1. Binh Y. Goldstein, PhD Epidemiology 243
Aflatoxin B1, Hepatitis B, and IFNA17 on the Risk of Liver Cancer: An example of the application of exposure markers in cancer epidemiology
Binh Y. Goldstein, PhD
Epidemiology 243

2. Introduction

3. Background: Epidemiology of liver cancer
Worldwide:
Sixth most common new cancer
Third most common cause of cancer death
Rates among men 2-3x higher than women
Over 80% of new cases occur in developing countries
Low 5-year relative survival rates (<15%)
Source: GLOBOCAN 2002

4. Age standardized incidence of liver cancer in world among men

5. Background: Epidemiology of liver cancer
US:
19,200 new cases and 16,800 deaths
Five year survival rate is 10%
8th leading cause of deaths from cancers in both sexes
6th for men
10th for women
Source: American Cancer Society, 2007
China:
345,844 new cases and 321,851 deaths
accounts for over 53% of all liver cancer cases and deaths worldwide
3rd most common cancer among men
Most common cause of death from cancer among men
Source: GLOBOCAN 2002

6. Background: Risk factors for liver cancer
Hepatitis B virus:
350 million people chronically infected worldwide
About two-thirds of liver cancers in China and Southeastern Asia are attributed to HBV infection
Chronic carriers have a 20-fold increase in risk compared with non-carriers
Major pathways by which HBV infection increases risk for liver cancer are:
(1) viral DNA integration
(2) oncogenic proteins
(3) inflammation

7. Background: Risk factors for liver cancer
Aflatoxin B1:
Toxin found in mildewed grains and nuts
Bioactivated intermediate AFB1-exo-8,9-epoxide has carcinogenic effect
Adducts associated with increased risk of liver cancer
Associated with a specific mutation in codon 249 of p53 tumor suppressor gene
Potential multiplicative interaction with Hepatitis B viral infection (HBV)

8. Background: Metabolism of aflatoxin B1
AFB1
AFB1-exo-8,9-epoxide
AFM1
AFQ1
AFB1-endo-8,9-epoxide
dietary intake
CYP3A4
(CYP1A2)
DNA-adducts
glutathione-AFB1 conjugate
AFB1-8,9-dihydrodiol
[phenolate resonance form]
protein adducts
excretion
GST-μ,
(GST-θ)
+ glutathione
H2O
(mEH)
CYPs

9. Background: Other risk factors: Potential protective factors
Hepatitis C virus
Alcohol consumption
Tobacco smoking
Contaminated drinking water (microcystins)
Potential protective factors
Antioxidants
Dietary nutrients
Selenium

10. Background: IFNA17 Located at position 9p22
Encodes interferon, alpha 17
Has viral inhibitory and viral anti-proliferative effects
Interferon, alpha investigated as a treatment for HBV and HCV infection and prevention of liver cancer among HBV infected individuals
IFNA17 has a polymorphic site that results in either an arginine or isoleucine amino acid in codon 184
The 184Arg allele has a higher frequency in Chinese populations (~50%) than in other populations (<35%)
Studied in cancers that have a viral component, including cervical cancer (papillomavirus) and nasopharyngeal cancer (Epstein-Barr virus)

11. Objectives Overall objective:
Gain insight into the mechanism of interaction observed between aflatoxin and HBV infection
Hypothesis:
AFB1 may differentially suppress IFNA17 protein activity, thereby increasing a person’s susceptibility to the sequelae of HBV if chronically infected and increasing the risk for liver cancer
Specific Aims:
Assess the independent effects of IFNA17 Ile184Arg polymorphic site on liver cancer risk
Explore the joint effects and three-way interaction among HBsAg-positivity, AFB1-albumin adduct level, and IFNA17 polymorphisms on the development of liver cancer

12. Research Design and Methods

13. Study Design
Population-based case-control study with 204 incident liver cancer cases (57% of all cases) and 415 randomly selected healthy population controls (89% response rate) in Taixing City, China
Collected epidemiologic data and blood specimens
IFNA17 genotyped using PCR-RFLP
Markers used to assess HBV chronic infection and aflatoxin B1 exposure (and HCV infection)

14. Taixing City, China
Located on the east bank of the Yangtze River in middle of Jiangsu province
Consists of 24 small villages, with estimated population of 1.28 million (660,000 males and 627,000 females), most of whom are farmers
Has a high rate of alimentary cancer, among the highest in the world
Has a tumor registry
After esophageal cancer, liver cancer is the second largest cause of deaths from cancers
In 2000, crude incidence rates for top three cancers (esophageal), 55.6 (liver), 54.8 (stomach) per 100,000
Incidence rate of liver cancer for males (84.6/100,000) is over three times the rate for females (25.0/100,000)

15. Taixing City, China
Taixing City

16. Exposure Marker: HBV
Different markers used to assess extent of infection with HBV
Detection of HBV surface antigen (HBsAg) used to assess new and chronic infections
Enzyme-linked immunosorbant assay (ELISA) used to detect HBsAg in serum

18. Exposure Marker: Aflatoxin B1
AFB1-exo-8,9-epoxide intermediate binds to DNA and proteins
Aflatoxin-albumin adduct detection to assess aflatoxin exposure
Competitive ELISA used to detect aflatoxin-albumin adducts in plasma

19. Statistical Analysis: Model
Unconditional logistic regression model
Complete analysis was used and missing data for independent variables were not imputed
For potential confounders that were missing a large amount of data (>10%), like BMI, we imputed the median of controls by sex
When aflatoxin B1 (~10% missing) was included as a potential confounder in a model, missing data was imputed using the median of controls

20. Results

21. Demographic data: Average (SD) age, BMI, and smoking pack-years of cases and controls

22. Demographic data: Gender, education, and alcohol consumption

23. Main Effects of HBsAg, AFB1 levels, and IFNA17 on liver cancer development
Variables
Case
Control
Crude
Age & Sex Adjusted
Fully Adjusted**
N (%)
OR (95%CI)
HBsAg - 72
(35.3)
312
(75.4) 1 +
132
(64.7)
102
(24.6)
5.61 ( )
5.21 ( )
5.68 ( )
AFB1
Mean (SD)
508.1
(328.7)
426.2
(250.4)
<247 33
(18.1) 94
(24.9) 46
(25.3)
1.39 ( )
1.38 ( )
1.15 ( ) 42
(23.1) 95
(25.2)
1.26 ( )
1.27 ( )
1.19 ( )
>545.1 61
(33.5)
1.85 ( )
1.75 ( )
1.63 ( )
p(trend)=0.031
p(trend)=0.055
p(trend)=0.109
IFNA17 II
(17.4)
(24.5) RI
104
(54.7)
193
(50.4)
1.54 ( )
1.49 ( )
1.67 ( ) RR 53
(27.9) 96
(25.1)
1.57 ( )
1.58 ( )
1.99 ( )
p(HW)=0.878
p(trend)=0.104
p(trend)=0.102
p(trend)=0.037
RI&RR
157
(82.6) 
289  
(75.5) 
1.55 ( )
1.52 ( )
1.77 ( )
**Model includes age, sex, BMI, education, alcohol consumption, tobacco smoking, HBsAg, imputed AFB1 levels, anti-HCV

24. Interaction between HBV and AFB1 and IFNA17
HBsAg
Case
Control
Crude
Age & Sex Adjusted
Fully Adjusted**
N (%)
OR (95%CI)
AFB1
<247 - 12
(6.6) 69
(18.4) 1 19
(10.4) 67
(17.8)
1.63 ( )
1.64 ( )
1.72 ( ) 15
(8.2) 71
(18.9)
1.22 ( )
1.22 ( )
1.34 ( )
>545.1 17
(9.3) 77
(20.5)
1.27 ( )
1.26 ( )
1.15 ( ) + 21
(11.5) 25
4.83 ( )
4.61 ( )
6.43 ( ) 27
(14.8)
(7.2)
5.75 ( )
5.30 ( )
4.68 ( ) 24
(6.4)
6.47 ( )
6.20 ( )
6.65 ( ) 44
(24.2) 16
(4.3)
15.82 ( )
13.75 ( )
16.72 ( )
1ORint (95%CI)=
0.73 ( )
0.70 ( )
0.42 ( )
2ORint (95%CI)=
1.10 ( )
1.10 ( )
0.77 ( )
3ORint (95%CI)=
2.58 ( )
2.38 ( )
2.27 ( )
IFNA17 II 13
(6.8) 66
(17.3)
RI&RR 50
(26.3)
220
(57.6)
1.15 ( )
1.14 ( )
1.34 ( ) 20
(10.5)
(7.1)
3.76 ( )
3.49 ( )
3.99 ( )
107
(56.3)
(18.1)
7.87 ( )
7.17 ( )
9.18 ( )
ORint (95%CI)=
1.81 ( )
1.81 ( )
1.71 ( )
**Model includes age, sex, BMI, education, alcohol consumption, tobacco smoking, imputed AFB1 levels, anti-HCV; 1ORint for AFB1 ( fmol/mg) and HBsAg; 2ORint for AFB1 ( fmol/mg) and HBsAg; 3ORint for AFB1 >545.1 fmol/mg) and HBsAg

25. Effects of IFNA17 stratified by HBsAg
HBsAg
Crude
Age & Sex Adjusted
Fully Adjusted**
OR (95%CI)
IFNA17 -
1.15 ( )
1.11 ( )
1.35 ( )
 (RI&RR vs. II) +
2.09 ( )
2.08 ( )
2.19 ( )
**Model includes age, sex, BMI, education, alcohol consumption, tobacco smoking, imputed AFB1 levels, anti-HCV
Effects of HBV and IFNA17 stratified by AFB1
AFB1
Crude
Age & Sex Adjusted
Fully Adjusted**
OR (95%CI)
HBsAg
<247
4.83 ( )
4.72 ( )
7.65 ( )
 (Pos. vs. Neg.)
3.53 ( )
3.14 ( )
2.77 ( )
5.33 ( )
5.27 ( )
5.89 ( )
>545.1
12.46 ( )
12.24 ( )
18.34 ( )
IFNA17
0.52 ( )
0.55 ( )
0.26 ( )
  (RI&RR vs. II)
1.62 ( )
1.21 ( )
2.85 ( )
3.27 ( )
3.11 ( )
5.89 ( )
1.19 ( )
1.19 ( )
1.42 ( )
**Model includes age, sex, BMI, education, alcohol consumption, tobacco smoking, HBsAg, anti-HCV

26. Interaction between HBsAg and IFNA17 stratified by AFB1
Case
Control
Crude
Age & Sex Adjusted
Fully Adjusted** N
OR (95%CI)
<388.9 - II 8 26 1
RI&RR 20 99
0.66 ( )
0.63 ( )
0.70 (0.24 + 9 13
2.25 ( )
2.04 ( )
2.07 ( ) 37
3.25 ( )
2.81 ( )
3.45 ( )
ORint (95%CI)=
2.20 ( )
2.20 ( )
2.39 ( )
>388.9 5 34 25
104
1.63 ( )
1.62 ( )
2.09 ( ) 11
8.31 ( )
8.07 ( )
9.22 ( ) 57 27
14.35 ( )
13.88 ( )
21.80 ( )
1.06 ( )
1.06 ( )
1.13 ( )
**Model includes age, sex, BMI, education, alcohol consumption, tobacco smoking, HCV

27. Discussion

28. Findings summarized Main Effects: Possible Interactive Effects:
Strong association between liver cancer and HBsAg
Moderate association between liver cancer and aflatoxin B1 and IFNA17 R allele
Possible Interactive Effects:
HBV-AFB1
HBV-IFNA17
AFB1-IFNA17
HBV-AFB1-IFNA17

29. IFNA17
Genotype frequencies are similar to previous studies in Chinese populations
No previous studies have evaluated association between IFNA17 and liver cancer
184Ile allele, the lower-risk allele for our study, was previously found to be positively associated with cervical and nasopharyngeal cancers
Difference in risk alleles may be due to differences in their specific activities, i.e. Ile protein product may have more antiviral activity against HBV/HCV, whereas Arg protein product may have more against human papillomavirus and Epstein-Barr virus

30. IFNA17 Positive results may be due to: 1. False positive
2. Direct functional involvement with HCC development
3. Linkage disequilibrium with a nearby risk gene (like IFNA10 or p16)

31. Interpretation of HBV, AFB1, and IFNA17 Joint Effects
AFB1 may negatively interact with IFNA17, leading to a differential decrease in protein function, resulting in a decreased resistance against HBV and increasing risk for the development of liver cancer

32. Limitations Recall bias Selection bias Reporting bias
Subjects’ awareness of disease status may alter recall of past exposures
Selection bias
Selection of patients with less advanced and aggressive cancers
Reporting bias
Behaviors or habits carry social stigma, like smoking and alcohol drinking
Confounding by indication
Since blood samples were collected after diagnosis, cases may have altered their diet to contain less AFB1

33. Strengths Population-based study design Relatively large sample size
controls were randomly selected from base population from which cases arose
Relatively large sample size
Detailed and extensive questionnaire
dietary habits, smoking, alcohol
Racially homogeneous population
race would not be a potential confounder or effect modifier

34. Significance – Public Health Applications
The associations and joint effects for IFNA17 have never been previously studied in liver cancer
Early detection of liver cancer and identification of high-risk individuals for intervention
Prevention strategies:
HBV vaccine
Control intake of foods that typically have higher levels of AFB1 and modify storage condition of food to prevent mold growth
Chemoprevention of liver cancer:
Interferon mixtures are currently under study to prevent liver cancer among HBV chronic carriers
Oltipraz protects against AFB1-induced liver cancers by inhibiting phase I enzymes and increasing phase II enzymes

35. Acknowledgements Collaborators: Dr. Zuo-Feng Zhang Dr. Regina Santella
Dr. Li-Na Mu
Dr. Shun-Zhang Yu
Dr. Qing-Wu Jiang
Dr. Wei Cao
Dr. Xue-Fu Zhou
Dr. Bao-Guo Ding
Dr. Ru-Hong Wang
Dr. Jinkou Zhou
Dr. Lin Cai
Mr. John Garcia
Laboratories at UCLA:
Dr. Steven Dubinett
Dr. Robert Lehrer
Dr. John Timmerman
Dr. Gang Zeng