umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
AP001056.1, A Prognosis-Related Enhancer RNA in Squamous Cell Carcinoma of the Head and Neck
Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.ORCID iD: 0000-0002-6574-3628
Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
Show others and affiliations
2019 (English)In: Cancers, ISSN 2072-6694, Vol. 11, no 3, article id 347Article in journal (Refereed) Published
Abstract [en]

A growing number of long non-coding RNAs (lncRNAs) have been linked to squamous cell carcinoma of the head and neck (SCCHN). A subclass of lncRNAs, termed enhancer RNAs (eRNAs), are derived from enhancer regions and could contribute to enhancer function. In this study, we developed an integrated data analysis approach to identify key eRNAs in SCCHN. Tissue-specific enhancer-derived RNAs and their regulated genes previously predicted using the computational pipeline PreSTIGE, were considered as putative eRNA-target pairs. The interactive web servers, TANRIC (the Atlas of Noncoding RNAs in Cancer) and cBioPortal, were used to explore the RNA levels and clinical data from the Cancer Genome Atlas (TCGA) project. Requiring that key eRNAs should show significant associations with overall survival (Kaplan-Meier log-rank test, p < 0.05) and the predicted target (correlation coefficient r > 0.4, p < 0.001), we identified five key eRNA candidates. The most significant survival-associated eRNA was AP001056.1 with ICOSLG encoding an immune checkpoint protein as its regulated target. Another 1640 genes also showed significant correlation with AP001056.1 (r > 0.4, p < 0.001), with the "immune system process" being the most significantly enriched biological process (adjusted p < 0.001). Our results suggest that AP001056.1 is a key immune-related eRNA in SCCHN with a positive impact on clinical outcome.

Place, publisher, year, edition, pages
MDPI, 2019. Vol. 11, no 3, article id 347
Keywords [en]
AP001056.1, lncRNA, enhancer, SCCHN, ICOSLG, tumor immunity
National Category
Cell and Molecular Biology Cancer and Oncology
Identifiers
URN: urn:nbn:se:umu:diva-159881DOI: 10.3390/cancers11030347ISI: 000468550200077PubMedID: 30862109OAI: oai:DiVA.org:umu-159881DiVA, id: diva2:1321919
Funder
Swedish Cancer Society, 18 05 42Swedish Cancer Society, 18 02 96Västerbotten County CouncilAvailable from: 2019-06-10 Created: 2019-06-10 Last updated: 2019-06-10Bibliographically approved

Open Access in DiVA

fulltext(2489 kB)32 downloads
File information
File name FULLTEXT01.pdfFile size 2489 kBChecksum SHA-512
3252e8481c573ba79be5d66b16cf9e42098db222571e5b307a1031b3a8635afb32b442e9aa7f79f7b9e681d73c98dac27c325c353c258352b19cb29f757dfe52
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMed

Authority records BETA

Gu, XiaolianWang, LixiaoBoldrup, LindaFåhraeus, RobinSgaramella, NicolaWilms, TorbenNylander, Karin

Search in DiVA

By author/editor
Gu, XiaolianWang, LixiaoBoldrup, LindaFåhraeus, RobinSgaramella, NicolaWilms, TorbenNylander, Karin
By organisation
PathologyOtorhinolaryngology
In the same journal
Cancers
Cell and Molecular BiologyCancer and Oncology

Search outside of DiVA

GoogleGoogle Scholar
Total: 32 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: 107 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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