02 September 2019 : Laboratory Research
lncRNA-D16366 Is a Potential Biomarker for Diagnosis and Prognosis of Hepatocellular Carcinoma
Yanjun Chao1CDEF, Dangjun Zhou1ABCD*DOI: 10.12659/MSM.915100
Med Sci Monit 2019; 25:6581-6586
Abstract
BACKGROUND: Long non-coding RNAs (lncRTNAs) are a new focus in cancer research. Although lncRNAs have no protein coding capacity, they are important in epigenetics as well as in regulating gene expression, playing an important role in various cancers. In the current study, we investigated the roles of lncRNA-D16366 in hepatocellular carcinoma (HCC) and expected to find a new biomarker for early detection and prognosis of the disease.
MATERIAL AND METHODS: Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression of lncRNA-D16366 in tissue and serum samples. The relationship between lncRNA-D16366 expression and clinicopathologic characteristics of patients with HCC was analyzed to estimate whether it was involved in malignancy development. Then, potential diagnostic and prognostic values were evaluated via receiver operating characteristic (ROC) curve, Kaplan-Meier and Cox regression analysis, respectively.
RESULTS: lncRNA-D16366 was proved to be decreased in the tissues and serum among patients with HCC compared with the corresponding controls. Its expression was influenced by tumor size, HbsAg, portal vein tumor thrombus, Child-Pugh score, therapies, and neoplasm metastasis. It had high diagnostic value, with an AUC of 0.752, accompanied by a sensitivity of 65.5% and a specificity of 84.6%. In addition, it was related to the prognosis of HCC.
CONCLUSIONS: lncRNA-D16366 was decreased in HCC, and might be an independent diagnostic and prognostic indicator in the disease.
Keywords: Diagnosis, Liver Neoplasms, RNA Caps, Biomarkers, Tumor, Carcinoma, Hepatocellular, Case-Control Studies, Proportional Hazards Models, ROC Curve
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