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Molecular Pathogenesis of
Hepatocellular Carcinoma:
Emphasis on HBV

Pei-Jer Chen
 National Taiwan University and Hospital
HCC: Prevalence in the World
Gastroenterology. 132(7): 2557-76 (2007)
Gastroentrology 2003;124:105-117
Liver cirrhosis and HCC
Sequence of events leading to malignant transformation of hepatocypes
Beta-catenin
P53
Genomic instability ?
cirrhosis
Cycles of selecting
Viral variants
modified by Buendia MA, 2002
Semin Liver Dis. 2007 Feb;27(1):55-76
Liver Cancer and Hepatitis
Viruses

HCC ranks 5th of human cancers in the
world.
 Two-thirds of HCC cases in Asia, due to a
prevalent chronic HBV infection.
 Universal vaccination programs against
hepatitis viruses is the best way, as shown
by HBV.
HBsAg carrier rate
Immunization
cohort
Non-immunization
cohort
25
20
15
10
5
2
4
6
8 10 12 14 17
30
Age (yr)
40
50
60
Liver Cancer and Hepatitis
Viruses

Universal vaccination programs began 20
years ago, it eliminates a lot of carriers from
children. However, for adults cohort (not
receiving vaccination) there are still about
300 millions HBV carries at risk to develop
liver cancer.
Sequence of events leading to malignant transformation of hepatocypes
cirrhosis
Cycles of Selecting
Cycles
of selecting
Viral
variants
Viral variants
modified by Buendia MA, 2002
HBV Variants: Evolution from Chronic Infections
Immune escape
Variants ?
1896A variant:
Pre-core
Modified from Hunt CM, Hepatology 2000
1762T/1764A variant:
Basal Core Promoter
Evolution of HBV in the children:
Decreasing proportion of wild-type
Prevalence of HBV pre-core 1896 and BCP
1762/1764 mutants by age
100%
90%
Prevalence (%)
80%
31.2
14.6
21.9
70%
60%
34.2
30.5
14.5
38.4
26.1
50%
40%
30%
11.3
15.7
13.0
8.0
12.6
23.4
22.0
20.0
30-39
40-49
50-59
15.5
20%
10%
13.8
Precore G1896A
alone
BCP
A1762T/G1764A
alone
19.6
Both Precore and
BCP predominant
mutants
13.7
Either mixed type
on precore or BCP
mutants
0%
Age
Both wild-type
60-65
HBV variants and HCC risk
Significance of New variants
Evolving from the Patients

May differ from wild-type at initial
infections.
 Different immunogenicity ?
 Different infectivity ?
 Different carcinogenecity potential.
HBV and Host

Among HBV infected patients, about twothirds remain healthy carriers (without
hepatitis activities) for their life-time.
 The other one-third succumb to liver
cirrhosis or HCC.
 Cases-Control--- Genetic association study
Viral Gene Proteins (Wild type or Variants)
+
Host Gene Products
(Wild type or Mutant)
Self-perpetuating
pathways promoting
cell regenerations, survival
and invasiveness
Familial Cancer:
Statistical Power of Multiplex Familial
Cancers
Relatives of HBsAg-positive HCC with familial History
Compared with those without familial History
case families control families odds ratio
All relative
HCC
Liver Cirrhosis
Simplex Families
LC
OR
5.6%
6.23
3.3%
1.9%
1.3%
0.8%
2.57
2.29
Multiplex Families Control Families
13.1%
15.30
2.4%
1
(MH Yu, et. al.)
Searching for Hereditary Components of HBVrelated HCCs: Adopting the Amsterdam Criteria

Amsterdam criteria


The Amsterdam criteria identify families likely to have Hereditary
nonpolyposis colorectal cancer (HNPCC).
At least 3 relatives with an HNPCC-associated cancer: colorectal
cancer, or cancer of the endometrium, small intestine, ureter or renal
pelvis.
One patient should be a first degree relative of the other two
At least two successive generations should be affected
At least one tumour should be diagnosed <50 years of age

Only 2-3% of HCC cases meeting the criteria.



TLCN: Taiwan Liver Cancer Networking
30/1/2008
Hospital
Register No. Tumor tissue Blood
Paraffin block
VGH TaiChung
393
351
346
298
VGH Kaohsiung
690
171
673
177
CGMH Kaohsiung 592
336
565
333
NTUH
507
287
333
238
CGMH Linko
498
263
279
304
Total
2680
1408
2196
1350
Phenotype distribution
Groups
SEX
Variable
N
Mean
Std Dev
Median
Minimum
Maximum
24
57.04
7.2
55.5
44
69
7
53.43
5.74
54
44
63
31
56.23
6.98
55
44
69
AGE
50
73.88
10.49
74.97
30.83
91.27
GOT
50
24.44
7.08
23
13
54
GPT
50
19.54
12.18
15
8
73
AGE
30
73.36
10.9
75.33
38.06
87.47
GOT
30
22.87
8.99
20.5
11
50
GPT
30
15.6
9.45
12
4
42
AGE
80
73.68
10.58
75.23
30.83
91.27
GOT
80
23.85
7.83
22
11
54
GPT
80
18.06
11.33
13.5
4
73
AGE
115
74.01
9.53
74.75
22.96
92.36
GOT
115
25.92
9.76
23
11
74
GPT
115
21.2
14.57
17
6
108
AGE
117
75.16
8.25
75.38
38.06
93.56
GOT
117
27.31
16.31
23
11
129
GPT
117
22.34
27.29
15
4
239
AGE
232
74.59
8.91
75.02
22.96
93.56
GOT
232
26.62
13.46
23
11
129
GPT
232
21.78
21.89
16
4
239
Male
31 Cases
Female
AGE
Total
MALE
80 controls
No family history
HBsAg(-)
Anti-HBs(+)
Anti-HBc(+)
Anti-HCV(-)
Female
Total
Male
232 controls
Female
Total
The Affymetrix Human SNP Array 6.0 features more than 1.8 million markers
for genetic variations.
- 906,600 SNPs.
- 946,000 probes for CNVs.
Programs for genome-wide CNV detection.
• Affymetrix Genotyping Console
• HelixTree Copy Number Analysis Module (CNAM)
• Partek's Genomics Suite

Strong predictors of diabetes were a family history of the disease,
an increased body-mass index, elevated liver-enzyme levels,
current smoking status, and reduced measures of insulin
secretion and action. Variants in 11 genes (TCF7L2, PPARG, FTO,
KCNJ11, NOTCH2, WFS1, CDKAL1, IGF2BP2, SLC30A8, JAZF1,
and HHEX) were significantly associated with the risk of type 2
diabetes independently of clinical risk factors.

The addition of specific genetic information to clinical factors
slightly improved the prediction of future diabetes, with a slight
increase in the area under the receiver-operating-characteristic
curve from 0.74 to 0.75; however, the magnitude of the increase
was significant (P=1.0x10–4). The discriminative power of genetic
risk factors improved with an increasing duration of follow-up,
whereas that of clinical risk factors decreased.


Conclusions As compared with clinical risk factors alone,
common genetic variants associated with the risk of diabetes had
a small effect on the ability to predict the future development of
type 2 diabetes. The value of genetic factors increased with an
increasing duration of follow-up.
NEJM November 20
Outcomes of Infection Diseases and Gender:
Science V.298,2002
Gender Disparity: Causes

Susceptibility of males to HBV-related
carcinogenesis
 Protection of females against HBV-related
carcinogenesis
 Roles of sex hormones are implicated.
Higher risk of HCC among male carriers with higher testosterone
Or androgen receptor genes with higher activities.
Reduced HCC incidence in mice lacking hepatic AR with
little change of serum testosterone
A
B
36 wks
Ma et al., GASTROENTEROLOGY, 2008
Gender effect of viral etiology of HCC in Taiwan
HBsAg/anti-HCV
Gender Ratio
(Male:Female)
Age (mean)
+/-
7.7
52.2
-/+
1.5
63.5
(n=1474
Dr. SN Lu)
HBV genome organization
Modified from Hunt et al
Cancer Research V.63 P.7553-7562
Hypothesis: HBx Activation of AR Axis and Potency
Androgen / R1881
HBx
Cytoplasm
AR
AR
Nucleus
ARE
ha
so
n
6.
de
xa
m
et
e
10
0n
M
5n
M
30
nM
ad
io
l3
og
en
5.
es
tr
4.
an
dr
2n
M
0.
5n
M
og
en
og
en
3.
an
dr
2.
an
dr
A
1.
m
oc
k
Relative luciferase activity
Fig.1
1200
reporter
AR
1000
HBx
AR+HBx
800
600
400
200
0
Fig.7
Androgen / R1881
(not estradiol, or glucocorticoid etc.)
HBx
Cytoplasm
Calcium signaling
Src kinase
PI3K (p85)
AR
AR
Nucleus
ARE
Cyclosporine A
PP2
HBV genome organization
Modified from Hunt et al
P = 0.028
HBsAg level (S/N)
109
HBV Titer
108
107
106
N = 20
105
Relative Luciferase Activity
104
3000
N = 20
M
F
P = 0.008
N=4
2500
1500
N=6
500
0
P < 0.001
200
150
100
N = 20
50
0
N = 20
M
F
100
p = 0.038
80
60
15
10
5
N = 19
0
N = 19
M
2000
1000
250
Relative HBV Transcripts Amounts
Gender difference of HBV factors in our HBV transgenic mice
M F
F
Androgen involved in regulating HBV titer and HBsAg level
Castration
Male HBV tg mice
20 days
40 days
Bleeding
Bleeding
Bleeding
P < 0.001 P = 0.003
Normal
100
(N=6)
50
Castrated
(N=6)
Relative HBV Titer (%)
Relative HBsAg (%)
150
0 day
250
P = 0.007
P = 0.006
200
150
Normal
100
(N=6)
50
Castrated
(N=6)
0
0
0
20
40
(day)
0
20
40
(day)
AR(+R1881) may directly bind to HBV Enhancer I
HepG2(2.2.15)
PCR primer set
Enh I region
GAPDH
Input / IP
Lenti
R1881
-
-
GFP
- +
+
+
GFP
R1881
-
AR -
AR
AR
GFP
Lenti
+
GFP -
+
b-actin -
200 bp 100 bp -
200 bp 100 bp Enh I region
Enh II region
Other region
PCR primer set
AR
-
+
750
1150
Luc gene
TAGAAAACTTCCTGTTAACAG
TAGAAATGTTCCTCATAACAG
Candidate ARE site
I-3
WT
Mut
Relative Activation Fold
One ARE site in HBV Enh I-3 region is determined
80
I-3 WT － R1881
I-3 WT ＋ R1881
I-3 Mut － R1881
I-3 Mut ＋ R1881
60
82 %
40
20
0
AR
-
+
Host factor
ARE
Enh I
Enh II
HBV
Virus factor
HBV mRNA
Protective Effect of Estrogen against HCC in Females:
HEPATOLOGY Vol.38, No. 6, December 2003
HEPATOLOGY Vol.38, No. 6, December 2003
A
B
Paried
Liver tissues
n
No stratification
Fold Change
p-value
Mean ± SD
80
5.59 ± 10.42
<0.0001 ***
HCC (all)
40
7.87 ± 14.09
0.0065 **
HCC (HBV)
40
3.30 ± 3.26
0.0003 ***
HCC (HCV)
16
1.11 ± 0.84
0.8682
FNH
*, P < 0.05; **, P < 0.01; ***, P < 0.001.
n
Female
Mean ± SD
40
20
20
7
9.17 ± 13.78
13.68 ±18.23
4.66 ± 3.80
1.30 ± 1.11
Stratified by gender factor
Male
Fold Change
n
Mean ± SD Female/Male
40
20
20
9
2.00 ± 1.90
2.06 ± 1.97
1.95 ± 1.87
0.97 ± 0.58
4.58
6.65
2.39
1.34
p-value
0.0023 **
0.0104 *
0.0079 **
0.4495
(Fig. 1)
An inverse correlation of miR-18a and ERa levels in female HCCs
ESR1 as a cellular target of miR-18a.
 ERa is a potential cellular target of miR-18a
Luciferase reporter constructs fused with the 3UTR of ERa gene
A
C
1
B
***
2
3
**
**
*
***
**
*
**
*
*
**
***
(Fig. 3)
Over-expression of miR-18a decreases the endogenous ERa protein
As effective as ER-siRNA
A
B
C
D
Increased miR-18a stimulates the proliferation of hepatoma cells
but represses proliferation of breast cancer cells
A
B
Huh-7
***
C
SNU-387
***
**
***
**
***
**
***
MCF-7
***
***
***
***
Gastroenterology. 132(7): 2557-76 (2007)
Prospect

Significance of new viral variants in
pathogenesis.
 Host genetic backgrounds in familial cases -- an extreme-case study example.
 Interesting interactions among infection
agents and gender, especially sex hormone
pathways.
 New targets for future prevention or therapy.
Acknowledgments

Prof. Ding-Shinn Chen, Ming-Yang Lai,
Jia-Horng Kao (HRC, NTUH).
 Dr. Shiou-Hwei Yeh’s group.
 Prof. CJ Chen, MW Yu. Adademia Sinica
and School of Public Health.
 Dr. CL Chen and SF Huang.
 NSC and DOH for grants support.
Patient ID
Pri-miR-18a Pre-miR-18a
miR-18a
ERa protein ERa RNA
B
2.5
13
15
40
41
11
20
33
35
16
18
37
42
12
17
19
39
14
34
36
38
0.9
0.8
0.7
1.0
1.1
1.5
1.3
1.4
1.5
1.0
0.4
1.6
1.6
0.8
1.2
1.2
1.2
2.1
0.9
0.7
10.3
6.9
18.3
5.8
25.7
13.3
7.5
13.1
7.2
3.9
2.1
3.9
2.0
3.3
1.5
4.4
1.6
2.9
2.7
0.9
15.6
17.7
11.4
12.6
32.5
13.8
7.7
7.7
5.1
5.2
3.2
3.5
1.7
2.0
2.5
2.7
1.3
1.0
1.7
0.4
0.1
0.2
0.3
0.3
0.2
0.3
0.2
0.4
0.5
0.6
0.8
0.7
1.1
0.8
0.8
0.9
1.0
1.1
0.9
0.9
1.4
1.8
1.1
0.9
0.9
1.0
0.5
1.3
0.8
0.8
1.2
1.2
1.0
1.0
1.2
1.0
1.0
0.9
1.1
1.9
1.4
0.8
1.3
1.3
1.0
0.8
0.6
0.8
0.7
0.8
0.3
0.6
0.9
1.4
1.2
1.1
1.0
1.1
1.3
1.1
0.7
0.4
0.9
0.6
0.6
FNH
69
70
71
73
74
Pri-miR-18a (T/NT)
HCC
R2 = 0.022
2.0
1.5
1.0
0.5
0.0
0
10
20
30
40
30
40
miR-18a (T/NT)
C
30
Pre-miR-18a (T/NT)
A
R2 = 0.433
25
20
15
10
5
0
0
10
20
miR-18a (T/NT)
(Fig. 5)
A
B
C
D
(Fig. 2)
A
B
C
D
(Fig. 4)