Application of genetic programming in analysis of quantitative gene expression profiles for identification of nodal status in bladder cancer
Poster Oct 29, 2007
Nodal involvement in bladder cancer is an independent indicator of prognosis. This study employed an iterative machine learning process called genetic programming on quantitative expression values of 70 genes to classify primary urothelial carcinoma samples into those associated with or without nodal metastasis. The generated rules showed a strong predilection for ICAM1, MAP2K6 and KDR resulting in gene expression motifs that cumulatively suggested a pattern ICAM1>MAP2K6>KDR for node positive cases.
A Tissue-based Proteomic Study of VEGFR2 in Human Term PlacentasPoster
VEGFR2 is the main regulator of placental angiogenesis and at term is localized in endothelial cells (EC) of the villous vasculature. VEGFR2 immunoprecipitation (IP) of membrane proteins, extracted from the fetal compartment, isolated 30 proteins that were identified by proteomic analysis.READ MORE
The Impact of MRI on Genitourinary and Gastrointestinal Toxicity after Radiation TherapyPoster
MRI has several advantages relative to other imaging modalities in evaluating, diagnosing, and planning treatment for prostate cancer. However, it is rarely ordered for localized disease. While the diagnostic abilities have been studied, little has been done to associate clinical outcomes with prostate cancer patients who received MRI.READ MORE