Hepatitis B virus combo mutations improve the prediction and … · 2015. 8. 19. · We aimed to...

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Hepatitis B virus combo mutations improve the prediction and active

prophylaxis of hepatocellular carcinoma: a clinic-based cohort study

Running title: Prediction and prophylaxis of HCC and death

Jianhua Yin,1 Junxue Wang,2 Rui Pu,1 Haiguang Xin,2 Zixiong Li,1 Xue Han,3 Yibo

Ding,1 Yan Du,1 Wenbin Liu,1 Yang Deng,1 Xiaowei Ji,1 Ming Wu,4 Min Yu,5

Hongwei Zhang,1 Hongyang Wang,6 Timothy C. Thompson,7 Wu Ni,2 Guangwen

Cao1

1 Department of Epidemiology, Second Military Medical University, Shanghai, China;

2 Department of Infectious Diseases, The 2nd Affiliated Hospital, Second Military

Medical University, Shanghai, China;

3 Division of Chronic Diseases, Center for Disease Control and Prevention of Yangpu

District, Shanghai, China;

4 Division of Chronic Diseases, Provincial Center for Disease Control and Prevention

of Jiangsu, Nanjing, China;

5 Division of Chronic Diseases, Provincial Center for Disease Control and Prevention

of Zhejiang, Hangzhou, China;

Cancer Research. on December 7, 2020. © 2015 American Association forcancerpreventionresearch.aacrjournals.org Downloaded from

Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on August 19, 2015; DOI: 10.1158/1940-6207.CAPR-15-0160

http://cancerpreventionresearch.aacrjournals.org/

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6 International Cooperation Laboratory on Signal Transduction, The 3rd Affiliated

Hospital, Second Military Medical University, Shanghai, China;

7 Department of Genitourinary Medical Oncology-Research, University of Texas MD

Anderson Cancer Center, Houston, Texas, USA.

The first 4 authors contributed equally to this work. Guangwen Cao and Wu Ni are

equal senior authors.

Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed by authors.

Grant support: This study was supported by the National Key Basic Research

Program (2015CB554000 to G. Cao) and Key Project for Infectious Diseases

(2012ZX10002-008 to G. Cao) from the Ministry of Science and Technology of China,

National Natural Science Foundation of China (91129301 to G. Cao, 81025015 to G.

Cao, 81302492 to Y. Du, 81221061 to H. Wang, 81373067 to J. Yin), and Outstanding

Young Investigator Project from Shanghai Municipal Health and Family Planning

Commission (XYQ2013072 to J. Yin).

Corresponding author: Guangwen Cao, Department of Epidemiology, Second

Military Medical University, 800 Xiangyin Road, Shanghai, 200433, People's

Republic of China. Phone: 86-21-81871060; Fax: 86-21-81871060; E-mail:




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[email protected].

Word count: Abstract 250; Main document 3417; References 39; Figures and Tables,

6; Supplementary Tables, 3; Supplementary Figures, 3.




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Abstract

We aimed to evaluate if hepatitis B virus (HBV) mutations at the core promoter region

could improve the prediction and specific prophylaxis of hepatocellular carcinoma

(HCC) in chronic HBV-infected patients. A total of 2114 HBV-infected patients

enrolled between August 1998 and December 2007 were followed-up for 18406

person-years. Of those, 612 received ≥48 week treatments with nucleos(t)ide analogue

(NA) and/or interferon-α. Baseline HBV mutations were identified by sequencing.

Propensity score matching was applied to reduce baseline differences between

antiviral and control cohorts. Multivariate Cox regression analyses including baseline

characteristics of 2114 patients showed that age, male, cirrhosis, and HBV mutations

(C1653T, T1753V, and A1762T/G1764A) independently increased HCC risk. In

control patients carrying A1762T/G1764A, addition of C1653T and/or T1753V

significantly increased HCC risk (HR=1.57; P=0.038); combo mutations with C1653T,

T1753V, and A1762T/G1764A improved the validity of HCC prediction by age, male,

and cirrhosis (P=0.002). In the matched cohorts, antiviral treatment reduced HCC

incidence (13.90/1000 vs. 7.70/1000 person-years, P=0.005); NA treatment for ≥60

months was required for the prophylaxis of HCC in cirrhotic patients (P=0.03);

antiviral treatment reduced HCC risk in patients carrying A1762T/G1764A

(HR=0.40; P=0.002) or C1653T (HR=0.45; P=0.04) and in those without T1753V

(HR=0.42; P=0.005), but could not reduce HCC risk in patients without

A1762T/G1764A or C1653T and in those with T1753V. In summary, HBV mutation




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A1762T/G1764A, C1653T, and T1753V in combination improve HCC prediction in

HBV-infected patients. To prevent HCC, patients infected with HBV carrying

A1762T/G1764A or C1653T, but not T1753V, should be given priority of receiving

antiviral treatments.

Keywords: hepatitis B virus; mutation; antiviral treatment; hepatocellular carcinoma;

cohort study




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Introduction

Primary liver cancer is the second leading cause of cancer-related death in men and

the fifth causes of cancer death in women and hepatocellular carcinoma (HCC)

accounts for 70% to 85% of the total liver cancer burden worldwide (1). Chronic

infection with hepatitis B virus (HBV) contributes to more than half of global HCC

cases. The lifetime (30-75 years) incidences of HCC for men and women positive for

hepatitis B surface antigen (HBsAg) were 27.38% and 7.99%, respectively, in Taiwan

(2), an area endemic for HBV genotypes B and C. Therefore, it is estimated that

approximately 20 million HCC cases caused by chronic HBV infection will be

diagnosed in next 50 years in Mainland China, an area with one-third of global

HBV-infected subjects. HCC is a highly fatal malignancy, with a 5-year survival rate

of 9.01% for patients without surgical treatment and 32.64% for those who received

surgery in Shanghai, China (3). Much hope for controlling HCC is placed with active

prophylaxis prior to its occurrence. Fortunately, the occurrence and recurrence of

HBV-related HCC can be reduced via active prophylaxis using anti-HBV treatments

with nucleos(t)ide analogue (NA) and/or interferon-α (IFN-α) (4-10). It is therefore

important to identify the HBV-infected patients who are more likely to develop HCC,

allowing timely intervention in those who will benefit most.

Epidemiological cohort studies have demonstrated that male gender, increasing age,

cirrhosis, high viral load (≥104 copies/ml), hepatitis B e antigen (HBeAg) expression,




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HBV genotype C2 (vs. genotype B2), low albumin, and elevated alanine

aminotransferase (ALT) increase the risk of HCC in chronic HBV-infected patients

(11-15). Some of these risk factors have been utilized to construct clinical scoring

systems for the prediction of HCC (12-15). However, HBeAg sero-status and the

levels of HBV DNA and ALT are usually changeable during the long-term HBV

infection, and differ among the patients infected with different HBV genotypes, which

might result in low discriminatory performance in different populations (16-21).

Therefore, more robust biomarkers are needed to improve the prediction power of the

current clinical scoring systems.

HBV demonstrates “mutation-selection-adaptation”, a viral evolutionary process

involved in hepatocarcinogenesis. During this process, HBV accumulates HCC-risk

mutations, predominantly in the core promoter region of HBV genome (22-26). Of

these mutations, A1762T/G1764A has been prospectively shown to be an independent

risk factor of HCC (15,26). A1762T/G1764A and A1762T/G1764A-based combo

mutants are potentially selected by the immunocompromised microenvironment

predisposed by genetic polymorphisms of key immune and proinflammatory

molecules, and in turn promote an aggressive phenotype of HCC, as well as the

recurrence of HCC after curative surgery (27-30). The objective of this study was to

clarify if the baseline HBV mutations can predict the outcome of HBV-infected

patients and if HCC risk contributed by the HBV mutations can be selectively reduced

by antiviral treatment. This study should lay foundation for effective prediction and




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specific prophylaxis of HCC in HBV-infected patients.

Materials and Methods

Cohort enrollment

This mixed cohort study was initiated in January 2008 and approved by the

institutional review board of Second Military Medical University. From August 1998

to December 2007, 3304 consecutive chronic HBV-infected patients admitted to the

Department of Infectious Diseases, the 2nd Affiliated Hospital of this university were

invited to participate in this study. Patients were included in the study if (i) they were

newly diagnosed as chronic hepatitis B; (ii) they provided sufficient cryopreserved

sera from peripheral blood harvested within 2 weeks before antiviral treatment or

during their initial visit; and (iii) they provided written informed consents. Patients

were excluded from the study if (i) they had decompensated liver cirrhosis or HCC; (ii)

they were co-infected with hepatitis A virus, hepatitis C virus, hepatitis D virus,

hepatitis E virus, human immunodeficiency virus, and/or Treponema pallidum; (iii)

they had autoimmune liver diseases; and (iv) they received antiviral treatment before

enrollment. Chronic hepatitis B, liver cirrhosis, and HCC were diagnosed as

previously described (25). Cirrhotic patients manifested with ascites, jaundice,

variceal bleeding or hepatic encephalopathy were diagnosed as decompensated

cirrhosis. A total of 2512 eligible patients were initially enrolled.




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Collection of baseline demographic and clinical data

A structured questionnaire was designed to extract baseline data of study participants

from their medical records. Data collected include sociodemographics, smoking,

alcohol consumption, medical history, and biochemical parameters from blood tests

such as liver function, antibodies, and platelet count within 2 weeks before antiviral

treatment or at their first admission. Microbiological and biochemical parameters

were tested as previously described (25).

HBV genotyping and mutation assay

HBV DNA was extracted from frozen sera, quantified twice using quantitative PCR,

and genotyped as previously described (20). The core promoter region from nt.1626 to

nt.2004 of HBV genome was amplified using nested PCR and directly sequenced or

sequenced after cloning (25,31). The sequences were aligned and analyzed using

MEGA5.0 and Bioedit 7.0 software packages and deposited in GenBank with

accession numbers KF164837-KF166793. A total of 18 “hotspots” with a mutation

frequency of >10% in this region as previously detailed (25) were evaluated.

Antiviral treatment




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Antiviral treatment was administered according to disease indications as well as

patients’ willingness, compliance, and cost. Generally, patients were suggested to

receive antiviral treatment if they had high serum ALT (≥twice the upper limit of

normal) and elevated HBV DNA titer (≥105 copies/mL for HBeAg-positive or ≥104

copies/mL for HBeAg-negative patients), or cirrhosis with detectable HBV DNA (32).

For oral NA treatment, lamivudine (LAM, 100mg), adefovir dipivoxil (ADV, 10mg),

entecavir (ETV, 0.5mg), or telbivudine (LdT, 600mg) was given daily for ≥48 weeks.

Adding-on or switch-to ADV was adopted as a rescue therapy for patients with viral

breakthrough and/or drug-resistant mutations under LAM, LdT or ETV treatment, and

vice versa. For cirrhosis-free patients who were resistant to LAM, recombinant

IFN-α1b was given if their liver function permitted. Intramuscular injection of

recombinant IFN-α1b (5MU every other day) and subcutaneous administration of

pegylated IFN-α (Peg-IFN-α2a, 180µg/week; Peg-IFN-α2b, 1.5µg/kg body

weight/week) were adopted. A 48-week IFN-treatment course was essential for most

patients. For those who had partial virological responses at week 24 of treatment,

IFN-α course was prolonged to 72 weeks. Patients who did not respond to antiviral

treatment mostly failed to complete antiviral treatment for ≥48 weeks and were

excluded from the final analysis.

Follow-up

Participants received regular follow-up examinations at our outpatient clinics or at




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their local tertiary hospitals. We collected information including real-life regimens of

antiviral treatment, liver function test results, and medical imaging findings by

checking their medical records. Information regarding HCC occurrence and death

before January 2008 was obtained through Shanghai Cancer Registry and Death

Certification System. Information regarding HCC occurrence and death after January

2008 was obtained by conducting regular telephone interviews, and/or household

visits. The follow-up was finished on May 31, 2013. Causes of death were determined

according to the primary diagnosis of hospitalization within 3 months before death.

The primary outcome was HCC occurrence. Death from HCC, decompensated

cirrhosis, and/or liver failure was termed as liver death. All participants were

self-reported Han Chinese.

Statistical analysis

Categorical variables were compared using chi-square test. Patients who survived or

died of other causes were censored at their last follow-up visit. Kaplan-Meier method

was applied to estimate the cumulative incidences of HCC and liver death, and

log-rank test was performed to compare the survival curves. The hazard ratio (HR)

and 95% confidence interval (CI) were calculated using the Cox proportional hazard

model. The significant factors in the univariate Cox analysis were introduced into the

multivariate Cox model to determine the factors independently contributing to HCC

occurrence and liver death. To evaluate the prophylactic effect of antiviral treatments




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on HCC and liver death, the propensity score (PS) matching method was used to

balance baseline variables between antiviral and control cohorts. A PS was estimated

for all patients with antiviral treatments using multiple logistic regression analysis.

Variables used in the model were age, gender, cirrhosis, HBV genotype, HBeAg,

HBV DNA, ALT, aspartate aminotransferase (AST), total bilirubin, direct bilirubin,

albumin, and platelet count. We performed the nearest available matching on the PS,

as described by Hosaka, et al (6). Demographic (gender, age, and cirrhosis) and all

factors (gender, age, cirrhosis, C1653T, T1753V, and A1762T/G1764A) that

independently increased HCC risk were introduced into the multivariate Cox model to

re-calculate regression coefficient (β) of each variable, respectively. Projected HCC

risk based on demographic and all independent risk factors were calculated using the

equations: demographic=∑βi×Xi (Xi: gender, age, and cirrhosis), and all independent

risk factors=∑βj×Xj (Xj: gender, age, cirrhosis, C1653T, T1753V, and

A1762T/G1764A). Discrimination was analyzed using receiver operating

characteristic (ROC). Area under ROC curve (AUC) was applied to evaluate if the

HBV mutations could improve the prediction power of the demographic factors. All

analyses were two-sided and conducted using SPSS version 18.0 for Windows (SPSS,

Chicago, IL), R (http://www.r-project.org/), and medcalc (http://www.medcalc.org/).

Significance was set as P<0.05.

Results




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Patient characteristics

Of 2512 eligible patients, 398 were excluded (Supplementary Figure 1). There were

no statistical differences in age, gender, cirrhosis, and major liver function parameters

between the enrolled and excluded patients (data not shown). The remaining 2114

patients were followed-up for a mean of 8.92 years (IQR, 6.67-11.00 years). Table 1

shows baseline characteristics and follow-up data of the study patients. Of the 2114

patients, 209 developed HCC during 18406 person-years of follow-up (incidence:

11.36/1000 person-years); 361 died of HBV-related liver diseases (mortality:

19.61/1000 person-years). Of 612 patients with antiviral treatment, 153 were treated

with IFN-α alone, 380 treated with NAs alone, and 79 treated with IFN-α plus NAs.

Antiviral treatment significantly reduced HCC occurrence and liver death. HBV

mono-genotype was identified in 1659 (78.48%) patients. HBV genotype B2

accounted for 26.94%; and genotype C2, 73.06%.

The PS matching with key baseline characteristics was applied to allow a common

background for comparison between antiviral and control cohorts, resulting in a

matched sample size with 521 patients in each cohort. In the antiviral cohort, 109

were treated with IFN-α alone, 347 treated with NAs alone, and 65 treated with IFN-α

plus NAs. Antiviral treatment significantly reduced HCC incidence and liver death in

the matched cohorts.




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Factors affecting HCC occurrence and liver death

Univariate Cox analyses including the baseline characteristics of 2114 patients

showed that male gender, increasing age, cirrhosis, HBV genotype C2, high direct

bilirubin (>7 μmol/L), low albumin (<35 g/L), high AFP (>20 ng/mL), low platelet

count (<100×109/L), and HBV mutations (C1653T, T1674CG, T1753V, and

A1762T/G1764A) were significant risk factors for HCC development; whereas

antiviral treatment was a protective factor of HCC. HBeAg and viral load were not

statistically associated with HCC, even in 1502 control patients without antiviral

treatment (data not shown). Multivariate Cox analysis indicated that male, age (≥40

yrs), cirrhosis, C1653T, T1753V, and A1762T/G1764A independently increased the

risk of HCC (Table 2).

Univariate Cox analysis using the baseline characteristics of 2114 patients indicated

that male, age (≥40 yrs), HBV DNA (≥106 copies/mL), AST (>37 U/L), total bilirubin

(>20 μmol/L), direct bilirubin (>7 μmol/L), albumin (<35 g/L), AFP (>20 ng/mL),

platelet count (<100×109/L), and the presence of cirrhosis, C1653T, T1674CG,

T1753V, and A1762T/G1764A were significant risk factors, whereas antiviral

treatment was a protective factor for liver death. Multivariate Cox analysis showed

that male, age (≥40 yrs), albumin (<35g/L), and platelet count (<100×109/L) were

independently risk factors, whereas antiviral treatment was an independent protective

factor for liver death (Supplementary Table 1).




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Baseline combo HBV mutations cumulatively increased the occurrences of HCC

and liver death and significantly improved HCC prediction by demographic

factors in control cohort

Patients with A1762T/G1764A had significantly higher cumulative risks of HCC and

liver death compared to patients without A1762T/G1764A. Furthermore, in patients

with A1762T/G1764A, addition of C1653T and/or T1753V significantly increased the

risks of HCC (HR=1.57, 95% CI=1.03-2.41; P=0.038) and liver death (HR=1.56,

95% CI=1.02-2.40; P=0.040). In genotype C2 HBV-infected patients with

A1762T/G1764A, addition of C1653T and/or T1753V significantly increased HCC

risk (HR=1.77, 95% CI=1.09-2.87; P=0.021). However, this effect was not found in

genotype B2 HBV-infected patients, possibly because of small sample size of patients

with the two or more viral mutations (Figure 1).

We plotted ROC curves for the development of HCC in 919 antiviral-naïve patients

(HCC, n=102) with baseline HBV mutation data. Combo HBV mutations (C1653T,

T1753V, and A1762T/G1764A) significantly improved the validity of HCC prediction

by age, gender, and cirrhosis (AUC: 0.727 vs. 0.676, P=0.002). Further stratification

analyses indicated that the combo HBV mutations significant improved the validity of

HCC prediction in genotype C2 HBV-infected patients (HCC incidence: 83/677), not

in genotype B2 HBV-infected patients (HCC incidence: 18/232) (Figure 2).




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Prophylactic effects of antiviral treatment in those with or without baseline

cirrhosis in the PS matched cohorts

We first evaluated the prophylactic effects of antiviral treatment in 236 patients with

cirrhosis. Compared to the matched controls, antiviral treatment did not affect HCC

occurrence but significantly reduced death (HR=0.49, 95% CI=0.29-0.81; P=0.005).

The survival benefit was observed in those treated with NAs alone (n=98), but not in

those treated with IFN-α (n=12) or with IFN-α plus NAs (n=8). NA treatment for

12-59 months (n=66) did not significantly reduce HCC occurrence and liver death;

whereas NA treatment for ≥60 months (n=32) had significant prophylactic effects on

HCC occurrence and liver death. In 806 patients without cirrhosis, antiviral treatment

significantly reduced HCC occurrence (HR=0.47, 96% CI=0.26-0.85; P=0.012) and

liver death (HR=0.50, 95% CI=0.32-0.77; P=0.002); interestingly, these benefits were

observed in patients treated with IFN-α alone (n=97) or IFN-α plus NAs (n=57), but

not in those treated with NAs alone (n=249); NA treatment for ≥60 months (n=77) did

not affect HCC occurrence but significantly reduced liver death (Figure 3).

Impact of the HBV mutations on HCC occurrence and liver death were

selectively repressed by antiviral treatment in the PS matched cohorts

We compared the effects of antiviral treatment on HCC occurrence and liver death of




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patients with one or more mutations (C1653T, T1753V, and A1762T/G1764A) and

patients without any of them. Antiviral treatment significantly reduced HCC

occurrence in those with the HBV mutation(s), but did not reduce HCC risk in those

without (Supplementary Figure 2). In patients with A1762T/G1764A, antiviral

treatment significantly reduced HCC occurrence, whereas in patients without

A1762T/G1764A, antiviral treatment did not reduce HCC occurrence; similar results

were obtained in patients with or without C1653T; interestingly, in patients with

T1753V, antiviral treatment did not reduce HCC occurrence, whereas in those without

T1753V, antiviral treatment significantly reduced HCC occurrence (Figure 4).

Antiviral treatment significantly reduced liver death in patients with and without

A1762T/G1764A or C1653T mutations. However, antiviral treatment did not affect

liver death in patients with T1753V, but reduced liver death in those without T1753V

(Supplementary Figure 3).

Factors affecting the prophylactic effect of antiviral treatments

We then assessed baseline factors affecting the prophylactic effect of antiviral

treatments in 612 patients with antiviral treatment. Multivariate Cox analyses showed

that age (≥60 yrs), male, and the presence of cirrhosis and T1753V independently

predicted HCC development (Supplementary Table 2); while age (≥60 yrs), male, and

T1753V independently predicted liver death (Supplementary Table 3).




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Discussion

In this study, male, age, cirrhosis, C1653T, T1753V, and A1762T/G1764A were found

to be independent risk factors of HCC in HBV-infected patients. High viral load, a

well-established risk factor of HCC (11-14), did not significantly increase HCC risk in

this study. The same was true for HBeAg, another risk factor of HCC (33). These

inconsistencies were also reported in the constituents of the HCC scoring systems

developed from hospital-based and community-based studies in East Asia (12-15),

possibly because these covariates were collected at different time points during

chronic HBV infection. In the natural history of chronic HBV infection, viral load can

be high (106-1010 copies/mL) at HBeAg-positive stage, and then decreases

dramatically (104-108 copies/mL) or fluctuates after HBeAg seroconversion (16). To

determine the contribution of HBV replication to HCC risk in HBV-infected subjects,

it may be better to determine the baseline HBV DNA level after HBeAg

seroconversion. Furthermore, age, male, HBeAg, HBV genotype C, abnormal ALT,

and high viral load can also predict the development of cirrhosis (14), a benign

disease vastly different from HCC, indicating that the current scoring systems based

on these demographic and clinical variables is not specific for HCC. During chronic

HBV infection, the HCC-risk HBV mutations including A1762T/G1764A, C1653T,

and T1753V accumulate consecutively prior to HCC occurrence. A1762T/G1764A is

an earlier generated HCC-risk mutation, whereas C1653T and T1753V are later

generated ones (25,31,34). Furthermore, HBV combo mutations have higher




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specificities than single ones in indicating HCC (24,25). These HBV mutations

accumulated during this evolutionary process should be more robust and more

specific than those changeable clinical markers in predicting HCC occurrence. The

HBV combo mutations significantly improved HCC prediction using the 3 significant

demographic factors (Figure 2). Thus, the HBV combo mutations should be

incorporated into the current risk prediction models to improve the prediction of HCC

in HBV-infected patients.

HBV X protein (HBx) contributes centrally to HCC development at least partially via

up-regulating HBx-induced cyclin D1 (35). HBV 1753/1762/1764 mutations at the

C-terminal of HBx are associated with active viral replication in human hepatoma cell

lines (36). It had been shown that A1762T/G1764A-based HBV combo mutants,

rather than those with A1762T/G1764A alone, accelerate p21 degradation and

stimulate expression of S-phase kinase-associated protein 2 in hepatocytes or HCC

cells (29). These data may help in explaining why A1762T/G1764A-based combo

mutation was more effective than A1762T/G1764A alone in predicting HCC and liver

death.

Following the identification of high-risk HBV-infected patients, it becomes

indispensible to develop an effective prophylactic option on HCC or liver death in

patients with these viral mutations. We found, for the first time, that antiviral

treatment significantly reduced HCC development in HBV-infected patients carrying




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A1762T/G1764A or C1653T mutation. These data indicate that HBV with

A1762T/G1764A and/or C1653T mutations has a more potent carcinogenic potential

than its wild-type counterparts and also responds efficiently to standard antiviral

treatment. Interestingly, the risk of HCC contributed by HBV T1753V mutation can

not be significantly reduced by standard antiviral treatment. The reason remains

unknown. We hypothesize that T1753V mutation introduces a novel drug-resistant

capacity of HBV or some idiopathetic drug-resistant mutations in HBV genome are

synchronously generated with T1753V during this revolutionary process. Further

studies are needed to address this issue. Therefore, HBV-infected patients with

A1762T/G1764A or C1653T should be given priority of receiving antiviral treatment;

while patients with T1753V should be monitored frequently to identify early,

resectable HCC.

Our stratification analysis indicated that the combo mutations significantly improved

HCC prediction in genotype C2 HBV-infected patients, but not in genotype B2

HBV-infected patients. A1762T/G1764A significantly increased HCC risk and liver

death in genotype B2 HBV-infected patients (Figure 1C, 1D). Genotype B2 HBV has

a relative weaker carcinogenic potential than does genotype C2, possibly because

genotype B2 has less HCC-related mutations. A1762T/G1764A is more frequent in

HBV genotypes C and D than in genotypes A and B (37). Although the HBV

mutations increase with increasing age of HCC-free HBV-infected subjects, the HBV

mutations such as A1762T/G1764A and T1753V are extremely higher in younger




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HBV-HCC patients, compared to the age-matched HCC-free HBV-infected subjects

(25). The HBV mutations independently predicted HCC occurrence (Table 2). Thus,

the HBV mutations, whose patterns differ among HBV genotypes, are HCC-specific

and the association of A1762T/G1764A-based HBV mutations with HCC risk may be

generalized to populations with different HBV genotypes.

The minimum period for NA treatment required to reduce HCC occurrence in

HBV-infected patients differs greatly among studies carried out in Taiwan (≥90 days),

USA (45 months), Japan (≥48 weeks), and South Korea (≥24 weeks) (4-7). Our data

indicated that NA treatment for ≥60 months was required for the prophylaxis of HCC

in cirrhotic patients. IFN-α treatment independently suppressed the development of

HCC in non-cirrhotic HBV-infected patients. This is supported by the fact that HBV

genotype B2 is less apt to cause cirrhosis and more sensitive to IFN-α treatment than

genotype C2 (38,39). Thus, these data are particularly important for the prophylaxis of

HCC in chronic HBV-infected patients.

This study has several limitations. First, 701 patients meeting the current standard for

antiviral treatment had not received antiviral treatment. Second, data concerning

fibrosis stage, maternal HBsAg status, family history of HCC, and quantitative

HBsAg were incomplete and therefore not included in the analyses.

In conclusion, baseline combo mutations in the core promoter region of HBV genome




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are more effective than A1762T/G1764A alone in predicting HCC occurrence and

liver death and significantly improve HCC prediction by well-established

demographic factors. Antiviral treatment was extremely effective in reducing HCC

occurrence in chronic HBV-infected patients carrying A1762T/G1764A or C1653T

but not in those carrying T1753V mutation. These data are helpful for effective

prediction and specific prophylaxis of HCC and liver death.




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Acknowledgements

We gratefully acknowledge Drs. Hua Wang, Weiwei Gong, and experts responsible

for the maintenance of Cancer Registry and Death Certification Systems of Shanghai

for their great help in the follow-up study. We regret that some articles relevant to this

study are not cited due to space limitations.




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31

FIGURE LEGENDS

Figure 1. Impact of baseline C1653T, T1753V, and A1762T/G1764A mutations on

HCC occurrence and liver death in control patients. (A) HCC occurrence in patients

with mutation data; (B) liver death in patients with mutation data; (C) HCC

occurrence in genotype B2 HBV-infected patients; (D) liver death in genotype B2

HBV-infected patients. (E) HCC occurrence in genotype C2 HBV-infected patients; (F)

liver death in genotype C2 HBV-infected patients. P values, log-rank test.

Figure 2. Comparison of HCC prediction by baseline demographic factors (age,

gender, and cirrhosis) with and without baseline combo mutations of HBV in control

patients. (A) All patients with mutation data; (B) Genotype B2 HBV-infected patients;

(C) Genotype C2 HBV-infected patients.

Figure 3. The effects of antiviral treatment on HCC occurrence and liver death in

patients with or without liver cirrhosis in the PS matched cohorts. (A) NA treatment

on HCC occurrence in cirrhotic patients; (B) NA treatment on liver death in cirrhotic

patients; (C) Antiviral treatment on HCC occurrence in non-cirrhotic patients; (D)

Antiviral treatment on liver death in non-cirrhotic patients; (E) NA treatment on HCC

occurrence in non-cirrhotic patients; and (F) NA treatment on liver death in

non-cirrhotic patients. P values, log-rank test.




32

Figure 4. Effect of antiviral treatment on HCC occurrence in chronic HBV-infected

patients with and without each of the HCC-risk mutations in the PS matched cohorts.

(A) patients with A1762T/G1764A; (B) patients without A1762T/G1764A; (C)

patients with C1653T; (D) patients without C1653T; (E) patients with T1753V; (F)

patients without T1753V. P values, log-rank test.




Table 1. Baseline characteristics and follow-up summary of study patients a

Variables

Entire Cohort Propensity Score Match Cohort

Control cohort

(n=1502)

Antiviral-treated

cohort (n=612) P

Control cohort

(n=521)

Antiviral-treated

cohort (n=521) P

Age (years)

<40 567(37.7) 345(56.4) <0.001 258(49.5) 275(52.8) 0.55

40-59 741(49.3) 232(37.9) 224(43.0) 212(40.7)

≥60 194(12.9) 35(5.7) 39(7.5) 34 (6.5)

Gender (Male) 1119(74.5) 505(82.5) <0.001 432(82.9) 430(82.5) 0.87

HBV genotype

B 289(19.2) 158(25.8) 0.15 126(24.2) 140(26.9) 0.58

C 829(55.2) 383(62.6) 324(62.2) 316(60.7)

Unclassified 384(25.6) 71(11.6) 71(13.6) 65(12.5)

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HBeAg positivity 490(32.6) 324(52.9) <0.001 253(48.6) 262(50.3) 0.58

Cigarette smoking 342(22.8) 129(21.1) 0.40 404(77.5) 415(79.7) 0.41

Alcohol drinking 309(20.6) 106(17.3) 0.09 105(20.2) 88(16.9) 0.18

Cirrhosis 362(24.1) 128(20.9) 0.12 118(22.6) 118(22.6) 1.000

HBV DNA (log10 copies/mL)

<6.0 905(60.3) 242(39.5) <0.001 208(39.9) 229(44.0) 0.29

≥6.0 597(39.7) 370(60.5) 313(60.1) 292(56.0)

Total bilirubin (μmol/L)

≤20 329(22.1) 180(30.0) <0.001 126(24.2) 127(24.4) 0.94

>20 1160(77.9) 420(70.0) 395(75.8) 394(75.6)

Direct bilirubin (μmol/L)

≤7 452(30.4) 239(39.8) <0.001 174(33.4) 176(33.8) 0.90

>7 1035(69.6) 361(60.2) 347(66.6) 345(66.2)

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Albumin (g/L)

≥35 921(61.6) 414(67.8) 0.007 333(63.9) 346(66.4) 0.40

<35 575(38.4) 197(32.2) 188(36.1) 175(33.6)

Alanine aminotransferase (U/L)

≤40 381(25.7) 94(15.7) <0.001 87(16.7) 92(17.7) 0.68

>40 1103(74.3) 506(84.3) 434(83.3) 429(82.3)

Aspartate aminotransferase (U/L)

≤37 300(22.9) 80(13.7) <0.001 67(12.9) 77(14.8) 0.37

>37 1010(77.1) 504(86.3) 454(87.1) 444(85.2)

Platelet count (109/L)

100-300 698(46.5) 306(50.0) 0.14 245(47.0) 251(48.2) 0.71

<100 804(53.5) 306(50.0) 276(53.0) 270(51.8)

Person-years of follow-up 13285 5121 4387 4287

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Follow-up duration (years)b 9.2(7.0-11.3) 8.2(6.3-10.6) 8.83(6.8-10.7) 8.17(6.3-10.4)

Hepatocellular carcinoma 173(11.5) 36(5.9) <0.001 61(11.7) 33(6.3) 0.002

Incidence (/1000 person-years) 13.02 7.02 0.001 13.90 7.70 0.005

Death from Liver Diseases 304(20.2) 57(9.3) <0.001 107(20.5) 54(10.4) <0.001

Fatality (/1000 person-years) 22.88 11.13 <0.001 24.39 12.60 <0.001

NOTE: a Data are number (%), unless otherwise indicated. Some percentages do not sum up to 100 because of rounding. b Median (IQR)

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Table 2. Cox analysis of factors significantly affected hepatocellular carcinoma occurrence in patients with chronic HBV infection a

Variable

No.(%) of

participants

(n=2114)

Person-years

of follow-up

No.

of

HCC

Incidence per

1000

person-years

Univariate

analysis

HR (95% CI)

P

Multivariate

analysis

HR (95% CI) c

P

Gender

Female 490(23.2) 4364 24 5.50 1.00 1.00

Male 1624(76.8) 14042 185 13.17 2.91(1.90-4.47) <0.001 3.10(1.76-5.45) <0.001

Age (years)

<40 912(43.1) 8473 54 6.37 1.00 1.00

40-59 973(46.0) 8123 123 15.14 2.58(1.87-3.55) <0.001 2.09(1.35-3.23) 0.001

≥60 229(10.8) 1809 32 17.69 3.44(2.21-5.36) <0.001 2.44(1.29-4.61) 0.006

Cirrhosis

No 1624(76.8) 14698 115 7.82 1.00 1.00

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Yes 490(23.2) 3709 94 25.34 2.94(2.22-3.89) <0.001 1.89(1.21-2.96) 0.005

HBV genotype

B 447(26.9) 3812 25 6.56 1.00

C 1212(73.1) 10752 125 11.63 1.61(1.05-2.48) 0.03

Antiviral therapy

No 1502(71.0) 13276 172 13.02 1.00 1.00

Yes 612(29.0) 5132 36 7.01 0.60(0.42-0.86) 0.006 0.64(0.41-1.00) 0.050

Direct bilirubin (μmol/L)

≤7 691(33.1) 6440 51 7.92 1.00

>7 1396(66.9) 11751 158 13.45 1.41(1.02-1.93) 0.036

Albumin (g/L)

≥35 1335(63.4) 12275 106 8.64 1.00

<35 772(36.6) 6073 102 16.80 1.68(1.27-2.22) <0.001

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α- fetoprotein (ng/mL)

≤20 1358(64.4) 12064 115 9.53 1.00

20-400 752(35.6) 6315 94 14.89 1.49(1.13-1.95) 0.004

Platelet count (109/L)

100-300 1004(47.5) 8960 66 7.37 1.00

<100 1110(52.5) 9445 143 15.14 1.83(1.36-2.45) <0.001

C1653T b

C 1166(82.3) 10410 88 8.45 1.00 1.00

T 250(17.7) 2160 47 21.76 2.43(1.70-3.48) <0.001 1.86(1.24-2.81) 0.003

T1674C/G b

T 1051(74.3) 9426 84 8.91 1.00

C or G 364(25.7) 3138 50 15.93 1.67(1.18-2.38) 0.004

T1753V b

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T 1180(83.9) 10530 96 9.12 1.00 1.00

V (C or A or G) 226(16.1) 1955 39 19.95 1.97(1.35-2.87) <0.001 1.58(1.03-2.43) 0.036

A1762T/G1764A b

Wild-type 549(39.8) 5086 23 4.52 1.00 1.00

Mutation 831(60.2) 7143 106 14.84 2.89(1.83-4.56) <0.001 1.96(1.18-3.26) 0.009

NOTE: a Data are number (%). b HBV mutation. c Only included significant covariates in univariate analysis.

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C

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C1653T / T1753V / A1762TG1764A C1653T / T1753V / A1762TG1764AA B

Follow-up time (months) Follow-up time (months)No. at risk -/-/- 348 332 323 307 236 162 73 9-/-/+ 276 250 239 216 172 114 62 9+/-/+ or -/+/+or +/+/+ 263 230 218 192 155 102 48 6

348 332 323 310 238 163 73 9276 252 242 221 181 119 65 9

263 237 224 204 170 110 49 6

Reference -/-/-

HR 3.76 (95% CI 1.99 - 7.08),P < 0.001

HR 5.92 (95% CI 3.22 - 10.88), P < 0.001-/-/--/-/++/-/+ or -/+/+or +/+/+

-/-/--/-/++/-/+ or -/+/+or +/+/+

-/-/-, Reference-/-/+, HR 2.02 (95% CI 1.38 - 2.97), P < 0.001+/-/+ or -/+/+ or +/+/+, HR 2.64 (95% CI 1.82 - 3.83), P < 0.001

0.30

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D

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of H

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F

No. at risk

No. at risk


-/-/- 136 125 122 117 86 56 27 4-/-/+ 69 63 56 50 37 18 9 2+/-/+ or -/+/+or +/+/+ 20 17 16 14 14 10 3

-/-/- 208 203 198 187 147 103 44 5-/-/+ 204 184 180 163 132 93 52 7+/-/+ or -/+/+or +/+/+ 241 211 200 177 140 91 44 6

136 125 122 118 86 56 27 469 63 57 51 39 21 9 2

20 17 16 15 14 10 3

208 203 198 189 149 104 44 5204 186 182 167 139 95 55 7

241 218 206 188 155 99 45 6

C1653T / T1753V / A1762TG1764A in genotype B C1653T / T1753V / A1762TG1764A in genotype B

C1653T / T1753V / A1762TG1764A in genotype C C1653T / T1753V / A1762TG1764A in genotype C

-/-/--/-/++/-/+ or -/+/+or +/+/+

-/-/--/-/++/-/+ or -/+/+or +/+/+

-/-/-, Reference-/-/+, HR 2.33 (95% CI 1.23 - 4.41), P = 0.009+/-/+ or -/+/+ or +/+/+, HR 2.37 (95% CI 0.94 - 5.97), P = 0.068

-/-/-, Reference-/-/+, HR 2.04 (95% CI 1.25 - 3.34), P = 0.005+/-/+ or -/+/+ or +/+/+, HR 2.89 (95% CI 1.82 - 4.58), P < 0.001

-/-/--/-/++/-/+ or -/+/+or +/+/+

-/-/--/-/++/-/+ or -/+/+or +/+/+

Reference, -/-/-

Reference -/-/-

HR 3.61 (95% CI 0.66 - 19.72),P = 0.138

HR 3.01 (95% CI 1.41 - 6.46),P = 0.005

HR 6.21 (95% CI 1.98 - 19.51), P = 0.002

HR 5.37 (95% CI 2.63 - 10.94), P < 0.001

0 24 48 72 96 120 144 168 192

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0 24 48 72 96 120 144 168 192

0 24 48 72 96 120 144 168 192 0 24 48 72 96 120 144 168 192

0 24 48 72 96 120 144 168 192 0 24 48 72 96 120 144 168 192

Figure 1




0.00 0.20 0.40 0.60 0.80 1.00

1.00

0.80

0.60

0.40

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0.00

AUC (95% CI)

Demographics+mutations 0.727 ( 0.677 - 0.777)Demographics 0.676 ( 0.623 - 0.730)

Sens

itivi

ty

1-Specificity

P = 0.002

Demographics+mutationsDemographics

B

P = 0.119

AUC (95% CI)Demographics 0.668 (0.604 - 0.729)

Demographics+mutations 0.746 (0.685 - 0.801)


0.00 0.20 0.40 0.60 0.80 1.001-Specificity

1.00

0.80

0.60

0.40

0.20

0.00

Sens

itivi

ty

A

C

P = 0.005


AUC (95% CI)Demographics 0.677 (0.641 - 0.712)

Demographics+mutations 0.725 (0.689 - 0.758)

1.00

0.80

0.60

0.40

0.20

0.00

Sens

itivi

ty

0.00 0.20 0.40 0.60 0.80 1.001-Specificity

Figure 2




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A B

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No. at risk Control 403 375 366 345 253 131 49 7IFN group 97 95 94 91 78 58 17 4NA group 249 239 233 199 111 54 17 1

No. at risk Control 118 95 83 71 55 32 11 112-59 mo. 66 57 51 34 22 13 2 ≥60 mo. 32 32 32 24 14 8

118 99 88 76 63 36 12 166 61 55 38 26 14 2 32 32 32 25 15 8

403 377 367 351 260 137 52 897 95 94 91 80 58 17 4

249 239 237 206 114 55 17 1

No. at risk Control 403 375 366 345 253 131 49 712-59 mon. 172 162 157 131 75 43 14 ≥60 mon. 77 77 76 68 36 11 3 1

403 377 367 351 260 137 52 8172 162 160 136 77 44 14 77 77 77 70 37 11 3 1

IFN plus NA 57 57 57 48 34 14 3 1 57 57 57 48 34 14 3 1

Control 12-59 mo.≥60 mo.

Control vs. 12-59 mo. P = 1.00Control vs. ≥ 60 mo. P = 0.03

Control 12-59 mo.≥60 mo.

Control vs. 12-59 mo. P = 0.11Control vs. ≥ 60 mo. P = 0.002

12-59 mo. vs. ≥ 60 mo. P = 0.04

12-59 mo. vs. ≥ 60 mo. P = 0.03

Control vs. IFN P = 0.01Control vs. NA P = 0.30Control vs. IFN plus NA P = 0.03 Control

IFN groupNA groupIFN plus NA

Control vs. IFN P = 0.01Control vs. NA P = 0.12Control vs. IFN plus NA P = 0.003

Control 12-59 mo.≥ 60 mo.

Control vs. 12-59 mo. P = 0.60Control vs. ≥ 60 mo. P = 0.2312-59 mo. vs. ≥ 60 mo. P = 0.37

Control 12-59 mo.≥ 60 mo.

Control vs. 12-59 mo. P = 0.63Control vs. ≥ 60 mo. P = 0.0212-59 mo. vs. ≥ 60 mo. P = 0.04

Follow-up time (months) Follow-up time (months)



1.00

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0 24 48 72 96 120 144 168 1920 24 48 72 96 120 144 168 192

0 24 48 72 96 120 144 168 192

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Control IFN groupNA groupIFN plus NA

Figure 3




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0.15

0.10

0.05

0.00

A

Cum

ulat

ive

Inci

denc

e of

HC

C

Follow-up time (months)No. at risk Control group 222 195 182 164 127 74 27 5 Antiviral 243 229 222 193 120 70 18 2treatment

Control groupAntiviral treatment group

A1762T/G1764A - positive

C1653T - positive

Cum

ulat

ive

Inci

denc

e of

HC

C

No. at risk Follow-up time (months)

Control group 60 47 43 38 27 15 5 2

C

Antiviral 63 58 56 48 36 23 7 2 treatment

T1753V - positive

Cum

ulat

ive

Inci

denc

e of

HC

C

No. at risk Follow-up time (months)

E

Control group 62 57 54 47 39 22 8 2 Antiviral 62 58 56 47 31 17 10 3treatment

HR 0.40 (95% CI 0.22 - 0.72), P = 0.002

HR 0.45 (95% CI 0.21 - 0.98),P = 0.04

HR 1.06 (95% CI 0.44 - 2.56), P = 0.89



BA1762T/G1764A - negative

Cum

ulat

ive

Inci

denc

e of

HC

C


HR 1.47 (95% CI 0.51 - 4.23), P = 0.479


156 145 142 136 93 56 17 2 136 132 131 122 84 53 12 2

C1653T - negativeD

HR 0.57 (95% CI 0.30 - 1.07),P = 0.08

Antiviral treatment groupControl group

Cum

ulat

ive

Inci

denc

e of

HC

C


332 307 294 275 203 120 41 5 327 314 307 276 174 103 24 3

0.25

0.20

0.15

0.10

0.05

0.00


Cum

ulat

ive

Inci

denc

e of

HC

C


324 291 278 261 187 110 37 5 326 312 306 276 178 109 21 2

T1753V - negativeF

HR 0.42 (95% CI 0.23 - 0.77), P = 0.005

0.25

0.20

0.15

0.10

0.05

0.00

0.60

0.50

0.40

0.30

0.20

0.10

0.00

0.60

0.50

0.40

0.30

0.20

0.10

0.00

0 24 48 72 96 120 144 168 192 0 24 48 72 96 120 144 168 192

0 24 48 72 96 120 144 168 192 0 24 48 72 96 120 144 168 192

0 24 48 72 96 120 144 168 192 0 24 48 72 96 120 144 168 192

Figure 4




Published OnlineFirst August 19, 2015.Cancer Prev Res Jianhua Yin, Junxue Wang, Rui Pu, et al. cohort studyactive prophylaxis of hepatocellular carcinoma: a clinic-based Hepatitis B virus combo mutations improve the prediction and

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