Multi-Scale Cancer Modeling: From Cell Phenotypes to Cancer Spread and Response

多尺度癌症模型：从细胞表型到癌症扩散和反应

• 批准号: 8381751
• 负责人: Vittorio Cristini
• 金额: $ 36.46万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8381751
• 关键词: Algorithms; Biological; Biophysics; Cancer Biology; Cancer Model; Cells; Complex; Computer Simulation; Coupling; Data; Development; Feedback; Hybrids; In Vitro; Inherited; Instruction; Investigation; Link; Lymphoma; Malignant Neoplasms; Measurement; Methods; Modeling; Molecular; Molecular Models; Phenotype; Physics; Research Project Grants; Shapes; Signal Transduction; Site; Staging; System; Techniques; Testing; Time; Validation; Variant; Vascularization; Vertebral column; chemotherapy; data modeling; design; follow-up; frontier; imaging modality; improved; in vivo; innovation; insight; leukemia/lymphoma; mathematical model; model development; molecular modeling; multi-scale modeling; research study; response; simulation; spatiotemporal; three-dimensional modeling; tumor; tumor growth; tumor progression

Overall, the project is designed to (1) add insights as to the biophysical mechanisms that link molecular- and cell-scale variations in the tumor and the microenvironment to the tumor's growth, (2) develop techniques that allow us to readily incorporate cutting-edge experimental measurements into the multi-scale model and thus more quickly determine their impact on overall tumor progression and response to therapy, (3) investigate and quantify the spatiotemporal dynamics of tumor response to therapy, (4) improve the in vivo-in silico development feedback loop that forms the backbone of true integrative modeling, and so (4) push the frontier of multi-scale, integrative cancer modeling. In order to quantify the relationships between complex cancer phenomena at different scales, we harness the advantages of both discrete and continuum modeling approaches by employing hybrid modeling. We implement hybrid, multi-scale algorithms as the next stage of cancer modeling in general, and lymphoma and leukemia modeling in particular. This involves dynamically coupling tumor-scale models and molecular/cell-scale models developed by Cristini, Macklin and coworkers with cell signaling and evolutionary/hereditary models developed by Research Project 2. This also requires integration with state of- the-art intravital time-course measurements of tumor growth, vascularization, and response to chemotherapy by Gambhir and co-workers. These experiments will (1) provide us with first-hand biological data that will shape the model development, (2) provide us with precise measurements of key model parameters that uniquely constrain the modeling framework, (3) provide additional, independent tests for model validation and testing, and (4) provide an opportunity for true integrative modeling, where our first round of investigating the calibrated model leads to follow-up experiments to test new cancer biology hypotheses and improve the multiscale model.

总体而言，该项目旨在（1）添加有关肿瘤和细胞尺度变化的生物物理机制的见解肿瘤对治疗反应的时空动力学，（4）改善体内硅内发育反馈回路，形成了真正的整合建模的骨干，因此（4）（4）推动了多尺度，综合癌建模的前沿。为了量化不同尺度上复杂的癌症现象之间的关系，我们通过采用混合建模来利用离散和连续性建模方法的优势。我们将杂种，多尺度算法作为癌症建模的下一个阶段，尤其是淋巴瘤和白血病建模。这涉及由Cristini，Macklin和Croworkers开发的，与研究项目2开发的细胞信号传导和进化/遗传模型开发的动态耦合肿瘤尺度模型以及分子/细胞尺度模型。这也需要与肿瘤经液的时间课程测量的状态进行肿瘤生长，血管生长，血管生长，血管生长，gambortor co-arker-co-arkhir和co-bambhir和co-bambhir和co-bambhir的综合。这些实验（1）将为我们提供塑造模型开发的第一手生物学数据，（2）为我们提供了对关键模型参数的精确度量，这些参数独特地限制了建模框架，（3）为模型验证和测试提供了额外的独立测试，（4）提供了一个真正的集成模型，以改进校准的癌症，以改进校准的癌症癌症，以进行校准的癌症，并提供了净程癌症的癌症。多尺度模型。