ have led to an increased interest in studying and predicting emergent aggregate behavior and interactions between the tumor and its microenvironment. Tumors are dynamic, rapidly evolving and undergoing ecological shifts; therefore, the understanding of tumor progression and response to therapy will benefit from studying eco-evolutionary interactions over time. Investigation of the spatial and spatiotemporal interactions within the tumor immune microenvironment requires computational approaches to identify and investigate the diverse ecological patterns that emerge by virtue of these complex dynamics. The Ecological Analysis Core will cater to the generation, investigation, and application of the spatial ecological models and techniques to support the two non-small cell lung cancer (NSCLC)-focused Projects of the proposal. Given that ecological change over space and/or time (the Δ-Ecology) is a central theme shared by both Projects, the Core is poised to support and tailor the tools to the requirements of each Project. The Core will have the capability to the ability to manage, visualize, store, share, and perform quantitative analyses of the high-dimensional and high-resolution clinical and experimental histology images. We will also build important computational approaches and developmental frameworks to improve our understanding and prediction of emergent tumor behavior using the images. In summary, the Core will develop and apply spatial ecological models in concert with mathematical models from the Mathematical Modeling Core to understand the evolutionary ecology underlying the diversity and maintenance of tumor heterogeneity, and how this can be leveraged to guide new therapeutic strategies for lung cancer.

摘要 - 生态核心 空间“ OMICS”的最新进展导致对研究和预测新兴的兴趣增加 肿瘤及其微环境之间的骨料行为以及相互作用。肿瘤是动态的 迅速发展并经历了生态转变；因此，理解肿瘤进展和 随着时间的推移，研究生态进化的相互作用将受益。调查 肿瘤免疫微环境内的空间和空间临时相互作用需要计算 识别和研究潜水员生态模式的方法 动力学。生态分析核心将迎合空间的产生，调查和应用 支持两个非小细胞肺癌（NSCLC）的研究模型和技术 提案。鉴于空间和/或时间（δ生物学）的生态变化是共享的中心主题 在这两个项目中，核心都被中毒以支持和量身定制每个项目要求的工具。 核心将具有管理，可视化，存储，共享和执行定量分析的能力 高维和高分辨率临床和实验组织学图像的图像。我们还将建立 重要的计算方法和发展框架，以提高我们的理解和 使用图像预测新兴肿瘤行为。总而言之，核心将开发和应用空间 与来自数学建模核心的数学模型共同了解的生态模型 肿瘤异质性多样性和维持的基础的进化生态，以及如何是 杠杆来指导肺癌的新治疗策略。