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.