Integrated Multi-Scale Analysis of Tumor and Host Response to Therapy

肿瘤和宿主对治疗反应的综合多尺度分析

• 批准号: 8381753
• 负责人: SHAN X. WANG
• 金额: $ 72.35万
• 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/8381753
• 关键词: Antibody Formation; Antineoplastic Agents; Cancer Intervention; Cancer Model; Complex; Computer Simulation; Cyclophosphamide; Cytarabine; Data Set; Disease; Disease model; Doxorubicin; Drug resistance; Drug toxicity; Etiology; Evaluation; Evolution; Feedback; Foundations; Future; Growth; Immune; Immune response; Inflammation; Instruction; Intervention; Malignant Neoplasms; Measurement; Measures; Mediating; Modeling; Modeling of Functional Interactions; Molecular; Monitor; Patients; Protein Microchips; RNA Interference; Relative (related person); Serum; Site; Small Interfering RNA; Statistical Models; System; Technology; Testing; Therapeutic; Time; Tissues; Treatment Failure; Treatment Protocols; angiogenesis; base; cytokine; cytotoxic; density; host neoplasm interaction; improved; in vivo; insight; intercellular communication; leukemia/lymphoma; mouse model; nano; neoplastic cell; novel; peripheral blood; protein profiling; response; standard care; tumor; tumor growth; tumor initiation; tumor progression; virtual

Many factors contribute to treatment failure in cancer including lack of tumor response to the drugs, toxicity to the host, tumor growth in sanctuary sites and the emergence of resistance to drugs among others. Typically, these factors are studied individually, but it is their action in concert that ultimately overwhelms the patient. Therefore, it is of paramount importance to take an integrated and systems approach to studying the interaction of how both the tumor and host respond over time and in response to various cancer interventions. Project 4 is dedicated to multi-scale measurements of the host response to cancer and its therapy and integrating this information with the tumor responses measured by the other projects into a comprehensive Virtual Cancer Model (VCM) of lymphoma and leukemia. Our host-level measurements will focus on two critical aspects of tumor-host interactions: host immune response and cytokines that mediate intercellular communication. Systems-level measurements of the dynamics of the host immune response will be obtained using a novel self-assembling high density protein microarray platform, and serum cytokine levels will be monitored using a highly sensitive magneto nano protein chip technology. Through careful coordination of mouse models, time points and treatment conditions with tumor-level measurements (in RPS), we will acquire a novel dataset that tracks the progression of the tumor and the host in two important in vivo tumor models of lymphoma and leukemia. This coordinated tumor/host (TH) dataset will be the foundation for developing a computational TH model of the functional interactions between tumor and host. The TH model will uncover a low dimensional subset of tumor/host variables needed to predict the future TH state based on the its past condition. In addition, by integrating the TH model with the molecular-cellular-tumor model (from RP1-3), we will develop a comprehensive, predictive Virtual Cancer Model (VCM) for leukemia and lymphoma. The VCM will be used to predict the temporal evolution of the disease at the cell, tumor and host levels in response to specific molecular interventions. VCM predictions will then feedback to all RPs in order to experimentally validate model predictions. We envision that the validated Virtual Cancer Model would enable the evaluation of molecularly targeted treatment regimens to arrive rationally at the most promising therapeutic strategy for attacking lymphoma and leukemia.

许多因素导致癌症治疗衰竭，包括对药物的缺乏反应，对宿主的毒性，避难所的肿瘤生长以及对药物的抗药性的出现。通常，这些因素是单独研究的，但是正是他们的一致行动最终使患者不堪重负。因此，采取一种综合和系统方法来研究肿瘤和宿主如何随着时间的反应以及对各种癌症干预措施的反应，这一点至关重要。项目4致力于对宿主对癌症及其治疗的宿主反应的多尺度测量，并将这些信息与其他项目测量的肿瘤反应整合到淋巴瘤和白血病的全面虚拟癌症模型（VCM）中。我们的宿主水平测量值将集中于肿瘤宿主相互作用的两个关键方面：宿主免疫反应和介​​导细胞间通信的细胞因子。使用新型的自组装高密度蛋白微阵列平台将获得宿主免疫反应动力学的系统级测量，并将使用高敏感的磁铁纳米蛋白蛋白芯片技术来监测血清细胞因子水平。通过仔细协调小鼠模型，时间点和治疗条件（在RPS中），我们将获得一个新型数据集，该数据集跟踪肿瘤的进展和宿主在两个重要的淋巴瘤和白血病的体内肿瘤模型中。该协调的肿瘤/宿主（TH）数据集将是开发肿瘤与宿主之间功能相互作用的计算模型的基础。 TH模型将根据其过去的状况来揭示肿瘤/宿主变量的低维子集，以预测未来状态。此外，通过将TH模型与分子 - 细胞肿瘤模型（来自RP1-3）相结合，我们将开发一种用于白血病和淋巴瘤的全面，预测的虚拟癌症模型（VCM）。 VCM将用于预测细胞，肿瘤和宿主水平的疾病的时间演变，以响应特定的分子干预。然后，VCM预测将反馈给所有RP，以实验验证模型预测。我们设想，经过验证的虚拟癌症模型将使分子靶向治疗方案的评估能够合理地达到攻击淋巴瘤和白血病的最有希望的治疗策略。