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25 May 2019 : Clinical Research  

Clinical Significance of TRMT6 in Hepatocellular Carcinoma: A Bioinformatics-Based Study

Yang Wang1BCDE, Qiao Huang2CD, Tong Deng1BF, Bing-Hui Li1BC, Xue-Qun Ren1AE*

DOI: 10.12659/MSM.913556

Med Sci Monit 2019; 25:3894-3901


BACKGROUND: The purpose of this study was to investigate the correlation between TRMT6 mRNA expression levels and clinicopathological features in primary HCC patients and to evaluate their prognostic value.

MATERIAL AND METHODS: The clinical information and the mRNA sequencing data of the patients with primary hepatocellular carcinoma (HCC) were extracted from The Cancer Genome Atlas (TCGA) Liver Cancer database. The correlation between the clinicopathological features and the expression of TRMT6 was analyzed by t test and chi-square test. The overall survival (OS) and recurrence-free survival (RFS) were estimated using the Kaplan-Meier method and Cox regression models. Gene set enrichment analysis (GSEA) was used to explore the potential mechanisms of TRMT6 dysregulation in primary HCC patients.

RESULTS: Compared to normal tissues, TRMT6 was significantly upregulated in primary HCC tissues. Kaplan-Meier survival curves revealed that higher TRMT6 expression was associated with reduced RFS (p=0.0146) and OS (p=0.0224) in HCC patients. Moreover, multivariable Cox regression analysis indicated that TRMT6 upregulation independently predicted poor RFS (HR: 1.871, 95% CI: 1.204, 2.905, p=0.005) and OS (HR: 2.176, 95% CI: 1.234, 3.836, p=0.007). Gene Set Enrichment Analysis (GSEA) indicated that primary HCC samples in the TRMT6 high expression group were enriched for the G2M checkpoint, spermatogenesis, and MYC target genes.

CONCLUSIONS: TRMT6 was upregulated in HCC tissues, and higher TRMT6 expression levels was correlated with reduced OS and RFS in patients with primary HCC. TRMT6 might be a promising prognostic biomarker for poor clinical outcomes in primary HCC patients.

Keywords: Carcinoma, Hepatocellular, Prognosis, tRNA Methyltransferases, Aged, Biomarkers, Tumor, Cohort Studies, Computational Biology, Disease-Free Survival, Kaplan-Meier Estimate, Liver Neoplasms, Membrane Proteins, Middle Aged, Proportional Hazards Models, RNA, Messenger, transcriptome

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Editorial: Infectious Disease Surveillance Using Artificial Intelligence (AI) and its Role in Epidemic and Pandemic Preparedness

Dinah V. Parums
Science Editor, Medical Science Monitor, International Scientific Information, Inc., Melville, NY, USA

DOI: 10.12659/MSM.941209

Med Sci Monit 2023; 29:e941209


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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750