PO-194 Identification of regulatory circuits specific to breast cancer development by enrichment based circuit finder

Abstract

IntroductionGene expression mechanism is regulated by transcriptional factors (TF) in transcriptional level and by miRNAs in post-transcriptional level. Transcription of mRNAs and miRNAs are controlled by TFs and TF expressions are regulated by miRNAs. Characterisation of these regulatory mechanisms in the cell is crucial to understand the diseases like breast cancer. For this purpose we have developed an enrichment based circuit finder and applied it to breast cancer data.Material and methodsThe system developed for the detection of active regulatory circuits (miRNA-TF-gene) in breast cancer formation has two analysis lines. The first one is ’local network analysis’. This step of the system involves determining the specific dual probabilities like TF-gene or miRNA-gene. The second line of analysis is the ’global network analysis’, in which global relations are obtained from existing databases. Differentially expression (DE) analysis is implemented for mRNA and miRNA expression data. According to this analysis, differentially expressed genes and miRNAs between tumour and normal samples are listed and transferred to next step. All studies in the literature, which are related with regulatory circuits, TF, miRNA and gene lists are selected based only on DE analysis. However, this may be resulted with missing significant network nodes which is not altered significantly between the two cases like tumour and normal. For this reason, GSEA (Gene Set Enrichment Analysis) and miSEA analyses were performed in order to determine TFs and miRNAs, which are not included in DE lists but enriched in the gene/miRNA clusters.Results and discussionsAs a result 128 closed loop circuits were obtained. mir17 family, mir106b-25 cluster, mir17-92 cluster, mir106a-363 cluster members and E2Fs constituted the major part of the members in these circuits. These regulatory elements were found to take part in cancer related pathways like apoptosis, cell cycle and p53. hsa-miR-16-E2F1-VEGFA was the most prominent of the circuits identified, which was also concordant with the existing studies on breast cancer in the literature. This indicated that other circuit members in the list may also be potential biomarker candidates that are not yet associated with breast cancer.ConclusionIn summary, our tool enabled us to investigate regulatory circuits in breast cancer development and significant results were obtained. Identification of the new circuits may provide further possibility to improve our information about breast cancer development and progression.