Molecular Epidemiology of Urothelial Carcinoma Prognosis Based on Microrna Expression Profiles

Urothelial carcinoma (UC) is the ninth most common diagnosed malignancy among men in Taiwan. There are 20% of UC patients belong to muscle-invasive or metastatic tumors at initial diagnosis and 50% of these patients will die within 2 to 3 years. In addition, the remaining 80% are superficial at initial diagnosis but 50% of these UC patients will recur accompanied with advanced tumor stage, grade and poor prognosis. Therefore, the discovery of potential biomarkers will be helpful for clinical diagnosis, treatment and prognosis of UC. MicroRNAs, a class of non-coding RNAs (20-25 nucleotides in length) that involve in posttranscriptional gene expression by base pairing with target mRNAs and lead to mRNA cleavage or translational silencing. Previous studies indicated that microRNAs are frequently dysregulated in tumor tissues comparing to adjacent normal tissues. Therefore, microRNAs have been thought to be useful biomarkers for the detection of cancer prognosis. The present study consists of 300 non-arsenic related UC (non-As-UC), 200 arsenic related UC (As-UC) and 500 cancer-free controls. In the first year, we will perform microRNAs microarray and real-time quantitative RT-PCR (qRT-PCR) to compare 60 tumor tissues and 20 adjacent normal tissues for discovering candidate biomarkers related to clinicopathological features. In the second year, we also apply microRNAs microarray and quantitative real-time PCR (qRT-PCR) to identify candidate biomarkers related to clinicopathological features in urine collected from 60 UC cases and 20 cancer-free controls. In the third year, the first step is to find out the consistently down-regulated microRNAs in tumor tissues and urine samples. Using bioinformatics analysis to discover potential polymorphisms located at candidate microRNAs and their target genes. Furthermore, we will perform in vitro approach to investigate the function of potential polymorphisms in candidate microRNAs and their target genes. Finally, we further integrated environmental risk factors such as arsenic exposure and cigarette smoking, experimental findings and clinicopathological features to discover useful biomarkers for the clinical diagnosis and prognosis of UC in Taiwan.