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Tian et al. Hepatoma Research 2018;4:27                          Hepatoma Research
               DOI: 10.20517/2394-5079.2018.24


               Original Article                                                              Open Access


               Expression quantitative trait loci for PVT1
               contributes to the prognosis of hepatocellular
               carcinoma


                                                          1,2
                                               1,2
                                                                         1,2
               Ting Tian 1,2# , Ci Song 1,2# , Zhe-Ning Pu , Zi-Jun Ge , Cheng-Xiao Yu , Ji-Bin Liu , Zhi-Bin Hu 1,2
                                                                                    3
               1 Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
               2 Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine,
               Nanjing Medical University, Nanjing 211166, China.
               3 Department of Hepatobiliary Surgery, Nantong Tumor Hospital, Nantong 226361, China.
               # The two authors contributed equally to this work.
               Correspondence to: Dr. Zhi-Bin Hu, Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention
               and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, School of Public Health, Nanjing Medical University,
               101 Longmian Rd., Nanjing 211166, China. E-mail: zhibin_hu@njmu.edu.cn

               How to cite this article: Tian T, Song C, Pu ZN, Ge ZJ, Yu CX, Liu JB, Hu ZB. Expression quantitative trait loci for PVT1 contributes to the
               prognosis of hepatocellular carcinoma. Hepatoma Res 2018;4:27. http://dx.doi.org/10.20517/2394-5079.2018.24
               Received: 19 Mar 2018  First Decision: 29 May 2018  Revised: 22 Jun 2018  Accepted: 22 Jun 2018  Published: 29 Jun 2018

               Science Editor: Guang-Wen Cao  Copy Editor: Jun-Yao Li  Production Editor: Huan-Liang Wu



               Abstract
               Aim: Plasmacytoma variant translocation 1 (PVT1), a long intergenic non-coding RNA, was overexpressed in liver
               cancer. A single nucleotide polymorphism (SNP) rs4733586 was identified as an expression quantitative trait
               loci (eQTL) for PVT1 using bioinformatics analysis. This study was to assess the association of PVT1 eQTL with
               hepatocellular carcinoma (HCC) prognosis.


               Methods: A case-only study was performed to assess the association between SNP and HCC overall survival in
               331 HCC patients with hepatitis B virus. Cox proportional hazard regression models were conducted for survival
               analysis with adjustment for age, gender, smoking status, drinking status, Barcelona-Clinic Liver Cancer stages,
               and chemotherapy or transcatheter hepatic arterial chemoembolization (TACE) status.

               Results: The variant genotype C allele of rs4733586 was significantly associated with a higher death risk
               compared with T allele (adjusted hazard ratio = 1.26, 95% confidence intervals = 1.05-1.51, P = 0.012 in the additive
               model). By stepwise Cox proportional hazard analysis, four variables (age, drinking status, chemotherapy or TACE
               status, PVT1 eQTL) were remained in the final regression model. In the stratified analysis, no heterogeneity was
               observed among different subgroups.


               Conclusion: These findings suggest that eQTL SNP for PVT1 may be susceptibility marker for the HCC overall
               survival.


                           © The Author(s) 2018. Open Access This article is licensed under a Creative Commons Attribution 4.0
                           International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use,
                sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long
                as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license,
                and indicate if changes were made.


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