Dataset Information

Transfer-RNA-Derived Fragments Are Potential Prognostic Factors in Patients with Squamous Cell Carcinoma of the Head and Neck.

ABSTRACT: Transfer-RNA-derived fragments (tRFs) are a class of small non-coding RNAs that are functionally different from their parental transfer RNAs (tRNAs). tRFs can regulate gene expression by several mechanisms, and are involved in a variety of pathological processes. Here, we aimed at understanding the composition and abundance of tRFs in squamous cell carcinoma of the head and neck (SCCHN), and evaluated the potential of tRFs as prognostic markers in this cancer type. We obtained tRF expression data from The Cancer Genome Atlas (TCGA) HNSC cohort (523 patients) using MINTbase v2.0, and correlated to available TCGA clinical data. RNA-binding proteins were predicted according to the calculated Position Weight Matrix (PWM) score from the RNA-Binding Protein DataBase (RBPDB). A total of 10,158 tRFs were retrieved and a high diversity in expression levels was seen. Fifteen tRFs were found to be significantly associated with overall survival (Kaplan-Meier survival analysis, log rank test p-value < 0.01). The top prognostic marker, tRF-20-S998LO9D (p < 0.001), was further measured in tumor and tumor-free samples from 16 patients with squamous cell carcinoma of the oral tongue and 12 healthy controls, and was significantly upregulated in tumor compared to matched tumor-free tongue (p < 0.001). Results suggest that tRFs are useful prognostic markers in SCCHN.

SUBMITTER: Gu X

PROVIDER: S-EPMC7698123 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Transfer-RNA-Derived Fragments Are Potential Prognostic Factors in Patients with Squamous Cell Carcinoma of the Head and Neck.

Gu Xiaolian X Wang Lixiao L Coates Philip J PJ Boldrup Linda L Fåhraeus Robin R Wilms Torben T Sgaramella Nicola N Nylander Karin K

Genes 20201113 11

Transfer-RNA-derived fragments (tRFs) are a class of small non-coding RNAs that are functionally different from their parental transfer RNAs (tRNAs). tRFs can regulate gene expression by several mechanisms, and are involved in a variety of pathological processes. Here, we aimed at understanding the composition and abundance of tRFs in squamous cell carcinoma of the head and neck (SCCHN), and evaluated the potential of tRFs as prognostic markers in this cancer type. We obtained tRF expression dat ...[more]

PMID: 33202812

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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.

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Transfer-RNA-Derived Fragments Are Potential Prognostic Factors in Patients with Squamous Cell Carcinoma of the Head and Neck.

Publications

Transfer-RNA-Derived Fragments Are Potential Prognostic Factors in Patients with Squamous Cell Carcinoma of the Head and Neck.

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