Statistical Inference on Chemotherapy Effects from Flow Cytometry Data
Statistical Inference on Chemotherapy Effects from Flow Cytometry Data
批准号:
8132502
负责人:
Ollivier Hyrien
金额:
$22.74万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-09-23 至 2013-08-31
关键词:
AntibodiesBiologicalBromodeoxyuridineCell CycleCell Cycle KineticsCell Differentiation processCell ProliferationCell surfaceCellsChemistryClinicalComputational algorithmCytometryDNADataData AnalysesDevelopmentDrug usageEstimation TechniquesFlow CytometryGrowthHealthIn VitroLabelMethodologyMethodsModelingMyelinNeuraxisOligodendrogliaPharmaceutical PreparationsPopulationProcessProteinsPublic HealthResortStatistical MethodsStem cellsStructureTechniquesTimeTissuesbasecell typechemotherapydesignin vivoleukemianeoplasticoligodendrocyte precursoroncologyresearch studyresponsetheoriestool
中文摘要
描述(由申请人提供):流式细胞术数据对化疗效果的统计推断-我们的初步研究已经产生了体外少突胶质细胞祖细胞克隆生长的随机模型。该模型已应用于多组实验数据,并在独立的延时实验中得到了验证。建立在这个模型上的新估计技术允许分析细胞增殖和分化的潜在过程,根据生物学上有意义的参数。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,并且很难以自动化的方式进行。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。这些实际的考虑激发了使用流式细胞术数据对细胞动力学的深入研究。该项目的具体目标是:(1)在流式细胞术实验中建立细胞动力学建模的随机框架;(2)基于所提出的随机模型,设计新的流式细胞术数据定量分析的统计推断方法;(三)在专门设计的生物学实验中验证所提出的方法;(4)评估这些方法在研究化疗药物对正常组织和肿瘤组织的影响方面的实用性。具体应用将集中在少突胶质细胞前体(中枢神经系统的髓磷脂形成细胞)和白血病祖细胞对用于白血病治疗的化疗药物的反应上。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,这对肿瘤学,特别是白血病治疗具有明显的临床和公共卫生意义。
英文摘要
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.
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