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miRFA: an automated pipeline for microRNA functional analysis with correlation support from TCGA and TCPA expression data in pancreatic cancer
Department of Surgical and Perioperative Sciences, Umeå University, Umeå, Sweden.
Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi. Department of Physics, Chemistry and Biology, Bioinformatics, Linköping University, Linköping, Sweden. (Translationell bioinformatik, Translational bioinformatics)ORCID-id: 0000-0001-7804-1177
Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi. (Translationell bioinformatik, Translational bioinformatics)ORCID-id: 0000-0001-6427-0315
Department of Surgical and Perioperative Sciences, Umeå University, Umeå, Sweden.
2019 (engelsk)Inngår i: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 20, nr 1, s. 1-17, artikkel-id 393Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

BACKGROUND: 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. 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.

RESULTS: Fifteen 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.

CONCLUSIONS: Our 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/ .

sted, utgiver, år, opplag, sider
BioMed Central, 2019. Vol. 20, nr 1, s. 1-17, artikkel-id 393
Emneord [en]
Functional enrichment, Mature miRNA, Pancreatic cancer, TCGA, TCPA, miRNA functional analysis, miRNA target prediction
HSV kategori
Forskningsprogram
Bioinformatik; INF502 Biomarkörer
Identifikatorer
URN: urn:nbn:se:his:diva-17456DOI: 10.1186/s12859-019-2974-3ISI: 000475761100001PubMedID: 31311505Scopus ID: 2-s2.0-85069159500OAI: oai:DiVA.org:his-17456DiVA, id: diva2:1338034
Tilgjengelig fra: 2019-07-19 Laget: 2019-07-19 Sist oppdatert: 2019-11-08bibliografisk kontrollert

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