Development of an Angiogenic T Cell Assay for Personalized Cytomics in Cardiovasc

描述(申请人提供)：这项研究的目标是开发一种新的基于流式细胞术的检测方法，用于临床检测促血管生成T细胞。如今，这样的化验方法还不存在。促血管生成T细胞，包括血管生成T细胞和Th17亚群，参与血管系统的修复机制、肿瘤血管生成和其他对血管系统整体健康至关重要的过程。T细胞测试可以作为独立的诊断工具部署，但最终将提供细胞血管健康概况(CytoVasHP)的最终核心模块，细胞血管健康概况是一种基于细胞的血液测试，用于评估血管健康。心血管学界已经意识到，具有相似心血管疾病风险的患者最终往往会发展(或不发展)一系列疾病，具有不同的发病率、死亡率和对治疗的反应。为了确定对个别患者最有效的护理，并确定那些最有可能从预防或治疗的特定干预中受益的人，迫切需要新的方法和工具，能够考虑到个别患者的差异，并提供对血管健康状况的全面衡量。将这一新的分析方法添加到CytoVasHP中，将大大增加该图谱的信息潜力。全球数以百万计的人可以从CytoVasHP的开发中受益。心血管疾病(CVD)在美国成年人中的患病率为37%，预计在未来20年内将增加10%。肥胖、高血压和糖尿病等心血管疾病风险因素在世界范围内普遍存在，发达国家的人口老龄化以及发展中国家饮食和文化习惯的变化加剧了这种情况。CytoVasHP是一种多组分的临床检测方法，它将一系列遗传和环境风险因素(包括血管微粒(MPS)和内皮祖细胞(EPC))的细胞生物标记物与一种独特而强大的模式识别计算方法相结合。促血管生成唐和Th17的测量将是CytoVasHP提供的血管健康综合测量的核心组成部分。这项测试将使用流式细胞术和生物计算来产生CytoVasHP，它可以部署在药物开发环境中，向制药公司通报新候选疗法的潜在血管益处或毒性。最终，CytoVasHP将在临床上用于正在考虑进行心血管预防治疗的无症状患者，用于评估正在接受心血管药物治疗的患者的治疗效果，或评估作为其他治疗的副作用的心血管毒性。该项目将开发一种单管流式细胞仪来量化促血管生成T细胞，包括CD3、CD4、CD31、KDR、IL23R、CD161和CD184(CXCR4)。样品制备和数据采集的实验室方案将与临床解释性分析的高维计算方法的改进和适应相结合。

DESCRIPTION (provided by applicant): The goal of this research is to develop a new flow cytometry-based test for the clinical measurement of proangiogenic T cells. Such an assay does not exist today. Proangiogenic T cells, including angiogenic T cell (Tang) and Th17 subsets, participate in reparative mechanisms in the vasculature, in oncogenic angiogenesis and in other processes central to the overall health of the vascular system. The T cell test could be deployed as a stand-alone diagnostic tool but will ultimately provide the final core module of the Cytometric Vascular Health Profile (CytoVasHP), a cell-based blood test for the assessment of vascular health. The cardiovascular community has realized that patients who present with similar risk of cardiovascular disease often end up developing (or not) a range of pathologies with different morbidity, mortality and responses to therapy. To determine the most effective care for individual patients and to identify those most likely to benefit from specific interventios for prevention or treatment, there is an urgent need for new methods and tools that can account for individual patient differences and provide a comprehensive measurement of vascular health status. The addition of this new assay to the CytoVasHP will substantially increase the information potential of the profile. Millions of people worldwide could benefit from the development of the CytoVasHP. Cardiovascular disease (CVD) prevalence in the USA is 37% among adults and is projected to increase by 10% over the next 20 years. CVD risk factors such as obesity, hypertension and diabetes have a high prevalence worldwide, exacerbated by aging populations in the developed world and by changing diets and cultural habits in the developing countries. CytoVasHP is a multicomponent clinical assay that will integrate a number of cellular biomarkers of genetic and environmental risk factors (including vascular microparticles (MPs) and endothelial progenitor cells (EPCs)) with a unique and powerful pattern-discerning computational method. Measurement of proangiogenic Tang and Th17 will be a core component of the comprehensive measure of vascular health offered by CytoVasHP. The test will use flow cytometry and biocomputation to yield the CytoVasHP, which could be deployed in the drug development environment to inform pharmaceutical companies of potential vascular benefits or toxicities of new candidate therapeutics. Ultimately, the CytoVasHP will be ordered in the clinic for asymptomatic individuals being considered for cardiovascular preventive treatment, for assessing therapeutic effectiveness in patients being treated with cardiovascular drugs, or to assess cardiovascular toxicities as a side effect of other therapies. This project will develop a single tube flow cytometric panel to quantify proangiogenic T cells, Tang and Th17, composed of CD3, CD4, CD31, KDR, Il23R, CD 161, and CD184 (CXCR4) measurements. Laboratory protocols for sample preparation and data acquisition will be combined with the refinement and adaptation of a high dimensional computational approach for clinical interpretive analysis.