Disease Markers

Disease Markers / 2014 / Article

Research Article | Open Access

Volume 2014 |Article ID 351863 | 10 pages | https://doi.org/10.1155/2014/351863

Promoter Methylation of SFRP3 Is Frequent in Hepatocellular Carcinoma

Academic Editor: Valeria Barresi
Received30 Jun 2013
Revised01 Oct 2013
Accepted22 Oct 2013
Published21 Jan 2014

Abstract

Oncogenic activation of the Wnt/β-catenin signaling pathway is common in human cancers. The secreted frizzled-related proteins (SFRPs) function as negative regulators of Wnt signaling and have important implications in carcinogenesis. Because there have been no reports about the role of SFRP3 in hepatocellular carcinoma (HCC), we investigated the level of methylation and transcription of SFRP3. Four HCC cell lines, 60 HCCs, 23 cirrhosis livers, 37 chronic hepatitis livers, and 30 control livers were prescreened for SFRP3 promoter methylation by methylation-specific polymerase chain reaction (MS-PCR) and bisulfite sequencing. SFRP3 promoter methylation was observed in 100%, 60%, 39.1%, 16.2%, and 0% in HCC cell lines, primary HCCs, cirrhosis livers, chronic hepatitis livers, and control livers, respectively. Demethylation treatment with 5-aza-2′-deoxycytidine in HCC cells restored or increased the SFRP3 mRNA expression. We next used quantitative MS-PCR (QMSP) to analyze the methylation level of SFRP3 in 60 HCCs and their corresponding nontumor tissues. Methylation of SFRP3 promoter region in HCCs increased significantly compared with control tissues. There is a positive correlation between promoter hypermethylation and SFRP3 mRNA downregulation. Our data suggest that promoter hypermethylation of SFRP3 is a common event in HCCs and plays an important role in regulation of SFRP3 mRNA expression.

1. Introduction

Hepatocellular carcinoma (HCC) is the most frequent primary malignancy of the liver and accounts for as many as 1 million deaths annually worldwide [15]. The major risk factors include chronic hepatitis B virus (HBV) infection, chronic hepatitis C virus (HCV) infection, environmental carcinogens such as aflatoxin B1 (AFB1), alcoholic cirrhosis, and inherited genetic disorder such as hemochromatosis, Wilson disease, and tyrosinemia. Among them, HBV, HCV, and AFB1 are responsible for approximately 80% of all HCC [1, 2]. Research on molecular genetics and pathogenesis of HCC has become a hot spot in cancer study because of its scientific merits and its clinical importance. Despite rapid expansion of information obtained from these researchers, the molecular mechanism of hepatocarcinogenesis and molecular genetics of HCC remain elusive.

The Wnt/β-catenin signaling pathway plays an important role in liver physiology and pathology by regulating a variety of crucial cellular events, including differentiation, proliferation, and survival [68]. The Wnt/β-catenin pathway can be activated through mutations in CTNNB1 (encoding β-catenin), AXIN1, and AXIN2 [6, 9] in human HCC. The common event is the stabilization of β-catenin, which translocates into the nucleus and associates with the T-cell factor (TCF) family of transcription factors for efficient activation of Wnt target genes [1017]. In addition to genetic mutations, epigenetic changes are also involved in the aberrant activation of Wnt/β-catenin signaling pathway in cancer cells [6, 9, 1822].

Abnormal hypermethylation of CpG islands serves as another mechanism for inactivation of the tumor suppressor gene (TSG) in cancer [2325]. Hypermethylation of gene promoters has been demonstrated as an early event in hepatocellular carcinogenesis [2628]. The secreted frizzled-related proteins (SFRPs) function as negative regulators of Wnt signaling and have important implications for carcinogenesis [29]. The secreted frizzled-related protein (SFRP) family plays a significant role in the inhibition of the Wnt signaling pathway in various cancers [30]. The frizzled-related protein (SFRP3) is generally thought to be an inhibitor of Wnt signaling in several cancers [31, 32]. Some reports have demonstrated that SFRP3 has tumor-suppressing activities and could inhibit cell invasiveness in prostate cancer and melanoma cells [31, 32]. However, SFRP3 promotes cell growth, invasion, and inhibition of apoptosis in renal cancer cells [33]. Because there have been no reports about the role of SFRP3 in hepatocellular carcinoma (HCC), we investigated the level of methylation and transcription of SFRP3.

Recently, we have shown that SFRPs are often downregulated through promoter hypermethylation in HCC cell lines and clinical HCC tissues [18, 34]. Furthermore, we have demonstrated that restoration of SFRPs could attenuate Wnt signaling in HCC cells with β-catenin mutation, decrease aberrant accumulation of free β-catenin in the nucleus, and then suppress cell growth [34]. We hypothesized that CpG island methylation of the SFRP3 promoter may play an important role in regulating SFRP3 expression in HCC. To test this hypothesis, we used MS-PCR, QMSP, and bisulfite sequencing method to analyze the SFRP3 methylation pattern in HCCs. The mRNA expression was assessed by quantitative RT-PCR assay. Further, we determined whether treatment of HCC cell lines with a DNA methylation inhibitor, 5-aza-2′-deoxycytidine (5-Aza-CdR), could then restore or increase expression of the SFRP3 mRNA.

2. Materials and Methods

2.1. Tissue Specimens

Sixty paired HCC samples (including HCC tissues, DNA, and RNA samples) and 30 hepatic hemangioma tissues were provided by the Taiwan Liver Cancer Network (TLCN). The TLCN is funded by the National Science Council to provide researchers in Taiwan with primary liver cancer tissues and their associated clinical information. The diagnosis of HCC was confirmed by histology. Experienced pathologist classified the nontumor tissues as chronic hepatitis livers (23 cases) and cirrhosis livers (37 cases). The use of the 60 HCC tissues, paired nontumor parts, and 30 hepatic hemangioma tissues (as control livers) in this study was approved by the Institutional Review Board and the TLCN User Committee.

2.2. Cell Lines

We obtained three human HCC cell lines from the American Type Culture Collection (ATCC, Rockville, MD): HepG2, HA22T, Hep3B, and TONG. They were all grown in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% (w/v) fetal bovine serum, penicillin at 100 U/mL, streptomycin at 100 μg/mL, and L-glutamine at 2 mmol/L (all from Invitrogen, Carlsbad, CA) at 37°C in an atmosphere of 5% (v/v) CO2 in air.

2.3. 5-Aza-2′-deoxycytidine Treatment

HCC cells were seeded at a density of  cells/100-millimeter dish and allowed to attach for 24 hr. Cells were incubated in 5 µM 5-aza-2′-deoxycytidine (5-Aza-CdR; Sigma Chemical Co., St. Louis, MO) diluted in phosphate-buffered saline (PBS) or in PBS alone for 96 hr to analyze the effect of methylation inhibition on SFRP3 mRNA expression. All incubations were performed in duplicate dishes, and cells were harvested directly for RNA and DNA isolation.

2.4. DNA Extraction

Genomic DNA was extracted from cell lines and tissue samples using a commercial DNA extraction kit (QIAmp Tissue Kit; Qiagen, Hilden, Germany). DNA was isolated according to the manufacturer’s protocol.

2.5. Bisulfite Modification and Methylation-Specific PCR (MS-PCR)

Genomic DNA isolated from cells and tissue was subjected to bisulfite methylation analysis. We treated DNA with bisulfite using an EZ DNA methylation kit (Zymo Research, Orange, CA) according to the protocol described in the user manual. Briefly, one µg of genomic DNA was denatured by incubation with 0.2 M NaOH. Aliquots of 10 mM hydroquinone and 3 M sodium bisulfite (pH 5.0) were added and the solution was incubated at 50°C for 16 hr. Treated DNA was purified on a Zymo-Spin I column, desulfonated with 0.3 M NaOH, repurified on a Zymo-Spin I column, and resuspended in 20 μL elution buffer. MS-PCR [35] was carried out in a volume of 25 μL containing 1 μL of the sodium-bisulfite-treated DNA with Gold Taq DNA polymerase (PE Applied Biosystems, Foster City, CA) as follows. After heating at 92°C for 10 min, PCR was performed in a thermal cycler (GeneAmp 2400, PE Applied Biosystems) for 35 cycles, each of which consisted of denaturation at 92°C for 30 sec, annealing at 61°C for 30 sec, and extension at 72°C for 30 sec, followed by a final 10 min extension at 72°C. The PCR products were analyzed by electrophoresis on a 3% agarose gel. The experiments were repeated three times to ensure reproducibility. The sequences of SFRP3 promoter, primer, and probes are summarized in Table 1.


Primer sequence ( )Primer nameAssay

GTGTTGTTTTGGGGTTTTGTATTTGTATGSFRP3 UFMSPCR
CTACCTCCCACCTAAAAAAAAACTCCACSFRP3 URMSPCR
TTGGGGTGGGTTTTTTAGTGAGGGGTBS01 FBS sequencing
AACAAAAAAAACRCTCAAAAAAAACCBS01 RBS sequencing
GGCGTTGTTTTGGGGTTTCGTATTCSFRP3 MFMSPCR, QMSP
TCCCGCCTAAAAAAAAACTCCGSFRP3 MRMSPCR, QMSP
CTCTACCCTCCAATACCprobeQMSP
TCCCGAGGCCATCGTTACTSFRP3 FQRT-PCR (SyBr)
AGGCTTACATTTACAGCGTTCACSFRP3 RQRT-PCR

Sequence of SFRP3 promoter:
aaaaaaaaagtccaagtgtattagagctgttagtttccacgttaacccttaaggagcaaagctcaagagttctaattccactaggtggggggggcgggaatagaaggaaaaaaccccttttccttgcttctggtggcctatttgtagtcat
gaacagcatttctttgtttctctctctctttttttttttttttaaaggcaatcctccccccacctcctcccccgcagttattgaaaatggagacctctgtagtcactagctctgggttgatatggctccaccgttgctcgcaggggtctgtgttttccg
ctacttggacaaagtgacattgcttaagcctttccccccaccaggtctgactttctgcagagccagtgattgcagaggaaaagctgtagtttgcttaaaggaaatacctccaggaaggagggtctcgggtgggttcccaagtggggaact
agggggacttttccgtagggaattggggtgggctcttcagtgaggggctaggggctcgtttctggggccaaagacgggttccctagtgtgagggcgcgctcgactcggcgctgtcttggggtctcgcactcgcacggcttcgcaccccac
cgcctgcgactcccaggccttctcttccccgggcgcccactccattctcgggaagagcagccggcactggagggcagagactgccccaggggcggagctccctctcaggcgggaggtaggaaagtgcagagccgcccgggcagagg
cacagacgtccctgcggggctcctcctgagcgtccctcctgccagccagggtcgcagccgcagcggcggccgcagctcttagcccacacaggacttgtaaactcttactgcacccttctctcccattaggagcttttcctccctccttccc
cccaacccctctgtcctcctcactttggggaatttaatgctttctttagcatctttttgtgtgcgtgatctaggggaggagacaccccagagctccaactagctctcagctgaattctacttttgtttttatgtcttcctcgcctcctctcgtgtcc
ctcttatctgactgatctgcgaagtctgatgcttctgccagagggagaggaataaatagatgttgctgcttccgaaggcttagacGTTGGGAAAGAGCAGCCTGGGCGGCAGGGGCGGTGGCTG
GAGCTCGGTAAAGCTCGTGGGACCCCATTGGGGGAATTTGATCCAAGGAAGCGGTGATTGCCGGGGGAGGAGAAGCTCCCAGATCCTTGTG
TCCACTTGCAGCGGGGGAGGCGGAGACGGCGGAGCGGGCCTTTTGGCGTCCACTGCGCGGCTGCACCCTGCCCCATCCTGCCGGGATC.

2.6. Bisulfite Sequencing

Bisulfite-treated genomic DNA was amplified using specific primers for human SFRP3. Amplified PCR product was purified and cloned into pCR4-TOPO vector (Invitrogen, Carlsbad, CA). DNA sequencing was performed on at least 5 individual clones using the 377 automatic sequencer (Applied Biosystems, Foster City, CA, USA). The primer sequences and the locations are summarized in Table 1.

2.7. Quantitative Methylation-Specific PCR (QMSP)

TagMan-based QMSP (MethyLight) [36] method was used to determine the methylation level of HCCs. We used type II collagen gene (COL2A) for an internal reference gene by amplifying the non-CpG sequences. Each sample was analyzed three times. The genomic DNA treatment with M.Sss I methyltransferase (New England Biolabs, Beverly, MA) was used as positive control. The QMSP reactions were done as our previous report [37]. The relative DNA methylation was determined based on the threshold cycles (Ct) of the gene of interest and of the internal reference gene (COL2A). The relative DNA methylation level [sample_gene/sample_COL2A] was calculated by the ΔCt method [36, 38]. Testing results with Ct-value of COL2A greater than 40 were determined as detection failure.

2.8. Quantitative RT-PCR

Quantitative RT-PCR analysis was performed on an ABI PRISM 7700 Sequence Detector (Applied Biosystems, Forster City, USA). The match primers and TagMan Probe were obtained from commercial Applied Biosystems Tagman Assay-on Demand Gene Expression products. Glyceraldehyde-3-phosphate dehydrogenase gene (GAPDH) was used as an internal control. PCR reaction was carried out using TaqMan PCR master mix reagents kit. Relative gene expression was determined based on the threshold cycles (Ct) of the gene of interest and of the internal reference gene. The mRNA levels of the interest genes were expressed as the ratio of the interest gene to GAPDH mRNA for each sample. The level of each interest gene mRNA in each cancer was compared to the level in the corresponding nontumor part [39]. The average Ct value of the GAPDH gene was subtracted from the average Ct value of the interest genes for each sample: SFRP3 Ct = (Avg. SFRP3 Ct − Avg. GAPDH Ct) and SFRP3 Ct = (Avg. − Avg.). The fold change () in expression of the target genes (SFRP3) relative to the internal control gene (GAPDH) of each analyzed HCC sample was calculated [18, 39].

2.9. Statistical Analysis

Associations between methylation of SFRP3 and clinical parameters were analyzed by using a chi-square test and Fisher’s exact test, where necessary. We correlated the SFRP3 methylation status with the liver disease status (control, chronic hepatitis, cirrhosis liver, and HCC) and downregulation of SFRP3 mRNA expression. Significant differences were analyzed using the paired sample -test or Mann-Whitney test. The significance level was defined as value < 0.05.

3. Results

3.1. Hypermethylation of SFRP3 Promoter in Primary HCCs

To investigate the promoter methylation of SFRP3 in HCC, we first tested for promoter methylation in 30 control livers, 60 primary HCCs, and their corresponding nontumor tissues using MSP (Figures 1(a) and 1(b), Table 2). Aberrant promoter methylation of SFRP3 gene was observed in 60%, 39.1%, 16.2%, and 0% in primary HCCs, cirrhosis livers, chronic hepatitis livers, and normal controls, respectively. The methylation level within the SFRP3 promoter was then validated by bisulfite sequencing. Representative results for bisulfite sequencing are shown in Figure 1(c). The CpGs in these regions were frequently methylated in HCC tumors (Figure 1(c), 5T). The methylation of SFRP3 promoter was detected in some nontumor parts from HCC patients with chronic hepatitis or cirrhosis (Figure 1(c), 5NT). In contrast, we did not detect promoter hypermethylation in control liver tissues (Figure 1(c), N4). Our data showed that methylation level of SFRP3 promoter region in HCCs increased significantly compared with control livers (Table 3).


Patient no.SFRP3 methylation Ct Ct SFRP3 tumor part
SFRP3-GAPDH Ct tumor  −   Ct nontumor Rel. to nontumor

1TU9.03 1.68 0.3121
1NTU7.35

2TM10.05 2.81 0.1426
2NTM7.24

3TU7.63 −0.47 1.3851
3NTU8.10

4TU7.58 −0.51 1.4191
4NTU8.09

5TU11.54 0.82 0.5684
5NTU10.72

6TU5.92 −0.29 1.2226
6NTU6.21

7TM7.40 1.38 0.3856
7NTU6.03

8TU15.00 6.10 0.0146
8NTU8.91

9TM8.95 1.91 0.2661
9NTU7.04

10TM9.03 1.790.2892
10NTM7.24

11TM15.00 9.03 0.0019
11NTM5.97

12TM9.10 1.35 0.3923
12NTM7.75

13TU9.62 1.58 0.3356
13NTU8.04

14TU6.27 −0.71 1.6358
14NTU6.98

15TM15.00 7.90 0.0042
15NTU7.10

16TM15.00 7.14 0.0071
16NTM7.86

17TM9.34 1.13 0.4569
17NTM8.21

18TU5.10 −1.01 2.0069
18NTU6.11

19TM6.75 1.04 0.4863
19NTM5.71

20TU15.00 7.87 0.0043
20NTU7.14

21TM15.00 8.13 0.0036
21NTU6.87

22TU9.92 3.48 0.0899
22NTU6.45

23T
23NT
M
M
9.05
7.63
1.42 0.3737

24TM8.47 1.24 0.4248
24NTM7.23

25TM6.96 0.61 0.6552
25NTM6.35

26TU5.14 0.11 0.9298
26NTU5.04

27TM12.37 5.31 0.0253
27NTM7.06

28TM15.00 6.21 0.0136
28NTU8.80

29TU5.67 2.49 0.1780
29NTU3.18

30TM9.23 1.44 0.3680
30NTU7.79

31TU15.00 6.34 0.0123
31NTU8.66

32TU8.28 1.18 0.4429
32NTU7.11

33TU12.14 5.96 0.0161
33NTU6.18

34TU7.63 2.47 0.1811
34NTU5.16

35TM6.98 4.65 0.0398
35NTM2.33

36TM15.00 5.01 0.0310
36NTM9.99

37TU15.00 9.40 0.0015
37NTU5.61

38TM15.00 10.72 0.0006
38NTM4.28

39TM7.90 1.10 0.4665
39NTU6.80

40TM15.00 7.48 0.0056
40NTU7.52

41TM8.97 1.22 0.4308
41NTU7.75

42TM9.25 2.17 0.2222
42NTU7.08

43TU15.00 8.77 0.0023
43NTU6.23

44TM8.76 0.22 0.8586
44NTM8.54

45TM8.92 2.86 0.1377
45NTU6.06

46T
46NT
U
U
10.34
8.17
2.17 0.2222

47TM15.00 9.13 0.0018
47NTU5.88

48TU15.00 9.16 0.0018
48NTU5.85

49TM15.00 9.43 0.0014
49NTU5.57

50TM15.00 6.78 0.0091
50NTU8.22

51TM15.00 6.16 0.0140
51NTU8.85

52TM15.00 10.77 0.0006
52NTU4.24

53TU11.21 3.77 0.0733
53NTU7.44

54TM12.27 10.28 0.0008
54NTU1.99

55TM15.00 4.94 0.0326
55NTU10.06

56TU7.74 1.98 0.2535
56NTU5.76

57TU10.39 3.52 0.0872
57NTU6.87

58TM15.00 9.01 0.0019
58NTU5.99

59TM11.36 3.99 0.0632
59NTU7.38

60TM7.52 2.55 0.1713
60NTU4.97

NT: nontumor part; T: tumor part; M: methylated; U: unmethylated.
The range given for SFRP3 tumor part relative to nontumor part is determined by evaluating the expression: 2−ΔΔCt.

DiagnosisNo. of cases with SFRP3 methylation value

Control livers* ( )0 (0%)<0.0001
Chronic hepatitis ( )6 (16.2%)
Cirrhosis ( )9 (39.1%)
HCC ( )36 (60%)

Thirty control tissues were from 30 hepatic hemangiomas. Statistical analysis was determined by chi-square test.
3.2. Promoter Methylation of SFRP3 and Downregulation of SFRP3 mRNA in HCC Cell Lines

We then investigated the methylation level of SFRP3 promoter in four HCC cell lines (HA22T, HepG2, Hep3B, and TONG) using MSP and bisulfite sequencing. Among four HCC cell lines, our data demonstrated SFRP3 was fully methylated in HA22T cells and partially methylated in the other cells (Figure 2(a)). Bisulfite sequencing results were summarized in Figure 2(b). The CpGs in these regions was frequently methylated (Figure 2(b)). Quantitative RT-PCR data showed that downregulation of SFRP3 mRNA in the four HCC lines with SFRP3 hypermethylation (Figure 2(c)). To confirm that the lack of expression of SFRP3 mRNA in the HCC lines was due to promoter hypermethylation, we treated cells with 5-aza-2′-deoxycytidine, an inhibitor of DNA methylation. After treatment with 5 µM of 5-aza-2′-deoxycytidine, the unmethylated promoter DNA was detected by MSP and bisulfite sequencing; SFRP3 mRNA was restored or increased in the four HCC cell lines (Figures 2(a), 2(b), and 2(c)). These data indicate that hypermethylation of SFRP3 may be responsible for the absence or downregulation of mRNA transcription.

3.3. Downregulation of SFRP3 mRNA Is Correlated with Promoter Methylation in Primary HCCs

To study the relation between SFRP3 promoter methylation level and SFRP3 mRNA expression, we first checked the mRNA level of 60 primary HCCs and their corresponding adjacent nontumor tissues by quantitative RT-PCR. Our data showed SFRP3 mRNA expression was significantly downregulated in the primary HCCs as compared with the adjacent nontumor tissues () (Figure 3(a)). Next, we checked the methylation status of the HCC cell lines and clinical HCC tissues by QMSP. Hypermethylation was confirmed in the HCC tissues compared with the nontumor liver tissues () (Figure 3(b)). In 36 of 60 HCCs (60%), SFRP3 mRNA was significantly downregulated (by >2-fold, Table 4). There was a statistically significant association between the downregulation of SFRP3 mRNA and the methylation status of SFRP3 in HCCs (35/36 versus 17/24 resp.; ) (Table 4). There were some HCCs without methylation; however, their SFRP3 mRNA expression were downregulated.


Methylation of CpG island
(no. of cases)
No methylation of CpG island
(no. of cases)
value

Downregulation of SFRP3 ≥ twofold
 Present3517
 Absent17

4. Discussion

Here we demonstrate that SFRP3 is significantly hypermethylated and downregulated in HCCs when compared with control livers and nontumor livers (containing chronic hepatitis or cirrhosis livers) (, Table 3 and Table 2). SFRP3 mRNA expression could be restored or increased after HCC cells treatment with a DNA methyltransferase (DNMT) inhibitor, 5-aza-2′-deoxycytidine (Figure 2). We found a significant correlation between methylation and transcription level in primary tissues (Table 4, ). In accordance with our data, promoter methylation has been detected in chronic hepatitis tissue and cirrhosis liver tissues, indicating that DNA methylation may be an early event in the pathogenesis of HCC [19, 40]. Put together, our data suggest that that downregulation of SFRP3 mRNA through promoter hypermethylation is an early event during carcinogenesis and may be involved in the aberrant activation of Wnt/β-catenin signaling in HCC. Moreover, SFRP3 mRNA was downregulated more than twofold in the absence of promoter hypermethylation in 71% of HCCs (17 of 24) (Table 4). The decreased SFRP3 mRNA level might be due to genetic changes or other epigenetic changes like histone modification.

Our data suggest that promoter hypermethylation of SFRP3 is a common event in HCCs and plays an important role in regulation of SFRP3 mRNA expression. Therefore epigenetic regulation of the Wnt/β-catenin pathway has been implicated as a possible therapeutic target in human cancer. Further investigations are required to explore the importance of SFRP3 in the development of hepatocellular carcinoma.

5. Conclusions

In conclusion, promoter hypermethylation of SFRP3 is a frequent event in HCCs and epigenetic downregulation of SFRP3 mRNA may contribute to aberrant activation of Wnt/β-catenin in HCC. This is the first report about hypermethylation and downregulation of SFRP3 mRNA in HCC.

Abbreviation

HCC:Hepatocellular carcinoma
SFRP3:Secreted frizzled-related protein 3
5-Aza-CdR:5-Aza-2′-deoxycytidine
MSP:Methylation-specific PCR
RT-PCR:Reverse transcription-polymerase chain reaction
HBV:Hepatitis B virus
HCV:Hepatitis C virus
TSG:Tumor suppressor gene.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgments

The authors would like to thank Taiwan Liver Cancer Network (TLCN) for providing the hepatocellular carcinoma tissue samples and related clinical data (all are anonymous) for their research work. This network currently includes five major medical centers (National Taiwan University Hospital, Chang-Gung Memorial Hospital-Linko, Veteran General Hospital-Taichung, Chang-Gung Memorial Hospital-Kaohsiung, and Veteran General Hospital-Kaohsiung). TLCN is supported by Grants from National Science Council since 2005 (NSC 100-2325-B-182-006) and National Health Research Institutes, Taiwan. This work was supported in part by the following Grants: DOH101-TD-C-111-008 from the Department of Health, Taiwan; 102-wf-eva-03 from the Wan Fang Hospital, Taiwan; NSC 98-2314-B-016-035-MY2, NSC 99-2314-B-016-015-MY2, NSC 100-2320-B-016-011, and NSC 101-2320-B-016-011 from the National Science Council, Taiwan; TSGH-C100-010-014-S03 from the Tri-Service General Hospital, Taiwan; and the Liver Disease Prevention and Treatment Research Foundation, Taiwan. The authors are grateful to Dr. Yu-Ching Chou, School of Public Health, National Defense Medical Center, Taipei, Taiwan, for the assistance on statistical analysis.

References

  1. F. X. Bosch, J. Ribes, R. Cléries, and M. Díaz, “Epidemiology of hepatocellular carcinoma,” Clinics in Liver Disease, vol. 9, no. 2, pp. 191–211, 2005. View at: Publisher Site | Google Scholar
  2. F. X. Bosch, J. Ribes, and J. Borràs, “Epidemiology of primary liver cancer,” Seminars in Liver Disease, vol. 19, no. 3, pp. 271–285, 1999. View at: Google Scholar
  3. A. S. Befeler and A. M. Di Bisceglie, “Hepatocellular carcinoma: diagnosis and treatment,” Gastroenterology, vol. 122, no. 6, pp. 1609–1619, 2002. View at: Google Scholar
  4. H. B. El-Serag, “Hepatocellular carcinoma: recent trends in the United States,” Gastroenterology, vol. 127, pp. S27–S34, 2004. View at: Publisher Site | Google Scholar
  5. H. B. El-Serag and A. C. Mason, “Rising incidence of hepatocellular carcinoma in the United States,” The New England Journal of Medicine, vol. 340, no. 10, pp. 745–750, 1999. View at: Publisher Site | Google Scholar
  6. M. D. Thompson and S. P. S. Monga, “WNT/β-catenin signaling in liver health and disease,” Hepatology, vol. 45, no. 5, pp. 1298–1305, 2007. View at: Publisher Site | Google Scholar
  7. T. Chiba, Y.-W. Zheng, K. Kita et al., “Enhanced self-renewal capability in hepatic stem/progenitor cells drives cancer initiation,” Gastroenterology, vol. 133, no. 3, pp. 937–950, 2007. View at: Publisher Site | Google Scholar
  8. G. Zeng, U. Apte, B. Cieply, S. Singh, and S. P. S. Monga, “siRNA-mediated β-catenin knockdown in human hepatoma cells results in decreased growth and survival,” Neoplasia, vol. 9, no. 11, pp. 951–959, 2007. View at: Publisher Site | Google Scholar
  9. J. Behari, “The Wnt/β-catenin signaling pathway in liver biology and disease,” Expert Review of Gastroenterology and Hepatology, vol. 4, no. 6, pp. 745–756, 2010. View at: Publisher Site | Google Scholar
  10. K. M. Cadigan and R. Nusse, “Wnt signaling: a common theme in animal development,” Genes and Development, vol. 11, no. 24, pp. 3286–3305, 1997. View at: Google Scholar
  11. C. Y. Logan, J. R. Miller, M. J. Ferkowicz, and D. R. McClay, “Nuclear β-catenin is required to specify vegetal cell fates in the sea urchin embryo,” Development, vol. 126, no. 2, pp. 345–357, 1999. View at: Google Scholar
  12. P. Polakis, “Wnt signaling and cancer,” Genes and Development, vol. 14, no. 15, pp. 1837–1851, 2000. View at: Google Scholar
  13. C. Yost, M. Torres, J. R. Miller, E. Huang, D. Kimelman, and R. T. Moon, “The axis-inducing activity, stability, and subcellular distribution of β-catenin is regulated in Xenopus embryos by glycogen synthase kinase 3,” Genes and Development, vol. 10, no. 12, pp. 1443–1454, 1996. View at: Google Scholar
  14. J. Behrens, J. P. von Kries, M. Kühl et al., “Functional interaction of β-catenin with the transcription factor LEF- 1,” Nature, vol. 382, no. 6592, pp. 638–642, 1996. View at: Publisher Site | Google Scholar
  15. J. Cui, X. Zhou, Y. Liu, Z. Tang, and M. Romeih, “Wnt signaling in hepatocellular carcinoma: analysis of mutation and expression of beta-catenin, T-cell factor-4 and glycogen synthase kinase 3-beta genes,” Journal of Gastroenterology and Hepatology, vol. 18, no. 3, pp. 280–287, 2003. View at: Publisher Site | Google Scholar
  16. A. de La Coste, B. Romagnolo, P. Billuart et al., “Somatic mutations of the β-catenin gene are frequent in mouse and human hepatocellular carcinomas,” Proceedings of the National Academy of Sciences of the United States of America, vol. 95, no. 15, pp. 8847–8851, 1998. View at: Publisher Site | Google Scholar
  17. P. A. Farazi and R. A. DePinho, “Hepatocellular carcinoma pathogenesis: from genes to environment,” Nature Reviews Cancer, vol. 6, no. 9, pp. 674–687, 2006. View at: Publisher Site | Google Scholar
  18. Y.-L. Shih, R.-Y. Shyu, C.-B. Hsieh et al., “Promoter methylation of the secreted frizzled-related protein 1 gene SFRP1 is frequent in hepatocellular carcinoma,” Cancer, vol. 107, no. 3, pp. 579–590, 2006. View at: Publisher Site | Google Scholar
  19. G. M. Caldwell, C. Jones, K. Gensberg et al., “The Wnt antagonist sFRP1 in colorectal tumorigenesis,” Cancer Research, vol. 64, no. 3, pp. 883–888, 2004. View at: Publisher Site | Google Scholar
  20. D. Sarrió, G. Moreno-Bueno, D. Hardisson et al., “Epigenetic and genetic alterations of APC and CDH1 genes in lobular breast cancer: relationships with abnormal E-cadherin and catenin expression and microsatellite instability,” International Journal of Cancer, vol. 106, no. 2, pp. 208–215, 2003. View at: Publisher Site | Google Scholar
  21. S. Satoh, Y. Daigo, Y. Furukawa et al., “AXIN1 mutations in hepatocellular carcinomas, and growth suppression in cancer cells by virus-mediated transfer of AXIN1,” Nature Genetics, vol. 24, no. 3, pp. 245–250, 2000. View at: Publisher Site | Google Scholar
  22. H. Suzuki, E. Gabrielson, W. Chen et al., “A genomic screen for genes upregulated by demethylation and histone deacetylase inhibition in human colorectal cancer,” Nature Genetics, vol. 31, no. 2, pp. 141–149, 2002. View at: Publisher Site | Google Scholar
  23. J. G. Herman and S. B. Baylin, “Gene silencing in cancer in association with promoter hypermethylation,” The New England Journal of Medicine, vol. 349, no. 21, pp. 2042–2054, 2003. View at: Publisher Site | Google Scholar
  24. J. G. Herman, A. Merlo, L. Mao et al., “Inactivation of the CDKN2/p16/MTS1 gene is frequently associated with aberrant DNA methylation in all common human cancers,” Cancer Research, vol. 55, no. 20, pp. 4525–4530, 1995. View at: Google Scholar
  25. M. Esteller, A. Sparks, M. Toyota et al., “Analysis of adenomatous polyposis coli promoter hypermethylation in human cancer,” Cancer Research, vol. 60, no. 16, pp. 4366–4371, 2000. View at: Google Scholar
  26. J. Yu, H. Y. Zhang, Z. Z. Ma, W. Lu, Y. F. Wang, and J. D. Zhu, “Methylation profiling of twenty four genes and the concordant methylation behaviours of nineteen genes that may contribute to hepatocellular carcinogenesis,” Cell Research, vol. 13, no. 5, pp. 319–333, 2003. View at: Publisher Site | Google Scholar
  27. B. Yang, M. Guo, J. G. Herman, and D. P. Clark, “Aberrant promoter methylation profiles of tumor suppressor genes in hepatocellular carcinoma,” American Journal of Pathology, vol. 163, no. 3, pp. 1101–1107, 2003. View at: Google Scholar
  28. U. Schagdarsurengin, L. Wilkens, D. Steinemann et al., “Frequent epigenetic inactivation of the RASSF1A gene in hepatocellular carcinoma,” Oncogene, vol. 22, no. 12, pp. 1866–1871, 2003. View at: Publisher Site | Google Scholar
  29. H. Suzuki, D. N. Watkins, K.-W. Jair et al., “Epigenetic inactivation of SFRP genes allows constitutive WNT signaling in colorectal cancer,” Nature Genetics, vol. 36, no. 4, pp. 417–422, 2004. View at: Publisher Site | Google Scholar
  30. P. W. Finch, X. He, M. J. Kelley et al., “Purification and molecular cloning of a secreted, Frizzled-related antagonist of Wnt action,” Proceedings of the National Academy of Sciences of the United States of America, vol. 94, pp. 6770–6775, 1997. View at: Google Scholar
  31. E. J. Ekström, V. Sherwood, and T. Andersson, “Methylation and loss of secreted frizzled-related protein 3 enhances melanoma cell migration and invasion,” PLoS ONE, vol. 6, no. 4, Article ID e18674, 2011. View at: Publisher Site | Google Scholar
  32. X. Zi, Y. Guo, A. R. Simoneau et al., “Expression of Frzb/secreted Frizzled-related protein 3, a secreted Wnt antagonist, in human androgen-independent prostate cancer PC-3 cells suppresses tumor growth and cellular invasiveness,” Cancer Research, vol. 65, no. 21, pp. 9762–9770, 2005. View at: Publisher Site | Google Scholar
  33. H. Hirata, Y. Hinoda, K. Ueno, S. Majid, S. Saini, and R. Dahiya, “Role of secreted frizzled-related protein 3 in human renal cell carcinoma,” Cancer Research, vol. 70, no. 5, pp. 1896–1905, 2010. View at: Publisher Site | Google Scholar
  34. Y.-L. Shih, C.-B. Hsieh, H.-C. Lai et al., “SFRP1 suppressed hepatoma cells growth through Wnt canonical signaling pathway,” International Journal of Cancer, vol. 121, no. 5, pp. 1028–1035, 2007. View at: Publisher Site | Google Scholar
  35. J. G. Herman, J. R. Graff, S. Myöhänen, B. D. Nelkin, and S. B. Baylin, “Methylation-specific PCR: a novel PCR assay for methylation status of CpG islands,” Proceedings of the National Academy of Sciences of the United States of America, vol. 93, no. 18, pp. 9821–9826, 1996. View at: Publisher Site | Google Scholar
  36. S. Ogino, T. Kawasaki, M. Brahmandam et al., “Precision and performance characteristics of bisulfite conversion and real-time PCR (MethyLight) for quantitative DNA methylation analysis,” Journal of Molecular Diagnostics, vol. 8, no. 2, pp. 209–217, 2006. View at: Publisher Site | Google Scholar
  37. H.-C. Lai, Y.-W. Lin, R.-L. Huang et al., “Quantitative DNA methylation analysis detects cervical intraepithelial neoplasms type 3 and worse,” Cancer, vol. 116, no. 18, pp. 4266–4274, 2010. View at: Publisher Site | Google Scholar
  38. W. B. Coleman and A. G. Rivenbark, “Quantitative DNA methylation analysis: the promise of high-throughput epigenomic diagnostic testing in human neoplastic disease,” Journal of Molecular Diagnostics, vol. 8, no. 2, pp. 152–156, 2006. View at: Publisher Site | Google Scholar
  39. K. J. Livak and T. D. Schmittgen, “Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCT method,” Methods, vol. 25, no. 4, pp. 402–408, 2001. View at: Publisher Site | Google Scholar
  40. Y. Kondo, Y. Kanai, M. Sakamoto, M. Mizokami, R. Ueda, and S. Hirohashi, “Genetic instability and aberrant DNA methylation in chronic hepatitis and cirrhosis—a comprehensive study of loss of heterozygosity and microsatellite instability at 39 loci and DNA hypermethylation on 8 CpG islands in microdissected specimens from patients with hepatocellular carcinoma,” Hepatology, vol. 32, no. 5, pp. 970–979, 2000. View at: Google Scholar

Copyright © 2014 Ya-Wen Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


More related articles

1214 Views | 699 Downloads | 10 Citations
 PDF  Download Citation  Citation
 Download other formatsMore
 Order printed copiesOrder

Related articles

We are committed to sharing findings related to COVID-19 as quickly and safely as possible. Any author submitting a COVID-19 paper should notify us at help@hindawi.com to ensure their research is fast-tracked and made available on a preprint server as soon as possible. We will be providing unlimited waivers of publication charges for accepted articles related to COVID-19. Sign up here as a reviewer to help fast-track new submissions.