Population based early cancer detection will require risk assessment, specimen collection, molecular analyses and long term follow up. We will identify subjects at varying degrees of increased risk for the development of lung or breast cancer (Aim number 1). For lung cancer, we will determine which of 335 heavy smokers have developed sputum atypia and bronchial dysplasia. For breast cancer, we will utilize a dedicated screening clinic which uses computerized programs, and germline mutational analyses to assign an age related risk to women. Suitable specimens will be collected from these subjects and those with cancer (100 cases/year of each tumor type) and from controls (Aim number 2). Specimens to be collected include blood plasma and, for lung, from surrogate organ, sputa, bronchial biopsies and brushes and bronchoalveolar lavage fluids. For breast, fine needle aspirates of periareolar tissue will be obtained. We will recruit 100-150 women/year. Subjects will be followed beyond the life of the proposal. On these specimens we will perform appropriate molecular analyses (Aim number 3). After identifying the molecular changes frequently present in tumors and their cell lines we will determine if they are abnormal during multistage pathogenesis or present in the plasma of patients with invasive cancer. Markers to be studied for risk assessment include onset of clonality, allelic losses at multiple regions, microsatellite alterations using multiple polymorphic markers and presence of aberrantly methylated genes. For early detection, we will use disease specific panels to search for aberrantly methylated genes in plasma DNA. We will develop and validate a microarray chip methodology for the detection of all genes known to be aberrantly methylated in human cancers. For data analysis, we will rely heavily on the Data management and Coordinating Center established by the EDRN. However we will utilize two other Data Analysis mechanisms that will closely collaborate with the EDRN Center: a) the Data Analysis Center established by the lung cancer SPOREs; and b) Data-Mining Technologies Inc, a private company that has developed sophisticated software which will be used for exploring complex relationships between markers, histopathological features, clinical data and known risk factors. A close collaboration has been established with investigators at Johns Hopkins Institution for establishing methodologies, for searching for new methylated gene markers, and for sharing specimens. A unique feature of this proposal is that it will utilize other funded sources for much of the patient accrual, screening and specimen collection, permitting access to large numbers. The multiple cases accessioned and specimens collected will permit sharing our resources with other EDRN investigators. At the end of the 5-year project we will have a deep understanding of the role of molecular markers for risk assessment and early diagnosis.
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