Epistasis Blog

From the Artificial Intelligence Innovation Lab at Cedars-Sinai Medical Center (www.epistasis.org)

Monday, February 16, 2009

MDR Survival Analysis

Our paper on using MDR to carry out a survival analysis of bladder cancer has been accepted for publication in Human Genetics.

Andrew, A.S. Gui, J., Sanderson, A.C., Mason, R.A., Morlock, E.V., Schned, A.R., Kelsey, K.T., Marsit, C.J., Moore, J.H., Karagas, M.R. Bladder cancer SNP panel predicts susceptibility and survival. Human Genetics, in press (2009).


Bladder cancer is the fourth most common malignancy in men and the eighth most common in women in western countries. A hereditary component is likely since a family history of bladder cancer and variations in genes that detoxify aromatic amines and repair DNA are associated with increased risk. SNPs in many other genes that regulate processes altered in carcinogenesis including telomere maintenance, mitosis, inflammation, and apoptosis have not been assessed extensively for this disease. Using a population-based study with 1191 controls and 832 bladder cancer cases, we assessed the relationship between genetic variation and cancer susceptibility or survival. Findings included an increased risk associated with variants in the methyl-metabolism gene, MTHFD2 (adjusted OR 1.7 95%CI 1.3-2.3), the telomerase TEP1 (adjusted OR 1.8 95%CI 1.2-2.6) and decreased risk for the inflammatory response gene variant IL8RB (adjusted OR 0.6 95%CI 0.5-0.9) compared to wild-type. We filtered for gene-gene interactions using Multifactor Dimensionality Reduction to predict combinations of SNPs associated with risk. Shorter survival was associated with apoptotic gene variants, including CASP9 (adjusted HR 1.8 95%CI 1.1-3.0). Variants in the detoxification gene EPHX1 experienced longer survival (adjusted HR 0.4 (95%CI 0.2-0.8). These results suggest that genetic variation in processes frequently altered in carcinogenesis is associated with bladder cancer risk and prognosis. These genes that can now be assessed in multiple study populations to identify and validate SNPs appropriate for clinical use.


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