Högskolan i Skövde

his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
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.
University of Skövde, School of Bioscience. University of Skövde, Systems Biology Research Environment. Department of Physics, Chemistry and Biology, Bioinformatics, Linköping University, Linköping, Sweden. (Translationell bioinformatik, Translational bioinformatics)ORCID iD: 0000-0001-7804-1177
University of Skövde, School of Bioscience. University of Skövde, Systems Biology Research Environment. (Translationell bioinformatik, Translational bioinformatics)ORCID iD: 0000-0001-6427-0315
Department of Surgical and Perioperative Sciences, Umeå University, Umeå, Sweden.
2019 (English)In: BMC Bioinformatics, E-ISSN 1471-2105, Vol. 20, no 1, p. 1-17, article id 393Article in journal (Refereed) 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/ .

Place, publisher, year, edition, pages
BioMed Central, 2019. Vol. 20, no 1, p. 1-17, article id 393
Keywords [en]
Functional enrichment, Mature miRNA, Pancreatic cancer, TCGA, TCPA, miRNA functional analysis, miRNA target prediction
National Category
Bioinformatics and Systems Biology
Research subject
Bioinformatics; INF502 Biomarkers
Identifiers
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
Note

CC BY 4.0

Available from: 2019-07-19 Created: 2019-07-19 Last updated: 2024-01-17Bibliographically approved

Open Access in DiVA

fulltext(2256 kB)366 downloads
File information
File name FULLTEXT01.pdfFile size 2256 kBChecksum SHA-512
b89705ec3248a1ab48d2716f0f6224d6b042202b6fa11a9d9f609f436cfb058ff9e2c76de3af1c17d1925e7a8627dcfd3791139eb991d11207957e899aab3b2b
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMedScopus

Authority records

de Weerd, Hendrik ArnoldLubovac-Pilav, Zelmina

Search in DiVA

By author/editor
de Weerd, Hendrik ArnoldLubovac-Pilav, Zelmina
By organisation
School of BioscienceSystems Biology Research Environment
In the same journal
BMC Bioinformatics
Bioinformatics and Systems Biology

Search outside of DiVA

GoogleGoogle Scholar
Total: 366 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 1170 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf