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Research Abstracts Online
January 2010 - March 2011

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University of Minnesota Twin Cities
Medical School
Department of Laboratory Medicine and Pathology

PI: Stephen C. Schmechel

Identification and Validation of Prognostic Prostate Cancer Biomarkers

Standard pre-operative prognostic factors such as prostate specific antigen (PSA) are important for the management of prostate cancer but they provide only limited information on extent and aggressiveness of disease. Understanding extent and aggressiveness is crucial for initial treatment planning, as these factors dictate whether local control is likely to be possible, and are important predictors of ultimate clinical outcome. Treatment of prostate cancer involves invasive techniques that may not be necessary in a subset of patients. New biomarkers are needed in order to accurately differentiate aggressive from non-aggressive prostate cancer tissue.

Through the meta-analysis of datasets from Singh et al. (2002) and Yu et al. (2004), these researchers have isolated a set of genes correlated to high aggressiveness and a set of genes correlated to non-aggressiveness. They will continue to interrogate the predictive value of these biomarkers by examining high-throughput tissue protein expression using immunohistochemical stains on tissue microarrays. To aid in the processing and analysis of data, they heavily utilize two programs available through MSI, SAS and Ingenuity Pathway Analysis. These programs assist in the creation of predictive models from the protein expression data.

Group Members

Stephen C. Dankbar, Undergraduate Student
Tony Eric Rizzardi, Staff
Nick Rosener, Undergraduate Student