Coordinating and Data Management Center for Translational and Basic Science Research in Early Lesions
Coordinating and Data Management Center for Translational and Basic Science Research in Early Lesions
批准号:
10517004
负责人:
Liang Li
金额:
$81.0万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-09-16 至 2027-08-31
关键词:
AdoptedAgeAreaAutomobile DrivingBasic ScienceBioinformaticsBiological MarkersBiological Specimen BanksBiometryBreastBudgetsCenter for Translational Science ActivitiesCervicalClinicalClinical ManagementClinical TrialsClinical Trials Data Monitoring CommitteesCollaborationsColonCommunicationCommunitiesComplexComputer softwareConsent FormsDNA Sequence AlterationDataData AnalyticsData ScienceDetectionDevelopmentDiabetes MellitusDiagnosisEarly DiagnosisEpidemiologic FactorsFacultyFundingGoalsHealthcareHuman ResourcesImageImage AnalysisImmunocompetenceIndolentIndustryInflammationInformation TechnologyInfrastructureKnowledgeLeadershipLesionLinkLogisticsMachine LearningMalignant NeoplasmsMalignant neoplasm of pancreasMediatingMethodsMolecularMolecular ProfilingMonitorMulticenter StudiesOnline SystemsPathologyPatient riskPatientsPreparationProceduresProcessProtocols documentationResearchResearch DesignResearch MethodologyResearch PersonnelScreening for cancerSoftware ToolsSpecialistStressTechnologyTestingTherapeutic EffectTimeTissuesTranslational ResearchTranslationsUnited States National Institutes of HealthUniversity of Texas M D Anderson Cancer CenterVisualizationWorkbiobankbiomarker developmentcancer diagnosiscancer typecare burdenchronic pancreatitiscostdata curationdata managementdata toolsdensityexperienceimage archival systemimprovedinnovationmortalitynoveloperationovertreatmentpatient stratificationpersonalized medicineprogramsprotocol developmentrepositoryresponserisk predictionsingle cell analysisstatisticstool
中文摘要
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英文摘要
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.
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