Integrated microRNA-mRNA analysis revealing the potential roles of microRNAs in tongue squamous cell cancer

Zhou,Xiao‑Li; Wu,Jun‑Hua; Wang,Xin‑Juan; Guo,Fu‑Jun

doi:10.3892/mmr.2015.3467

Integrated microRNA-mRNA analysis revealing the potential roles of microRNAs in tongue squamous cell cancer

Authors:
- Xiao‑Li Zhou
- Jun‑Hua Wu
- Xin‑Juan Wang
- Fu‑Jun Guo
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Affiliations: Department of Stomatology, The First Affiliated Hospital of Henan University of Science and Technology, Luoyang, Henan 471003, P.R. China, Department of Prosthodontics, School of Stomatology, Tongji University, Shanghai 200072, P.R. China
Published online on: March 11, 2015 https://doi.org/10.3892/mmr.2015.3467
Pages: 885-894
Copyright: © Zhou et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY_NC 3.0].

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Abstract

Tongue squamous cell carcinoma (TSCC) is a rare and aggressive type of cancer, which is associated with a poor prognosis. Identification of patients at high risk of TSCC tumorigenesis may provide information for the early detection of metastases, and for potential treatment strategies. MicroRNA (miRNA; miR) and mRNA expression profiling of TSCC tissue samples and normal control tissue samples were obtained from three Gene Expression Omnibus (GEO) data series. Bioinformatics analyses, including the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes were used to identify genes and pathways specifically associated with miRNA‑associated TSCC oncology. A total of 25 miRNAs and 769 mRNAs were differentially expressed in the two groups assessed, and all the differentially expressed miRNA and mRNA target interactions were analyzed. The miRNA target genes were predominantly associated with 38 GO terms and 13 pathways. Of the genes differentially expressed between the two groups, and confirmed in another GEO series, miRNA‑494, miRNA‑96, miRNA‑183, runt‑related transcription factor 1, programmed cell death protein 4 and membrane‑associated guanylate kinase were the most significantly altered, and may be central in the regulation of TSCC. Bioinformatics may be used to analyze large quantities of data in microarrays through rigorous experimental planning, statistical analysis and the collection of complete data on TSCC. In the present study, a novel differential miRNA‑mRNA expression network was constructed, and further investigation may provide novel targets for the diagnosis of TSCC.

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