Detection of miRNA regulatory effect on triple negative breast cancer transcriptome

摘要: Identifying key microRNAs (miRNAs) contributing to the genesis and development of a particular disease is focus many recent studies. We introduce here rank-based algorithm detect miRNA regulatory activity in cancer-derived tissue samples which combines measurements gene expression levels sequence-based target predictions. The method designed modest but coordinated changes predicted genes. applied our cohort 129 tumour healthy breast tissues showed its effectiveness identifying functional miRNAs possibly involved disease. These observations have been validated using an independent publicly available cancer dataset from Cancer Genome Atlas. focused on triple negative subtype highlight potentially relevant this subtype. For those identified as potential regulators, we characterize function affected genes by enrichment analysis. In two datasets, targets are not necessarily same, display similar enriched categories, including related processes like cell substrate adherens junction, regulation migration, nuclear pore complex integrin pathway. R script implementing together with datasets used study can be downloaded (http://bioinfo-out.curie.fr/projects/targetrunningsum).