A multidisciplinary BCC for ovarian cancer early detection: translating discoveries to clinical use with a by-design approach

项目总结(总体) 高级别浆液性卵巢癌是卵巢上皮性癌最常见的组织学亚型 癌症。拟议的生物标记表征中心(BCC)的总体目标是通过- 基于生物学的HGSOC发病机制和未满足的临床需求的设计方法以识别、验证和 优先处理和验证生物标记物，并将其发展为体外诊断多变量指数分析 (IVDMIA)，目的是在高危妇女的早期阶段捕获HGSOC，包括I) 先兆，二)局限于卵巢/输卵管或三)高危妇女的低容量疾病(BRCA1/2 运营商)。我们建议在本提案中发现和验证的生物标记物是针对早期 但不一定要在普通人群中进行筛查。BCC在高级数据方面的能力 发电技术、多重靶标分析开发和生物信息学/数据科学将作为 EDRN的资源。在我们目前EDRN项目取得成功的基础上，本中心将继续我们的- 正在进行的生物标记物开发研究，包括对我们已经确定的候选生物标记物的验证 通过当前的BDL。我们提出了以下具体目标： 1.优化和使用新的标本收集和处理技术，并迭代和 利用我们在卵巢癌中新获得的生物学知识的累积过程 发病机制。BDL 2.优化和应用创新的生物信息学、数据科学和AI/ML工具，将现有的 知识和数据以改进低频生物标志物的发现，这些生物标志物与其功能共享 通路/网络可以共同提供更高的敏感性，同时保持高度的特异性。BDL 3.在以下方面进一步发展和优化高效多重靶向分析开发过程 满足广泛光谱的分析性能、吞吐量和样品体积要求 候选生物标记物采用“因地制宜”的方法。BRL 4.优化和应用设计方法，将发现转化为临床试验。它的应用已经 在JHU团队成员为术前进行的两项FDA合格测试的开发中发挥了关键作用 卵巢恶性肿瘤风险的评估。BDL/BRL 5.向整个EDRN社区提供专业知识以及分析和数据科学能力。 我们组建的多学科团队(分子癌症生物学、病理学、临床化学、 质谱学，生物统计学，数据科学，生物工程)，独特的，新颖的，生物和 统计上可靠的方法，以及我们在生物标志物研究和翻译方面的长期经验 FDA的发现通过了临床测试，所有这些都确保了拟议中的BCC的成功。

Project Summary (Overall) High-grade serous ovarian carcinoma (HGSOC) is the most common histological subtype of epithelial ovarian cancer. The overarching goal of the proposed Biomarker Characterization Center (BCC) is to apply a by- design approach based on biology of HGSOC pathogenesis and unmet clinical needs to identify, verify and prioritize, and validate biomarkers, and to develop them into an in vitro diagnostic multivariate index assay (IVDMIA) with the intended use to capture HGSOC in high-risk women at the early stages including i) precursors, ii) confinement to the ovary/fallopian tube or iii) low-volume diseases in high-risk women (BRCA1/2 carriers). The biomarkers that we propose to discover and validate in this proposal are intended for early detection but not necessarily for screening in general population. The BCC’s capability in advanced data generation technologies, multiplexed target assay development, and bioinformatics/data science will serve as resources for the EDRN. Based on the success of our current EDRN projects, this BCC will continue our on- going biomarker development studies including the validation of candidate biomarkers that we have identified through the current BDL. We propose the following specific aims: 1. To optimize and use novel specimen collection and processing technologies, and an iterative and cumulative process that takes advantage of our newly gained knowledge of the biology in ovarian cancer pathogenesis. BDL 2. To optimize and apply innovative bioinformatics, data sciences, and AI/ML tools that incorporate existing knowledge and data to improve discovery of low frequency biomarkers that with their functionally shared pathways/networks could collectively deliver an improved sensitivity while retaining a high specificity. BDL 3. To further develop and optimize the process for efficient multiplex targeted assay development with respect to analytical performance, throughput, and specimen volume requirement for a broad spectrum of candidate biomarkers using a “fit for purpose” approach. BRL 4. To optimize and apply a by-design approach to translating discoveries into clinical tests. Its application had been critical in the development of two FDA cleared tests by JHU team members for the preoperative assessment of ovarian malignancy risk. BDL/BRL 5. To provide expertise and analytical and data science capabilities to the entire EDRN community. The multi-disciplinary team that we have assembled (molecular cancer biology, pathology, clinical chemistry, mass spectrometry, biostatistics, data science, bioengineering), the unique, novel yet biologically and statistically sound approaches, and our long-standing experience in biomarker research and translating discoveries to FDA cleared clinical tests all together ensure the success of this proposed BCC.