Coordinating and Data Management Center for Translational and Basic Science Research in Early Lesions

早期病变转化和基础科学研究协调和数据管理中心

• 批准号: 10705661
• 负责人: Liang Li
• 金额: $ 79.38万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-16 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10705661
• 关键词: Adopted; Age; Area; Automobile Driving; Basic Science; Bioinformatics; Biological Specimen Banks; Biometry; Breast; Budgets; Center for Translational Science Activities; Cervical; Clinical; Clinical Management; Clinical Trials; Clinical Trials Data Monitoring Committees; Collaborations; Colon; Communication; Communities; Complex; Computer software; Consent Forms; DNA Sequence Alteration; Data; Data Analytics; Data Coordinating Center; Data Science; Detection; Development; Diabetes Mellitus; Diagnosis; Early Diagnosis; Epidemiologic Factors; Faculty; Funding; Goals; Healthcare; Human Resources; Image; Image Analysis; Immunocompetence; Indolent; Industry; Inflammation; Information Technology; Infrastructure; Knowledge; Leadership; Lesion; Link; Logistics; Machine Learning; Malignant Neoplasms; Malignant neoplasm of pancreas; Mediating; Methods; Molecular; Molecular Profiling; Monitor; Multicenter Studies; Pathology; Patient risk; Patients; Preparation; Procedures; Process; Protocols documentation; Research; Research Design; Research Methodology; Research Personnel; Screening for cancer; Software Tools; Specialist; Stress; Technology; Testing; Therapeutic Effect; Time; Tissues; Translational Research; Translations; United States National Institutes of Health; University of Texas M D Anderson Cancer Center; Visualization; Work; biobank; biomarker development; biomarker identification; cancer diagnosis; cancer type; care burden; chronic pancreatitis; cost; data curation; data management; data tools; density; experience; image archival system; improved; innovation; mortality; novel; operation; overtreatment; patient stratification; personalized medicine; programs; protocol development; repository; response; restraint; risk prediction; single cell analysis; statistics; tool; web platform

Project Summary Early diagnosis of cancer can improve therapeutic effect and prolong patient survival. The increasingly sensitive and widely adopted early cancer screening technologies have led to significantly more detection of early lesions that may or may not progress to cancer. Elucidating the mechanisms that drive or restrain early cancer would allow differentiation of aggressive cancer versus indolent types, improving personalized treatment and avoiding over-diagnosis and over-treatment. Whether an early lesion progress to cancer or not is not solely decided by the molecular profile of the lesion but also is impacted by the surrounding microenvironment and mediated by other epidemiologic factors. Meanwhile, the progression of an early lesion to malignancy is a complex process that may take years to occur. The complexities of the problem highlight the unmet needs for researchers from basic to translational science to collaborate and coordinate in the research of the underlying mechanisms between early lesion and cancer development. In response to RFA-CA-21-055, we propose a Coordinating and Data Management Center (CDMC) for the Translational and Basic Science Research in Early Lesions (TBEL) Program. The CDMC interacts closely with other entities of the Program, including the Steering Committee, the Research Centers, biospecimen and image repository, pathology centers, sequencing facilities, Data and Safety Monitoring Board (DSMB), and NCI, and provides critical scientific, administrative, regulatory, managerial, logistic, and data-analytic support to the TBEL Program. Our proposed CDMC infrastructure and operating procedures have been time-tested in an ongoing NIH-funded Consortium for the Study of Chronic Pancreatitis, Diabetes and Pancreatic Cancer. Specifically, the proposed work includes the three aspects of required responsibilities: consortium coordination (Aim 1), statistical and computational support (Aim 2), and data management, study protocol development and implementation (Aim 3). Our team of experts include information technology specialists who have been supporting and developing innovative software tools for numerous basic and translation cancer studies, experienced research coordinators who have worked on both NIH- and industry-funded multicenter studies, and faculty statisticians and bioinformaticians who have led CDMC work for large NIH consortiums and are well- known experts in biostatistics and bioinformatics methodological research areas closely related to biomarker development, risk prediction, single cell analysis, image analysis, machine learning, and clinical trials.

项目概要 癌症的早期诊断可以提高治疗效果并延长患者的生存期。越来越多的 敏感且广泛采用的早期癌症筛查技术显着提高了检测率 可能会或可能不会发展为癌症的早期病变。阐明驱动或抑制的机制 早期癌症将能够区分侵袭性癌症与惰性类型，从而改善 个性化治疗，避免过度诊断和过度治疗。是否为早期病变 是否进展为癌症不仅取决于病变的分子特征，还受到影响 由周围微环境和其他流行病学因素介导。与此同时， 早期病变进展为恶性肿瘤是一个复杂的过程，可能需要数年时间才能发生。这 问题的复杂性凸显了从基础科学到转化科学的研究人员的需求未得到满足 合作和协调早期病变和早期病变之间的潜在机制的研究 癌症的发展。为了回应 RFA-CA-21-055，我们提出了协调和数据管理 早期病变转化和基础科学研究中心 (CDMC) (TBEL) 计划。这 CDMC 与该计划的其他实体密切互动，包括指导委员会、 研究中心、生物样本和图像存储库、病理中心、测序设施、数据和 安全监察委员会 (DSMB) 和 NCI，并提供关键的科学、行政、监管、 为 TBEL 计划提供管理、后勤和数据分析支持。我们提议的 CDMC 基础设施 和操作程序已经在 NIH 资助的正在进行的研究联盟中经过了时间测试 慢性胰腺炎、糖尿病和胰腺癌。具体来说，拟议的工作包括三项 所需职责的各个方面：联盟协调（目标 1）、统计和计算 支持（目标 2），以及数据管理、研究方案制定和实施（目标 3）。我们的 专家团队包括一直支持和开发的信息技术专家 用于众多基础和翻译癌症研究的创新软件工具，经验丰富的研究 曾从事 NIH 和行业资助的多中心研究的协调员以及教师 曾为大型 NIH 联盟领导 CDMC 工作的统计学家和生物信息学家，并且非常擅长 与密切相关的生物统计学和生物信息学方法学研究领域的知名专家 生物标志物开发、风险预测、单细胞分析、图像分析、机器学习和 临床试验。