19 August 2019 : Clinical Research
Decreased Expression of Long Non-Coding RNA GMDS Divergent Transcript (GMDS-DT) is a Potential Biomarker for Poor Prognosis of Hepatocellular CarcinomaDuo Wang1BCE, Xiufang Du2BCD, Tao Bai3BD, Miao Chen1BD, Jie Chen3BDF, Junjie Liu1BF, Lequn Li3BF, Hang Li1AG*, Chunyan Zhang2AG
Med Sci Monit 2019; 25:6221-6229
BACKGROUND: Increasing evidence suggests that long non-coding RNA (lncRNA) is closely related to the development of cancer. The present study investigated the potential predictive value of lncRNA GMDS divergent transcript (GMDS-DT) in the prognosis of patients with hepatocellular carcinoma (HCC) after hepatectomy.
MATERIAL AND METHODS: GMDS-DT was acquired by microarray data in 3 pairs of M1 and M2 macrophage duplicate samples. Real-time polymerase chain reaction (PCR) was performed to evaluate expression levels of GMDS-DT in liver cancer relative to normal tissue of 198 patients. The significance of GMDS-DT in prognosis after hepatectomy was examined via Kaplan-Meier test and Cox regression analysis.
RESULTS: The expression of GMDS-DT in liver cancer tissue was significantly lower than that in adjacent normal liver tissue (P<0.001), and was significantly associated with drinking history and metastasis (both P<0.05). The Kaplan-Meier test suggested that patients with lower expression levels of GMDS-DT in liver cancer tissue had significantly shorter disease-free survival and overall survival times after hepatectomy (P=0.028 and P=0.003, respectively). Cox regression analysis further indicated that GMDS-DT was an independent risk factor for disease-free survival and overall survival times of patients after hepatectomy (P=0.015 and P=0.001, respectively).
CONCLUSIONS: LncRNA GMDS-DT might be a potential biomarker for the prognosis of patients with liver cancer after hepatectomy.
Keywords: Carcinoma, Hepatocellular, Prognosis, RNA, Long Noncoding, Adult, Aged, Biomarkers, Tumor, Disease-Free Survival, Gene Expression Regulation, Neoplastic, Kaplan-Meier Estimate, Liver Neoplasms, Middle Aged, Proportional Hazards Models, Real-Time Polymerase Chain Reaction, Risk Factors, transcriptome
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