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.

项目概要 该项目旨在发现和验证用于早期检测卵巢癌的血浆生物标志物。一个 癌症的标志是不受控制的细胞分裂，导致肿瘤倍增。这种指数级的增长 与几乎所有其他疾病中血浆蛋白的稳定或缓慢变化形成鲜明对比 或在健康受试者中。该项目将利用这一独特的标志来发现和验证血浆蛋白 用于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 通过识别随着时间的推移以指数方式显着升高的蛋白质来确定生物标志物 病例的一小部分，但在大多数对照中随着时间的推移仍保持相对稳定。这需要血浆检测超过 一大套蛋白质的 CV 低于蛋白质随时间的生物变异，可低至 10%的简历。此外，低体积要求对于获取形成的珍贵生物样本至关重要 来自长期大型早期检测试验。 Olink AB 开发了邻近延伸分析 (PEA) 一套约 1,500 种蛋白质，CV 范围为 6-12%，最小体积要求为 3微升。将 Olink 蛋白质组检测应用于 PLCO 受试者的连续诊断前血浆 研究期间诊断患有卵巢癌（病例 n=50）并采集 4:1 的连续血浆样本 匹配对照 (n=200)：病例 (n=50) 队列将提供约 1,500 种血浆蛋白的纵向数据 用于识别 ED 候选生物标志物的病例和对照。在每个病例发生癌症之前， 随着时间的推移，生物标志物将保持稳定，而在癌症发生后，生物标志物将呈指数增长，反映出 肿瘤倍增。这种行为由案例中的变化点模型表示，而相同的生物标志物 没有卵巢癌的女性（对照）的轮廓是扁平的。 ED 生物标志物是具有以下特征的蛋白质： 在相当一部分病例中是一个变化点，同时在大多数（98%）对照中保持稳定。我们将确定 排名前 20 的 ED 生物标志物，其纳入标准是病例比例、互补性的组合 已选择的蛋白质，以及较早起床者优先的起床时间。 20 ED 鉴定后 生物标记物方面，Olink 将开发一个包含 20 个 ED 标记物的定制面板，具有绝对定量功能。习俗 小组将分析与发现中使用的相同的 PLCO 血浆样本。这些数据将被分析 多变量纵向变化点模型形成 ED 的多标记纵向算法。这 分类器将被锁定。分类器将通过分析 20 个 ED 的定制面板进行验证 独立 PLCO 系列血浆样本集上的生物标志物，来自病例 (n=50) 和 10:1 匹配对照 （n=500）。根据这些数据，将评估分类器的两个维度的敏感性以进行早期检测：(i) PLCO 检测前的月数，以及 (ii) 检测到的病例比例，同时 (iii) 保持 98% 的高特异性目标 - 或 2% 的假阳性率。这种低误报率需要大量的 控制（n = 500）以进行准确评估。