Computer Science and Engineering, Department of
Date of this Version
Dogan et al. BMC Medical Genomics (2020) 13:161 https://doi.org/10.1186/s12920-020-00797-8
Background: Obesity contributes to high cancer risk in humans and the mechanistic links between these two pathologies are not yet understood. Recent emerging evidence has associated obesity and cancer with metabolic abnormalities and inflammation where microRNA regulation has a strong implication. Methods: Inthisstudy,wehavedevelopedanintegratedframeworktounravelobesity-cancerlinkagefroma microRNA regulation perspective. Different from traditional means of identifying static microRNA targets based on sequence and structure properties, our approach focused on the discovery of context-dependent microRNA-mRNA interactions that are potentially associated with disease progression via large-scale genomic analysis. Specifically, a meta-regression analysis and the integration of multi-omics information from obesity and cancers were presented to investigate the microRNA regulation in a dynamic and systematic manner.
Results: Ouranalysishasidentifiedatotalnumberof2,143uniquemicroRNA-geneinteractionsinobesityandseven types of cancer. Common interactions in obesity and obesity-associated cancers are found to regulate genes in key metabolic processes such as fatty acid and arachidonic acid metabolism and various signaling pathways related to cell growth and inflammation. Additionally, modulated co-regulations among microRNAs targeting the same functional processes were reflected through the analysis.
Conclusion: WedemonstratedthestatisticalmodelingofmicroRNA-mediatedgeneregulationcanfacilitatethe association study between obesity and cancer. The entire framework provides a powerful tool to understand multifaceted gene regulation in complex human diseases that can be generalized in other biomedical applications
The Author(s). 2020