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Keywords:

  • hepatocellular carcinoma;
  • single nucleotide polymorphisms;
  • VEGFA;
  • promoter activity;
  • realtime PCR

Abstract

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

Accumulated evidences indicate that single nucleotide polymorphisms (SNP) in angiogenesis and tumorigenesis related genes are associated with risk of hepatocellular carcinoma (HCC). Vascular endothelial growth factor A (VEGFA), one of the most significant mediators of angiogenesis, plays an important role in carcinogenesis and development via promoting tumor growth. We carried out a two-stage association study in 1,838 chronic hepatitis B (CHB) patients and 1,207 hepatitis B virus (HBV) related HCC patients in Han Chinese populations from Beijing, Guangxi and Jiangsu. We systematically screened polymorphisms in the VEGFA gene and examined the association between the SNPs and susceptibility to HCC. Functional analyses were conducted to verify biological significances of associated SNPs. We identified two promoter SNPs (rs833061 and rs1570360) were associated with susceptibility to HCC (rs833061: ptrend = 0.008 in Youan_Beijing samples, ptrend = 0.01 in Guangxi samples, ptrend = 0.01 in Jiangsu samples. rs1570360: ptrend = 0.00003 in Youan_Beijing samples, ptrend = 0.006 in Guangxi samples, ptrend = 0.02 in Jiangsu samples). These two SNPs were further validated in four independent groups of major HBV outcomes, indicating rs833061 and rs1570360 may associate exclusively to HCC. Functional analyses show that CA haplotype constructed by rs833061 and rs1570360 had higher luciferase activity compared with TG haplotype (p < 0.05). A 18 bp insert/del polymorphism was in absolute linkage disequilibrium (LD) with rs833061. The 18 bp insert allele created a Sp1 binding site. We observed higher VEGFA transcription in peripheral blood of HCC patients compared with CHB patients and healthy individuals (p < 0.05). These findings indicate that VEGFA promoter SNPs may contribute to susceptibility of HCC by altering promoter activity.

Abbreviations
ALT

alanine aminotransferase

AST

aspartate aminotransferase

CHB

chronic hepatitis B

GAPDH

Glyceraldehyde-3-phosphate dehydrogenase

GWAS

genome-wide association study

HBV

hepatitis B virus

HCC

hepatocellular carcinoma

HWE

Hardy–Weinberg equilibrium

LD

linkage disequilibrium

MAF

minor allele frequency

SNP

single nucleotide polymorphism

VEGFA

vascular endothelial growth factor A

Hepatocellular carcinoma (HCC) ranks fifth in men and eighth in women among causes of cancer mortality worldwide. It is estimated that about 564,000 new cases of HCC are reported throughout the world each year.[1] The geographic areas at highest risk of HCC are located in Eastern Asia, e.g., China.[1, 2] The cause of HCC is a complex interplay between multiple factors.[3] In China, hepatitis B virus (HBV) infection is the most frequent cause of HCC. Accumulated evidences in molecular genetics indicate that single nucleotide polymorphisms (SNP) in immune response, angiogenesis and tumorigenesis related genes are associated with susceptibility to HCC.[4-7] Recent progress in genome-wide association study (GWAS) also have identified new susceptibility loci for HCC,[8, 9] which is helpful to understand the underlying mechanism of genetic variations in the development of HCC.

Angiogenesis plays an important role in cancer from the initial stage of carcinogenesis to the end.[10] Vascular endothelial growth factor A (VEGFA) appears to be the most important angiogenic factor in HCC known thus far.[11] VEGFA activates multiple signaling networks that promote endothelial cell growth, migration, differentiation and vascular permeability.[12, 13] Polymorphisms in VEGFA are associated with susceptibility to multiple cancers, e.g., glioma, HCC, ovarian cancer, bladder cancer, breast cancer.[14-18] Increased expression of VEGFA mRNA and protein are detected in human HCC tissues.[19, 20] Till date, however, the results of association studies between HCC and VEGFA are controversial.[7, 15, 21, 22]

The human VEGFA gene resides on chromosome 6p21.3 and is organized into eight exons.[23] Alternative exon splicing of the VEGFA gene produces various splice variants: VEGFA206, VEGFA189, VEGFA183, VEGFA165, VEGFA148, VEGFA145 and VEGFA121.[24, 25] Exons 1–5 and 8 are preserved in all variants, whereas the presence or absence of exons 6a, 6b and 7 distinguish variants.

According to the above evidence, we used a candidate gene strategy and carried out a two-stage association study. We systematically screened sequence variations in VEGFA gene and then examined the association between the variations and HCC susceptibility in independent Chinese populations.

Material and Methods

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

Subjects

The subjects enrolled in the present study included four independent case–control groups in a total of 1,838 chronic hepatitis B (CHB) patients and 1,207 HBV related HCC patients.

The first group consisted of 101 HCC patients and 110 CHB patients enrolled from the 302 Hospital of the PLA (Beijing). The second group consisted of 402 HCC patients and 1,043 CHB patients enrolled from Beijing Youan Hospital (Beijing). The third group consisted of 337 HCC patients and 310 CHB patients enrolled from Guangxi Cancer Hospital (Nanning, Guangxi). The fourth group consisted of 367 HCC patients and 375 CHB patients enrolled from Qidong Liver Cancer Institute (Qidong, Jiangsu).

Controls were CHB patients whose serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were continuously >40 IU/L; they were HBsAg seropositive and HBeAg seropositive for 6 months; their serum HBV DNA >2,000 copies/mL and confirmed by liver ultrasonography.

Cases were pathologically HCC patients, pathologically confirmed and proved not to have other cancers. They were also confirmed by liver ultrasonography and/or computed tomography.

The subjects were excluded if (i) there was evidence of past or current infection with other hepatitis viruses or hepatitis not caused by HBV; (ii) they were not of Han ethnicity. The main features of the subjects included are summarized in Table 1. The study was carried out in accordance with the guidelines of the Helsinki Declaration after obtaining written informed consent from all the subjects and was approved by the ethics committee of the Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences.

Table 1. Clinical features of the subjects included in the study
 302_BeijingYouan_BeijingGuangxiJiangsu
 HCCCHBpHCCCHBpHCCCHBpHCCCHBp
  1. Abbreviations: CHB: chronic hepatitis B; HCC: hepatocellular carcinoma.

Number101110 4021043 337310 367375 
Age, y mean ± SD48.6 ± 10.448.3 ± 14.00.8653.9 ± 11.035.1 ± 12.5<0.00144.7 ± 11.044.3 ± 12.30.6752.0 ± 10.051.6 ± 10.60.66
Gender (male/female)83/1890/200.95339/63781/262<0.001298/39254/560.02298/69313/620.42
Smoking (Yes/No)46/5525/450.20197/205253/781<0.001141/192128/1820.79   
Drinking (Yes/No)50/5129/410.30211/191269/761<0.00198/23992/2180.87   
Family history of HBV (Yes/No)69/3281/290.40175/227604/394<0.001      
Family history of HCC (Yes/No)      58/27914/296<0.001   
HbeAg (±)36/6564/460.001147/255752/291<0.001      
ALT (IU/L) mean ± SD114 ± 108327 ± 326<0.00198 ± 97219 ± 210<0.001      
AST (IU/L) mean ± SD143 ± 96159 ± 1320.40120 ± 117134 ± 1270.18      
LG HBV–DNA (copy/mL) mean ± SD5.3 ± 1.66.1 ± 2.10.024.8 ± 1.66.2 ± 2.0<0.001      

SNP selection and genotyping

Genomic DNA was extracted from peripheral blood by using a salting-out protocol. The gene region of VEGFA (including all exons, relevant exon–intron boundaries and ∼2.6-kb promoter region; see Fig. 1) was sequenced in 24 randomly selected CHB patients. The primer sequences are available upon request. A total of 12 SNPs with minor allele frequency (MAF) >10% were found. Among them, rs699947, 18 bpI/D, rs1005230, rs36026135, rs833061 and rs13207351 were in absolute linkage disequilibrium (LD), as well as rs3025039 and rs3025040. Further sequencing was conducted in another 72 randomly selected CHB patients to confirm the LD between these eight SNPs. We finally confirmed the absolute LD in 96 samples. We took rs833061 and rs3025040 as representative, so six SNPs (rs833061, rs1570360, rs2010963, rs25648, rs3025040, rs40434), which could represent all potential functional SNP in VEGFA with MAF >10% were genotyped using TaqMan method (Applied Biosystems, Foster City, CA), according to the manufacture's protocols. All the samples were successfully genotyped. For genotyping quality control, 5% samples were randomly selected and directly sequenced, and we obtained 100% identical results.

image

Figure 1. Genomic location of SNPs identified in relation to the exon/intron structure of the human VEGFA gene. The exons are marked with boxes, in which white areas represents untranslated regions. The PCR fragments used for SNP screening are marked with lines below the gene.

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Functional analyses

We constructed four reporter plasmids encompassing −1,661 to +279 bp of VEGFA promoter (+1 relative to the first nucleotide of transcription start site), which could represent four haplotypes constructed by rs699947, 18 bp I/D polymorphism, rs1005230, rs36026135, rs833061, rs13207351 and rs1570360. The PCR products were ligated into pGL3-Basic vector (Promega, Madison, WI). Full length of Sp1 cDNA of HepG2 cell were PCR-amplified and then ligated into p3XFLAG-CMV™-14 vector (Sigma, St. Louis). The PCR primers used in construction of plasmids were available upon request. All constructs used in this study were sequenced to confirm their authenticity.

HepG2 cells were purchased from cell culture center of Chinese Academy of Medical Sciences, The Institute of Basic Medical Sciences (Beijing, People's Republic of China). SK-Hep-1 and HeLa cells were kindly gifts from professor Long Yu (State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, People's Republic of China). The cells were propagated in MEM/NEAA medium (HepG2) or RPMI-1640 medium (SK-Hep-1 and HeLa) with 10% fetal calf serum. All cultures were maintained with 5% CO2 at 37°C. We seeded 2 × 105 of each cells per well in 24-well plates and transfected them with pGL3-basic (a promoterless control), pGL3-promoter (a promoter control) or pGL3-basic constructed plasmids, or together with Sp1 expression plasmids, by use of the Lipofectamine™ 2000 (Invitrogen, Carlsbad, CA). The renilla luciferase expression vector pRL-TK (Promega) was cotransfected as a normalizing control. All transfections were carried out in tetramerous and repeated five times. After 48 hr of incubation, cells were collected and analyzed for luciferase activity with Dual-Luciferase Reporter Assay System (Promega).

A double-stranded oligonucleotides (sense: 5'-TCCCACTCTTCCCACAGG-3' and antisense: 5'- CCTGTGGGAAGAGTGGGA-3') representing the 18 bp insert allele were 5'biotin-labeled by Sangon BioTech (Shanghai, People's Republic of China). The oligonucleotides and HeLa cell nuclear extract (Promega) were incubated at room temperature for 20 min using the LightShift Chemiluminescent EMSA Kit (Pierce, Rockford). The reaction mixture was separated on 6% PAGE, and the products were detected by Stabilized Streptavidin-Horseradish Peroxidase Conjugate (Pierce). Unlabeled oligonucleotides at 100-fold excess were added to the reaction for cold competition. We confirmed the identity of the DNA-binding protein in assays using antibodies specific to Sp1 or nonspecific rabbit IgG (Upstate, Billerica).

Total RNA was extracted from the peripheral blood by RNAprep pure Blood Kit (TianGen, Beijing, People's Republic of China). cDNA was synthesize in a 20 µL reaction volume containing Oligo (dT)18 primers (MBI Fermentas, Lithuania), and RevertAid™ H minus M-MuLV reverse transcriptase (MBI Fermentas, Lithuania). Expression of VEGFA mRNA was measured by TaqMan relative quantitative analysis using the Bio-Rad iQ5 Real-Time PCR Detection system (Bio-Rad, Hercules, CA). Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as an internal control. The primers and probes used for qPCR are available upon request. The detailed qPCR conditions comprised 95°C for 10 min, followed by 40 cycles of 92°C for 15 sec and 58°C for 1 min. Each experiment was performed in triplicate assay. The comparative Ct (2−ΔΔCt) method was employed to quantify VEGFA expression as described previously.[26]

Statistical analysis

By using the χ2 test, we tested whether the genotype distributions for the studied SNP were in the Hardy–Weinberg equilibrium (HWE). We used 2 × 2 or 2 × 3 contingency tables for comparing allele and genotype frequencies between groups. Tests for association between genotypes and quantitative traits were performed using the Mann-Whitney U test for traits with nonnormal distributions, or ANOVA for normally distributed traits. Student's t test was used to examine the mean differences in luciferase reporter gene expression or in VEGFA mRNA expression between two groups. p < 0.05 was the criterion for statistical significance. All statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS), version 13.0 (SPSS, Chicago, IL). We obtained estimates of LD values (r2, D') and the haplotype estimation using the SHEsis online software.[27]

Results

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

We first conducted genotyping experiments for the six VEGFA polymorphisms in the 302_Beijing group of samples. Genotype distributions of the studied SNPs were in HWE in both cases and controls. We analyzed the degree of LD for these six SNPs, and found there was no apparent LD (r2 ≤ 0.451). The genotype distributions and allelic frequencies of VEGFA polymorphisms in CHB and HCC patients were represented in Table 2. The frequency of A allele of rs1570360 was 9.4% in HCC patients vs. 17.7% in CHB patients (p = 0.013, OR = 0.48, 95% CI = 0.27-0.87). We used binary logistic regression to adjust for confounding factors and the result showed that rs1570360 was still independently associated with HCC (p = 0.02, OR = 0.45, 95% CI = 0.23–0.88). On the other hand, rs833061 showed borderline significance (p = 0.068). Considering that rs833061 was in absolute LD with another five SNPs, among which there was an 18 bp I/D polymorphism, we speculated rs833061 may be important. The four other SNPs, however, were not associated with HCC under any model.

Table 2. Genotype distributions of 6 SNPs in VEGFA gene of the 302_Beijing samples
 Allele, n (ratio)Genotype, n (ratio)Cochran Armitage trend testLogistic regression[1]
 1/212p/OR (95% CI)111222pp/OR (95% CI)
  1. p values were adjusted for age, gender, smoking and drinking by binary logistic regression under additive model.

  2. Abbreviations: CHB: chronic hepatitis B; CI: confidence interval; HCC: hepatocellular carcinoma; OR: odds ratio.

rs833061C/T        
HCC (n = 101) 39(0.193)163(0.807)0.0683(0.030)33(0.327)65(0.644)0.0780.078
CHB (n = 110) 59(0.268)161(0.732)0.65(0.41–1.03)11(0.100)37(0.336)62(0.564) 0.63(0.38–1.05)
rs1570360A/G        
HCC (n = 101) 19(0.094)183(0.906)0.0131(0.010)17(0.168)83(0.822)0.0150.02
CHB (n = 110) 39(0.177)181(0.823)0.48(0.27–0.87)4(0.036)31(0.282)75(0.682) 0.45(0.23–0.88)
rs2010963C/G        
HCC (n = 101) 94(0.465)108(0.535)0.7521(0.208)52(0.515)28(0.277)0.750.86
CHB (n = 110) 99(0.450)121(0.550)1.06(0.73–1.56)24(0.218)51(0.464)35(0.318) 1.04(0.67–1.62)
rs25648T/C        
HCC (n = 101) 23(0.114)179(0.886)0.541(0.010)21(0.208)79(0.782)0.540.26
CHB (n = 110) 21(0.095)199(0.905)1.22(0.65–2.27)2(0.018)17(0.155)91(0.827) 1.56(0.72–3.38)
rs3025040T/C        
HCC (n = 101) 34(0.168)168(0.832)0.401(0.010)32(0.317)68(0.673)0.390.72
CHB (n = 110) 44(0.200)176(0.800)0.81(0.50–1.33)4(0.036)36(0.327)70(0.636) 0.90(0.50–1.62)
rs10434A/G        
HCC (n = 101) 45(0.223)157(0.777)0.735(0.050)35(0.347)61(0.604)0.730.40
CHB (n = 110) 46(0.209)174(0.791)1.08(0.68–1.72)3(0.027)40(0.364)67(0.609) 1.28(0.72–2.27)

We next replicated genotyping of rs1570360 and rs833061 in three independent case–control samples from Beijing, Guangxi and Jiangsu respectively. The result was presented in Table 3. These two SNPs were associated with HCC significantly both with the same tendency as the first group of samples (rs833061: ptrend = 0.008 in Youan_Beijing samples, ptrend = 0.01 in Guangxi samples, ptrend = 0.01 in Jiangsu samples. rs1570360: ptrend = 0.00003 in Youan_Beijing samples, ptrend = 0.006 in Guangxi samples, ptrend = 0.02 in Jiangsu samples). These two SNPs were further validated in four independent groups of major HBV outcomes as 294 random controls, 502 non-HBV controls, 254 self-limited infection subjects and 253 LC patients (Table 4). Our results showed that the allele frequencies of rs833061 and rs1570360 were almost the same in random controls, non-HBV controls, self-limited infection subjects, CHB patients and LC patients, except for that in HCC patients, indicating that rs833061 and rs1570360 may associate exclusively to HCC. Haplotype analyze of rs833061 and rs1570360 showed that there were four haplotypes. C-A was a protective haplotype of HCC and T-G was risk haplotype of HCC in both Youan_Beijing, Guangxi and Jiangsu groups of subjects (data not shown).

Table 3. Association results for rs833061 and rs1570360 in replication studies
 Allele, n (ratio)Genotype, n (ratio)Cochran Armitage trend testLogistic regression[1]
 1/212p/OR (95% CI)111222pp/OR (95% CI)
  1. p values were adjusted for age, gender, smoking and drinking by binary logistic regression under additive model.

  2. Abbreviations: CHB: chronic hepatitis B; CI: confidence interval; HCC: hepatocellular carcinoma; OR: odds ratio.

Youan_Beijing         
rs833061C/T        
HCC (n = 402) 178(0.221)626(0.779)0.00816(0.040)146(0.363)240(0.597)0.0080.009
CHB (n = 1043) 562(0.269)1524(0.731)0.77(0.64–0.93)78(0.075)406(0.389)559(0.536) 0.71(0.55–0.92)
rs1570360A/G        
HCC (n = 402) 102(0.127)702(0.873)0.000024(0.010)94(0.234)304(0.756)0.000030.001
CHB (n = 1043) 405(0.194)1681(0.806)0.60(0.48–0.76)47(0.045)311(0.298)685(0.657) 0.61(0.46–0.82)
Guangxi         
rs833061C/T        
HCC (n = 337) 177(0.263)497(0.737)0.0121(0.062)135(0.401)181(0.537)0.010.02
CHB (n = 310) 202(0.326)418(0.674)0.74(0.58–0.94)35(0.113)132(0.426)143(0.461) 0.76(0.59–0.96)
rs1570360A/G        
HCC (n = 337) 134(0.199)540(0.801)0.00516(0.047)102(0.303)219(0.650)0.0060.02
CHB (n = 310) 164(0.265)456(0.735)0.69(0.53–0.89)25(0.081)114(0.368)171(0.552) 0.74(0.57–0.96)
Jiangsu         
rs833061C/T        
HCC (n = 367) 162(0.221)572(0.779)0.0118(0.049)126(0.343)223(0.608)0.01 
CHB (n = 375) 208(0.277)542(0.723)0.74(0.58–0.94)36(0.096)136(0.363)203(0.541)  
rs1570360A/G        
HCC (n = 367) 113(0.154)621(0.846)0.0212(0.033)89(0.242)266(0.725)0.02 
CHB (n = 375) 151(0.201)599(0.799)0.72(0.55–0.95)23(0.061)105(0.280)247(0.659)  
Table 4. Genotype distribution of rs833061 and rs1570360 in HBV-infected individuals with different clinical outcomes
 Random controls, n = 294 (ratio)Non-HBV controls, n = 502 (ratio)Self-limited infection, n = 254 (ratio)LC, n = 253 (ratio)HCCa, n = 402 (ratio)
  1. a

    Patients from Youan_Beijing group.

  2. Abbreviations: HBV: hepatitis B virus.

rs833061
CC18(0.061)36(0.072)16(0.063)15(0.059)16(0.040)
CT116(0.395)194(0.386)102(0.402)103(0.407)146(0.363)
TT160(0.544)272(0.542)136(0.535)135(0.534)240(0.597)
C152(0.259)266(0.265)134(0.264)133(0.263)178(0.221)
T436(0.741)738(0.735)374(0.736)373(0.737)626(0.779)
rs1570360
AA13(0.044)22(0.044)14(0.055)12(0.047)4(0.010)
AG82(0.279)140(0.279)72(0.283)69(0.273)94(0.234)
GG199(0.677)340(0.677)168(0.661)172(0.680)304(0.756)
A108(0.184)184(0.183)100(0.197)93(0.184)102(0.127)
G480(0.816)820(0.817)408(0.803)413(0.816)702(0.873)

To evaluate the VEGFA promoter polymorphisms on VEGFA transcriptional activity, we generated four luciferase reporter vectors (pGL3 basic), spanning −1661 to +279 bp of the VEGFA promoter region, that had identical sequences except for the rs699947, 18 bp I/D polymorphism, rs1005230, rs36026135, rs833061, rs13207351 and rs1570360. Since the previous six SNPs were in absolute LD, the four luciferase reporter vectors could be simply represented by rs833061 and rs1570360 as T-A, C-A, T-G, C-G. The CA haplotype had 2.59 fold higher luciferase activity compared with TG haplotype in HepG2 cells (p < 0.05) and 1.52 fold higher luciferase activity in SK-Hep-1 cells (p < 0.05), but in HeLa cells there was no significant difference (Figs. 2a2c). When Sp1 expression plasmids were co-transfected, the luciferase activity is elevated ∼2-fold, but there were no significant differences between different haplotypes in any of the three cell lines (Figs. 2a2c).

image

Figure 2. Correlation of VEGFA expression with the alleles and genotypes. (a–c) Influence of SNPs on VEGFA promoter activity. The horizontal axis represents the relative proportion of luciferase activity to corresponding pGL3-basic vectors. Data are mean±SD. (a) HepG2, (b) HeLa, (c) SK-Hep-1. (d) Binding affinity of nuclear proteins to biotin-labeled double-stranded oligonucleotides. Competitor, 100-fold unlabeled probe. (e) Supershift assays with Sp1 antibody. Lane 1, probes and nuclear extracts; Lane 2, with a rabbit IgG, Lane 3, with antibody to Sp1. (f) Quantification of VEGFA mRNA expression. GAPDH was used as an internal control gene. Final abundance figures were adjusted to yield an arbitrary value of 1 for HCC patients. Data are mean±SD. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

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We then examined whether the 18 bp ins allele had created a binding site of transcriptional factor Sp1, as suggested by computational analysis (AliBaba 2 software). As shown by electrophoretic mobility-shift assays (Fig. 2d), Sp1-containing nuclear extracts specifically bound to the biotin-labeled 18 bp ins probe. A 100-fold excess of unlabeled 18 bp oligonucleotide or Sp1 consensus oligonucleotide (ATT CGA TCG GGG CGG GGC GAG C) but not Sp1 mutant oligonucleotide (ATT CGA TCG GTT CGG GGC GAG C) competed with this binding. We next verified that the protein bound to the 18 bp ins allele was Sp1 by abolishing binding in supershift assays through the addition of specific antibodies against Sp1 (Fig. 2e).

Expression of VEGFA mRNA levels was measured in RNA from WBCs in 20 HCC patients, 37 CHB patients and 90 HBsAg-negative healthy individuals (Fig. 2f). Expression levels of VEGFA mRNA for the three different genotypes of rs833061 and rs1570360 were also compared in CHB patients and HBsAg-negative healthy individuals. The result showed that HCC patients had 6.95-fold and 5.16-fold higher VEGFA mRNA expression than HBsAg-negative healthy individuals and CHB patients (p < 0.05). The VEGFA mRNA level between different genotypes of rs833061 and rs1570360 in healthy individuals and CHB patients had no significant differences, though the homozygous of the major allele had lower VEGFA mRNA level than other genotypes of rs833061 and rs1570360 in either healthy individuals or CHB patients (data not shown).

Discussion

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

VEGFA is a highly polymorphic gene with more than 20 reported potential functional SNPs in cancer risk association studies. Some widely studied SNPs, i.e., −2578C/A (rs699947), −2,549 insertion/deletion polymorphism, −460C/T (rs833061), −1154G/A (rs1570360), −634C/G (rs2010963), +936C/T (rs3025039), +1612G/A (rs10434), are reported to be associated with multiple cancers but with controversial results.[28-31] On the other hand, there are only a few studies concerning HCC risk and VEGFA polymorphisms,[21, 22] with small sample size and limited polymorphisms studied. In the present study, we sequenced the VEGFA gene region, and finally chose six SNPs which could represent all potential functional SNP with MAF >10%. The LD between VEGFA polymorphisms region was very complicated.[7] We confirmed the absolute LD of six SNPs in the promoter and two SNPs in 3'-UTR in 96 samples. To the best of our knowledge, these LD were not reported by other references and should be confirmed in future validation studies.

The distribution of gene polymorphism differed greatly in different ethnicity and region. In this study, we collected samples from east, south and north of China, which may represent the population differences. The genotype distribution of rs833061 and rs1570360 between Beijing, Jiangsu and Guangxi population is different (Tables 2 and 3); however, the tendency of differences between CHB and HCC groups is similar. The association between rs833061, rs1570360 and HCC has been replicated in all three populations, which indicates that rs833061 and rs1570360, as well as polymorphisms in LD with rs833061, may have a genetic influence in the development of HCC.

Angiogenesis plays an important role in cancer from the initial stage of carcinogenesis to the end stage of metastatic disease and clearly plays a role in the pathogenesis of HCC.[32] VEGFA appears to play an important role in the early stage of hepatocarcinogenesis. Its expression increases gradually from low-grade dysplastic nodules to high-grade dysplastic nodules to early HCC.[33] Functional polymorphisms of VEGFA gene can influence the expression of mRNA and protein levels. The G allele of rs1570360 is shown to be associated with higher VEGFA production in stimulated leukocytes in vitro.[34] Stevens et al. showed that haplotypes containing the polymorphisms at rs833061/rs2010963 have a 71% higher basal promoter activity when compared with the wild-type sequence.[35]

The association of common VEGFA polymorphisms with multiple cancer susceptibility has been investigated in numerous studies but the results are often conflicting.[21, 22, 28-31] This may due to different types of cancers, different ethnicity of populations and sample size. Our result showed that only rs833061 and rs1570360, as well as rs699947, 18 bpI/D, rs1005230, rs36026135 and rs13207351 that were in absolute LD with rs833061, were associated with HCC susceptibility. As all the associated SNPs are in promoter, and in LD with each other, studying the combined effects of these SNPs may be helpful to clarify functional role of these SNPs.

Till date, some studies have attempted to find the role of one or a few SNPs in VEGFA promoter region with promoter activity, but these studies have yielded conflicting results.[35-37] The present result of luciferase assay showed that in HepG2 and SK-Hep-1 cell lines (which both were HCC cell lines), the rs1570360A and rs833061C allele had higher promoter activity compared with rs1570360G and rs833061T allele, which was in accordance with Radovich et al.[37] This result was also in accordance with the real-time RT-PCR and EMSA experiment of the present study. As suggested by computational analysis (AliBaba 2 software), of the seven associated promoter SNPs, only the 18 bpI/D polymorphism changed the binding site of transcriptional factors. The 18 bp ins allele created a binding site of Sp1. The EMSA experiment confirmed this. Since the 18 bp ins allele is in absolute LD with rs833061C, creating a binding site of Sp1 may increase promoter activity.

Several limitations of this study need to be addressed. Some clinical features between CHB and HCC patients did not match well, especially in the Youan_Beijing group of samples. In future studies, clinical features should be well matched. The real-time primers were designed on Exon 2 and Exon 3, which was aimed to test the total VEGFA mRNA expression. However, splice variants are common, so it is informative to test different splice variants expression levels in future studies.

In conclusion, we carried out a two-stage association study and found rs833061 and rs1570360 located in promoter region of VEGFA gene to be strongly associated with HBV related HCC, together with functional evidences.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

The authors are thankful to all the subjects participated in this study.

References

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References