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）：根据流式细胞术数据对化疗效果的统计推断-我们的初步研究产生了少突胶质细胞祖细胞体外克隆生长的随机模型。该模型已应用于多组实验数据，并在独立的延时实验中得到验证。基于该模型构建的新估计技术可以根据具有生物学意义的参数来分析细胞增殖和分化的基本过程。然而，从业者从所提出的方法中受益的能力是有限的，因为克隆分析非常费力并且难以以自动化方式进行。相比之下，DNA、蛋白质或细胞表面标记物的体外实验很容易通过流式细胞术实现自动化。一些标记技术 (BrdU) 提供了体内条件下细胞周期结构所需的信息。这些实际考虑因素激发了使用流式细胞术数据对细胞动力学进行深入研究。该项目的具体目标是：（1）开发流式细胞术实验中细胞动力学建模的随机框架； (2) 基于所提出的随机模型，设计用于流式细胞术数据定量分析的新统计推断方法； (3) 在专门设计的生物实验中验证所提出的方法； (4) 评估这些方法在研究化疗药物对正常和肿瘤组织的影响方面的效用。具体应用将集中于少突胶质细胞前体、中枢神经系统髓磷脂形成细胞和白血病祖细胞对用于白血病治疗的化疗药物的反应。公共卫生相关性：该项目关注化疗对正常组织和肿瘤组织的影响，这对一般肿瘤学，特别是白血病治疗具有明显的临床和公共卫生影响。