BPG is committed to discovery and dissemination of knowledge
Articles Published Processes
4/27/2018 3:25:40 AM | Browse: 1105 | Download: 1794
 |
Received |
|
2018-03-27 09:53 |
|
Peer-Review Started |
|
2018-03-27 10:47 |
|
First Decision by Editorial Office Director |
|
2018-04-02 23:03 |
|
Return for Revision |
|
2018-04-06 09:21 |
|
Revised |
|
2018-04-10 08:12 |
 |
Publication Fee Transferred |
|
|
|
Second Decision by Editor |
|
2018-04-13 09:36 |
|
Second Decision by Editor-in-Chief |
|
|
|
Final Decision by Editorial Office Director |
|
2018-04-15 23:09 |
|
Articles in Press |
|
2018-04-15 23:09 |
|
Edit the Manuscript by Language Editor |
|
|
|
Typeset the Manuscript |
|
2018-04-25 11:13 |
|
Publish the Manuscript Online |
|
2018-04-27 03:25 |
| ISSN |
1007-9327 (print) and 2219-2840 (online) |
| Open Access |
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2018. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
|
| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
|
| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Gastroenterology & Hepatology |
| Manuscript Type |
Review |
| Article Title |
Naturally occurring hepatitis B virus reverse transcriptase mutations related to potential antiviral drug resistance and liver disease progression
|
| Manuscript Source |
Invited Manuscript |
| All Author List |
Yu-Min Choi, So-Young Lee and Bum-Joon Kim |
| ORCID |
|
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Korea Health Technology R&D Project through the Korea Health Industry Development Institute and the Ministry of Health and Welfare |
HI14C0955 |
|
| Corresponding Author |
Bum-Joon Kim, PhD, Professor, Department of Biomedical Sciense, Microbiology and Immunology, and Liver Research Institute, Seoul National University, College of Medicine, 103, Daehak-ro, Jongno-gu, Seoul 110799, South Korea. kbumjoon@snu.ac.kr |
| Key Words |
Hepatitis B virus; Polymerase; Reverse transcriptase; Preexisting mutations; Hepatocellular carcinoma |
| Core Tip |
The prevalence of preexisting reverse transcriptase (RT) mutations in treatment-naïve patients largely depends on geographic factors, HBV genotypes, HBeAg serostatus, hepatitis B virus (HBV) viral loads, disease progression, intergenotypic recombination, co-infection with HIV and the method used for detecting the mutation. Genotype-dependent polymorphic amino acid substitutions in RT may affect the emergence of drug resistance, and genotype C exhibits relatively elevated spontaneous RT mutation rates. HBeAg-negative status and low viral loads are significantly associated with a higher frequency and prevalence of HBV preexisting RT mutations. Preexisting mutations are most frequently found in the A-B interdomain of RT, mutations of which can lead to simultaneous viral immune escape. |
| Publish Date |
2018-04-27 03:25 |
| Citation |
Choi YM, Lee SY, Kim BJ. Naturally occurring hepatitis B virus reverse transcriptase mutations related to potential antiviral drug resistance and liver disease progression. World J Gastroenterol 2018; 24(16): 1708-1724 |
| URL |
http://www.wjgnet.com/1007-9327/full/v24/i16/1708.htm |
| DOI |
http://dx.doi.org/10.3748/wjg.v24.i16.1708 |
All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.
