Data-Driven Biomarker Panel Discovery In Ovarian Cancer Using Heterogenous Data Fusion On Exosomal And Non-Exosomal Microrna Expression Data, Paritra Mandal

All Dissertations

Ovarian cancer (OC) is an aggressive gynecological cancer and is currently the 5th leading cause of deaths due to cancer in women. High mortality rates are attributable to the vague pathogenesis and asymptomatic nature of the early stages. The development of a liquid biopsy for routine OC screening could help identify the disease at an earlier stage, making treatments more likely to be effective thereby increasing survival rates. Exosomes, small (~100nm) extracellular vesicles present in body fluids, have been shown to contain cancer-progression, onset, and related factors, making them good candidates for use in liquid biopsies. However, to date, only …

A Systematic Approach To Rna-Associated Motif Discovery, Tian Gao, Jiang Shu, Juan Cui

School of Computing: Faculty Publications

Background: Sequencing-based large screening of RNA-protein and RNA-RNA interactions has enabled the mechanistic study of post-transcriptional RNA processing and sorting, including exosome-mediated RNA secretion. The downstream analysis of RNA binding sites has encouraged the investigation of novel sequence motifs, which resulted in exceptional new challenges for identifying motifs from very short sequences (e.g., small non-coding RNAs or truncated messenger RNAs), where conventional methods tend to be ineffective. To address these challenges, we propose a novel motif-finding method and validate it on a wide range of RNA applications.

Results: We first perform motif analysis on microRNAs and longer RNA fragments from …

Mirwip: Microrna Target Prediction Based On Microrna-Containing Ribonucleoprotein-Enriched Transcripts, Molly Hammell, Dang Long, Liang Zhang, Andrew Lee, C. Steven Carmack, Min Han, Ye Ding, Victor Ambros

Victor R. Ambros

Target prediction for animal microRNAs (miRNAs) has been hindered by the small number of verified targets available to evaluate the accuracy of predicted miRNA-target interactions. Recently, a dataset of 3,404 miRNA-associated mRNA transcripts was identified by immunoprecipitation of the RNA-induced silencing complex components AIN-1 and AIN-2. Our analysis of this AIN-IP dataset revealed enrichment for defining characteristics of functional miRNA-target interactions, including structural accessibility of target sequences, total free energy of miRNA-target hybridization and topology of base-pairing to the 5' seed region of the miRNA. We used these enriched characteristics as the basis for a quantitative miRNA target prediction method, …

Immunopurification Of Ago1 Mirnps Selects For A Distinct Class Of Microrna Targets, Xin Hong, Molly Hammell, Victor Ambros, Stephen Cohen

Victor R. Ambros

microRNAs comprise a few percent of animal genes and have been recognized as important regulators of a diverse range of biological processes. Understanding the biological functions of miRNAs requires effective means to identify their targets. Combined efforts from computational prediction, miRNA over-expression or depletion, and biochemical purification have identified thousands of potential miRNA-target pairs in cells and organisms. Complementarity to the miRNA seed sequence appears to be a common principle in target recognition. Other features, including miRNA-target duplex stability, binding site accessibility, and local UTR structure might affect target recognition. Yet computational approaches using such contextual features have yielded largely …