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Christophe Le Priol

MicroRNAs and messenger RNAs expression variance in cancer

Published on 19 September 2019
Thesis presented September 19, 2019

The majority of gene expression studies focus on looking for genes whose mean expression is different when comparing two or more populations of samples. In this context, the variance is treated as a parameter to be controlled. However, similarly to a difference of mean, a difference of variance in gene expression between sample populations may also be biologically and physiologically relevant.
MicroRNAs (miRNAs) are key gene expression regulators. The large number of their targets and the fine tuning of their regulation confer to miRNAs a buffering role. The objective of my thesis is to study the variance in expression of miRNAs and messenger RNAs (mRNAs), especially those targeted by miRNAs, in particular during cancerogenesis. We hope that this approach can identify genes which cannot be identified by the traditional differential expression analysis and yet serve as potential biomarkers or therapeutic targets. Furthermore, by combining both miRNA and mRNA expression and analyzing their variance at a system level, we aim at better characterize the buffering role of miRNAs.
Several methods including statistical tests of equality of variance and models based on the negative binomial distribution were evaluated. The performances of these methods were thoroughly tested on simulated datasets. Then, they were applied to The Cancer Genome Atlas datasets in order to identify genes with a differential expression variance when comparing normal and tumor samples. Many miRNAs and mRNAs with an increase of expression variance in tumors were detected. Interestingly, among these mRNAs, some key biological functions such as catabolism or autophagy are over-represented in most cancers. Thus, analyzing genes having a differential expression variance is relevant to gain knowledge in tumor progression and opens a new space for the discovery of new potential biomarkers and therapeutic avenues.

RNA-seq, variance, cancer, miRNA

On-line thesis.