Breast Cancer Research and Treatment

, Volume 125, Issue 3, pp 849–853 | Cite as

Association of a vascular endothelial growth factor gene 936 C/T polymorphism with breast cancer risk: a meta-analysis

  • Dae Sik Yang
  • Kyong Hwa Park
  • Ok Hee Woo
  • Sang Uk Woo
  • Ae-Ree Kim
  • Eun Sook Lee
  • Jae-Bok Lee
  • Yeul Hong Kim
  • Jun Suk Kim
  • Jae Hong Seo
Epidemiology

Abstract

Published studies on the association between the vascular endothelial growth factor (VEGF) gene 936 C/T polymorphism and breast cancer risk are inconclusive, and a meta-analysis is required to verify the association. Nine studies, including a total of 4,973 cases and 5,035 controls, were subjected to meta-analysis. When all eligible subjects were pooled for meta-analysis, the CT + TT genotypes were not associated with a significant decrease in breast cancer risk (odds ratio = 0.87; 95% confidence interval 0.75–1.02; P = 0.087). We also categorized by ethnicity (Caucasian, Asian, or mixed) for subgroup analysis, however, according to this subgroup analysis, we found no significant association between the CT and TT versus CC genotype with breast cancer risk reduction in any of the subgroups. We conclude that the VEGF gene 936 C/T polymorphism does not affect breast cancer risk.

Keywords

VEGF 936 C/T polymorphism Breast cancer risk Meta-analysis 

Introduction

Breast cancer is the second most common cancer in women after skin cancer, accounting for about one-third of all cancers in women [1]. Angiogenesis plays a critical role in the development of cancer. Solid tumors smaller than 1–2 mm3 are not vascularized. In order to grow larger than 2 mm3, tumors need blood vessels to supply oxygen and nutrients and remove metabolic waste. At the critical size of 2 mm3, it is difficult for oxygen and nutrients to diffuse to the cells in the center of the tumor, causing a state of cellular hypoxia that triggers the onset of tumoral angiogenesis [2, 3, 4].

In hypoxic tumors, vascular endothelial growth factor (VEGF) expression is upregulated in areas surrounding necrosis foci, suggesting a means by which the hypoxic environment created by the growing tumor mass may be upregulating angiogenic factors to increase their supply of oxygen [5, 6]. Study of the VEGF sequence has revealed the presence of a consensus binding sequence for HIF-1α. HIF-1α is a transcriptional regulator that is activated in response to hypoxic conditions. HIF-1α can increase transcription of VEGF mRNA, as well as stabilize the mRNA by associating with a HIF-1α binding site in the VEGF promoter region [7].

VEGF is a key regulator of vasculogenesis and angiogenesis with a specific mitogenicity for endothelial cells. In addition, VEGF is able to increase capillary permeability, dilate arteries, and chemotactically attract monocytes [8, 9]. VEGF is a disulfide-bonded dimeric glycoprotein, sharing close sequence homology with placenta growth factors, VEGF-B and VEGF-C, and lower sequence homology with platelet-derived growth factor [10, 11]. The human VEGF gene is located on chromosome 6p21.3 and contains eight exons, with a coding region of ~14 kb [12, 13]. The promoter regions and 5′-untranslated region of the VEGF gene were first screened for polymorphisms by Watson et al. [14]. Renner et al. [15] reported three novel polymorphisms (C702T, C936T, and G1612A) in the 3′-untranslated region and found that carriers of the 936T allele had significantly lower VEGF plasma levels than non-carriers, and Krippl et al. [16] reported that carriers of the VEGF 936T allele are at decreased risk for breast cancer. However, subsequent reports have shown that the VEGF 936T allele is not associated with breast cancer risk [17, 18, 19, 20, 21, 22]. The inconclusive nature of these results might be explained by the possible small effect of the polymorphism on breast cancer risk and the relatively small sample size in each of the published studies. Therefore, we performed a meta-analysis of the published studies for a more precise evaluation of this association.

Methods

Search strategy

We searched the literature from the National Library of Medicine and the Cochrane Library to identify relevant available articles. The key words and subject terms “936 C/T (rs3025039) polymorphism,” or “VEGF polymorphism” and “breast cancer” were used for the search. The language in which the papers were written was not restricted. All eligible studies were retrieved, and their bibliographies were checked for other relevant publications. Review articles and bibliographies of other relevant studies identified were searched by hand to find additional eligible studies. Only published studies with full text articles were included.

Inclusion criteria

The inclusion criteria were: (a) evaluation of the 936 C/T polymorphism and breast cancer risk, (b) case–control studies, and (c) sufficient published data for estimating an odds ratio (OR) with a 95% confidence interval (CI).

Data extraction

We followed a standard protocol for data extraction. For each study, the following data were recorded: first author’s surname, year of publication, ethnicity, criteria of enrolled patients, study design, total number of cases and controls, and number of cases and controls with the 936 C/T polymorphism (CC genotype vs. CT and TT genotypes). Too few homozygote variants were available to analyze the heterozygous and homozygous females separately; therefore, we compared the CC genotype (wild-type) with combined CT and TT genotypes (variant types).

Statistical analysis

The Q-statistic was used to investigate the degree of heterogeneity between the trials, and a P value of <0.1 was interpreted as significant heterogeneity. The I2 index expresses the percentage of the total variation across studies due to heterogeneity. I2 values of 25, 50, and 75% were used as evidence of low, moderate, and high heterogeneity, respectively. When there was no statistical heterogeneity, we used a fixed effect model. If heterogeneity was present, we used a random effect model (DerSimonian–Laird method) to account for inter-study heterogeneity instead of the fixed effect model [23]. All statistical analyses were performed with the use of STATA MP statistical software (Version 10.1; Stata Corporation, College Station, TX, USA). All statistical tests were two-sided.

Results

Study characteristics

Seven publications met the inclusion criteria for the study and provided complete data. Among them, Jin et al. [20] examined polymorphisms in the VEGF gene in familial breast cancer cases from Poland and Germany and in unselected breast cancer cases from Sweden, together with ethnically and geographically selected controls. Therefore, this study was analyzed separately according to nationality (Poland, Germany, and Sweden). In total, seven publications (nine studies), including 4,973 breast cancer cases and 5,035 controls, were included in the meta-analysis. Among the seven publications, six presented the numbers of CC, CT, and TT genotypes separately whereas one study showed only CC genotype and combined CT + TT genotypes. Since the number of TT genotype was too small for meta-analysis, we categorized 936 C/T polymorphisms as wild genotype (CC) versus variant genotype (CT + TT). According to ethnicity, we performed subgroup analysis for the five Caucasian studies, two Asian studies, and one mixed ethnicity study. The other characteristics of the studies included in the present meta-analysis are listed in Table 1.
Table 1

Characteristics of all studies included in the meta-analysis

Reference

Ethnicity

Enrolled patients

Sample size: cases/control

Cases

Control

CC

CT + TT

CC

CT + TT

Krippl et al. [16]

Caucasian

Prevalent breast cancer

500/500

412

88

353

147

Jin et al. [20] (Polish)

Caucasian

Familial breast cancer

412/422

298

114

297

125

Jin et al. [20] (German)

Caucasian

Familial breast cancer

153/163

120

33

128

35

Jin et al. [20] (Swedish)

Caucasian

Unselected breast cancer

924/934

708

216

720

214

Jacob et al. [18]

Caucasian

Postmenopausal breast cancer

488/489

360

128

363

126

Jakubowska et al. [19]

Caucasian

BRCA1 mutated breast cancer

319/290

245

74

202

88

Kataoka et al. [21]

Asian

Unselected breast cancer

1109/1195

744

365

793

402

Lin et al. [22]

Asian

Unselected breast cancer

220/334

155

65

211

123

Balasubramanian et al. [17]

Mixed

Unselected breast cancer

848/708

624

224

531

177

Meta-analysis results

The Q-statistic showed the between-study heterogeneity among the nine studies included in our meta-analysis (P = 0.004), and the I2-statistic detected the presence of heterogeneity (64.2%). Overall, when all the eligible studies were pooled into the meta-analysis, we found that a significantly decreased breast cancer risk was not associated with the CT and TT variant genotype in a dominant model (OR = 0.87; 95% CI 0.75–1.02; P = 0.087). In the subgroup analysis by ethnicity, between-study heterogeneity was shown in Caucasians (I2-statistic 71.0%; P = 0.004); however, between-study homogeneity was shown in Asians (I2-statistic 51.6%; P = 0.150). According to subgroup analysis by ethnicity, there was no significant association of the CT and TT versus CC genotypes with breast cancer risk reduction in the Caucasian group (OR = 0.83; 95% CI 0.66–1.06; P = 0.135), Asian group (OR = 0.87; 95% CI 0.66–1.15; P = 0.336), or mixed ethnicity group (OR = 1.08; 95% CI 0.86–1.35; P = 0.525), respectively (Fig. 1).
Fig. 1

Meta-analysis for the VEGF gene 936 C/T polymorphism and breast cancer risk

Publication bias

Begg’s funnel plot and Egger’s test were performed to analyze the publication bias of the literature. The shapes of the funnel plots did not reveal any obvious asymmetry (data not shown). The Harbord’s modified test for small-study effects was used to verify publication bias. The results did not suggest any evidence of publication bias (P = 0.274 for CC vs. CT + TT genotype).

Discussion

There are two possible explanations for the potential mechanism by which the VEGF 936T allele causes lower VEGF plasma levels as reported by Renner et al. [15]. One is that the 936 C/T mutation results in the loss of a potential binding site for AP-4. AP-4 is a helix-loop-helix transcription factor that enhances the expression of several viral and cellular genes by binding to specific enhancer sites [24, 25]. The other is that the association between the 936 C/T mutation and VEGF plasma levels could be due to linkage disequilibrium between this mutation and another yet unknown functional mutation elsewhere in the VEGF gene sequence [15].

Tumor growth over 2 mm3 requires an angiogenic switch, referred to as angiogenesis. Plasma VEGF levels are critical for tumor growth, and therefore, plasma VEGF may have an impact on cancer invasion and metastasis process. If plasma VEGF levels affect breast cancer risk, we would have evidence of a new mechanism for the initiation of breast carcinogenesis by plasma VEGF. In general, the disease state of cancer appears late in tumor development [4]. Before being diagnosed, a tumor can remain in a dormant state for a prolonged period of time [26]. Dormant human cancer is commonly defined as a microscopic tumor that does not expand in size and remains asymptomatic [27]. The escape of tumors from dormancy is considered to depend on the so-called angiogenic switch, a discrete event that can be triggered by various signals including angiogenic factors, such as VEGF and VPF [28]. There have been several reports that VEGF 936 C/T polymorphisms are associated with differences in plasma VEGF levels [15, 16]. Plasma high VEGF level could render an asymptomatic dormant tumor to become a more aggressive and clinically apparent tumor through stimulation of the angiogenesis mechanism. Therefore, we hypothesize that a high plasma VEGF level might indirectly influence clinically apparent breast cancer development.

Although several VEGF gene polymorphisms (VEGF 2578 C/A, VEGF 634 G/C, VEGF 1154 G/A, VEGF 460 T/C, and VEGF 405 G/C) [17, 18, 20, 21, 29] and VEGFR gene polymorphisms (VEGFR1 962 C/T, VEGFR2 889 G/A, and VEGFR2 1416 A/T) [30] associated studies about breast cancer risk were reported, however, studies about these polymorphisms showed no association with breast cancer risk and were limited number of articles for meta-analysis. They usually reported two or three articles which were summarized in Table 2. Therefore, we could perform meta-analysis only VEGF gene 936 C/T polymorphism which was reported more than seven articles.
Table 2

Other VEGF gene and VEGFR gene associated polymorphisms and allele frequency

Gene polymorphism

Author

Ethnicity

Case

Control

HWE P valuea

VEGF 2578 C/A

Jacobs et al.

Caucacian

498

495

0.30

Jin et al.

Caucacian

1503

1525

0.10

VEGF 634 G/C

Jacobs et al.

Caucacian

495

500

0.59

Jin et al.

Caucacian

936

941

0.25

VEGF 1154 G/A

Smith et al.

Caucacian

134

263

0.24

Jacobs et al.

Caucacian

495

492

0.68

Jin et al.

Caucacian

570

586

0.45

VEGF 460 T/C

Balasubramanian et al.

Mixed

493

498

0.77

Kataoka et al.

Asian

1123

1222

0.50

VEGF 405 G/C

Balasubramanian et al.

Mixed

490

498

0.78

Kataoka et al.

Asian

1095

1198

0.18

VEGFR1 962 C/T

Schneider et al.

Caucacian

NA

NA

0.24

VEGFR2 889 G/A

Schneider et al.

Caucacian

NA

NA

0.71

VEGFR2 1416 A/T

Schneider et al.

Caucacian

NA

NA

1.00

aHWE, Hardy–Weinberg equilibrium

Krippl et al. [16] reported that carriers of a VEGF 936T allele are at decreased risk for breast cancer (OR = 0.51, 95% CI 0.38–0.70) in 500 women with breast cancer and 500 sex- and age-matched healthy control subjects, and Jakubowska et al. [19] also reported that VEGF 936T allele appears to decrease breast cancer risks in BRCA1 carriers. However, other reports failed to find a statistically significant correlation between the VEGF 936 C/T polymorphism and breast cancer risk [17, 18, 20, 21, 22]. Therefore, the clinical significance of this polymorphism has been inconclusive until now. We performed a meta-analysis to verify the relationship of the VEGF 936 C/T polymorphism with breast cancer risk.

Our pooled results showed that a significant decrease in breast cancer risk was not associated with the CT + TT variant genotypes in a dominant model (OR = 0.87; 95% CI 0.75–1.02; P = 0.087). The effect of a single polymorphism on cancer susceptibility could vary between ethnic populations. Therefore, we performed a subgroup analysis to evaluate the susceptibility difference of the VEGF gene 936 C/T polymorphism according to ethnicity (Caucasian, Asian, and mixed). However, our subgroup analysis failed to show a significant association between the CT + TT versus CC genotype with breast cancer risk reduction in the Caucasian group, Asian group, and mixed ethnicity group. Therefore, we carefully suggest that the VEGF 936 C/T polymorphism does not influence breast cancer risk.

Notes

Acknowledgments

This study was supported by a grant of the Korean Health 21 R&D Project, Ministry of Health and Welfare, Republic of Korea (0412-CR01-0704-001).

Conflict of interest

None.

References

  1. 1.
    Bray F, McCarron P, Parkin DM (2004) The changing global patterns of female breast cancer incidence and mortality. Breast Cancer Res 6:229–239CrossRefPubMedGoogle Scholar
  2. 2.
    Folkman J (1971) Tumor angiogenesis: therapeutic implications. N Engl J Med 285:1182–1186CrossRefPubMedGoogle Scholar
  3. 3.
    Folkman J, Cole P, Zimmerman S (1966) Tumor behavior in isolated perfused organs: in vitro growth and metastases of biopsy material in rabbit thyroid and canine intestinal segment. Ann Surg 164:491–502CrossRefPubMedGoogle Scholar
  4. 4.
    Folkman J, Kalluri R (2004) Cancer without disease. Nature 427:787CrossRefPubMedGoogle Scholar
  5. 5.
    Semenza GL (1998) Hypoxia-inducible factor 1: master regulator of O2 homeostasis. Curr Opin Genet Dev 8:588–594CrossRefPubMedGoogle Scholar
  6. 6.
    Tacchini L, Bianchi L, Bernelli-Zazzera A, Cairo G (1999) Transferrin receptor induction by hypoxia. HIF-1-mediated transcriptional activation and cell-specific post-transcriptional regulation. J Biol Chem 274:24142–24146CrossRefPubMedGoogle Scholar
  7. 7.
    Wang GL, Semenza GL (1995) Purification and characterization of hypoxia-inducible factor 1. J Biol Chem 270:1230–1237CrossRefPubMedGoogle Scholar
  8. 8.
    Clauss M, Gerlach M, Gerlach H, Brett J, Wang F, Familletti PC, Pan YC, Olander JV, Connolly DT, Stern D (1990) Vascular permeability factor: a tumor-derived polypeptide that induces endothelial cell and monocyte procoagulant activity, and promotes monocyte migration. J Exp Med 172:1535–1545CrossRefPubMedGoogle Scholar
  9. 9.
    Senger DR, Galli SJ, Dvorak AM, Perruzzi CA, Harvey VS, Dvorak HF (1983) Tumor cells secrete a vascular permeability factor that promotes accumulation of ascites fluid. Science 219:983–985CrossRefPubMedGoogle Scholar
  10. 10.
    Keck PJ, Hauser SD, Krivi G, Sanzo K, Warren T, Feder J, Connolly DT (1989) Vascular permeability factor, an endothelial cell mitogen related to PDGF. Science 246:1309–1312CrossRefPubMedGoogle Scholar
  11. 11.
    Maglione D, Guerriero V, Viglietto G, Delli-Bovi P, Persico MG (1991) Isolation of a human placenta cDNA coding for a protein related to the vascular permeability factor. Proc Natl Acad Sci USA 88:9267–9271CrossRefPubMedGoogle Scholar
  12. 12.
    Tischer E, Mitchell R, Hartman T, Silva M, Gospodarowicz D, Fiddes JC, Abraham JA (1991) The human gene for vascular endothelial growth factor. Multiple protein forms are encoded through alternative exon splicing. J Biol Chem 266:11947–11954PubMedGoogle Scholar
  13. 13.
    Vincenti V, Cassano C, Rocchi M, Persico G (1996) Assignment of the vascular endothelial growth factor gene to human chromosome 6p21.3. Circulation 93:1493–1495PubMedGoogle Scholar
  14. 14.
    Watson CJ, Webb NJ, Bottomley MJ, Brenchley PE (2000) Identification of polymorphisms within the vascular endothelial growth factor (VEGF) gene: correlation with variation in VEGF protein production. Cytokine 12:1232–1235CrossRefPubMedGoogle Scholar
  15. 15.
    Renner W, Kotschan S, Hoffmann C, Obermayer-Pietsch B, Pilger E (2000) A common 936 C/T mutation in the gene for vascular endothelial growth factor is associated with vascular endothelial growth factor plasma levels. J Vasc Res 37:443–448CrossRefPubMedGoogle Scholar
  16. 16.
    Krippl P, Langsenlehner U, Renner W, Yazdani-Biuki B, Wolf G, Wascher TC, Paulweber B, Haas J, Samonigg H (2003) A common 936 C/T gene polymorphism of vascular endothelial growth factor is associated with decreased breast cancer risk. Int J Cancer 106:468–471CrossRefPubMedGoogle Scholar
  17. 17.
    Balasubramanian SP, Cox A, Cross SS, Higham SE, Brown NJ, Reed MW (2007) Influence of VEGF-A gene variation and protein levels in breast cancer susceptibility and severity. Int J Cancer 121:1009–1016CrossRefPubMedGoogle Scholar
  18. 18.
    Jacobs EJ, Feigelson HS, Bain EB, Brady KA, Rodriguez C, Stevens VL, Patel AV, Thun MJ, Calle EE (2006) Polymorphisms in the vascular endothelial growth factor gene and breast cancer in the Cancer Prevention Study II cohort. Breast Cancer Res 8:R22CrossRefPubMedGoogle Scholar
  19. 19.
    Jakubowska A, Gronwald J, Menkiszak J, Gorski B, Huzarski T, Byrski T, Edler L, Lubinski J, Scott RJ, Hamann U (2008) The VEGF_936_C>T 3′UTR polymorphism reduces BRCA1-associated breast cancer risk in Polish women. Cancer Lett 262:71–76CrossRefGoogle Scholar
  20. 20.
    Jin Q, Hemminki K, Enquist K, Lenner P, Grzybowska E, Klaes R, Henriksson R, Chen B, Pamula J, Pekala W, Zientek H, Rogozinska-Szczepka J, Utracka-Hutka B, Hallmans G, Forsti A (2005) Vascular endothelial growth factor polymorphisms in relation to breast cancer development and prognosis. Clin Cancer Res 11:3647–3653CrossRefPubMedGoogle Scholar
  21. 21.
    Kataoka N, Cai Q, Wen W, Shu XO, Jin F, Gao YT, Zheng W (2006) Population-based case–control study of VEGF gene polymorphisms and breast cancer risk among Chinese women. Cancer Epidemiol Biomarkers Prev 15:1148–1152CrossRefPubMedGoogle Scholar
  22. 22.
    Lin GT, Tseng HF, Yang CH, Hou MF, Chuang LY, Tai HT, Tai MH, Cheng YH, Wen CH, Liu CS, Huang CJ, Wang CL, Chang HW (2009) Combinational polymorphisms of seven CXCL12-related genes are protective against breast cancer in Taiwan. OMICS 13(2):165–172CrossRefPubMedGoogle Scholar
  23. 23.
    DerSimonian R, Laird N (1986) Meta-analysis in clinical trials. Control Clin Trials 7:177–188CrossRefPubMedGoogle Scholar
  24. 24.
    Hu YF, Luscher B, Admon A, Mermod N, Tjian R (1990) Transcription factor AP-4 contains multiple dimerization domains that regulate dimer specificity. Genes Dev 4:1741–1752CrossRefPubMedGoogle Scholar
  25. 25.
    Mermod N, Williams TJ, Tjian R (1988) Enhancer binding factors AP-4 and AP-1 act in concert to activate SV40 late transcription in vitro. Nature 332:557–561CrossRefPubMedGoogle Scholar
  26. 26.
    Demicheli R (2001) Tumour dormancy: findings and hypotheses from clinical research on breast cancer. Semin Cancer Biol 11:297–306CrossRefPubMedGoogle Scholar
  27. 27.
    Uhr JW, Scheuermann RH, Street NE, Vitetta ES (1997) Cancer dormancy: opportunities for new therapeutic approaches. Nat Med 3:505–509CrossRefPubMedGoogle Scholar
  28. 28.
    Carmeliet P, Jain RK (2000) Angiogenesis in cancer and other diseases. Nature 407:249–257CrossRefPubMedGoogle Scholar
  29. 29.
    Smith KC, Bateman AC, Fussell HM, Howell WM (2004) Cytokine gene polymorphisms and breast cancer susceptibility and prognosis. Eur J Immunogenet 31:167–173CrossRefPubMedGoogle Scholar
  30. 30.
    Schneider BP, Radovich M, Sledge GW, Robarge JD, Li L, Storniolo AM, Lemler S, Nguyen AT, Hancock BA, Stout M, Skaar T, Flockhart DA (2008) Association of polymorphisms of angiogenesis genes with breast cancer. Breast Cancer Res Treat 111:157–163CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC. 2010

Authors and Affiliations

  • Dae Sik Yang
    • 1
  • Kyong Hwa Park
    • 2
  • Ok Hee Woo
    • 3
  • Sang Uk Woo
    • 4
  • Ae-Ree Kim
    • 5
  • Eun Sook Lee
    • 4
  • Jae-Bok Lee
    • 4
  • Yeul Hong Kim
    • 2
  • Jun Suk Kim
    • 2
  • Jae Hong Seo
    • 2
  1. 1.Department of Radiation OncologyKorea University Guro HospitalSeoulKorea
  2. 2.Division of Medical Oncology, Department of Internal MedicineKorea University Guro HospitalSeoulKorea
  3. 3.Department of Diagnostic RadiologyKorea University Guro HospitalSeoulKorea
  4. 4.Department of SurgeryKorea University Guro HospitalSeoulKorea
  5. 5.Department of PathologyKorea University Guro HospitalSeoulKorea

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