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Identification and validation a TGF-?-associated long non-coding RNA of head and neck squamous cell carcinoma by bioinformatics method.

ABSTRACT: BACKGROUND:The role of transforming growth factor? (TGF-?)-induced tumor progression in advanced malignancy is well established, but the involvement of long non-coding RNAs (lncRNAs) in TGF-? signaling remains unclear. This study aimed to identify TGF-?-associated lncRNAs in head and neck squamous cell carcinoma (HNSCC). METHODS:Expression profiling of lncRNAs was obtained using Gene Expression Omnibus and The Cancer Genome Atlas. Real-time quantitative PCR was used to analyze the expression of EPB41L4A-AS2 in HNSCC cell line. We used bioinformatics resources (DAvID) to conduct Gene Ontology biological processes and KEGG pathways at the significant level. Wound healing assay, cell migration and invasion assays, were used to examine the effects of EPB41L4A-AS2 on tumor cell metastasis in vivo. Protein levels of EPB41L4A-AS2 targets were determined by western blot. RESULTS:A novel TGF-?-associated lncRNA, EPB41L4A-AS2, was found downregulated by TGF-? and associated with invasion and metastasis. The relationship of EPB41L4A-AS2 with the clinicopathological features and prognosis of HNSCC patients was evaluated. Bioinformatic analyses revealed that EPB41L4A-AS2 may be involved in processes associated with the tumor-associated signaling pathway, especially the TGF-? signaling pathway. Furthermore, a TGF-?-induced epithelial-to-mesenchymal transition (EMT) model was established. Low EPB41L4A-AS2 expression was determined, and overexpression of this gene inhibited cell migration and invasion in the EMT model. Moreover, EPB41L4A-AS2 suppressed TGFBR1 expression. CONCLUSIONS:EPB41L4A-AS2 might serve as a negative regulator of TGF-? signaling and as an effective prognostic biomarker and important target in anti-metastasis therapies of HNSCC patients.

SUBMITTER: Huang T

PROVIDER: S-EPMC5831574 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Identification and validation a TGF-β-associated long non-coding RNA of head and neck squamous cell carcinoma by bioinformatics method.

Huang Teng T Huang Wei W Lu Hong H Zhang Bi-Yun BY Ma Jun J Zhao Di D Wang Yi-Jun YJ Yu Da-Hai DH He Xia X

Journal of translational medicine 20180228 1

<h4>Background</h4>The role of transforming growth factorβ (TGF-β)-induced tumor progression in advanced malignancy is well established, but the involvement of long non-coding RNAs (lncRNAs) in TGF-β signaling remains unclear. This study aimed to identify TGF-β-associated lncRNAs in head and neck squamous cell carcinoma (HNSCC).<h4>Methods</h4>Expression profiling of lncRNAs was obtained using Gene Expression Omnibus and The Cancer Genome Atlas. Real-time quantitative PCR was used to analyze the ...[more]

PMID: 29490660

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Project description:BackgroundThis study aimed to develop multi-RNA-based models using a competing endogenous RNA (ceRNA) regulatory network to provide survival risk prediction in head and neck squamous cell carcinoma (HNSCC).MethodsAll long non-coding RNA (lncRNA), microRNA (miRNA), and mRNA expression data and clinicopathological features related to HNSCC were derived from The Cancer Genome Atlas. Differentially expressed RNAs were calculated using R. Prognostic factors were identified using univariate Cox regression analysis. Functional analysis was performed using GO, KEGG pathways, and PPI network. Based on the results, we derived a risk signature and compared high- and low-risk subgroups using LASSO regression analysis. Survival analysis and the relationship between risk signature and clinicopathological features were performed using log-rank tests and Cox regression analysis. A ceRNA regulatory network was constructed, and prognostic lncRNAs and miRNA expression levels were validated in vitro and in vivo.ResultsA list of 207 lncRNAs, 18 miRNAs and 362 mRNAs related to overall survival was established. Five lncRNAs (HOTTIP, LINC00460, RMST, SFTA1P, and TM4SF19-AS1), one miRNA (hsa-miR-206), and one mRNA (STC2) were used to construct the ceRNA network. Three prognostic models contained 13 lncRNAs, eight miRNAs, and 17 mRNAs, which correlated with the patient status, disease-free survival (DFS), stage, grade, T stage, N stage, TP53 mutation status, angiolymphatic invasion, HPV status, and extracapsular spread. KEGG pathway analysis revealed significant enrichment of "Transcriptional misregulation in cancer" and "Neuroactive ligand-receptor interaction." In addition, HOTTIP, LINC00460, miR-206 and STC2 were validated in GTEx data, GEO microarrays and six HNSCC cell lines.ConclusionsOur findings clarify the interaction of ceRNA regulatory networks and crucial clinicopathological features. These results show that prognostic biomarkers can be identified by constructing multi-RNA-based prognostic models, which can be used for survival risk prediction in patients with HNSCC.

Dataset Information

Identification and validation a TGF-?-associated long non-coding RNA of head and neck squamous cell carcinoma by bioinformatics method.

Publications

Identification and validation a TGF-β-associated long non-coding RNA of head and neck squamous cell carcinoma by bioinformatics method.

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