Systems Biology of Diversity in Cancer

癌症多样性的系统生物学

• 批准号: 8068280
• 负责人: CHRIS SANDER
• 金额: $ 271.64万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-05-01 至 2015-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8068280
• 关键词: Systems; Biology; Diversity; Cancer

DESCRIPTION (provided by applicant): A critical issue in modern cancer research is how diversity, both genetic and non-genetic, influences tumor progression and response to therapy. The Center for Cancer Systems Biology (CCSB) at MSKCC assembles a consortium of investigators who integrate computational and experimental strategies to investigate diversity in cancer at the level of individual cells, tumor microenvironment, and patients. The research program for this CCSB is organized into four inter-related subprojects. (I)We study the variability of cellular responses to growth factors and drugs during tumorigenesis, using competition for the growth factor IL-6 in melanoma and breast cancer cells as a model system. We use computational modeling of the dynamics of the IL-6 pathway in order to optimize new chemotherapeutic protocols that rely on cellular diversity to maximize tumor cytotoxicity. (II) We use expression profiling of protease networks in both tumor and stromal cells and genome-wide profiling of subpopulations of tumor-associated macrophages to learn predictive statistical models of tumor-stromal cell interactions. We also use agent-based computational models to simulate cancer-cell macrophage interactions. Computational predictions will be validated with in vitro and in vivo experiments. (Ill)We focus on predictive network models of differences in signaling information flow in distinct tumor subtypes. Using the results of systematic drug perturbation experiments, we will design Hopfield network models based on non-linear differential equations to decipher the differences in signaling networks between primary glioblastoma subtypes and to investigate the changes in network dynamics during the evolution of drug resistance. (IV) We study the endogenous diversity of B cell signaling pathways in Chronic Lymphocytic Leukemia (CLL) patients. We will generate biochemical models of signaling pathways to identify key signaling regulators whose variation in expression predicts functional heterogeneity, validate the predictions with single-cell profiling, and define a new set of functional markers to better characterize disease progression. By elucidating the consequences of diversity in cancer, this research will ultimately guide the development of new cancer therapies.

描述（由申请人提供）：现代癌症研究中的一个关键问题是遗传和非遗传学的多样性如何影响肿瘤的进展和对治疗的反应。 MSKCC的癌症系统生物学中心（CCSB）组装了一个研究人员，他们整合了计算和实验策略，以研究单个细胞，肿瘤微环境和患者的癌症多样性。该CCSB的研究计划被组织成四个相关的副标题。 （i）我们研究了黑色素瘤和乳腺癌细胞中生长因子IL-6作为模型系统的生长因子IL-6的竞争，研究细胞对生长因子和药物的反应变异性。我们使用IL-6途径动力学的计算模型，以优化依赖细胞多样性以最大化肿瘤细胞毒性的新化学治疗方案。 （ii）我们在肿瘤和基质细胞中使用蛋白酶网络的表达分析，以及肿瘤相关巨噬细胞亚群的全基因组分析，以学习肿瘤 - 基质细胞相互作用的预测统计模型。我们还使用基于代理的计算模型来模拟癌细胞巨噬细胞相互作用。计算预测将通过体外和体内实验验证。 （疾病）我们专注于不同肿瘤亚型信号信息流中差异的预测网络模型。使用系统的药物扰动实验的结果，我们将设计基于非线性微分方程的Hopfield网络模型，以解读原代胶质母细胞瘤亚型之间信号网络的差异，并研究药物抗性演化期间网络动力学的变化。 （iv）我们研究慢性淋巴细胞性白血病（CLL）患者B细胞信号通路的内源性多样性。我们将生成信号通路的生化模型，以识别其表达变化预测功能异质性，通过单细胞分析验证预测的关键信号调节器，并定义一组新的功能标记，以更好地表征疾病进展。通过阐明癌症多样性的后果，这项研究最终将指导新的癌症疗法的发展。