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A Systems Biology Approach to Link Nuclear Factor Kappa B Activation with Lethal Prostate Cancer

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Annual rept. 1 May 2012-30 Apr 2013

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Since this application was written, it has become increasingly appreciated that NF B activation can either promote cancer cell death or cancer cell survival the outcome being dependent on the context of parallel biological processes. Notably, the presence of tumor suppressors influences the outcome. Our bioinformatic approach to define a cancer promoting NF B gene activation signature is proving to be well suited for accounting for the varied and opposing roles of NF B activation. Specifically, our prostate cancer specific work has identified absence of a unique set of tumor suppressors which leads to cancer cell survival and ultimately lethal prostate cancer. Notably, PTEN was not one of these tumor suppressors. It is also now appreciated that indiscriminate inhibition of NF B activation may be problematic as this may block the anti-cancer effect of NF B activation. As such the increased understanding of NF B activation s context dependency adds further support for the work we are doing. In year one and two of the project we have found elevated cytokines and presence of T. Vaginalis at time of diagnosis of prostate cancer are not associated with higher grade disease nor risk of relapse after prostatectomy. We have also identified a 31 tumor gene signature which correlates with relapse with lethal disease post prostatectomy in our training set. We have also used the 31 gene signature and publically available data-bases to computationally create a refined network of cancer promoting NF B gene activation. This network is now being used to i further inform selection of genes to test in multiple independent data sets for association with lethal disease ii inform and increase power for identification of new SNPs in GWAS datasets associated with lethal outcome, and iii help to interpret the mechanisms of action of genes associated with lethal disease identified separately in the tumor gene expression profiling and SNP analyses.

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  • Medicine and Medical Research

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