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Genome-wide methylation profiling of the different stages of hepatitis B virus-related hepatocellular carcinoma development in plasma cell-free DNA reveals potential biomarkers for early detection and high-risk monitoring of hepatocellular carcinoma

BACKGROUND: An important model of hepatocellular carcinoma (HCC) that has been described in southeast Asia includes the transition from chronic hepatitis B infection (CHB) to liver cirrhosis (LC) and, finally, to HCC. The genome-wide methylation profiling of plasma cell-free DNA (cfDNA) has not prev...

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Autores principales: Zhao, Yangxing, Xue, Feng, Sun, Jinfeng, Guo, Shicheng, Zhang, Hongyu, Qiu, Bijun, Geng, Junfeng, Gu, Jun, Zhou, Xiaoyu, Wang, Wei, Zhang, Zhenfeng, Tang, Ning, He, Yinghua, Yu, Jian, Xia, Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4391300/
https://www.ncbi.nlm.nih.gov/pubmed/25859288
http://dx.doi.org/10.1186/1868-7083-6-30
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author Zhao, Yangxing
Xue, Feng
Sun, Jinfeng
Guo, Shicheng
Zhang, Hongyu
Qiu, Bijun
Geng, Junfeng
Gu, Jun
Zhou, Xiaoyu
Wang, Wei
Zhang, Zhenfeng
Tang, Ning
He, Yinghua
Yu, Jian
Xia, Qiang
author_facet Zhao, Yangxing
Xue, Feng
Sun, Jinfeng
Guo, Shicheng
Zhang, Hongyu
Qiu, Bijun
Geng, Junfeng
Gu, Jun
Zhou, Xiaoyu
Wang, Wei
Zhang, Zhenfeng
Tang, Ning
He, Yinghua
Yu, Jian
Xia, Qiang
author_sort Zhao, Yangxing
collection PubMed
description BACKGROUND: An important model of hepatocellular carcinoma (HCC) that has been described in southeast Asia includes the transition from chronic hepatitis B infection (CHB) to liver cirrhosis (LC) and, finally, to HCC. The genome-wide methylation profiling of plasma cell-free DNA (cfDNA) has not previously been used to assess HCC development. Using MethylCap-seq, we analyzed the genome-wide cfDNA methylation profiles by separately pooling healthy control (HC), CHB, LC and HCC samples and independently validating the library data for the tissue DNA and cfDNA by MSP, qMSP and Multiplex-BSP-seq. RESULTS: The dynamic features of cfDNA methylation coincided with the natural course of HCC development. Data mining revealed the presence of 240, 272 and 286 differentially methylated genes (DMGs) corresponding to the early, middle and late stages of HCC progression, respectively. The validation of the DNA and cfDNA results in independent tissues identified three DMGs, including ZNF300, SLC22A20 and SHISA7, with the potential for distinguishing between CHB and LC as well as between LC and HCC. The area under the curve (AUC) ranged from 0.65 to 0.80, and the odds ratio (OR) values ranged from 5.18 to 14.2. CONCLUSIONS: Our data revealed highly dynamic cfDNA methylation profiles in support of HBV-related HCC development. We have identified a panel of DMGs that are predictive for the early, middle and late stages of HCC development, and these are potential markers for the early detection of HCC as well as the screening of high-risk populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1868-7083-6-30) contains supplementary material, which is available to authorized users.
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spelling pubmed-43913002015-04-10 Genome-wide methylation profiling of the different stages of hepatitis B virus-related hepatocellular carcinoma development in plasma cell-free DNA reveals potential biomarkers for early detection and high-risk monitoring of hepatocellular carcinoma Zhao, Yangxing Xue, Feng Sun, Jinfeng Guo, Shicheng Zhang, Hongyu Qiu, Bijun Geng, Junfeng Gu, Jun Zhou, Xiaoyu Wang, Wei Zhang, Zhenfeng Tang, Ning He, Yinghua Yu, Jian Xia, Qiang Clin Epigenetics Research BACKGROUND: An important model of hepatocellular carcinoma (HCC) that has been described in southeast Asia includes the transition from chronic hepatitis B infection (CHB) to liver cirrhosis (LC) and, finally, to HCC. The genome-wide methylation profiling of plasma cell-free DNA (cfDNA) has not previously been used to assess HCC development. Using MethylCap-seq, we analyzed the genome-wide cfDNA methylation profiles by separately pooling healthy control (HC), CHB, LC and HCC samples and independently validating the library data for the tissue DNA and cfDNA by MSP, qMSP and Multiplex-BSP-seq. RESULTS: The dynamic features of cfDNA methylation coincided with the natural course of HCC development. Data mining revealed the presence of 240, 272 and 286 differentially methylated genes (DMGs) corresponding to the early, middle and late stages of HCC progression, respectively. The validation of the DNA and cfDNA results in independent tissues identified three DMGs, including ZNF300, SLC22A20 and SHISA7, with the potential for distinguishing between CHB and LC as well as between LC and HCC. The area under the curve (AUC) ranged from 0.65 to 0.80, and the odds ratio (OR) values ranged from 5.18 to 14.2. CONCLUSIONS: Our data revealed highly dynamic cfDNA methylation profiles in support of HBV-related HCC development. We have identified a panel of DMGs that are predictive for the early, middle and late stages of HCC development, and these are potential markers for the early detection of HCC as well as the screening of high-risk populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1868-7083-6-30) contains supplementary material, which is available to authorized users. BioMed Central 2014-12-02 /pmc/articles/PMC4391300/ /pubmed/25859288 http://dx.doi.org/10.1186/1868-7083-6-30 Text en © Zhao et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Zhao, Yangxing
Xue, Feng
Sun, Jinfeng
Guo, Shicheng
Zhang, Hongyu
Qiu, Bijun
Geng, Junfeng
Gu, Jun
Zhou, Xiaoyu
Wang, Wei
Zhang, Zhenfeng
Tang, Ning
He, Yinghua
Yu, Jian
Xia, Qiang
Genome-wide methylation profiling of the different stages of hepatitis B virus-related hepatocellular carcinoma development in plasma cell-free DNA reveals potential biomarkers for early detection and high-risk monitoring of hepatocellular carcinoma
title Genome-wide methylation profiling of the different stages of hepatitis B virus-related hepatocellular carcinoma development in plasma cell-free DNA reveals potential biomarkers for early detection and high-risk monitoring of hepatocellular carcinoma
title_full Genome-wide methylation profiling of the different stages of hepatitis B virus-related hepatocellular carcinoma development in plasma cell-free DNA reveals potential biomarkers for early detection and high-risk monitoring of hepatocellular carcinoma
title_fullStr Genome-wide methylation profiling of the different stages of hepatitis B virus-related hepatocellular carcinoma development in plasma cell-free DNA reveals potential biomarkers for early detection and high-risk monitoring of hepatocellular carcinoma
title_full_unstemmed Genome-wide methylation profiling of the different stages of hepatitis B virus-related hepatocellular carcinoma development in plasma cell-free DNA reveals potential biomarkers for early detection and high-risk monitoring of hepatocellular carcinoma
title_short Genome-wide methylation profiling of the different stages of hepatitis B virus-related hepatocellular carcinoma development in plasma cell-free DNA reveals potential biomarkers for early detection and high-risk monitoring of hepatocellular carcinoma
title_sort genome-wide methylation profiling of the different stages of hepatitis b virus-related hepatocellular carcinoma development in plasma cell-free dna reveals potential biomarkers for early detection and high-risk monitoring of hepatocellular carcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4391300/
https://www.ncbi.nlm.nih.gov/pubmed/25859288
http://dx.doi.org/10.1186/1868-7083-6-30
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