Spatiotemporal Tumor Analytics for Guiding Sequential Targeted-Inhibitor: Immunotherapy Combinations (ST-Analytics)

用于指导序贯靶向抑制剂的时空肿瘤分析：免疫治疗组合（ST-Analytics）

• 批准号: 10526101
• 负责人: James R. Heath
• 金额: $ 270.26万
• 依托单位: INSTITUTE FOR SYSTEMS BIOLOGY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-22 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10526101
• 关键词: Address; Adoptive Cell Transfers; Algorithms; Automobile Driving; Biological; Biopsy; Cell physiology; Cells; Clinical; Clinical Data; Clinical Trials; Clinical Trials Design; Combination immunotherapy; Combined Modality Therapy; Communities; Coupled; Data; Databases; Development; Disadvantaged; Disease model; Distal; Dose; Education and Outreach; Educational Models; Environment; Environment Design; Epigenetic Process; Evaluation; Genetic Transcription; Immune; Immune system; Immunologic Factors; Immunooncology; Immunotherapy; Individual; Internships; K-12 Education; Kinetics; Knowledge; Lead; Leadership; Malignant Neoplasms; Measurement; Metastatic malignant neoplasm to brain; Mitogen-Activated Protein Kinase Inhibitor; Modeling; Nature; Neoplasm Metastasis; Outcome; Patients; Pharmaceutical Preparations; Pilot Projects; Play; Primary Neoplasm; Proteomics; Research; Research Personnel; Research Project Grants; Resistance; Resources; Role; Science; Science, Technology, Engineering and Mathematics Education; Scientist; Self-Examination; Series; Structure; System; Systems Biology; Therapeutic; Time; Tissues; Visual; Work; base; biobank; cancer immunotherapy; combinatorial; computing resources; demographics; design; immune checkpoint blockade; in silico; in vivo; inhibitor; inhibitor therapy; medical schools; melanoma; model design; mouse model; multiple omics; outreach; outreach program; prevent; programs; recruit; spatiotemporal; tool; transcriptomics; tumor; tumor-immune system interactions

Overall Project Summary The proposed U54 program Spatiotemporal Tumor Analytics for Guiding Sequential Targeted-Inhibitor -- Immunotherapy Combinations (ST-Analytics) is designed to develop the recent conceptual advance that targeted inhibitor + cancer immunotherapy (IT) combination treatments may yield significantly greater patient benefit if those treatments are administered in sequence rather than simultaneously. Analysis of retrospective clinical data coupled with in vivo therapeutic modeling using syngeneic models of murine melanoma strongly support this concept. In fact, the picture that has emerged in melanoma is that immune factors can play a strong role in driving resistance to MAPK inhibitor (MAPKi) therapy, and that lead-in immune checkpoint blockade (ICB) can ‘prime’ both the primary tumor and distal metastases (including brain metastases) for eradication when the IT is subsequently combined with MAPKi. This observation opens the doors for immune based strategies, such as ICB or adoptive cell therapy (ACT), as sequential combinatorial agents to prevent MAPKi resistance. However, this concept introduces a number of new variables, including dosing, sequence, and timing. This can make the design and execution of clinical trials that can yield statistically significant outcomes impractical. This is the scientific and translational problem we address in the proposed ST-Analytics U54. The ST-Analytics U54 center is populated by leading scientists at the ISB, the UCLA Geffen School of Medicine, and Yale, and is comprised of two research projects and two research cores, with each project integrating both state-of-the-art experimentation and computational work. This structure is further designed to bring together the scientific, experimental, and computational and administrative resources to develop a data base that captures the kinetics of lead-in monotherapy tumor priming, and apply that data base to the development of predictive in silico models that can inform the design of such targeted inhibitor – immunotherapy sequence combinations for clinical trials. This requires close integration and cycles of iteration between of state-of-the-art experimentation, leading edge computation, and realistic disease models, continuously calibrated through the analysis of highly relevant, biopsied patient tumors. The resulting science also provides exciting opportunities for high impact STEM outreach. We propose to act on those opportunities by leveraging a long-standing systems education outreach program at ISB that already has impacted K-12 STEM education in all 50 states, and places an emphasis on those communities that have been historically under-represented in STEM.

总体项目摘要 拟议的U54程序时空肿瘤分析用于指导顺序靶向抑制剂 - 免疫疗法组合（St-Analytics）旨在发展最近的概念进步 靶向抑制剂 +癌症免疫疗法（IT）组合治疗可能会产生更大的患者 如果这些治疗是按顺序而而不是简单地给药的好处。回顾性分析 临床数据结合使用鼠黑色素瘤的合成模型的体内治疗模型 支持这个概念。实际上，黑色素瘤中出现的图片是免疫因素可以发挥强大 在驱动对MAPK抑制剂（MAPKI）疗法的抗性中的作用，该铅免疫切解点阻滞（ICB） 当原发性肿瘤和远端转移（包括脑转移）可以消除时， 随后将其与MAPKI结合使用。这种观察为免疫策略打开了大门 作为ICB或自适应细胞疗法（ACT），作为顺序组合剂，以防止MAPKI抗性。 但是，这个概念引入了许多新变量，包括剂量，序列和时机。这可以 进行临床试验的设计和执行，这些试验可能不切实际地产生统计上显着的结果。这 是我们在拟议的ST-Analytics U54中解决的科学和翻译问题。 St-Analytics U54中心由UCLA Geffen医学院ISB的主要科学家组成， 和耶鲁大学，由两个研究项目和两个研究核心组成，每个项目都整合 最新的实验和计算工作。这种结构的旨在将 科学，实验，计算和行政资源，以开发捕获的数据库 铅单一疗法肿瘤启动的动力学，并将数据基础应用于预测的发展 可以告知此类靶向抑制剂的设计的硅模型 - 免疫疗法序列组合 临床试验。这需要在最新实验之间进行紧密整合和迭代循环， 领先的计算和现实疾病模型通过高度分析不断校准 相关的，活检的患者肿瘤。最终的科学还为高影响力提供了令人兴奋的机会 STEM外展。我们建议通过利用长期存在的系统教育来对这些机会采取行动 ISB的外展计划已经影响了所有50个州的K-12 STEM教育，并将 强调那些在STEM中历史上代表性不足的社区。