Posted March 14, 2013
Christopher Moskaluk, M.D., Ph.D. University of Virginia, Charlottesville, Virginia

FY09 Lung Cancer Biospecimen Resource Network Award

Team Photo Early detection of malignant lung lesions in their potentially curable stages is essential in improving the prognosis and long-term survival of lung cancer patients. Development of diagnostic tools, candidate biomarkers (indicators of disease), and novel therapies are desperately needed to improve the care of lung cancer patients. Unfortunately, lung cancer research has been hindered by the lack of high-quality, well-annotated specimens obtained in a systematic and reproducible fashion. To address the needs of patients and clinicians alike, the LCRP awarded Dr. Moskaluk a $3.8 million grant in fiscal year 2009 to establish the first national early lung cancer biospecimen repository. This repository is designed to collect, annotate, store, and distribute early lung cancer patient samples to serve the research community, and ultimately, lung cancer patients. The specimens in the Lung Cancer Biospecimen Resource Network (LCBRN) will include tissues from thoracotomies, bronchoscopy washings, blood, saliva, and urine. Each specimen is linked to clinical and outcome data. The LCBRN collects patient samples at three participating sites, which are the University of Virginia, the Medical University of South Carolina, and Washington University in St. Louis. Importantly, the LCBRN has established collaborations with some Department of Veterans Affairs hospitals to address the needs of military personnel. Military personnel and veterans are at an increased risk for developing lung cancer due to increased exposure to environmental toxins and increased smoking rates. The LCBRN is the first national lung cancer biospecimen resource created outside of a clinical trials network that will be available to all biomedical researchers. The LCBRN aims to assist clinical investigators in the study of lung cancer genetics, novel diagnostic and prognostic tests for cancer, and candidate biomarkers.

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