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.

主动监测 (AS)，推迟对低风险 PCa 患者的治疗，直至出现进展迹象 通过仔细监测发现的，被开发为减少低危患者过度治疗的潜在解决方案 有患癌症的风险。对于此 BCC/BDL，我们建议开发多模式生物标志物组和相关的体外 用于两种特定临床预期用途的诊断多变量指数测定（IVDMIA），以改善 AS 的有效性：1) IVDMIA 使用血清、尿液和活检组织生物标志物来识别低血压患者 预防患有侵袭性疾病的 PCa 风险，和/或提供准确的临床分级和分期以协助 AS入学； 2) 非侵入性（血清和尿液）生物标志物的 IVDMIA，可灵敏地检测早期症状 疾病重新分类，并为明确治疗提供具有临床意义的提前时间。开发这些生物标志物 小组中，我们提出了四个具体目标。目标 1. 进行蛋白质组学和糖蛋白质组学的整合 多模式临床标本的表征，以从头发现和开发生物标志物 整合现有的或来自我们当前的 BDL/BRL 的生物标志物，用于两种特定的预期用途；目标 2. 工作 与我们的 BCC 的 BRL 组件一起开发高质量的检测方法，以准确有效地评估 选定的候选生物标志物；目标 3.（与 BRL 共同目标）开发和评估 IVDMIA 以在临床上实现 对于预定义的临床用途有意义的性能特征；目标 4. 参与 EDRN 网络研究项目，包括积极参与正在进行的和未来的网络并为其做出贡献 项目，与其他 BCC 和 CVC 合作，并与 EDRN 领导层、执行委员会和 数据管理和协调中心（DMCC）有关研究方向、数据和结果报告 准则/标准以及总体工作协调。 BDL 的创新包括独特的目标 AS 人群、 用于生物标志物发现和预验证的最先进的蛋白质组学和糖蛋白质组学技术 相、用于检测特定修饰蛋白质形式的免疫测定、组织定量分析 通过单细胞分析和免疫组织化学染色以及使用 液体组织测量。创新的生物信息学方法包括结合现有临床的工具 和疾病的生物学知识进入定量分析以进行发现和 IVDMIA 模型 通过单细胞分析和批量表达对 PCa 蛋白质组进行优化和确证分析 数据反卷积。总之，拟议的 BCC/BDL 汇集了一系列独特的井 代表预期目标人群的多模式生物样本收集特征；和 使用最先进和创新的蛋白质组学、糖蛋白质组学、统计学和 用于生物标志物发现和 IVDMIA 验证的生物信息学方法，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至关重要 前列腺癌主动监测。