Systematic analysis of the role of differential expression of microRNAs associated with cell death decisions
Author(s)Guillén, Nancy, Ph. D. Massachusetts Institute of Technology
Massachusetts Institute of Technology. Department of Biological Engineering.
Douglas A. Lauffenburger.
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The link between abnormal microRNA expression and cancer has been widely reported. However, little is known about the relationships between temporal microRNA expression and changes in cell behavior. To better understand how microRNA expression is involved in cell responses it is necessary to know what time dependent changes happen in response to cellular stimuli. Here, we demonstrate that, in the hepatocellular carcinoma (HCC) cell line Huh7, microRNA expression changes resulting from treatments with different combinations of the cytokines IFN-[gamma] and TRAIL follow a time-dependent pattern that correlates with cell death. An initial stimulus with IFN-y, followed by a second stimulus with TRAIL is most effective at inducing cell death. By applying other combinations of these two cytokines, we induce different levels of cell death after 48 and 72 hours of the initial treatment. MicroRNA expression data from high throughput sequencing analysis was used to construct data-driven multivariate models. Expression profiles associated to different cytokine treatments were identified using principal component analysis (PCA) and, cell death was defined as a function of microRNA expression using partial least square regression (PLSR). Differential expression analysis was performed to identify relevant microRNAs from the conditions most highly associated to cell death. Global microRNA expression one hour after the second cytokine treatment is most predictive of cell death. Several microRNAs were identified as strong predictors of cell death, including let-7c, miR- 181a and miR-92b, and others. Gene ontology analysis of the targets of these, and other highly predictive microRNAs, suggests that there is an enrichment of apoptosis related targets for the microRNAs that are up-regulated upon cytokine treatment. These studies illustrate that the expression dynamics of microRNAs provide important insights into the role of microRNAs in cell decisions processes, bringing us closer to designing new strategies for diagnosis and treatment of HCC.
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2014.Cataloged from PDF version of thesis.Includes bibliographical references (pages 96-100).
DepartmentMassachusetts Institute of Technology. Department of Biological Engineering.
Massachusetts Institute of Technology