Background: MicroRNA (miRNA) mediate post-transcriptional gene repression and are involved in a variety of human diseases, including cancer. Soft tissue sarcomas are rare malignancies with a variety of histological subtypes which may occur virtually anywhere in the human body. Leiomyosarcoma is one of the most common subtypes, shows a smooth muscle phenotype and its cancerogenesis is still unclear. The aim of our study was to investigate the potential role of miRNA differential expression in leiomyosarcoma development.
Methods: We first employed the Sarcoma microRNA Expression Database, a repository that describes the patterns of over 1000 miRNA expression in various human sarcoma types, to identify differentially expressed miRNA comparing leiomyosarcoma and smooth muscle samples. Subsequently, we identified putative target genes of those miRNAs with the TargetScan prediction tool. Finally, we evaluated whether the retrieved pool of putative targets was enriched in genes belonging to specific molecular pathways by means of the Enrichr analysis tool. Protein-protein network analysis was analyzed by means of the STRING web tool.
Results: Out of 1120 miRNAs tested, the expression of 301 miRNAs was statistically significantly different between leiomyosarcoma and smooth muscle samples. The hypothetical targets could be predicted for 172 miRNAs. 438 genes were predicted to be the targets with high confidence (cumulative weighted context score cut-off level less than - 1.0) and analyzed for belonging to specific molecular pathways. Pathway analysis suggested that RNA Polymerase III, tRNA functions and synaptic neurotransmission (with special regard to dopamine mediated signaling) could be involved in leiomyosarcoma development.
Conclusions: Our results demonstrate that data mining of publicly available repositories can be useful to suggest molecular pathways underlying the pathogenesis of rare tumors such as leiomyosarcoma.
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| http://dx.doi.org/10.1186/s12967-019-1907-2 | DOI Listing |
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