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  • Title: Evaluating the diagnostic and prognostic value of long non-coding RNA SNHG15 in pancreatic ductal adenocarcinoma.
    Author: Guo XB, Yin HS, Wang JY.
    Journal: Eur Rev Med Pharmacol Sci; 2018 Sep; 22(18):5892-5898. PubMed ID: 30280769.
    Abstract:
    OBJECTIVE: Long non-coding RNA SNHG15 (SNHG15) has been reported to play very important roles in the malignancy behaviors of various tumors, including pancreatic ductal adenocarcinoma (PDAC). However, its clinical significance in PDAC remains largely unclear. The aim of this study was to investigate whether the aberrant expression of SNHG15 can be used as potential prognostic and diagnostic markers of human PDAC. MATERIALS AND METHODS: TaqMan Real Time-PCR was performed to investigate the expression of SNHG15 in PDAC tissues and serum samples. Receiver operator characteristic (ROC) analysis was applied to obtain the diagnostic utility of SNHG15. Association between SNHG15 levels and clinicopathological factors was analyzed. Kaplan-Meier curves and multivariate Cox proportional models were used to study the impact on clinical outcome. RESULTS: SNHG15 levels were significantly up-regulated in both sera and tumors tissues from PDAC patients. ROC curve analysis revealed that SNHG15 may be a potential biomarker for differentiating PDAC tissues from normal pancreatic tissues, and the plasma levels of SNHG15 may be a potential biomarker for differentiating PDAC patients from healthy controls. Clinicopathologic analysis revealed that high SNHG15 expression was associated with tumor differentiation (p = 0.000), lymph node metastasis (p = 0.001) and tumor stage (p = 0.005). Furthermore, patients with high SNHG15 expression had a shorter overall survival compared with the low SNHG15 expression group (p = 0.003). Also, Cox multivariate analyses confirmed that SNHG15 expression was an independent prognostic factor in PDAC (p < 0.004). CONCLUSIONS: Our study firstly indicated the potential value of SNHG15 as an important biomarker for the diagnosis and prognosis prediction of PDAC.
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