Biomarker Development Laboratory

生物标志物开发实验室

• 批准号: 10701247
• 负责人: Hui Zhang
• 金额: $ 37.87万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-20 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10701247
• 关键词: Adoption; Affect; Bioinformatics; Biological; Biological Assay; Biological Markers; Biopsy; Body Fluids; Cancer Patient; Characteristics; Circulation; Classification; Clinical; Collaborations; Collection; Data; Data Coordinating Center; Detection; Development; Disease; Disease Progression; Early Detection Research Network; Early Diagnosis; Early Intervention; Effectiveness; Enrollment; Evaluation; Future; Gleason Grade for Prostate Cancer; Immunoassay; Immunohistochemistry; Knowledge; Lead; Leadership; Liquid substance; Magnetic Resonance Imaging; Malignant neoplasm of prostate; Measurement; Meta-Analysis; Modeling; Monitor; Nature; Newly Diagnosed; PSA screening; Pathological Staging; Patient Triage; Patients; Performance; Phase; Play; Population Surveillance; Post-Translational Protein Processing; Proteins; Proteome; Proteomics; Protocols documentation; Public Health; Recording of previous events; Reporting; Research; Research Project Grants; Resources; Role; Sampling Errors; Screening for Prostate Cancer; Serum; Signal Transduction; Specimen; Staging; Stains; Target Populations; Technology; Time; Tissues; Translating; Translations; Urine; Urology; Validation; Variant; Work; assay development; biomarker development; biomarker discovery; biomarker panel; biomarker validation; cancer biomarkers; cancer diagnosis; cancer risk; candidate marker; candidate selection; disorder risk; genomic signature; glycoproteomics; glycosylation; improved; in-vitro diagnostics; indexing; innovation; laboratory development; member; multimodality; multiple omics; overtreatment; progression risk; prostate cancer cell; prostate cancer progression; prostate cancer risk; research clinical testing; single cell analysis; single cell proteins; statistics; success; tissue biomarkers; tool; ultrasound

Active surveillance (AS), which holds off on treatment for low-risk PCa patients until signs of progression are detected through careful monitoring, was developed as a potential solution to decrease over-treatment of low- risk cancer. For this BCC/BDL, we propose to develop multimodal biomarker panels and associated in vitro diagnostic multivariate index assays (IVDMIAs) for two specific clinical intended uses to improve the effectiveness of AS: 1) IVDMIAs using serum, urine, and biopsy tissue biomarkers to identify patients with low- risk PCa from those with aggressive disease, and/or to provide accurate clinical grading and staging to assist in AS enrollment; and 2) IVDMIAs of non-invasive (serum and urine) biomarkers to sensitively detect early signs of disease reclassification with clinically meaningful lead time for definitive treatment. To develop these biomarker panels, we propose four specific aims. Aim 1. To perform integrated proteomic and glycoproteomic characterization of multimodal clinical specimens to discover and develop biomarkers de novo as well as integrate biomarkers existing or from our current BDL/BRL for the two specific intended uses; Aim 2. To work with the BRL component of our BCC to develop high-quality assays for accurate and efficient evaluation of selected candidate biomarkers; Aim 3. (co-Aim with BRL) To develop and evaluate IVDMIAs to achieve clinically meaningful performance characteristics for the predefined clinical uses; and Aim 4. To participate in EDRN network research projects, including actively participating in and contributing to on-going and future network projects, collaborate with other BCCs and CVCs, and work with EDRN leadership, Executive Committee, and Data Management and Coordinating Center (DMCC) regarding research direction, data and results report criteria/standards, and general effort coordination. Innovations of the BDL include unique targeted AS population, state-of-the-art proteomic and glycoproteomic technologies for both biomarker discovery and pre-validation phases, immunoassays for the detection of specific modified protein forms, quantitative analysis of tissue proteins by single-cell analysis and immunohistochemistry staining as well as quantitative measurement using liquid tissue measurement. Innovative bioinformatics approaches include tools that incorporate existing clinical and biological knowledge of the disease into the quantitative analysis for discovery and IVDMIA model optimization and corroborative analysis of the PCa proteome through single-cell analysis and bulk expression data deconvolution. In summary, the proposed BCC/BDL has assembled a unique collection of well characterized multimodal biospecimen collections representative of the intended targeted populations; and proposed a clear path using state-of-the-art and innovative proteomics, glycoproteomics, statistics, and bioinformatics approaches for biomarker discovery and validation of IVDMIAs to achieve clinically meaningful performance for the two clearly defined intended clinical uses that are critically important for the success of prostate cancer active surveillance.

主动监视（AS），该（AS）在低风险PCA患者的治疗中停留，直到进展迹象为 通过仔细的监测检测，作为潜在的解决方案，以减少低 - 风险癌。对于此BCC/BDL，我们建议开发多模式生物标志物和相关的体外 诊断性多元指数分析（IVDMIA），用于两种特定的临床预期用途，以改善 AS的有效性：1）使用血清，尿液和活检组织生物标志物鉴定低 - 患者的IVDMIA 风险来自患有侵略性疾病的人，和/或提供准确的临床分级和分期以帮助 作为入学； 2）非侵入性（血清和尿液）生物标志物的IVDMIA，以敏感地检测到早期迹象 疾病重新分类，具有临床意义的确定性治疗时间。开发这些生物标志物 面板，我们提出了四个具体目标。目标1。执行集成的蛋白质组学和糖蛋白质组学 多模式临床标本的表征，以发现和发展从头开始生物标志物以及 将现有的生物标志物或从我们当前的BDL/BRL中整合在一起，以供两种特定的预期用途；目标2。工作 借助我们BCC的BRL组成部分，可以开发高质量的测定法，以准确有效地评估 选定的候选生物标志物；目标3。（与BRL共同）开发和评估IVDMIA以实现临床 预定义临床用途的有意义的性能特征；目标4。参加EDRN 网络研究项目，包括积极参与并为正在进行的网络做出贡献 项目，与其他BCC和CVC合作，并与EDRN领导层，执行委员会和 有关研究方向，数据和结果报告的数据管理和协调中心（DMCC） 标准/标准和一般努力协调。 BDL的创新包括针对人口的独特目标， 最先进的蛋白质组学和糖蛋白质组学技术，用于生物标志物发现和预验证 阶段，用于检测特定修饰蛋白质形式的免疫测定，组织的定量分析 通过单细胞分析和免疫组织化学染色以及使用定量测量的蛋白质 液体组织测量。创新的生物信息学方法包括包含现有临床的工具 以及对疾病的生物学知识，以发现发现和IVDMIA模型的定量分析 通过单细胞分析和大量表达对PCA蛋白质组的优化和佐证分析 数据反卷积。总而言之，拟议的BCC/BDL组装了独特的井集 代表预期目标人群的多模式生物测量收集。和 提出了使用最先进和创新的蛋白质组学，糖蛋白质组学，统计和 生物标志物发现和验证IVDMIA的生物信息学方法，以实现临床意义 两种明确定义的预期临床用途的性能，对于成功的成功至关重要 前列腺癌主动监测。