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Predictive experiment-based multiscale models of angiogenesis in breast cancer

基于预测实验的乳腺癌血管生成多尺度模型

基本信息

批准号：
8917130
负责人：
ALEKSANDER S. POPEL
金额：
$ 52.61万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-02-13 至 2019-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8917130
关键词：
Accounting American Cancer Society Angiogenic Factor Binding Biological Markers Blood Blood Vessels Blood Volume Brain Breast Cancer Cell Breast Cancer Model Breast Cancer cell line Breast cancer metastasis Cancer Biology Cancer Etiology Cell Communication Cell Line Cell Surface Receptors Cells Cessation of life Characteristics Clinical Data Computer Simulation Computers Coupled Data Development Diagnosis Diagnostic Neoplasm Staging Differential Equation Drug Kinetics ERBB2 gene Epithelial Cells Estrogens Extracellular Matrix Family Fatty acid glycerol esters Female Goals Growth Human Hybrids Hypoxia IL6 gene Image Imaging Techniques Immune Immunohistochemistry Intercellular Fluid Interleukin-6 Lead Ligands Luciferases Lung Lymphatic Lymphatic Endothelial Cells Lymphatic vessel MCF7 cell MDA MB 231 Malignant Neoplasms Malignant neoplasm of lung Mammary Neoplasms Mammary gland Measurement Mesenchymal Metastatic Neoplasm to the Lung Microscopy Modeling Molecular Mus NRP1 gene Neoadjuvant Therapy Neoplasm Metastasis Operative Surgical Procedures Organ PGF gene Patients Pharmaceutical Preparations Pharmacodynamics Play Primary Neoplasm Process Progesterone RANTES Regimen Regulation Research Role Signal Transduction Site Source Staging Testing Therapeutic Therapeutic Intervention Tissues Transport Process Tumor Angiogenesis Tumor stage United States VEGFA gene Validation Vascular Endothelial Growth Factor Receptor-1 Vascular Endothelial Growth Factors Vascular Permeabilities Vascular blood supply Woman Xenograft procedure angiogenesis base bone cancer cell cell type chemokine computer studies cytokine effective therapy in vivo Model insight killings malignant breast neoplasm multi-scale modeling neoplastic cell outcome forecast pharmacodynamic model public health relevance receptor reconstruction research study screening therapeutic target three-dimensional modeling triple-negative invasive breast carcinoma tumor tumor growth tumor microenvironment tumor progression tumor xenograft

项目摘要

DESCRIPTION (provided by applicant): This research will focus on triple-negative breast cancer (TNBC), which is highly metastatic, has the worst prognosis among breast cancer subtypes, and is lacking effective therapies. Interactions between different cell types in the tumor microenvironment and metastatic niches are determinants of metastatic progression. In particular, tumor angiogenesis plays an important role since tumors require blood supply to grow and metastasize. A quantitative understanding of the complexity of these interactions is presently lacking. To achieve a better understanding of these processes, the development of predictive experiment-based molecular-detailed computational models of tumor growth and metastasis is necessary. The long-term goal of this project is to develop experiment-based mechanistic models of breast cancer and apply them to modeling therapeutic interventions. Specifically, we will use experimental and computational approaches to: (1) investigate key angiogenic factors, cytokines and chemokines in the progression of breast tumors to metastases; (2) investigate the characteristics of lung metastasis, the most common site for TNBC metastases; (3) test anti-metastatic agents by targeting selective cytokines, angiogenic factors and chemokines. The computational developments will be tightly coupled to the cutting-edge imaging techniques at the molecular, cellular, microvascular, and tissue levels. Invasive human breast cancer cell lines will be used to generate orthotopic xenografts in the mammary fat pad of female mice. The measurements will include the characterization and localization of receptor and ligand expression for a wide range of molecules of the VEGF family together with selected cytokines and chemokines at different stages of tumor growth and metastasis, such as interleukin-6 and CCL5; temporal and spatial development of hypoxia and microvasculature in growing tumors, and functional characteristics of the tumor vasculature and interstitium, e.g. blood volume, vascular permeability, diffusive transport in the tumor extracellular matrix (ECM). Immunohistochemistry and 3D microscopy will be used to characterize lung metastases. Part of these data will serve as the input to computational models and part used for model validation. Several therapeutic, anti-metastatic agents targeting selective cytokines, chemokines and angiogenic factors will be used, and their molecular interactions and transport will be modeled using ordinary differential equation-based compartmental models, three-dimensional partial differential equation-based models, agent-based models, and hybrid models. The research will contribute to a fundamental understanding of breast cancer biology, to the identification of therapeutic targets and biomarkers, and to a quantitative interpretation of clinical data. The synergistic combination of computational and experimental studies will provide significant insights into metastatic TNBC.

描述（由申请人提供）：本研究将重点关注三阴性乳腺癌（TNBC），其具有高度转移性，在乳腺癌亚型中预后最差，并且缺乏有效的治疗方法。肿瘤微环境和转移小生境中不同细胞类型之间的相互作用是转移进展的决定因素。特别是，肿瘤血管生成起着重要的作用，因为肿瘤需要血液供应来生长和转移。目前缺乏对这些相互作用复杂性的定量了解。为了更好地理解这些过程，有必要开发基于预测实验的肿瘤生长和转移的分子详细计算模型。该项目的长期目标是开发基于实验的乳腺癌机制模型，并将其应用于治疗干预的建模。具体而言，我们将使用实验和计算方法：（1）研究乳腺肿瘤向转移进展中的关键血管生成因子、细胞因子和趋化因子;（2）研究肺转移的特征，肺转移是TNBC转移的最常见部位;（3）通过靶向选择性细胞因子、血管生成因子和趋化因子来测试抗转移剂。计算技术的发展将与分子、细胞、微血管和组织水平的尖端成像技术紧密结合。侵袭性人乳腺癌细胞系将用于在雌性小鼠的乳腺脂肪垫中产生原位异种移植物。测量将包括在肿瘤生长和转移的不同阶段，VEGF家族的广泛分子以及所选细胞因子和趋化因子（如白细胞介素-6和CCL 5）的受体和配体表达的表征和定位;生长肿瘤中缺氧和微血管的时间和空间发展，以及肿瘤血管和微血管的功能特征，例如血容量，血管通透性，肿瘤细胞外基质（ECM）的扩散运输。将使用免疫组织化学和3D显微镜来表征肺转移。这些数据的一部分将作为计算模型的输入，一部分用于模型验证。将使用靶向选择性细胞因子、趋化因子和血管生成因子的几种治疗性抗转移剂，并且将使用基于常微分方程的房室模型、基于三维偏微分方程的模型、基于试剂的模型和混合模型来建模它们的分子相互作用和转运。该研究将有助于对乳腺癌生物学的基本理解，识别治疗靶点和生物标志物，以及对临床数据的定量解释。计算和实验研究的协同组合将为转移性TNBC提供重要见解。