Identify the DNA Adduct and Associated Metabolic Alterations in Bladder Cancer of Smokers

Smoking is a major risk factor for bladder cancer (BCa). Patients with current or past history of smoking have a three times higher likelihood of developing BCa. Smoking is also known to have a potential dose-dependent effect on the grade and stage of BCa, with high-dose smokers having more aggressive disease. In addition, smokers with BCa have a higher likelihood of failing chemotherapy. Currently, markers that can stratify smokers based on their risk of developing BCa are lacking. Furthermore, predictive markers for aggressive BCa among high-dose smokers are also lacking. The central goal of this application is to characterize the DNA adducts and biochemical alterations observed in smoking-associated BCa and use this information to develop metabolite-based predictive markers and therapeutic strategies for this deadly disease. Cigarette smoke contains a number of xenobiotic compounds that include arylamines, methylated metabolites, Nicotinederived nitrosamine ketone (NNK), Benzo[a]pyrene (BaP), nicotine etc which are usually metabolized by the xenobiotic metabolism and excreted in the urine. Our strong preliminary data demonstrates altered DNA adducts and reprogramming of xenobiotic metabolism in BCa smokers. This effect is exaggerated by components of cigarette smoke including nicotine. Using a novel metabolomics approach, we had earlier shown that BCa was associated with a unique metabolic signature. From the patients perspective it is important to be able to measure these markers non-invasively in body fluids like urine. Intriguingly, metabolites are the end products of overall cellular metabolism. These are small molecules that could be easily monitored in body fluids to interrogate disease phenotype in question. Quiet provocatively, our group is being established to utilize metabolites to further monitor tumors. Thus, our current proposal aims to identify DNA adducts and associated metabolites in BCa smokers and use the information to develop markers for early identification of patients who are at risk for developing aggressive bladder cancer. Further will enable clinicians to take an informed decision about more appropriate therapeutic strategies towards personalized medicine.