An integrated systems biology approach for ovarian cancer biomarker discovery

用于发现卵巢癌生物标志物的综合系统生物学方法

• 批准号: 8307215
• 负责人: ELEFTHERIOS P DIAMANDIS
• 金额: $ 26.46万
• 依托单位: SINAI HEALTH SYSTEM
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2013-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8307215
• 关键词: Abdomen; Age; Algorithms; Antibodies; Applications Grants; Ascites; Benign; Biological; Biological Assay; Biological Markers; Blinded; CA-125 Antigen; Cancer cell line; Case-Control Studies; Categories; Coupled; Data Set; Deposition; Diagnosis; Diagnostic; Disease; Early Detection Research Network; Early Diagnosis; Enzyme-Linked Immunosorbent Assay; Enzymes; Evaluation; Family; Future; Generations; Goals; Human; Immunoassay; Kininogenase; Laboratories; Lead; Liquid substance; Literature; Malignant Neoplasms; Malignant neoplasm of ovary; Mass Spectrum Analysis; Measures; Methods; Mining; Outcome; Ovarian; Ovarian Carcinoma; Ovarian Cysts; Pathology; Patients; Phase; Principal Investigator; Proteins; Proteome; Proteomics; Reagent; Receiver Operating Characteristics; Recording of previous events; Research Design; Research Personnel; Sampling; Screening for Ovarian Cancer; Screening for cancer; Sensitivity and Specificity; Serum; Specificity; Specimen; Staging; Statistical Data Interpretation; Symptoms; Systems Biology; Technology; Therapeutic; Tissues; United States; Universities; Uterine Fibroids; Validation; WFDC2 gene; Woman; analytical tool; assay development; base; cancer diagnosis; case control; design; endometriosis; improved; member; multiple reaction monitoring; novel; phase 1 study; preclinical study; prospective; response; sample collection; uterus endometriosis

DESCRIPTION (provided by applicant): There is now convincing evidence that early cancer detection can lead to better patient outcomes through early administration of therapy. One of the best ways to early diagnose cancer is to use serum biomarkers. Unfortunately, for most cancers, we do not have effective biomarkers for either early detection or prediction of therapeutic response. With this grant application, we aim to identify such biomarkers for ovarian cancer - the most lethal gynecological malignancy in the United States. The major objective of this grant application is to examine if a panel of newly discovered ovarian cancer biomarkers (via an integrated systems biology proteomic approach), in combination with the classical ovarian cancer biomarker, CA125 and 9 other promising biomarkers such as HE4 and a group of kallikrein enzymes, constitutes a new, multiparametric serum panel for early ovarian cancer diagnosis with high sensitivity and specificity. By employing immunoassays and immuno-mass spectrometry-based technologies, we will perform a Phase I preclinical study on our top 40 novel biomarkers from which we will select only those displaying 98% specificity and 30% sensitivity for Phase II evaluation. The Phase ll case-control study, using validated immunoassays developed as part of this grant application, will utilize the PRoBE study design for sample collection and only those markers displaying at least 98% specificity and at least 70% sensitivity will proceed for an independent, blinded study using the EDRN CVC ovarian cancer reference sample set. It is anticipated that 2-4 new candidates, along with some of the 10 known markers will constitute a multiparametric panel with high specificity and sensitivity, suitable for early diagnosis and possible screening for ovarian cancer.

描述（由申请人提供）：现在有令人信服的证据表明，早期癌症检测可以通过早期治疗为患者带来更好的结果。早期诊断癌症的最佳方法之一是使用血清生物标志物。不幸的是，对于大多数癌症，我们没有有效的生物标志物来早期检测或预测治疗反应。通过这项拨款申请，我们的目标是确定卵巢癌（美国最致命的妇科恶性肿瘤）的生物标志物。本拨款申请的主要目的是检查一组新发现的卵巢癌生物标志物（通过集成系统生物学蛋白质组学方法）与经典卵巢癌生物标志物 CA125 和其他 9 种有前景的生物标志物（如 HE4 和一组激肽释放酶）相结合，是否构成了一种新的多参数血清组合，用于早期卵巢癌诊断，具有高灵敏度和高灵敏度。 特异性。通过采用免疫测定和基于免疫质谱的技术，我们将对 40 种排名前列的新型生物标志物进行 I 期临床前研究，我们将仅选择那些表现出 98% 特异性和 30% 敏感性的生物标志物进行 II 期评估。 II 期病例对照研究使用作为本拨款申请的一部分开发的经过验证的免疫测定法，将利用 PRoBE 研究设计进行样本收集，并且只有那些表现出至少 98% 特异性和至少 70% 敏感性的标记物才会使用 EDRN CVC 卵巢癌参考样本集进行独立、盲法研究。预计 2-4 个新候选物以及 10 个已知标记物中的一些将构成具有高特异性和敏感性的多参数组合，适合卵巢癌的早期诊断和可能的筛查。