Proteomic Analyses of Serial Prediagnostic PLCO Serum in Cases and Controls to Identify Early Detection Ovarian Cancer Biomarkers Rising in a Substantial Fraction of Cases and Stable in Most Controls

对病例和对照中的系列诊断前 PLCO 血清进行蛋白质组学分析，以识别早期检测卵巢癌生物标志物，这些生物标志物在大部分病例中上升，而在大多数对照中保持稳定

• 批准号: 10703252
• 负责人: Steven J Skates
• 金额: $ 12万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-15 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10703252
• 关键词: Acute-Phase Proteins; Age; Algorithms; Behavior; Biological; Biological Assay; Biological Markers; Blood Proteins; Blood specimen; CA-125 Antigen; Cancer Etiology; Cell division; Consumption; Custom; Data; Detection; Diagnosis; Diagnostic; Disease; Early Diagnosis; Early identification; Goals; Growth; High Risk Woman; Inflammation; Investigation; Light; Longitudinal Studies; Malignant Neoplasms; Malignant neoplasm of ovary; Measures; Modeling; Pattern; Performance; Persons; Pilot Projects; Plasma; Plasma Proteins; Probability; Process; Proteins; Proteomics; Resources; Sampling; Screening for Ovarian Cancer; Serum; Signal Transduction; Specificity; Statistical Models; Symptoms; Technology; Test Result; Testing; Time; Validation; Variant; WFDC2 gene; Woman; arm; biobank; biomarker discovery; biomarker identification; blood-based biomarker; cancer biomarkers; cancer diagnosis; candidate marker; cohort; detection sensitivity; early detection biomarkers; longitudinal analysis; mortality; new technology; novel; programs; protein biomarkers; response; screening; tumor; two-dimensional

Project Summary This project aims to discover and validate plasma biomarkers for the early detection of ovarian cancer. A hallmark of cancer is uncontrolled cell division, leading to a doubling time of the tumor. This exponential growth stands in stark contrast to the stable or slowly changing profile of plasma proteins in almost all other diseases or in healthy subjects. This project will leverage this unique hallmark to discover and validate plasma protein biomarkers for the early detection of ovarian cancer. We will discover early detection (ED) plasma protein biomarkers by identifying the proteins that significantly rise over time in an exponential fashion in a substantial fraction of cases and yet remain relatively stable over time in most controls. This requires plasma assays over a large suite of proteins with CVs lower than the protein's biological variation over time which can be as low as a CV of 10%. Furthermore, a low volume requirement is essential for access to precious biospecimens formed from long-term large early detection trials. Olink AB has developed proximity extension assays (PEAs) for a suite of ~1,500 proteins with CVs ranging from 6-12% and with a minimal volume requirement of 3 µL. Applying the Olink proteomic assays to serial pre-diagnostic plasma from subjects in the PLCO who were diagnosed with ovarian cancer during the study (cases n=50) and to serial plasma samples from a 4:1 matched control (n=200) : case (n=50) cohort will provide longitudinal data on ~1,500 plasma proteins from cases and controls by which to identify ED candidate biomarkers. Prior to cancer developing in each case, a biomarker will be stable over time, while after cancer inception the biomarker will rise exponentially reflecting tumor doubling. This behavior is represented by a change-point model in cases while the same biomarker in women without ovarian cancer (controls) will have a flat profile. ED biomarkers will be the proteins which have a change-point in a substantial fraction of cases while remaining stable in most (98%) controls. We will identify the top 20 ED biomarkers where the criteria for inclusion is a combination of fraction of cases, complementarity to proteins already selected, and time of rise with earlier risers having priority. After identification of the 20 ED biomarkers, Olink will develop a custom panel of 20 ED markers with absolute quantification. The custom panel will assay the same PLCO plasma samples as used in discovery. These data will be analyzed with a multivariate longitudinal change-point model to form a multiple marker longitudinal algorithm for ED. This classifier will be locked down. The classifier will be validated by assaying the custom panel of 20 ED biomarkers on an independent PLCO serial plasma sample set, from cases (n=50) and 10:1 matched controls (n=500). From these data the classifier will be assessed for two dimensions of sensitivity for early detection: (i) the number of months prior to detection in PLCO, and (ii) proportion of cases detected, while (iii) maintaining a high specificity goal of 98% - or a false positive rate of 2%. This low false positive rate requires a large number of controls (n=500) for its accurate assessment.

项目摘要 该项目旨在发现和验证血浆生物标志物以早期发现卵巢癌。一个 癌症的标志是不受控制的细胞分裂，导致肿瘤的两倍时间。这种指数增长 与几乎所有其他疾病中等离子体蛋白的稳定或缓慢变化的特征形成鲜明对比 或在健康的受试者中。该项目将利用这个独特的标志来发现和验证血浆蛋白 早期检测卵巢癌的生物标志物。我们将发现早期检测（ED）血浆蛋白 生物标志物通过识别以指数方式显着增长的蛋白质，以实质性的方式升高 在大多数控件中，案例的一部分却随着时间的流逝而相对稳定。这需要等离子体测定 随着时间的流逝，一大堆CVS的蛋白质比蛋白质的生物学变异低于该蛋白质 简历为10％。此外，低容量要求对于访问珍贵的生物测量至关重要 来自长期大型早期检测试验。 Olink AB已开发了近距离扩展测定法（豌豆） CVS的约1,500蛋白的套件范围为6-12％，而且量很少。 3 µL。将Olink蛋白质组学测定应用于PLCO中的受试者的连续诊断前血浆 研究期间诊断为卵巢癌（病例n = 50）和4：1的串行血浆样品 匹配的对照（n = 200）：案例（n = 50）队列将提供〜1,500个血浆蛋白的纵向数据 识别ED候选生物标志物的案例和对照。在每种情况下发生癌症之前， 生物标志物会随着时间的流逝而保持稳定，而在癌症开始后，生物标志物将成倍地反映 肿瘤加倍。在情况下，此行为由变更点模型表示 没有卵巢癌（对照组）的女性将具有平坦的特征。 ED生物标志物将是具有的蛋白质 在很大一部分情况下的变化点，同时在大多数（98％）对照中保持稳定。我们将确定 纳入标准的前20名ED生物标志物是案例分数的组合 对于已经选择的蛋白质，并且具有优先级的较早立管的时间。识别20 ed之后 Olink生物标志物将开发一个具有绝对定量的20个ED标记的自定义面板。习俗 面板将测定与发现相同的PLCO等离子体样品。这些数据将通过 多元纵向变化点模型，形成ED的多个标记纵向算法。这 分类器将被锁定。分类器将通过分析20 ed的自定义面板来验证 来自案例（n = 50）和10：1匹配的对照组的独立PLCO串行等离子体样品集的生物标志物 （n = 500）。从这些数据中，将评估分类器的敏感性两个维度的早期检测：（i） PLCO检测前几个月的数量，以及（ii）检测到的病例比例，而（iii）维持 高特异性目标为98％ - 或误报率为2％。低误报率需要大量 对照（n = 500）的准确评估。