Centers for Cancer Systems Therapeutics (CaST)

癌症系统治疗中心 (CaST)

• 批准号: 9976471
• 负责人: ANDREA CALIFANO
• 金额: $ 204.16万
• 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 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9976471
• 关键词: AKT1 gene; Address; Adopted; Adult; Architecture; Cancer Center; Cell Line; Cells; Clinic; Clinical Research; Combined Modality Therapy; Communities; Complex; Computer Models; Data; Dependence; Disease Resistance; Drug resistance; Environment; Epigenetic Process; Evaluation; Event; Evolution; FRAP1 gene; Fostering; Genetic; Genomics; Heart; Heterogeneity; Homeostasis; In Vitro; Individual; Investments; 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; Statistical Models; Structure; System; Systems Biology; Therapeutic; Time; Universities; Xenograft procedure; base; cancer cell; drug sensitivity; in vivo; inhibitor/antagonist; innovation; interdisciplinary approach; kinetic model; 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.

项目摘要 构成系统生物学基础的定量模型驱动方法正在出现 作为一个越来越重要的方法库，真正“精确”实施精准癌症 药考虑到目前的方法越来越多的局限性，这一点尤其重要。 癌基因成瘾范例即使药理学抑制携带激活的癌基因， 改变已经成为靶向治疗的一个有价值的理由，>75%的所有成人恶性肿瘤缺乏任何改变。 可采取行动的改变或存在不可治疗的改变和典型癌基因的抑制剂已经显示， 在临床上反应平平。最关键的是，在最初的、有时是显著的反应之后， 治疗几乎总是导致耐药性疾病的复发。系统治疗数百个细胞 具有数百种化合物的细胞系表明，除了少数明显的例外，突变远非 代表靶向试剂敏感性的最佳预测因子。这并不奇怪，因为药物敏感性显然 代表复杂的多基因表型，需要同样复杂和肿瘤特异性的模型。这个中心 该提案涵盖了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 重编程为与进展或耐药性相关的不同等基因状态。具体来说，三 互补的方向将追求：第一，阐明调控模块架构（肿瘤 检查点）和这些模块（主调节器）内的特定蛋白质，这些蛋白质包括失调的 主导肿瘤稳态的机制（即，细胞维持其肿瘤状态的能力， 突变景观和内源/外源信号异质性）。这将通过 开发基于模型的方法来分析代表肿瘤不同区室的组学数据， 从肿瘤块到间质/肿瘤区室，再到单细胞，遵循生理学、遗传学和 药理学干扰。第二，研究肿瘤状态改变的机制， 通过采用和扩展生理学研究方法， 分化和重编程。该分析将整合亚克隆基因组表征，使用 创新的计算模型，具有来自原发性肿瘤和患者来源的异种移植物的单细胞数据， 阐明主导肿瘤可塑性的机制。最后，使用机械的监管框架 从这些研究中出现，以阐明可操作的肿瘤依赖性，导致不可逆的崩溃， 体外和体内肿瘤稳态。这将通过组装和实验验证来实现 肿瘤检查点调节的概率和动力学模型，从以下时间序列数据中组装而成： 系统性小分子扰动。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。