Bioinformatics Seminars

Bioinformatics Seminar

Time: 10:45am Tuesdays.
Venue:
Level 7 Seminar Room 2, WEHI1

19 March 2019

Post-Transcriptional Regulatory Networks within Breast Cancer Progression

Holly Whitfield
WEHI Bioinformatics

Over the past decade there have been large advances in our ability to investigate 'non-coding' RNAs (ncRNAs). It has become increasingly apparent that ncRNAs play an important role in regulating cell behaviour, and accordingly, RNA is not just an intermediate product involved in the production of proteins from genes. A class of ncRNAs known as microRNAs (miRNAs) appears to be critical for the correct regulation of specific target genes.

The leading cause of death for breast cancer patients is metastasis, mediated in part by epithelial-to-mesenchymal transition (EMT), a regulatory program controlling cell phenotype. The miR-200 family plays a central role in EMT regulatory networks that underlie breast cancer progression. MicroRNAs can control cellular phenotypes through the coordinated effects of multiple mRNAs, including additive effects of multiple miRNA co-targeting individual or functionally-related mRNAs, as well as individual miRNAs targeting multiple mRNAs. Furthermore, it has been proposed that transcripts with numerous binding sites for miRNAs can 'sponge up' or sequester the miRNA, decreasing its availability for regulating other transcripts, also known as the competitive endogenous RNA (ceRNA) hypothesis. As a consequence, miRNAs operate within the context of a larger RNA regulatory network, however, experimental approaches often require the isolation of miRNAs and their targets, disregarding much of their broader biological context.

In this talk I will discuss some of my work on ceRNAs and describe my approaches to address broader regulatory interactions which may help to reinforce, or lead to the dysregulation of, miRNA activity. To investigate these dynamic regulatory interactions during EMT, I have constructed a miRNA-mediated regulatory network which integrates computationally predicted interactions with experimental evidence. By using transcriptomic data from both an EMT cell line model, as well as publicly available patient-derived tumour samples, I have prioritised candidate ceRNA relationships for experimental validation. With evidence of a regulatory effect, I propose a mechanism through which candidate ceRNAs may disrupt core regulatory motifs that control EMT and the metastatic cascade, thus contributing to our understanding of the molecular mechanisms that underpin breast cancer progression.


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