Statistical Inference on Chemotherapy Effects from Flow Cytometry Data

从流式细胞术数据对化疗效果的统计推断

• 批准号: 8320725
• 负责人: Ollivier Hyrien
• 金额: $ 22.74万
• 依托单位: UNIVERSITY OF ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-23 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8320725
• 关键词: Antibodies; Biological; Bromodeoxyuridine; Cell Cycle; Cell Cycle Kinetics; Cell Differentiation process; Cell Proliferation; Cell surface; Cells; Chemistry; Clinical; Computational algorithm; Cytometry; DNA; Data; Data Analyses; Development; Drug usage; Estimation Techniques; Flow Cytometry; Growth; Health; In Vitro; Label; Methodology; Methods; Modeling; Myelin; Neuraxis; Oligodendroglia; Pharmaceutical Preparations; Population; Process; Proteins; Public Health; Resort; Statistical Methods; Stem cells; Structure; Techniques; Time; Tissues; base; cell type; chemotherapy; design; in vivo; leukemia; neoplastic; oligodendrocyte precursor; oncology; research study; response; theories; tool

DESCRIPTION (provided by applicant): Statistical Inference on Chemotherapy Effects from Flow Cytometry Data- Our preliminary studies have resulted in a stochastic model of clonal growth of oligodendrocyte progenitor cells in vitro. The model has been applied to several sets of experimental data and validated in independent time-lapse experiments. New estimation techniques built on this model allow analysis of the underlying processes of cell proliferation and differentiation in terms of biologically meaningful parameters. However, the ability of practitioners to benefit from the proposed methodology is limited because clonal analyses are very laborious and difficult to conduct in an automated fashion. By contrast, in vitro experiments with DNA, protein, or cell surface markers are readily amenable to automatization by resorting to flow cytometry. Some labeling techniques (BrdU) provide the needed information on the structure of cell cycle under in vivo conditions. These practical considerations motivate an in-depth study of cell kinetics using flow cytometry data. The specific aims of this project are: (1) To develop a stochastic framework for modeling cell kinetics during flow cytometry experiments; (2) To design new methods of statistical inference for the quantitative analysis of flow cytometry data by building on the proposed stochastic models; (3) To validate the proposed methods in specially designed biological experiments; (4) To assess the utility of these methods to study effects of chemotherapeutic drugs on normal and neoplastic tissues. Specific applications will be focused on responses of oligodendrocyte precursors the myelin-forming cells of the central nervous system - and leukemic progenitor cells to chemotherapeutic drugs used for leukemia treatment. PUBLIC HEALTH RELEVANCE: This project is concerned with the effects of chemotherapy on normal and neoplastic tissues, which has obvious clinical and public health implications for oncology in general and for leukemia treatment in particular.

描述（由申请人提供）：流式细胞术数据对化学疗法作用的统计推断 - 我们的初步研究导致了一种体外少突胶质细胞祖细胞克隆生长的随机模型。该模型已应用于几组实验数据，并在独立的延时实验中进行了验证。基于该模型的新估计技术允许分析细胞增殖和分化的基本过程，从生物学上有意义的参数方面进行分析。但是，从业人员从提出的方法学中受益的能力受到限制，因为克隆分析非常费力且难以以自动化的方式进行。相比之下，使用DNA，蛋白质或细胞表面标记的体外实验可以通过诉诸流式细胞仪来轻松自动化。某些标记技术（BRDU）提供了有关在体内条件下细胞周期结构的所需信息。这些实际考虑促使使用流式细胞仪数据对细胞动力学进行了深入研究。该项目的具体目的是：（1）开发一个随机框架，用于在流式细胞仪实验过程中对细胞动力学进行建模； （2）通过在提出的随机模型上构建流式细胞仪数据的定量分析来设计新的统计推断方法； （3）在专门设计的生物学实验中验证所提出的方法； （4）评估这些方法的实用性，以研究化学治疗药物对正常和肿瘤组织的影响。特定的应用将集中在少突胶质细胞前体的反应上，中枢神经系统的髓磷脂形成细胞以及白血病祖细胞对用于白血病治疗的化学治疗药物的反应。公共卫生相关性：该项目与化学疗法对正常和肿瘤组织的影响有关，这对肿瘤学对肿瘤学具有明显的临床和公共卫生影响，尤其是对白血病的治疗。