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Novel Prostate Cancer Pathway Modeling using Boolean Implication
Annual summary 15 Aug 2010-14 Aug 2012
LELAND STANFORD JUNIOR UNIV CA
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Prostate cancer is the second most common cause of cancer deaths in men. We explore relationship between genes based on our novel approaches BooleanNet and MiDReG in prostate cancer and correlate them to patient information. Human prostate cancer is typically characterized by luminal cell expansion and the absence of basal cells. In normal prostate, tissue basal cells express Keratin 5 KRT5 and Keratin 14 KRT14. In the microarray datasets of primary prostate cancers, we observe a robust pattern where KRT14 high samples are always KRT5 high, but not vice versa. We summarize this in the form of a Boolean relationship KRT14 high KRT5 high. We identified three groups of patients in three independent prostate cancer gene expression microarray datasets KRT14-KRT5-, KRT14-KRT5, and KRT14KRT5. Recurrence-free survival analysis of these three independent datasets revealed that KRT14-KRT5- patients have the worst, KRT14KRT5 patients have the best, and KRT14-KRT5 patients have intermediate clinical outcome. Based on this data, we predict that KRT14KRT5 cells are upstream of KRT14-KRT5 cells, which could be upstream of KRT14- KRT5- luminal cells in normal prostate tissue.
APPROVED FOR PUBLIC RELEASE