Metabolic Rewiring Promotes AA PCa by Regulating Stromal-Epithelial Interaction

点击翻译按钮获取中文摘要

The long-term objective of our research plan is to reduce the disproportionate effects of prostate cancer on African American men. In this application, we have used the technique of metabolomic profiling to uncover underlying biochemical differences between prostate cancers of African American and European American origin. Metabolomics describes the science of quantifying the levels of metabolites (e.g., small molecules) that are the byproducts of cellular metabolism. That is to say, in this kind of analysis we are measuring the biochemical entities (or metabolites) that are produced by the functional machinery of the cell. With knowledge of the identity of specific metabolites we can infer the biological processes that produced them, thus gaining insight into a cell’s metabolism. Given this, a guiding principle of application is that unique biochemical differences exist between prostate cancers of African American and European American origin and that these differences can influence the tumors and their surrounding cells termed stroma such that together they can promote the progression of the tumors. Since African American prostate cancer grow and progress more rapidly than European American tumors, our studies will potentially address some of the causes underlying prostate cancer health disparity. In addition, it will also build a first-of-its-kind biomarker panel that can predict cancer recurrence in ancestry verified African American men with prostate cancer. In this proposal, we will i) identify the biochemical mechanism that drives elevated levels of inosine in African American Prostate Cancer, ii) evaluate the function of elevated inosine in making African American tumors aggressive and invoke tumor promoting properties in the surrounding stromal cells and iii) develop plasma based metabolic markers for biochemical recurrence in African American men. At the conclusion of this study, we will have developed a racially derived metabolomic model for prostate cancer as well as identified candidate pathways for future drug targeting. We would have also built a proof-of-principle metabolite-based test with the ability to predict cancer recurrence based on the ancestry of the patient. In the longer term, this test will be validated and translated into a clinical assay that should have the ability to predict the recurrence of prostate cancer in an ancestry informed fashion in prostate cancer patients.