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dc.rights.licenseAttribution 4.0 International (CC BY 4.0)
dc.creatorZhang, Fan
dc.creatorDing, Linda
dc.creatorCui, Li
dc.creatorBarber, Robert C.
dc.creatorDeng, Bin
dc.date.accessioned2022-06-29T17:06:30Z
dc.date.available2022-06-29T17:06:30Z
dc.date.issued2019-01-31
dc.identifier.citationZhang, F., Ding, L., Cui, L., Barber, R., & Deng, B. (2019). Identification of long non-coding RNA-related and -coexpressed mRNA biomarkers for hepatocellular carcinoma. BMC medical genomics, 12(Suppl 1), 25. https://doi.org/10.1186/s12920-019-0472-0
dc.identifier.issn1755-8794
dc.identifier.urihttps://hdl.handle.net/20.500.12503/31214
dc.description.abstractBackground: While changes in mRNA expression during tumorigenesis have been used widely as molecular biomarkers for the diagnosis of a number of cancers, the approach has limitations. For example, traditional methods do not consider the regulatory and positional relationship between mRNA and lncRNA. The latter has been largely shown to possess tumor suppressive or oncogenic properties. The combined analysis of mRNA and lncRNA is likely to facilitate the identification of biomarkers with higher confidence. Results: Therefore, we have developed an lncRNA-related method to identify traditional mRNA biomarkers. First we identified mRNAs that are differentially expressed in Hepatocellular Carcinoma (HCC) by comparing cancer and matched adjacent non-tumorous liver tissues. Then, we performed mRNA-lncRNA relationship and coexpression analysis and obtained 41 lncRNA-related and -coexpressed mRNA biomarkers. Next, we performed network analysis, gene ontology analysis and pathway analysis to unravel the functional roles and molecular mechanisms of these lncRNA-related and -coexpressed mRNA biomarkers. Finally, we validated the prediction and performance of the 41 lncRNA-related and -coexpressed mRNA biomarkers using Support Vector Machine model with five-fold cross-validation in an independent HCC dataset from RNA-seq. Conclusions: Our results suggested that mRNAs expression profiles coexpressed with positionally related lncRNAs can provide important insights into early diagnosis and specific targeted gene therapy of HCC.
dc.description.sponsorshipThis work was supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under grant number P20GM103449. Publication of this article was sponsored by P20GM103449 grant.
dc.publisherBioMed Central Ltd.
dc.relation.urihttps://doi.org/10.1186/s12920-019-0472-0
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceBMC Medical Genomics
dc.subjectbiomarker discovery
dc.subjecthepatocellular carcinoma
dc.subjectlong non-coding RNA
dc.subject.meshCarcinoma, Hepatocellular
dc.subject.meshGene Expression Profiling
dc.subject.meshGenetic Markers
dc.subject.meshHumans
dc.subject.meshLiver Neoplasms
dc.subject.meshRNA, Long Noncoding
dc.subject.meshRNA, Messenger
dc.titleIdentification of long non-coding RNA-related and -coexpressed mRNA biomarkers for hepatocellular carcinoma
dc.typeArticle
dc.rights.holderCopyright © The Author(s). 2019
dc.type.materialtext
dc.creator.orcid0000-0001-6857-0286 (Barber, Robert C.)
dc.identifier.volume12
dc.identifier.issueSuppl 1


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)