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Cancer Biomarkers Research Group

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Extraordinary Opportunities for Early Cancer Detection and Risk Assessment Research

Molecular Taxonomy of Preneoplasia

Pathologic criteria for classifying preneplastic lesions can benefit from recent discoveries in genetics and molecular biology. For example, the identification of mismatch repair genes could possibly be incorporated in establishing the pathologic criteria for classifying hereditary non-polyposis colon cancer. What are the specific criteria, for example, of microsatellite instability? How does genetic inheritance affect the interpretation of pathologic findings? What are the biomolecular characteristics and clinical history that can help establish minimum pathologic criteria for cases to be entered into a registry? Integrating genetic and molecular criteria into classifying preneoplastic lesions are some of the research areas for which CBRG is interested in supporting.

The clinical behavior of tumors is unpredictable without reliable biomarkers. New quantitative pathology techniques, such as DNA ploidy, could more reproducibly reflect behavior. For example, flow cytometric DNA ploidy, and the S-phase fraction are potentially useful parameters to estimate colorectal carcinoma pathology and aneuploidy and high replicative neoplastic activity correlated with histopathologic features that are commonly associated with the prognosis of colorectal carcinoma. But even these are crude predictors. Several studies have also suggested an association between biomarkers and pathologic stages, thereby reinforcing the clinical utility of biomarkers. For example, the expression of TGF-beta2 is found to be highly correlated with Stage T2a and Gleason grade of 3 or less of early prostate cancer may contribute to TGF-beta2 levels. These findings suggest that biomarkers, in addition to their value in early detection, could also help in the staging of the disease. A staging system integrating molecular and genetic profiles of cells must be developed that meticulously evaluate tumor volume, secretion of biomarkers, and the site of the origin of tumors in patients. Informatics could play an important role in the integration of complex information from analysis of multiple markers simultaneously.

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