ORIGINAL ARTICLE – TRANSLATIONAL RESEARCH AND BIOMARKERS
Recurrence and Poor Prognosis Following Resection of SmallHepatitis B-Related Hepatocellular Carcinoma Lesions AreAssociated with Aberrant Tumor Expression Profiles of Glypican3 and Osteopontin
Ming-Chin Yu, MD1,2, Yun-Shien Lee, PhD3,4, Sey-En Lin, MD, PhD5, Hsiang-Yao Wu, MS2,
Tse-Ching Chen, MD, PhD6, Wei-Chen Lee, MD1, Miin-Fu Chen, MD1, and Chi-Neu Tsai, PhD2
1Department of Surgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan; 2Graduate Institute of Clinical Medical
Sciences, Chang Gung University, Taoyuan, Taiwan; 3Department of Biotechnology, Ming Chuan University, Taoyuan,
Taiwan; 4Genomic Medicine Research Core Laboratory, Chang Gung Memorial Hospital, Taoyuan, Taiwan; 5Department
of Pathology, Taipei Medical University Hospital, Taipei, Taiwan; 6Department of Pathology, Chang Gung Memorial
Hospital, Chang Gung University, Taoyuan, Taiwan
ABSTRACT
Background. Early detection and following appropriate
treatments of hepatocellular carcinoma (HCC) is still the
gold standard for favored outcome of HCC patients; nev-
ertheless, a small portion of hepatitis B virus (HBV)-
related small HCC (\5 cm) patients got poor prognosis.
Furthermore, the study for small HBV–HCC was limited.
Therefore, the aim of this study was to explore the potential
genetic signature for HBV-related small HCC as novel
prognostic factors.
Methods. We examined expression profiles of HBV-rela-
ted small HCC using an Affymetrix U133A GeneChip,
evaluated differential gene expression by quantitative real-
time polymerase chain reaction (qRT-PCR), and finally
validated these expression patterns by immunohistochem-
istry (IHC).
Results:. A total of 57 genes were differentially expressed
between tumor and normal parts (n = 20 pairs) using
Affymetrix U133A chip, and 16 genes were further eval-
uated by qRT-PCR. The result was compatible with the
finding of oligonucleotide microarray (Pearson’s correla-
tion, r = 0.87). Furthermore, the expression pattern in
HCC tissue by IHC in another group of small HBV–HCC
(n = 100) showed overexpression of either osteopontin
(OPN) or glypican 3 (GPC3) is an independent prognostic
factor for disease-free survival (DFS) in HBV-positive
small HCC (P \ 0.01 and 0.03, respectively). Long-term
DFS and overall survival (OS) for small HBV–HCC
patients with high risk (both elevated GPC3?/OPN?) were
DFS 0%, OS 0%, respectively; on the other hand, DFS and
OS in patients with moderate (only 1 gene elevated) or low
(OPN-/GPC3-) risk were 35.0 and 46.5%, respectively.
Conclusions. Elevation of both OPN and GPC3 may act as
an adverse indicator for HBV-related small HCC patients
after curative resection.
Primary liver cancer, hepatocellular carcinoma (HCC), is
one of the most common cancers worldwide. Globally, it is
the third highest cause of cancer mortality, having a yearly
fatality ratio of approximately 1.1 In Taiwan, HCC was
ranked in the annual report of the Department of Health
(DOH) as the first cause of cancer mortality in men and the
second in women.2 The main etiology of HCC is chronic
infection with hepatitis B or C virus (HBV or HCV). Tai-
wan has one of the highest prevalence rates in the world;
about 15–20% of the population are chronic carriers of
HBV, and the relative risks of hepatocarcinogenesis have
Electronic supplementary material The online version of thisarticle (doi:10.1245/s10434-011-1946-2) contains supplementarymaterial, which is available to authorized users.
� Society of Surgical Oncology 2011
First Received: 1 February 2011
M.-F. Chen, MD
e-mail: [email protected]
C.-N. Tsai, PhD
e-mail: [email protected]
Ann Surg Oncol
DOI 10.1245/s10434-011-1946-2
been reported to be 9.6 for HBV surface antigen (HBsAg)-
seropositive patients and 60.2 for those positive for HBsAg
and HB envelope antigen (HBeAg).3 Recently, a large-scale
cohort study—the risk evaluation of viral load elevation and
associated liver disease/cancer-hepatitis B virus (REVEAL-
HBV) study—demonstrated that having a serum level
greater than 104 copies/ml of HBV–DNA upon entry into
the study was an important risk factor for HBV hepatocar-
cinogenesis, independent of HBe Ag seropositivity.4 HCC
commonly occurs between the ages of 50 and 60 years in
Taiwanese, at a time of life when these patients are a main
economic support for their families.5 Therefore, HBV-
related HCC is a major public health threat that has a sig-
nificant socioeconomic impact in our country.
Prognosis for these patients remains poor despite many
advances in HCC treatment regimens; therefore, predicting
clinical outcomes for patients is a challenge for clinicians
and researchers. Retrospective clinical analyses have been
performed in eastern and western countries regarding
patients who presented with pathological factors such as
multiplicity, satellite nodules, vascular invasion, and lack
of tumor encapsulation.6–9 Although partial hepatectomies
were potentially curative treatments, the recurrence rate of
all resectable HCC was still more than 75% in long-term
follow-up.8,10 For recurrence of small HCC, most reports
of recurrence were 50–70%, and long-term outcome is
acceptable.11,12
Despite the odds, early detection, especially of small
(\5 cm) HCC lesions (small HCC) coupled with appro-
priate treatment is very important for good prognosis.
However, this imposes diagnostic challenges for clinicians
because of the low sensitivity of currently available
screening biomarkers, such as a-fetoprotein (AFP), des-c-
carboxyprothrombin (DCP), and lens culinaris agglutinin
A-reactive fraction of AFP (AFP-L3).13 There are no ‘‘gold
standard’’ serum markers for small HCC at the present
time, and therefore the search for potential biomarkers for
early diagnosis or surveillance is an ongoing task.14
To investigate the roles of genetics or signaling pathway
in HCC carcinogenesis, methods such as comparative
genomic hybridization, transcriptome microarray, and
proteomics have been used. In recent years, oligonucleo-
tide microarray and systemic biology have been powerful
tools for finding potential useful biomarkers for clinical
application in signaling pathways.15–17 Most previous
studies analyzed gene signatures involved in vascular
invasion, recurrence, methylation, single or multiple nod-
ules, and differences between HBV- and HCV-related
HCC; however, only a few reports have addressed differ-
ential gene expression in small or early HCC.18–30 In this
study, we analyzed molecular signatures of HBV-related
small HCC by using Affymetrix human U133A Gene-
Chips. The molecular genetic signature was further
validated by quantitative real-time polymerase chain
reaction (qRT-PCR) and IHC analysis. In addition, we also
evaluated 2 independent significant prognostic factors in
survival analysis from the microarray genetic signatures in
early HBV–HCC patients.
PATIENTS AND METHODS
Patients
Microarray Studies From 2008 to 2009, 20 patients with
HBV-related HCC who underwent partial hepatectomy
were enrolled as the first cohort. Informed consents were
obtained under the approval of the Institutional Review
Boards (IRB 97-1371C) of Chang Gung Memorial Hospital
(CGMH). Inclusion criteria were defined as presence on an
image study (including sonography, computed tomog-
raphy [CT], and angiography) of a single hepatic lesion of
less than 5 cm. Patients with positivity in a resection
margin and HCV carriers were excluded, as were patients
who had unresectable disease, synchronous cancers, distant
metastasis, or prior history of another malignancy. Patients
with small HCC and/or decompensated liver cirrhosis were
suggested for liver transplantation and excluded in this study.
Noncancerous control samples were selected 3 cm away
from HCC lesions. Demographic data for these patients are
shown in Supplementary Table 1.
Immunohistochemical Studies Tumor specimens were
obtained by partial hepatectomy from another 100
patients with HBV-related small HCC recruited
consecutively at our institution from 2000 to 2008 as the
second cohort (Supplementary Table 2). The clinical
specimen used for PCR validation is the same as samples
applied for microarray studies (as training set in this study).
The formalin-embedded tissues used for IHC staining (as
validation set in this study) were different from samples
applying for microarray and PCR experiment. Clinical and
pathological data were collected; all patients had regular
follow-up examinations. Tumor recurrence was diagnosed
by elevated AFP levels or when dynamic CT revealed
typical features. Treatment for recurrence included
transarterial chemoembolization (TACE), radiofrequency
ablation (RFA), or chemotherapy.
RNA Extraction, Microarray Data Processing, and
Affymetrix GeneChip Analyses
The experimental procedures of RNA extraction and
microarray data processing was as previously described.31
To filter the lower variance genes, 6,252 probe sets were
M.-C. Yu et al.
filtered from the original 22,215 using a standard deviation
[0.5. Unsupervised (principal component analysis [PCA])
and supervised (t test) methods have been used for the
analysis of gene expression data.32 The t tests statistical and
PCAs were performed with MATLAB version 7.4 and Sta-
tistic toolbox version 3.1 (The MathWorks, Boston, MA).33
The differentially expressed genes were selected with paired
t tests. A total of 78 probe sets were selected using the criteria
of undergoing a fourfold change in gene expression with
P \ 0.0001. Some probe sets were annotated with the same
genes; from the 20 sample pairs a total of 59 (42 downreg-
ulated and 17 upregulated) genes were defined as
differentially expressed genes. The profiles of the selected 59
genes were visualized by the Cluster 3.0 and Tree View
programs using average-linkage clustering algorithms.16
qRT-PCR
The first-strand cDNA was synthesized from 5 lg of total
RNA, and 0.5 ll of cDNA was mixed with the Taqman probe
(Assay-on-Demand, Applied Biosystems, Foster City, CA),
RNase-free water, and TaqMan Universal PCR Master Mix.
Real-time PCR was performed according to the manufac-
turer’s protocol. Glyceraldehyde-3-phosphate dehydro-
genase (GAPDH) was used as an internal control. Paired
samples were processed and mean the fold-change of
duplicate samples was calculated. For each normalized
sample, relative gene expression was calculated using the
differences in threshold cycles (Delta Ct, DCt), a calibrated
DCt value (DCt = Ct,internal control - Ct,sample). For quantita-
tion of gene expression levels between tumor and normal
tissue from the same patient, the comparative Ct method (also
known as the 2�DDCt method), where DDCt = DCt,tumor -
DCt,normal, was used. The catalog numbers of the Taqman
probes used for these gene assays are listed in Supple-
mental Table 3.
Immunohistochemistry
Formalin-fixed and paraffin-embedded resection speci-
mens were sectioned to 4 lm in thickness and then
deparaffinized, rehydrated, and processed for antigen
retrieval. The slides were further incubated with appropriate
dilutions of antibodies at room temperature for 1 h; anti-
bodies and dilutions used are listed in Supplemental Table 3.
All tumor and normal tissues were examined by an inde-
pendent pathologist and the expression level was scored on a
scale from -3 (underexpression) to ?3 (overexpression).
Statistical Analysis
The Wilcoxon signed ranks test was used for comparison
of the relative signal intensities of immunohistochemical
staining scores between paired cancerous and normal tis-
sues. Cases and controls were compared using t tests for
continuous variables and the v2 test for categorical vari-
ables. Unconditional logistic regression analysis was used
to calculate odds ratios (ORs) and 95% confidence intervals
(95% CIs). All analyses were performed using Statistical
Analysis Software for Windows, version 8.12 (SAS insti-
tute, Gary, NC).
RESULTS
Differential Gene Expression Profiles in HBV-Related
Small HCC
Differential gene expression patterns between HCC
tumor and normal tissue pairs fell into 2 distinct clusters,
PC1 and PC2, using PCA (Fig. 1a). The goal of PCA is to
reduce the dimensionality of the data matrix by finding new
small set variables, termed principal components, and to
allow the experimental conditions to be compared directly
and visualized in 2 or 3 dimensions.33 In this study, the first
2 principal components can explain 80% of the variance in
the original gene expression data. The highest levels of
differential gene expression had a fourfold change (log
2 [ 2 and P \ 0.0001) between tumor and normal tissue.
In total 59 (78 probe sets) out of 6,252 genes were selected
from array data by volcano plot (Fig. 1b) and are displayed
graphically in Fig. 1c. The most differentially expressed
genes in HCC tumor specimens are shown in Supplemental
Tables 4a and 4b: 17 genes were upregulated and 42 were
downregulated. The most downregulated genes were
involved in oxidation–reduction (the cytochrome P450
gene family: CYP1A2, CYP2A6, CYP2E1, …, etc.),
alcohol metabolism (alcohol dehydrogenase gene family:
ADH1A, ADH1B, ADH1C), lipid metabolism (cholesteryl
ester transfer protein, plasma [CETP], hydroxyacid oxidase
2 [HOA2], phosphoenolpyruvate carboxykinase 1 [PCK1],
and some of the cytochrome P450 gene family), bile acid
catabolic processing (CYP39A1), detoxification (metallo-
thionein [MT]: MT1E, MT1F, MT1G, MT1H, MT1M,
MT1P2, MT1X, MT2A), and the immune response family
(complement component: C9, C8A, C-type lectin domain
family 1, member B [C1EC1B], C-type lectin domain
family 4, member M [CLEC4M]); all of which might
reflect the downregulation of liver function and the
immune response during hepatocarcinogenesis (Supple-
mentary Table 4a).
In contrast, the most upregulated genes were involved
in cell proliferation (abnormal spindle like microcephaly-
associated protein [ASPM], geminin, DNA replication
inhibitor [GMNN], karyopherin alpha 2 [KPNA2],
nucleolar and spindle associated protein 1 [NUSAP1],
Aberrant Gene Expression in Small HBV–HCC
ribonucleotide reductase M2 [RRM2], sex-determining
region Y [SRY]-box 4 [SOX4]), tumor growth signal-
ing pathways (gamma-aminobutyric acid B receptor 1
[GABBR1], glypican3 [GPC3], collagen type I alpha 2
[COL1A2]), response to hypoxia (CD24), chemotaxis/cell
adhesion (osteopontin [OPN], chemokine [C–C motif]
ligand 20 [CCL20], roundabout, axon guidance receptor
homolog 1 [Drosophila], [ROBO1]), and cellular alde-
hyde metabolic processes (aldo–keto reductase family 1,
member B10 [AKR1B10]); all of which might reflect
the uncontrolled nature of cell proliferation involved
in tumor growth (Supplementary Table 4b). To summa-
rize: The most differentially expressed genes in HCC
tumors are involved in abnormal cell proliferation
and chemotaxis/cell adhesion, as well as in repression
of normal liver function and the normal immune
response.
Microarray Validation
Of the 20 paired samples described previously, only 17
offered enough specimens to validate the results of
microarray by qRT-PCR. The most upregulated and
downregulated probe sets were selected; these included 7
upregulated and 9 downregulated genes in the microarray
assay. The results of qRT-PCR for 16 selected genes were
compatible with the corresponding microarray data
(Fig. 2), and the correlation was substantial (Pearson’s
correlation, r = 0.87).
Expression of 8 Selected Genes in 100 HBV-Positive
Small HCC Specimens Validated by IHC Staining
To distinguish specific cell types in the tumor mass
having aberrant gene expression, consecutive tissue sec-
tions from 100 additional patients with HBV-positive small
HCC (as validation set in this study) were subjected to
immunohistochemical staining. The median age of these
patients was 51 (ranging from 24 to 81 years); 90 were
male and 10 female. All were positive for HBs Ag and
negative for anti-HCV. The median tumor diameter was
2.75 cm (range 0.6–5.0 cm) and AFP level was 533 ng/ml
(range 1–14,665 ng/ml). Pathologic variables included:
cirrhosis (67%), microscopic vascular invasion (23%),
satellite lesion (12%), and encapsulation (76%). One
patient died of surgical complications. The median follow-
up was 66.5 months. These data are shown in Supple-
mentary Table 2.
Among the most upregulated and downregulated of 59
genes, the most differentially expressed 8 genes were
selected for validation, including 3 upregulated gene
products (OPN, GPC3, and AKR1B10) and 5 downregu-
lated gene products (CYP2E1, ADH1B, MT, NNMT, and
HAMP). All HCC tumor and normal tissues were exam-
ined by two independent pathologists, and the expression
level was scored on a scale from -3 (underexpression) to
?3 (overexpression). The expression patterns of these
protein are shown in Fig. 3. Association of selected IHC
expression profiles with clinical variables in this cohort
was determined.
0.4
0.3
0.2
0.1
0.0
−0.1
0.1680.1640.1600.1560.1520.148
PC1 (relative units)
PC2 (relative units)
18
16
14
12
10
8
6
4
2
531−1− 43 20−2−4−5
Log2 (T/N)
−Log10 (P value)
FIG. 1 Differential transcripts
distinguish tumor and normal
tissue counterparts in 20 pairs of
HCC samples. a Principle
component analysis using
expression levels of 22,215
probe sets (yellow, normal
counterpart; blue, HCC).
b Selection of the most
differentially expressed
transcripts, based on t tests
(P \ 0.0001) and a fourfold
change in expression (yellowcolor = selected probesets).
c Unsupervised hierarchical
clustering of 59 genes. Profiles
visualized by the Cluster 3.0
and Tree View programs using
average-linkage clustering
algorithms
M.-C. Yu et al.
Elevated GPC3 and OPN Associated with Poor
Prognosis of Small HBV–HCC
To examine if the aberrant expression of 8 proteins
associated with any clinicopathological factors of small
HBV–HCC, we retrospectively analyzed 16 clinical vari-
ables of patients with these genes expression by IHC
scoring systems. Underexpression of CYP2E1 was signif-
icantly associated with a higher grade (P = 0.038),
whereas underexpression of ADH1B was significantly
8
6
4
2
0
−2
−4
−6
−8
Gene expressions(log2 ratio)
AD
H1A
20
15
10
5
0
−5
qRT-PCR( CT)ΔΔ Spearman rho = 0.87
10
Microarray (log2 ratio)OPM
AD
H1B
AD
H1C
CX
CL
12
CX
CL
2
CY
P231
HA
MP
MT
1G
NN
MT
AK
R1B
10
AN
XA
2
CC
L20
CD
24
GPC
3
SPIN
K1 86420−2
FIG. 2 Validation of 16 differentially expressed genes. a Microarray
transcript levels: yellow bars; qRT-PCR assays: blue bars. See text
for calculation methods. Glyceraldehyde-3-phosphate dehydrogenase
(GAPDH) used as internal control in qRT-PCR assays. b Expression
of SPINK1 was as example of correlation between microarray data
and qRT-PCR results (Pearson’s correlation, r = 0.87). X axes, genes
selected from microarray results; Y axes, expression levels for each
gene in qRT-PCR experiment
HAMP
ADH1B
CYP2E1
NNMT
MTs
OPN
AKR1B10
GPC3
(A) (E) (I) (M)
(B)
(C)
(F) (J) (N)
(G) (K) (O)
(D) (H) (L) (P)
Under-expression Under-expressionOver-expression Over-expression
FIG. 3 Expression pattern of 8 selected genes in HCC tumors by
evaluation of immunohistochemical staining. Expression (brownstaining) of CYP2E1, NNMT, and MTs indicated that the proteins
were localized in the cytoplasm of HCC tumor cells; whereas the
expression of GPC3, OPN, HAMP, and ADH1B showed both
cytoplasmic and membranous staining pattern in HCC tumor cells.
The expression level of each proteins was scoring by two independent
pathologists and the scoring for underexpressed (a–d and i–l) or
overexpression (e–h and m–p) of each proteins were showed in this
figure. HAMP hepcidine, ADH1B alcohol dehydrogenase gene family
1B, NNMT nicotinamide N-methyltransferase, CYP2E1 cytochrome
P450 gene family 2E1, MTs metallothionein family, AKR1B10 aldo–
keto reductase family 1, member B10, OPN osteopontin, GPC3glypican3
Aberrant Gene Expression in Small HBV–HCC
associated with a higher indocyanine green retention test at
15 min (ICG), lower AFP, and a lower grade (P = 0.042,
0.043, and 0.046, respectively) (Supplemental Table 5).
Overexpression of OPN was associated with higher
Aspartate aminotransferase (AST) levels, and tumors
without necrosis (P = 0.030 and 0.017, respectively)
(Supplemental Table 5).
Since 14 of the 100 patients had incomplete IHC data,
86 patients were enrolled in Cox proportional hazard
models. Firstly, The 10 clinicopathological variables were
analyzed in Cox proportional hazard models, and only
vascular invasion was the independent prognostic factor
(Table 1). Tumor size and rupture were not incorporated in
analysis because all enrolled cases were less than 5 cm, and
there was no tumor rupture in the series. Secondly,
expression of 8 proteins was analyzed with stratification of
vascular invasion, the significant clinical factors. Only
elevation of OPN or GPC3 were independent prognostic
factors for disease-free survival (DFS) in HBV-positive
small HCC (P \ 0.01 and P = 0.03, respectively)
(Table 2). As shown by Kaplan–Meier plots, long-term
DFS and overall survival (OS) of 10 years for small HBV–
HCC patients dichotomized into high risk (elevated both
OPN and GPC3; GPC3?/OPN?), and moderate (elevated
OPN or GPC3; OPN?/GPC3-; OPN-/GPC3?) or low risk
(decreased OPN and GPC3; OPN-/GPC3-) were DFS 0%,
OS 0% and DFS 35.0%, OS 46.5%, respectively. This
difference in DFS and OS was statistically significant by a
log-rank test (P \ 0.001 and P = 0.003, respectively)
(Fig. 4). Elevated both OPN and GPC3 may act as an
adverse indicator for HBV-related small HCC patients after
curative resection.
DISCUSSION
Treatment following early detection of cancer is
considered essential for good prognosis; however, a
portion of HBV–HCC patients do poorly in spite of
having small tumors at the time of diagnosis. Therefore,
finding an aberrant tumor-specific genetic signature for
potential clinical use remains a focus of research. In this
study, we correlated patients’ clinicopathological char-
acteristics with aberrant gene expression in HBV-positive
small HCC lesions and retrospectively analyzed clinical
outcomes. Our results suggest that clinicians might
consider more aggressive treatments for those patients
having high risks identified in this study and that they
should possibly have more rigorous follow-up after sur-
gical resection.
Heat shock protein 70 (HSP70), GPC3, telomerase
reverse-transcriptase (TERT), serine/threonine kinase 15
(STK15), phospholipase A2 (PLAG12B), LYVE-1, and
survivin have been shown to be prognostic factors by
genome-wide DNA microarray or qRT-PCR.27,30,34 To
improve long-term outcome, the search for validated, novel
biomarkers continues through the wide implementation of
surveillance programs. Using either a genetic or proteomic
approach, several potentially therapeutic molecular targets
have been identified and clinical trials are ongoing;
examples include therapies targeting growth receptors,
vascular endothelial growth factor receptor (VEGF), and
mTOR, for advanced HCC, as systemic or adjuvant treat-
ments.35 Among new molecular medicines, sorafenib,
targeted at VEGF and platelet-derived growth factor
receptor (PDGFR), has proved effective for advanced HCC
treatment in western and eastern countries.36
TABLE 1 Cox proportional hazard models for disease-free survival
(DFS): analysis of clinicopathological factors in 100 HCC patients
Variables HR 95.0% CI P
Vascular invasion (yes vs. no) 3.40 1.56–7.40 \0.01*
Satellite lesions (yes vs. no) 0.87 0.281–2.4 0.73
Edmondson–Steiner grade
(III, IV vs. I, II)
0.59 0.23–1.09 0.08
Cirrhosis (yes vs. no) 1.60 0.76–3.35 0.22
Encapsulation (yes vs. no) 0.70 0.32–1.55 0.38
AFP ([400 vs. B400 ng/ml) 0.71 0.33–1.54 0.39
AST ([72 vs. B72 U/l) 2.04 0.58–7.18 0.27
ALP ([94 vs. B94 U/l) 1.67 0.65–4.29 0.28
ALB (B3.5 vs. [3.5 g/dl) 1.35 0.30–6.07 0.69
Margin involved (yes vs. no) 1.27 0.98–1.65 0.07
AFP a-fetoprotein, AST aspartate aminotransferase, ALP alkaline
phosphatase, ALB albumin
* Indicated statistically significance: P \ 0.05
TABLE 2 Cox proportional hazard models for disease-free survival
(DFS): gene expression analysis
Aberrant gene expression HR 95.0% CI P
HAMP 0.90 0.45–1.78 0.75
ADH1B 0.89 0.43–1.85 0.76
NNMT 1.35 0.52–3.51 0.54
CYP2E1 0.52 0.23–1.18 0.12
MTs 0.61 0.19–1.94 0.41
AKR1B10 0.62 0.32–1.21 0.16
OPN 3.74 1.65–8.47 \0.01*
GPC3 2.18 1.07–4.45 0.03*
HR was compared with overexpression versus underexpression
HAMP hepcidine, ADH1B alcohol dehydrogenase gene family 1B,
NNMT nicotinamide N-methyltransferase, CYP2E1 cytochrome P450
gene family 2E1, MTs metallothionein family, AKR1B10 aldo–keto
reductase family 1, member B10, OPN osteopontin, GPC3 glypican3
* Indicated statistically significance: P \ 0.05
M.-C. Yu et al.
In this study, downregulation of genes related to fatty
acid and alcohol metabolic processes and oxidative
reduction was seen. In alcohol-mediated hepatocarcino-
genesis, ADH and CYP2E1 have been reported to interact
with reactive oxygen species and play a role in DNA
adduction; changes in early HCC lesions were correlated
with clinical outcomes.37 Furthermore, loss of DNA repair
mechanisms occurred in Glycine-N methyltransferase
(GNMT) knockout and aflatoxin B(1)-treated mice,
meaning that DNA adduction and methyltransferase were
affected at an early stage.38 Genes involved in detoxifica-
tion, such as cytochrome P450 family and NNMT, were
downregulated in this study, which may alter the cellular
microenvironment. Interestingly, CYP2E1 was induced
following exposure to alcohol and acetone or in nonalco-
holic steatohepatitis, but decreased expression of CYP2E1
in tumors has been reported to be associated with absence
of a tumor capsule and poorly differentiated HCC.39
GPC3, HSP70, adenylate cyclase-associated protein 2
(CAP2), and glutamine synthetase have been proposed as
early molecular markers for HCC in Japan; GPC3 was
assumed to be an oncofetal protein, a marker of liver
regeneration that is inactive in normal adult liver.40,41
GPC3 also functions as a secretory protein and has been
used as a serum marker (cutoff: 300 ng/l, sensitivity
47.0%, and specificity 93.5%) in HBV-positive HCC
patients.42
OPN was the most upregulated gene in our microarray
and qRT-PCR assays, but only 13 of 98 patients had high
expression in the IHC analysis; these data are compatible
with a previous study in which 24.2% of HCC patients had
upregulated OPN.43 There have been some studies dem-
onstrating that OPN is a useful marker for vascular
invasion, tumor grading, and predicting surgical out-
come.44,45 OPN has been identified as a transformation-
associated protein in some human cancers, such as stomach
and breast, and functions as a metastatic signal in HCC cell
lines.46,47 Furthermore, elevation of serum OPN has been
associated with advanced HCC, and a level of 1.85 log
10 ng/ml was significantly predictive of outcome following
transarterial chemoembolization.48 The current study
demonstrates that OPN can be an independent predictor of
outcome for patients with HBV-positive small HCC.
In conclusion, this study began with an oligonucleotide
microarray, which identified 59 genes undergoing expres-
sion changes early in the development of HBV-positive
small HCC. Microarray results were validated by qRT-
PCR and IHC analysis. In a cohort analysis of DFS,
aberrant tumor expression of OPN and GPC3 were prog-
nostic factors for recurrence and poor outcome. Therefore,
the elevation both of OPN and GPC3 was a genetic sig-
nature as one prognostic factor for DFS and OS in small
HBV–HCC following resection.
ACKNOWLEDGMENT We are grateful to all our colleagues in
the Department of Cancer Center, Pathology and the Genomic
Medicine Research Core Laboratory of Chang Gung Memorial
Hospital for their technical assistance. This study was supported
by Chang Gung Memorial Hospital (CMRPG361521-2, Chen MF;
CMRPG391001, Yu MC) and the National Science Council
(NMRPG380081, Yu MC), Taiwan.
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Proportional overall survival P = 0.003
8642 91 753
(A) (B)
FIG. 4 Elevated expression of OPN and GPC3 in tumors was
associated with shorter overall survival (OS) and disease-free survival
(DFS) for HBV-related small HCC. Long-term DFS and OS for small
HBV–HCC patients with high risk (both elevated GPC3?/OPN?)
were DFS 0%, OS 0%, respectively; on the other hand, DFS and OS
in patients with moderate (elevated only one gene) or low (OPN-/
GPC3-) risk were 35.0 and 46.5%, respectively. a Kaplan–Meier plot
for 10-year DFS, P \ 0.001. b Kaplan–Meier plot for overall
survival, P = 0.003
Aberrant Gene Expression in Small HBV–HCC
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Aberrant Gene Expression in Small HBV–HCC
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