Protein arrays to profile cytokine expression in ovaria*

用于分析卵巢细胞因子表达的蛋白质阵列*

• 批准号: 6783990
• 负责人: RUO-PAN HUANG
• 金额: $ 7.65万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-06-01 至 2006-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6783990
• 关键词: angiogenesis factor; antibody; bioinformatics; biomarker; chemokine; clinical research; cytokine; early diagnosis; endopeptidases; growth factor; human tissue; microarray technology; neoplasm /cancer diagnosis; neoplasm /cancer genetics; ovary neoplasms; pathologic process; prognosis; proteomics; statistics /biometry

DESCRIPTION (provided by applicant): Ovarian cancer is one of the leading causes of cancer death among females in the United States and Europe. Most of mortality is resulted from the late diagnosis of this tumor of cancer patients. Early diagnosis is the key to reduce the mortality rates of this tumor. It is urgent to develop markers for early diagnosis and for prognosis and for personalized medicine. Alteration of cytokine levels is associated with cancer progression, response to chemotherapy and metastatic status. Therefore, cytokines will provide new insight on cancer biology, identify new molecular targets for cancer treatment and discover new biomarkers for diagnosis and prognosis. However, since the limitation of technology, previous studies only measured single or few cytokines at once. This greatly limits our understanding of the roles of those factors in ovarian cancer and the potential application in clinical diagnosis and prediction of clinical outcome. Recently, we have developed the first cytokine antibody array systems to simultaneously detect the expression of multiple cytokines, chemokines, growth factors, angiogenic factors and proteases. Such systems feature high specificity and sensitivity. The ability to simultaneously detect multiple cytokines will greatly facilitate the biomarker discovery. Using this novel technology, we have examined the cytokine profiling from plasma samples of ovarian cancer patients and normal subjects. Our preliminary data suggest that the protein array systems we have developed may be used to identify new biomarkers for diagnosis and prognosis and profile for molecular classification. In this grant application, with the goal to identify biomarkers for diagnosis, prognosis and personalized medicine, we will apply protein array technology developed in the Principal Investigator's lab to profile the expression levels of approximate 200 different cytokines, chemokines, growth factors, angiogenic factors and proteases in plasma samples from normal subjects versus ovarian cancer subjects. The data will be analyzed using statistics and bioinformatics tool and correlated with pathological and clinical data. The successful outcome of this grant may impact on the development of new biomarkers for patient-care management.

描述（由申请人提供）： 卵巢癌是美国和欧洲女性癌症死亡的主要原因之一。大多数死亡是由于癌症患者的这种肿瘤的晚期诊断造成的。早期诊断是降低该肿瘤死亡率的关键。迫切需要开发用于早期诊断、预后以及个性化医疗的标志物。细胞因子水平的改变与癌症进展、化疗反应和转移状态有关。因此，细胞因子将为癌症生物学提供新的见解，确定癌症治疗的新分子靶点，并发现用于诊断和预后的新生物标志物。然而，由于技术的限制，以往的研究仅一次测量单一或少数细胞因子。这极大地限制了我们对这些因素在卵巢癌中的作用的理解以及在临床诊断和临床结果预测中的潜在应用。最近，我们开发了第一个细胞因子抗体阵列系统，可以同时检测多种细胞因子、趋化因子、生长因子、血管生成因子和蛋白酶的表达。此类系统具有高特异性和敏感性。同时检测多种细胞因子的能力将极大地促进生物标志物的发现。利用这项新技术，我们检查了卵巢癌患者和正常受试者血浆样本的细胞因子分析。我们的初步数据表明，我们开发的蛋白质阵列系统可用于识别用于诊断和预后的新生物标志物以及分子分类的概况。 在本次拨款申请中，为了确定用于诊断、预后和个性化医疗的生物标志物，我们将应用首席研究员实验室开发的蛋白质阵列技术来分析大约 200 种不同细胞因子、趋化因子、生长因子、血管生成因子和正常受试者与卵巢癌受试者血浆样本中的蛋白酶。将使用统计学和生物信息学工具对数据进行分析，并将其与病理和临床数据相关联。 这笔资助的成功结果可能会影响用于患者护理管理的新生物标志物的开发。