Intercellular Interactions Modulate Carcinogenesis Course: A Dynamic System Study

细胞间相互作用调节癌发生过程：动态系统研究

基本信息

批准号：
8639489
负责人：
Lynn Hlatky
金额：
$ 135.03万
依托单位：
GENESYS RESEARCH INSTITUTE, INC.
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-05-01 至 2014-09-30
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): To study cancer, very powerful modern experimental methods -- including high-throughput approaches -- and modern statistics/computer-science methods are now used. Mechanistic quantitative models of cancer time-development, from very early stages to clinical disease, have been somewhat less well explored. A highly interdisciplinary, unusually closely interacting team of cancer biologists, molecular biologists, mathematicians, physicists, and computer scientists has been assembled to work toward dynamic, mechanistic carcinogenesis models so parsimoniously parameterized they have predictive capability. The overriding goal is to make the models more realistic and credible by taking into account the influence of intercellular interactions during carcinogenesis. The time-course of effects involving a diverse, interacting cell population and/or of tumor progression, a comparatively late stage in the lengthy cancer latency period, will be emphasized. The phenomena of microscopic tumor dormancy, recently found to be almost ubiquitous in humans, and of emergence from dormancy due to "switching on" of blood supply recruitment, will be one main focus. The team will work under an iterative paradigm: experiments, mathematical/computational model, experiments, etc. Data will be gathered from various sources: in vitro experiments, including modern high throughput results, and in depth studies of particular proteins; experiments using genetically engineered mice; highly developed imaging approaches; and results in the literature on human cancer incidence or mortality. Several of the individual projects will involve ionizing radiation, a carcinogen whose action has been unusually well characterized at very small time and length scales, as well as over a whole human lifetime and for whole organisms, so that it is highly informative about cancer development in general. Mathematical methods will include the following: classic mathematical biology approaches with systems of ordinary or partial differential equations; modern discrete and hybrid discrete-continuous models based on treating many cells, each represented as an entity which can interact with other cells and with its microenvironment according to comparatively simple rules, with complicated whole-system behavior arising from those rules; probabilistic "stochastic-process" models, needed since most new stages of cancer evolution putatively originate with a single cell at risk for eradication or accidental extinction; and multi time-scale computational modeling, in which effects governed by comparatively very short time scales influence much longer time-scale cancer evolution and vice-versa.

描述（由申请人提供）：为了研究癌症，现在使用了非常强大的现代实验方法 - 包括高通量方法 - 现代统计/计算机科学方法现已使用。从非常早期到临床疾病的癌症时间发展的机械定量模型的探索程度较低。一支高度跨学科的，异常相互作用的癌症生物学家，分子生物学家，数学家，物理学家和计算机科学家的团队已被组装为朝着动态的，机械的致癌模型努力，因此，与众不同的参数化，因此具有预测能力。重要的目标是通过考虑到癌变期间细胞间相互作用的影响，使模型更现实和可信。将强调涉及多样化，相互作用的细胞种群和/或肿瘤进展的效应时间，这是冗长的癌症潜伏期的晚期。微小肿瘤休眠的现象，最近发现在人类中几乎无处不在，并且由于“启动血液供应募集”而引起的休眠状况将是一个主要重点。该团队将在迭代范式下工作：实验，数学/计算模型，实验等。数据将从各种来源收集：体外实验，包括现代的高吞吐量结果，以及对特定蛋白质的深入研究；使用基因工程小鼠的实验；高度发达的成像方法；并导致有关人类癌症发病率或死亡率的文献。几个个别项目将涉及电离辐射，这是一种致癌物，其作用在很小的时间和长度尺度以及整个人类的生命周期和整个生物体上都具有异常表征，因此总体上对癌症的发展非常有用。数学方法将包括以下内容：具有普通或部分微分方程系统的经典数学生物学方法；现代离散和混合离散的连续模型基于处理许多细胞，每个模型都表示为一个实体，可以根据相对简单的规则与其他单元相互作用，并与其微环境相互作用，并带有复杂的全系统行为，由这些规则产生；概率的“随机过程”模型，由于癌症进化的大多数新阶段都具有根除或意外灭绝风险的单个细胞。以及多时间尺度的计算建模，在相对较短的时间尺度上控制的效果会影响更长的时间尺度癌症演化，反之亦然。