Novel HBV mutations and their value in predicting efficacy of conventional interferon
 
Da-Xian Wu, Xiao-Yu Fu, Guo-Zhong Gong, Ke-Wei Sun, Huan-Yu Gong, Ling Wang, Juan Wu and De-Ming Tan
Changsha, China
 
Author Affiliations: Department of Infectious Diseases, Xiangya Hospital, Central South University, Key Laboratory of Viral Hepatitis of Hunan Province (Wu DX, Fu XY, Wang L, Wu J and Tan DM); Department of Infectious Diseases, The Second Xiangya Hospital, Central South University (Gong GZ); Department of Infectious Diseases, The First Affiliated Hospital, Hunan University of Chinese Medicine (Sun KW); Department of Infectious Diseases, The Third Xiangya Hospital, Central South University (Gong HY), Changsha, China
Corresponding Author: De-Ming Tan, MD, Department of Infectious Diseases, Xiangya Hospital, Central South University, Key Laboratory of Viral Hepatitis of Hunan Province, Xiangya Road 87, Changsha 410008, China (Fax: +86-731-84327252; Email: dmt3008@163.com)
 
© 2017, Hepatobiliary Pancreat Dis Int. All rights reserved.
doi: 10.1016/S1499-3872(16)60184-4
Published online February 24, 2017.
 
 
Contributors: GGZ, SKW, GHY and TDM conceived and designed the research. FXY and WL carried out sample collation, quality control and interpretation of the experiment. WJ was responsible for genotyping and sequencing for the study. WDX contributed to data analysis and drafted the article. TDM is the guarantor.
Funding: This study was supported by a grant from National Novel Drug Development plan (2011ZX09101-008-05).
Ethical approval: The study protocol was approved by the Ethics Committee of the Xiangya Hospital, Central South University.
Competing interest: No benefits in any form have been received or will be received from a commercial party related directly or indirectly to the subject of this article.
 
 
BACKGROUND: Accumulating studies assessing the impacts of hot spot mutations on conventional interferon (IFN) efficacy come to discrepant conclusions; studies regarding the mutations in S and RT regions are also unclear. The present study aimed to evaluate the impacts of HBV mutations on the efficacy of conventional IFN.
 
METHODS: A total of 126 patients who received conventional IFN treatment for 48 weeks were enrolled. Biochemical and serological parameters were routinely tested. The sequences of HBV from 78 serum samples were amplified by nested-PCR; mutations were identified with sequence scanner V1.0 after ABI 3730xl direct sequencing, HBV genotypes were determined according to RT gene sequences utilizing NCBI Genotyping Tool which was based on phylogenetic analysis.
 
RESULTS: The baseline DNA levels of virological response (VR) group were significantly lower than those of no VR group [7.13±0.76 vs 7.69±0.56 lg (copies/mL), P=0.001]. The baseline ALT levels were significantly higher in the HBeAg clearance group (204.72±88.65 vs 162.80±85.81 IU/L, P<0.05) and HBeAg seroconversion group (204.89±95.68 vs 166.75±84.43 IU/L, P<0.05). Females and lower BMI levels (20.01±2.33 vs 21.65±3.66 kg/m2, P<0.05) were prone to acquired biochemical response (BR). PC-W28STOP (ntG1896A) was significantly higher in the combined response (CR) group than that in the no CR group (91.7% vs 39.7%, P=0.001). Multivariate logistic regression analysis showed that baseline DNA, PC-P159T (ntC2288A), BCP-N118T (ntA1726C) and BCP-L134L (ntA1775C/G/T) influenced VR independently. PC-G182C (ntG2357T), PC-S64A/T (ntT2003G/A) and BMI were independent influence factors for HBeAg clearance, HBeAg seroconversion and BR, respectively. The new predicting model concluded that baseline DNA and new mutations for VR were established successfully, and ROC analysis showed that AUC was 0.842 (P<0.001) with a sensitivity of 0.652 and a specificity of 0.933.
 
CONCLUSIONS: PC-P159T (ntC2288A), BCP-N118T (ntA1726C), BCP-L134L (ntA1775C/G/T), PC-G182C (ntG2357T) and PC-S64A/T (ntT2003G/A) were novel identified mutations that impacted IFN therapeutic efficacy. These novel mutations could serve as important predictors before conventional IFN treatment.
 
(Hepatobiliary Pancreat Dis Int 2017;16:189-196)
 
KEY WORDS: hepatitis B virus; interferon; mutation; treatment efficacy
 
 
Introduction
Approximately one third of the world’s population has serological evidence of past or present hepatitis B virus (HBV) infection; 350-400 million people are chronic HBV surface antigen (HBsAg) carriers.[1] In China, there are approximately 93 million people with HBV infection and 20 million chronic hepatitis B (CHB) patients.[2] It has been reported that HBV-related end-stage liver diseases or hepatocellular carcinoma (HCC) were responsible for 200-300 thousand deaths per year[3] and 5%-10% of liver transplants.[4] Robust evidences suggest that in patients with untreated CHB, the 5-year cumulative incidence of developing cirrhosis ranges from 8%-20% and the 5-year cumulative incidence of hepatic decompensation is approximately 20%.[5] Therefore, the effective treatment for CHB is an immediate healthcare concern to relieve the public health burden.
 
Interferon (IFN) is one of the two types of antiviral drugs based on mechanism of action against HBV, although its response rate is lower than the nucleos(t)ide analogue (NUC), only 20%-30% of HBV e antigen (HBeAg) positive cases and 20%-40% of HBeAg negative cases respond well to IFN treatment. Furthermore, this treatment may result in several adverse reactions and poor tolerance in patients.[6] Comparing with NUC, however, IFN therapy does offer defined treatment duration and has been shown to be more effective in terms of sustained off-therapy HBV e antibody (HBeAb) seroconversion, HBsAg loss, and seroconversion to HBV surface antibody (HBsAb).[7] Based on these data, the up-to-date guideline for the prevention and treatment of CHB drafted by the National Institute for Health and Care Excellence (NICE) regards pegylated interferon (Peg-IFN) as the first-line treatment agent.[8] IFN-based therapy is preferred in patients with compensated liver diseases, particularly in young patients, females, and children.[9] Conventional IFN, the first approved cytokine with antiviral, antiproliferative, and immunomodulatory effects,[10] remains a benchmark therapy for CHB although it has been gradually replaced by Peg-IFN, especially for population in developing countries. In this case, discriminating patients who respond well to conventional IFN from common candidates is crucially important to enhance efficacy of conventional IFN.
 
It is widely accepted that hot spot mutations in basal core promoter (BCP) or precore (PC) region play important roles in antiviral therapy responses of patients treated with IFN.[11, 12] However, studies on the roles of those hot spot mutations are inconclusive, studies regarding to the mutations in surface (S) and reverse transcriptase (RT) regions are also unclear. A comprehensive evaluation of HBV mutations with whole gene sequencing is required. This study aimed to evaluate the impacts of baseline HBV gene mutations on the efficacy of conventional IFN in HBeAg positive patients with whole gene sequencing.
 
 
Methods
Patients
A total of 126 CHB patients, who had completed conventional IFN therapy for 48 weeks, were recruited from four hospitals in Hunan Province of China from 2010 to 2011. The CHB diagnosis was based on published guidelines.[13] The inclusion criteria are 18-65 years old, HBsAg positive for at least 6 months, HBeAg positive, and HBeAb negative, HBV DNA >1×105 copies/mL and alanine aminotransferase (ALT) 2-10 upper limit of normal (ULN). Patients who had received previous IFN treatment within 1 year, or NUC at any time were excluded. Additional exclusion criteria included patients with other forms of liver diseases which had evidences of hepatic decompensation, pancreatitis, HCC or coinfection with hepatitis C, hepatitis D, or the human immunodeficiency virus (HIV). Present study was conducted in compliance with the ethics principles of the Declaration of Helsinki as well as the Good Clinical Practice of China. The study protocol was approved by the Ethics Committee of the Xiangya Hospital, Central South University. Written informed consent was obtained from every screened patient.
 
Detection of HBV serological and biochemical markers
ALT was routinely tested at the Central Clinical Laboratory of Xiangya Hospital. HBV DNA, HBsAg, and HBeAg were routinely tested at the Key Laboratory of Viral Hepatitis of Hunan Province. HBV DNA detection kit was commercially available from Hunan Sansure Biotechnology Company (Changsha, China), the lower limit of HBV DNA detection was 10 copies/mL. The linearity range was 50-5×108 copies/mL. HBsAg and HBeAg levels were quantified by ARCHITECT i2000SR (Abbott, Chicago, USA).
 
Genotyping and detection of HBV gene mutations
HBV DNA was extracted from 200 µL of serum utilizing TIANamp Virus DNA Kit (QIAGEN, Shanghai, China) according to the manufacturer’s protocol. To amplify the RT region, the first round PCR was carried out with primers RT-1S (5’-TCT AGA CTC GTG GTG GAC TTC TCT TC-3’) and RT-1A (5’-AGT TCC GCA GTA TGG ATC GG-3’) as previously described by Hamidi-Fard et al.[14] PCR conditions were as follows: 94 �� for 5 min, 30 cycles of 94 �� for 30 s, 68 �� for 40 s, and 72 �� for 60 s, and finally 72 �� for 5 min; the second round PCR was performed with RT-2S (5’-TGG ACT TCT CTC AAT TTT CT-3’) and RT-2A (5’-TGA CAG ACT TTC CAA TCA AT-3’), PCR reactions were carried out as previously described by Han et al.[15] To amplify the S region, the first round PCR reaction used primers S-1S (5’-CCT GCT GGT GGC TCC AGT TCA-3’) and S-1A (5’-AAA GCC CAA AAG ACC CAC AAT-3’), reaction parameters were as previously described.[16] The second round of PCR was carried out with primers S-2S (5’-GGA CCC TGT ACC GAA CAT G-3’) and S-2A (5’-GTT CCT GTG GCA ATG TGC C-3’), parameters were the same as used in the first round. The amplification of the BCP/PC region was executed by two couple of nested PCR primers,[17] the primers were BCP-1S (5’-GAC GTC CTT TGT YTA CGT CC-3’) and BCP-1A (5’-TCT GCG ACG CGG CGA TTG AG-3’) for the first round and BCP-2S (5’-ACT TCG CTT CAC CTC TGC AC-3’) and BCP-2A (5’-ATC CAC ACT CCA AAA GAY ACC-3’) for the second round. The first round parameters were: 94 �� for 3 min, followed by 40 cycles of 94 �� for 35 s, 56 �� for 35 s, and 72 �� for 70 s, with a final extension at 72 �� for 5 min. The second round PCR was performed as described by Xu et al.[17] The nucleotide numbers of primers and the sizes of amplified products were shown in Table 1. PCR was performed in 50 µL and 25 µL of reaction volumes for the first and second rounds, respectively. The reaction mixture consisted of 1×PCR buffer (50 mmol/L KCl, 10 mmol/L Tris HCl, 1.5 mmol/L MgCl2), 200 µmol/L of each of the dNTPs, 0.05 U/µL rTaq enzyme (TaKaRa, Dalian, China), and 0.2 µmol/L of each of the primers. Second round PCR products were directly sequenced using the Big Dye Terminator Cycle Sequencing Kit V3.0 on an ABI 3730xl sequencing machine (Life Technologies, Foster City, USA). The sequences obtained with the 3730xl sequencer were analyzed and aligned using sequence scanner V1.0 (Life Technologies, USA). After the alignment, the nucleotide with the highest frequency at each site in the HBV RT/S/BCP/PC region was termed as the wild type nucleotide. Nucleotide substitutions with the other three nucleotides at each site were termed as mutations. The HBV genotype was determined based on a comparison of RT gene sequences from second round PCR products with the NCBI sequences data library (http://www.ncbi.nlm.nih.gov/projects/genotyping/formpage.cgi). In total of 126 patients, 78 serum samples were available for sequencing and genotyping.
 
The evaluation of therapeutic effects
Treatment effects were evaluated with virological response (VR), HBsAg loss, HBeAg clearance, HBeAg seroconversion, biochemical response (BR), and combined response (CR) in patients. Here, VR was defined as HBV DNA levels below 2000 IU/mL (10 000 copies/mL); HBsAg loss and HBeAg clearance were defined as that HBsAg and HBeAg were immeasurable respectively; HBeAg seroconversion was defined as HBeAg clearance and seroconversion to HBeAb; BR was defined as normalization of serum ALT levels; CR was defined as the presence of VR, HBeAg clearance, and BR. All of these therapeutic indices were determined before treatment and at the end of follow-up.
 
Statistical analysis
The SPSS 18.0 was used to perform statistical analysis. Categorical data were evaluated using the Chi-square test or the Fisher’s exact test. Continuous variables were analyzed using the Student’s t test or nonparametric Wilcoxon signed-ranked test. Multivariate analysis with logistic regression was used to determine independent factors. Receiver operating characteristics (ROC) curve analysis was used as appropriate. A P value of <0.05 was considered statistically significant. All tests were two-tailed.
 
 
Results
Therapeutic responses to conventional IFN in HBeAg positive patients
Of the 126 CHB patients who completed the treatment, 49 (38.9%) obtained VR, 41 (32.5%) achieved HBeAg clearance, and 32 (25.4%), 56 (44.4%), 30 (23.8%) achieved HBeAg seroconversion, BR and CR, respectively. However, only 2 (1.6%) patients converted to HBsAg negative.
 
The impacts of baseline clinical characteristics on the efficacy of conventional IFN treatment
Baseline DNA levels in the VR group were significantly lower than those in the no VR group [7.13±0.76 vs 7.69±0.56 lg (copies/mL), P=0.001]. Baseline ALT levels were significantly higher in the HBeAg clearance group (204.72±88.65 vs 162.80±85.81 IU/L, P=0.012) and HBeAg seroconversion group (204.89±95.68 vs 166.75±84.43 IU/L, P=0.035). Females (P=0.032) and individuals with lower BMI levels (20.01±2.33 vs 21.65±3.66 kg/m2, P=0.003) were prone to BR. Finally, no clinical characteristics associated with CR were found (Table 2).
 
The prevalence of baseline HBV mutations
Out of 78 serum samples, 70 could be amplified to obtain PC sequences, the mutations of BCP region were successfully analyzed in 73 cases, and the mutations of 74 cases were available in RT and S region. A complete depiction of HBV mutations frequency is shown in Table 3.
 
The impacts of HBV mutations on the efficacy of IFN treatment
Present study found that the frequencies of PC-P159T (ntC2288A), BCP-V116V (ntG1721A), BCP-N118T (ntA1726C) and BCP-L134L (ntA1775C/G/T) mutations were significantly higher in the VR group than those in the no VR group. Furthermore, this research identified a higher occurrence of mutations in BCP region of the VR group than that in the no VR group. The frequency of the PC-G182C (ntG2357T) mutation was significantly higher in the HBeAg clearance group than in the HBeAg persistent group. The occurrence of the PC-S64A/T (ntT2003G/A) mutation was significantly higher in the HBeAg seroconversion group than that in the HBeAg persistent group. Finally, the PC-W28STOP (ntG1896A) mutation was significantly higher in the CR group than that in the no CR group. No mutations were found to be statistically over represented in the BR group compared to the no BR group. There were no mutations in the RT and S regions associated with any of the measured responses (Table 3).
 
The independent impact factors for different responses
The impact factors on therapeutic response were listed in Table 2 and 3. Multivariate logistic regression analysis showed that baseline DNA, PC-P159T (ntC2288A), BCP-N118T (ntA1726C) and BCP-L134L (ntA1775C/G/T) mutations influenced VR independently. Furthermore, PC-G182C (ntG2357T), PC-S64A/T (ntT2003G/A) and BMI were independent indicators for HBeAg clearance, HBeAg seroconversion and BR, respectively (Table 4).
 
The new predicting model for VR
In order to evaluate the predictive value of independent influence factors for VR, a new predictive model was established with logistic regression analysis (Y=3.858-0.999×Baseline DNA+2.494×PC-P159T+2.360×BCP-N118T+3.934×BCP-L134L). The area under ROC curve (AUC) of this model was 0.842 (95% CI: 0.734-0.950) with a sensitivity of 0.652 and a specificity of 0.933 at the cut-off point of -0.3572 (Table 5 and Fig.).
 
 
Discussion
There are currently two different types of drugs in CHB treatment, conventional IFN or Peg-IFN and NUC.[1, 18] IFN based therapy is superior to NUC treatment because INF achieves either HBsAg loss or sustained off-therapy response.[19] However, only a small proportion of patients achieve durable response after IFN therapy.[20] The limited efficacy of IFN indicates the need of development of new predictors.
 
This research firstly observed the therapeutic efficacy of conventional IFN for 48 weeks, and the results were similar to the previous studies.[21, 22] Secondly, the present study also evaluated the influences of baseline clinical characteristics on therapeutic effects of IFN, lower viral load was associated with VR and relatively high baseline ALT levels were found to be predictive of HBeAg clearance and HBeAg seroconversion. These results also agreed with the previous researches.[21, 23] However, the influence of age, gender and genotype to IFN effects was not noticed, which was different from previous studies.[6,24] Possible reasons for this discrepancy may include: first, patients enrolled in this study were young and their age range was relatively narrow; second, only B and C genotypes were determined in the present study, and 78.2% (61/78) patients were type B, the predictive role of genotype may be influenced by its unbalanced distribution to some extent.
 
Furthermore, our research indicated that the most frequent mutation in the PC region is PC-P34T (ntC1913A) and in the BCP region, BCP-K118N/D119E/F142L (ntA1727T/ntC1730G/ntC1799G) triple mutations, which were inconsistent with other studies.[25-27] It was previously reported that the PC-W28STOP (ntG1896A) mutation was associated with HBeAg and HBsAg seroconversion,[28, 29] and was independently associated with CHB survival rates.[30, 31] This study also identified that the PC-W28STOP (ntG1896A) mutation was a predictive marker of CR. Moreover, some novel mutations that impacted IFN efficacy were also identified. Mutations PC-P159T (ntC2288A), BCP-N118T (ntA1726C), and BCP-L134L (ntA1775C/G/T) were shown to be independent influence factors for VR. The frequency of PC-G182C (ntG2357T) mutant was significantly higher in the HBeAg clearance group. In the HBeAg seroconversion group, PC-S64A/T (nt2003G/A) was significantly higher.
 
Interestingly, although baseline clinical characteristics and HBV mutations influence HBeAg clearance, HBeAg seroconversion in univariate analysis, multivariate logistic regression analysis showed that only some HBV mutations were independent influence factors for the above responses. What is more, the new model concluded that the baseline DNA and new mutations could predict VR and therefore, HBV mutations detection before treatment is especially important for the decision making for CHB patients.
 
What is noteworthy is that the BCP-L134L (ntA1775C/G/T) mutation, with a base substitution from A to C/G/T, does not lead an amino acid change; however it plays an important role in VR. It has been shown the BCP contains major nuclear binding sites which are recognized by various nuclear receptors super families. These include the hepatocyte nuclear factor 4 (HNF4), the peroxisome proliferator-activated receptor α-retinoid X receptor α (PPARα-RXRα) heterodimer, and a variety of transcription factors, such as CCAAT/enhancer binding protein (C/EBP), which regulates the transcription of precore RNA and core RNA.[32] Therefore, a base substitution may alter the binding affinity of gene to nuclear receptors or the activity of transcription, then influence the replication of HBV, those may explain why BCP-L134L (ntA1775C/G/T) influences VR.
 
There are still several limitations in the present study. First, larger multi-centric and prospective cohorts should be established to validate the efficacy of these novel mutations, especially for the novel predictive model. Second, advanced studies should be investigated to clarify if these novel predictive mutations observed in HBeAg positive patients treated with conventional IFN are suitable for HBeAg negative patients or Peg-IFN treatment.
 
In conclusion, the present study investigated the impacts of baseline clinical characteristics on therapeutic effects of IFN and discovered some mutations impacted IFN responses independently, especially some novel mutations in PC and BCP regions. These mutations could serve as important predictors for patients treated with conventional IFN treatment.
 
 
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Received January 5, 2016
Accepted after revision October 10, 2016