Modélisation des réseaux d'interactions qui régulent la stabilité des ARN messagers et leur implication dans le cancer


Gabrielle Perron

Université McGill


Domaine : cancer

Programme Formation de doctorat

Concours 2019-2020


ONCOPOLE_Société de recherche sur le cancer

Gene expression is the process by which genetic instructions contained in a cell's deoxyribonucleic acid (DNA) is used to synthesize gene products. The cell's genes are read to produce messenger ribonucleic acid (mRNA) molecules, which carry their genetic information, in a process called transcription. Gene expression is often de-regulated in diseases such as cancer, as many genes have either increased or decreased expression compared to normal cells, leading to their abnormal behavior. However, the specific mechanisms that lead to these changes are mostly unknown. Identifying these processes would allow us to better understand the underlying mechanisms of cancer development and to develop potential therapeutic approaches to reverse it. 

Several aspects of the gene expression process can be modulated in cancer. The goal of my research project is to investigate the regulation of mRNA stability, one of the least characterized aspects of gene expression regulation in cancer. The stability of individual mRNAs determines their lifespan, which in turn determines the amount of gene products that they will be able to produce. However, the genes that have altered stability in cancer and the factors responsible for these changes are still mostly unknown. To address this question, I will systematically analyze genomics data from multiple cancer types, in order to determine which genes are regulated at the stability levels in different cancers. In addition, I will create models that can infer the specific factors responsible for the observed changes in mRNA stability, notably micro-RNAs (miRNAs). miRNAs are short RNAs which function primarily to regulate gene expression. I will also identify proteins that regulate the activity of these miRNAs. These models will allow us to better understand how gene expression is regulated and will provide new insights into the causes of gene expression changes in cancer, pointing to new therapeutic approaches.