Regulation of gene expression is a complex process in mammalian cells with many levels of control. In recent years non-coding RNAs in the form of microRNAs (miRNA) have surfaced as important regulators of protein coding genes, with biologically important roles in development, differentiation and cell growth. In this dissertation the complex interactions between miRNAs and mRNAs in ovarian cancer are investigated using a combination of computational and experimental techniques. In vitro studies and current models predict that increases in levels of miRNA should result in corresponding decreases in the levels of targeted mRNAs due to miRNA induced degradation. Profiling the global miRNA and mRNA expression patterns in epithelial ovarian cancer cells from patients and surface epithelial cells from normal ovaries reveal only ~11% of predicted targets of miRNAs are inversely correlated in vivo. In an effort to dissect the mechanisms behind these unexpected observations single miRNA transfection experiments are carried out followed by gene expression profiling. Analysis of genes altered following these transfections reveal majority of the altered genes are not direct targets of the miRNAs. Network analysis however suggests that miRNAs may target "hub genes" to cause altered expression in downstream transcripts. Pathway enrichment analysis of altered genes demonstrates miRNAs may regulate specific pathways rather than causing random off-target effects. Finally investigation of miRNA regulation reveals miRNAs may also affect the levels of other miRNAs, which may indirectly affect more genes downstream. Together these results provide a detailed view of the mechanisms employed by miRNAs to regulate the expression of hundreds of genes in ovarian cancer cells.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/44753 |
| Date | 19 May 2011 |
| Creators | Shahab, Shubin |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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