MiRFA: an automated pipeline for microRNA functional analysis with correlation support from TCGA and TCPA expression data in pancreatic cancer

Emmy Borgmästars,Hendrik Arnold De Weerd,Malin Sund,Zelmina Lubovac-Pilav

doi:10.1186/s12859-019-2974-3

Emmy Borgmästars, Hendrik Arnold De Weerd + Show 2 more

Open Access

https://doi.org/10.1186/s12859-019-2974-3

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Abstract

BackgroundMicroRNAs (miRNAs) are small RNAs that regulate gene expression at a post-transcriptional level and are emerging as potentially important biomarkers for various disease states, including pancreatic cancer. In silico-based functional analysis of miRNAs usually consists of miRNA target prediction and functional enrichment analysis of miRNA targets. Since miRNA target prediction methods generate a large number of false positive target genes, further validation to narrow down interesting candidate miRNA targets is needed. One commonly used method correlates miRNA and mRNA expression to assess the regulatory effect of a particular miRNA.The aim of this study was to build a bioinformatics pipeline in R for miRNA functional analysis including correlation analyses between miRNA expression levels and its targets on mRNA and protein expression levels available from the cancer genome atlas (TCGA) and the cancer proteome atlas (TCPA). TCGA-derived expression data of specific mature miRNA isoforms from pancreatic cancer tissue was used.ResultsFifteen circulating miRNAs with significantly altered expression levels detected in pancreatic cancer patients were queried separately in the pipeline. The pipeline generated predicted miRNA target genes, enriched gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes (KEGG) pathways. Predicted miRNA targets were evaluated by correlation analyses between each miRNA and its predicted targets. MiRNA functional analysis in combination with Kaplan-Meier survival analysis suggest that hsa-miR-885-5p could act as a tumor suppressor and should be validated as a potential prognostic biomarker in pancreatic cancer.ConclusionsOur miRNA functional analysis (miRFA) pipeline can serve as a valuable tool in biomarker discovery involving mature miRNAs associated with pancreatic cancer and could be developed to cover additional cancer types. Results for all mature miRNAs in TCGA pancreatic adenocarcinoma dataset can be studied and downloaded through a shiny web application at https://emmbor.shinyapps.io/mirfa/.

Highlights

MicroRNAs are small RNAs that regulate gene expression at a post-transcriptional level and are emerging as potentially important biomarkers for various disease states, including pancreatic cancer
The tool was built in R and to make it even more accessible to users not familiar with R, we developed a shiny web app available at https://emmbor.shinyapps.io/mirfa/, where results for all miRNAs detected in the cancer genome atlas (TCGA)-Pancreatic adenocarcinoma (PAAD) can be retrieved [17]
We implemented miRNA isoform quantification data from TCGA in order to separate between expression levels of -3p and -5p arms of mature miRNAs

Summary

Introduction

MicroRNAs (miRNAs) are small RNAs that regulate gene expression at a post-transcriptional level and are emerging as potentially important biomarkers for various disease states, including pancreatic cancer. One of the mature miRNAs, called the passenger strand, is degraded and the other strand, often referred to as guide strand, is playing a role in miRNA-mediated regulation [1]. Both strands may act in miRNA-mediated regulation. MiRNAs are generally considered down-regulators of mRNAs at a post-transcriptional level, but they can act as upregulators [2, 3]. Positive regulation seems to be restricted to certain cell conditions, for instance cells in G0 cell cycle state [2]

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