Abstract 234: Computational characterization of microRNA-mediated association between obesity and cancer

Abstract MicroRNAs control gene expression in many fundamental cellular processes that are associated with pathogenesis of human cancer and obesity. However, the microRNA-mediated association between cancer and obesity is largely under-investigated, in spite of the emerging evidences indicating 1) a higher risk of pancreatic cancer and breast cancer in obese people 2) a novel mechanism to understand the links, e.g. upregulation of insulin-like growth factor-1 (IGF-1) in overweight individuals may promote pancreatic cancer 3) IGF-1 regulation of tumor suppressive miRNAs such as miR-15b, miR-98, miR-195, miR-200b, let-7c and let-7g. Based on limited knowledge of the relationship between obesity and cancer, we have applied an omics-driven integrative approach to systematically study the regulatory role of microRNA in cancer and obesity and to elucidate the association between these two types of diseases from the microRNA regulation perspective. Specifically, we have collected large-scale genomics data on obesity and three types of cancer, namely, pancreatic cancer, gastric cancer and ovarian cancer in this analysis. Given the fact that most of current methodologies for microRNA target prediction are largely dependent on computational identification of the static binding sites on mRNAs according to the sequence and structural features, they often produce a considerable number of false positive results. To tackle this problem, we have developed a new approach for identifying microRNA-mRNA interactions using sophisticated bioinformatics techniques in cooperation with genomics information. The dynamic binding feature has been taken into consideration, which integrates both cooperative and competitive manners of microRNA-mRNA binding in human. Our analysis has identified a list of obesity-associated microRNAs, part of which shows strong association with cancers under investigation. Through our new target prediction, a few such disease-related microRNAs are found to participate in various metabolic processes, such as cellular acetyl-CoA and lipid metabolism pathway (e.g. miR-103, miR-200a, miR-30c and miR-107) and cancer pathways (e.g. miR-519, miR-27a/b, miR-96 and miR-143) through regulating their targets. Moreover, we have discovered alterations of the microRNA-mRNA interaction network across cancer progression through dynamic modeling. Overall, we demonstrates such integrative study using computational modeling and omics information can effectively facilitate the discovery of disease-related microRNA regulation network and bring new insights into understanding of the association between obesity and cancer. Citation Format: Jiang Shu, Kevin Chiang, Juan Cui. Computational characterization of microRNA-mediated association between obesity and cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 234. doi:10.1158/1538-7445.AM2015-234