Centers for Cancer Systems Therapeutics (CaST)

癌症系统治疗中心 (CaST)

• 批准号: 9752983
• 负责人: ANDREA CALIFANO
• 金额: $ 206.55万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-08 至 2021-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9752983
• 关键词: AKT1 gene; Address; Adopted; Adult; Architecture; Cancer Center; Cell Line; Cells; Clinic; Clinical Research; Combined Modality Therapy; Communities; Complex; Computer Simulation; Data; Dependence; Disease Resistance; Drug resistance; Environment; Epigenetic Process; Evaluation; Event; Evolution; FRAP1 gene; Fostering; Genetic; Genomics; Heart; Heterogeneity; Homeostasis; In Vitro; Individual; Investments; Kinetics; Logic; MYC Family Protein; Maintenance; Malignant Neoplasms; Methodology; Methods; Modeling; Molecular Analysis; Mutation; Network-based; Oncogenes; Patients; Pharmacology; Phenotype; Physiological; Primary Neoplasm; Proteins; Recurrence; Regulation; Regulator Genes; Relapse; Research; Research Personnel; Series; Signal Transduction; Structural Genes; System; Systems Biology; Therapeutic; Time; Universities; Xenograft procedure; base; cancer cell; drug sensitivity; in vivo; inhibitor/antagonist; innovation; interdisciplinary approach; neoplastic cell; novel; oncogene addiction; precision oncology; response; small molecule; software development; symposium; targeted agent; targeted treatment; tumor; tumor microenvironment; tumorigenesis

PROJECT SUMMARY The quantitative, model driven approaches that constitute the underpinning of systems biology are emerging as an increasingly critical methodological repertoire for a truly “precise” implementation of precision cancer medicine. This is especially relevant in view of the increasing limitations of current approaches based on the oncogene addiction paradigm. Even though pharmacological inhibition of oncogenes harboring activating alterations has emerged as a valuable rationale for targeted therapy, >75% of all adult malignancies lack any actionable alteration or present with undruggable ones and inhibitors of canonical oncogenes have shown lackluster response in the clinic. Most critically, following initial and at times remarkable response, targeted therapy almost invariably leads to relapse to drug-resistant disease. Systematic treatment of hundreds of cell lines with hundreds of compounds has shown that, with few notable exceptions, mutations are far from representing optimal predictors of targeted agent sensitivity. This is not surprising, as drug sensitivity clearly represents a complex polygenic phenotype, requiring equally complex and tumor-specific models. This center proposal encompasses studies across multiple levels of granularity, representing the full complexity of the tumor phenotype: from tumor/microenvironment interactions to single cell plasticity, supporting tumors reprograming to distinct isogenic states associated with progression or drug resistance. Specifically, three complementary directions will be pursued: First, elucidation of the regulatory module architecture (tumor checkpoint) and specific proteins within these modules (master regulators) that comprise the dysregulated mechanisms presiding over tumor homeostasis (I.e., a cell's ability to maintain its tumor state independent of mutational landscape and endogenous/exogenous signal heterogeneity). This will be accomplished by developing model-based approaches to analyze omics data representing distinct compartments of the tumor, ranging from tumor bulk, to stroma/tumor compartments, to single cells, following physiologic, genetic, and pharmacologic perturbations. Second, study the mechanisms by which tumor state can be altered to induce progression or drug resistance by adopting and extending approaches for the study of physiologic differentiation and reprograming. This analysis will integrate subclonal genomic characterization, using innovative computational models, with single cell data from primary tumors and patient derived xenografts to elucidate the mechanisms presiding over tumor plasticity. Finally, using the mechanistic regulatory frameworks emerging from these studies to elucidate actionable tumor dependencies leading to irreversible collapse of tumor homeostasis in vitro and in vivo. This will be accomplished by assembling and experimentally validating both probabilistic and kinetic models of tumor checkpoint regulation, assembled from time-series data following systematic small molecule perturbations. Center-developed software and methods will be disseminated to the Research Community, using proven strategies.

项目总结 构成系统生物学基础的定量的、模型驱动的方法正在出现 作为一种越来越重要的方法论宝库，可以真正实现精确癌症 医药。这一点尤其重要，因为基于 致癌基因成瘾模式。即使对具有激活作用的癌基因进行药物抑制 改变已经成为靶向治疗的一个有价值的理论基础，75%的成人恶性肿瘤缺乏任何改变。 典型癌基因的可操作改变或出现不可用药的改变和抑制物已显示 临床反应平淡。最关键的是，在最初的、有时是显著的反应之后，有针对性 治疗几乎总是会导致耐药疾病的复发。数百个细胞的系统治疗 数百种化合物的谱线表明，除了几个值得注意的例外，突变远远不是 代表靶向试剂敏感度的最佳预测值。这并不令人惊讶，因为药物敏感性显然 代表一种复杂的多基因表型，需要同样复杂的和肿瘤特异性的模型。这个中心 提案包含多个粒度级别的研究，代表了 肿瘤表型：从肿瘤/微环境相互作用到单细胞可塑性，支持肿瘤 重新编程到与进展或耐药相关的不同的等基因状态。具体地说，三个 将寻求相辅相成的方向：第一，阐明调节模块架构(肿瘤 Checkpoint)和这些模块(主调节器)中的特定蛋白质组成了失调的 支配肿瘤稳态的机制(即，细胞维持其肿瘤状态的能力独立于 突变景观和内源/外源信号异质性)。这将通过以下方式实现 开发基于模型的方法来分析代表肿瘤不同部分的组学数据， 从肿瘤体积到间质/肿瘤隔间，再到单细胞，遵循生理学、遗传学和 药理上的干扰。第二，研究改变肿瘤状态以诱发肿瘤的机制 采用和推广生理学研究方法研究耐药进展 分化和重新编程。这项分析将整合亚克隆基因组特征，使用 创新的计算模型，使用来自原发肿瘤和患者来源的异种移植的单细胞数据 阐明控制肿瘤可塑性的机制。最后，利用机械化的监管框架 从这些研究中出现，以阐明可操作的肿瘤依赖导致不可逆转的崩溃 体内和体外肿瘤动态平衡。这将通过组装和实验验证来完成 肿瘤检查点调节的概率和动力学模型，由下列时间序列数据组合而成 系统的小分子扰动。中心开发的软件和方法将分发给 研究社区，使用经过验证的策略。