Indian Journal of Cancer Home 

[Download PDF]
Year : 2014  |  Volume : 51  |  Issue : 4  |  Page : 512--517

Association of vascular endothelial growth factor single nucleotide polymorphisms on the prognosis of breast cancer patients

J Rani1, B Rahul1, G Ramesh1, L Krishnamoorthy1, C Shilpa1, G Ramaswamy1, V Deshmane2,  
1 Department of Biochemistry, Kidwai Memorial Institute of Oncology, Bangalore, Karnataka, India
2 Department of Surgical Oncology, Kidwai Memorial Institute of Oncology, Bangalore, Karnataka, India

Correspondence Address:
L Krishnamoorthy
Department of Biochemistry, Kidwai Memorial Institute of Oncology, Bangalore, Karnataka


Background: Vascular endothelial growth factor (VEGF), a major mediator of vascular permeability and angiogenesis, may play a pivotal role in mediating the development and progression of breast cancer. In the present study, we examined the genetic variations of the VEGF gene to assess its possible relation to breast cancer. Materials And Methods: A total of 200 patients with histologically confirmed cases of breast cancer and 200 healthy women were genotyped for VEGF single nucleotide polymorphisms (405G > C and −1154G > A) by polymerase chain reaction-restriction fragment length polymorphism analysis. Pre-operative plasma VEGF levels were determined by enzyme-linked immunosorbent assay in 200 women with breast cancer and in 200 normal female controls. Results: The genotype frequencies of the +405G > C, −1154G > A polymorphisms did not show a significant deviation from the Hardy-Weinberg expectation. The minor allele frequencies of the +405G > C and −1154G > A polymorphisms among cases and controls were 33.5% (C allele), 31.5% (A allele) and 35% (C allele), 34.5% (A allele) respectively. +405GG and −1154GG genotypes were associated with higher levels of VEGF among breast cancer cases and controls. Increased plasma VEGF levels were significantly associated with, clinical stage of the disease (P = 0.035). Conclusion: Although none of the polymorphisms were significantly associated with breast cancer, some of the VEGF genotypes may influence tumor growth through an altered expression of VEGF and tumor angiogenesis.

How to cite this article:
Rani J, Rahul B, Ramesh G, Krishnamoorthy L, Shilpa C, Ramaswamy G, Deshmane V. Association of vascular endothelial growth factor single nucleotide polymorphisms on the prognosis of breast cancer patients.Indian J Cancer 2014;51:512-517

How to cite this URL:
Rani J, Rahul B, Ramesh G, Krishnamoorthy L, Shilpa C, Ramaswamy G, Deshmane V. Association of vascular endothelial growth factor single nucleotide polymorphisms on the prognosis of breast cancer patients. Indian J Cancer [serial online] 2014 [cited 2019 Sep 21 ];51:512-517
Available from:

Full Text


Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death among females. Presently, 75,000 new cases of breast cancer occur in Indian women every year. It has also been pointed that in the metropolitan cities of New Delhi and Mumbai, the most common cancer in women is breast cancer. Nearly, 80% of Indian women with breast cancers are below 65 years.[1]

A considerable number of studies observed much higher association between cancer risk and vascular endothelial growth factor (VEGF) genetic polymorphisms among Indians. Prakash et al.,[2] which demonstrated a much greater risk for end stage renal disease in the patients carrying a combination of VEGF −2578C and −2549D alleles. Mittal et al.[3] found that the haplotypes A-A and A-G (VEGF 2578, VEGF −1154) were associated with reduced risk for allograft rejection in renal transplant recipients. Agrawal et al.[4] reported two common polymorphisms of the VEGF gene, −1154G/A and +936C/T, increase the risk of recurrent miscarriages in North Indian women. Data for single polymorphism and single cancer type; however, was insufficient to validate an association. It appears that much more experiments involving larger sample size, cross-tabulating genetic polymorphisms and environmental factors are required in order to identify the genetic markers for different cancers in Indian populations.

The VEGF gene is located on chromosome 6p21.3 and consists of eight exons that exhibit alternate splicing to form a family of proteins.[5] Purified VEGF is an approximately 46-kDa protein, which dissociates upon reduction into two apparently identical 23-kDa subunits.[6] There is considerable variation between individuals in VEGF expression and analysis of the 5' flanking region of the gene has shown the presence of many polymorphisms.[7],[8] Association has been reported in case-control studies between VEGF 405G > C polymorphisms and diseases such as macular degeneration,[9] lung cancer [5] and endometriosis.[10]

The +405G > C polymorphisms in the 5'-untranslated region has a significant effect on VEGF protein production and was found to be associated with VEGF production in healthy subjects. G allele at position +405, which probably lies within the myeloid zinc finger protein binding site, affects transcriptional activity and increases VEGF production in peripheral blood mononuclear cells (PBMC) in response to lipopolysaccharide.[11] Awata et al.[12] reported that individuals with the +405CC genotype had a higher fasting serum VEGF level than those with other genotypes and that they carried an increased risk of diabetic retinopathy. In a recent in vitro study, carrying a haplotype containing the +405G and −460C polymorphisms was found to significantly increase basal VEGF promoter activity and phorbol ester-induced responsiveness.[13]

The polymorphism at position −1154, which is located within the promoter region and have been shown to be associated with VEGF production from stimulated PBMC.In vitro work showed that −1154GG genotypes had increased VEGF secretion in human PBMC compared with carriage of a rare allele.[14],[15] Pander et al.[16] reported that the variant allele for −1154G > A results in lower VEGF expression. Yang et al.[17] also reported that −1154G allele was associated with higher VEGF protein levels in patients.

Schneider et al.[18] in a case control study evaluated the effect −1154G > A polymorphism in breast cancer patients reported an improved median overall survival in patients with VEGF −1154AA genotypes. Lu et al.[19] evaluated the association of G +405C and C −460T genotypes with breast cancer characteristics and found that these polymorphisms were unrelated to the TNM Stage (Tumor-Node-Metastasis), estrogen receptor (ER) and progesterone receptor (PR) status of cancer at diagnosis. Kataoka et al.[20] in a study involving 1093 cases and 1184 controls also reported that the −460T/405G/936T haplotype was associated with a reduced risk of breast cancer, particularly in premenopausal women. They did not find any statistically significant association of the two single nucleotide polymorphisms (SNP's) (−460T, +405G) in relation to breast cancer risk. Beeghly-Fadiel et al.[21] in case-control study involving 2079 cases and 2148 controls found no association between +405G > C SNP and breast cancer risk.

We hypothesized that VEGF, +405G and −1154A alleles might be associated with breast cancer prognosis and evaluated this hypothesis in a case-control study conducted among South Indian women.

 Materials and Methods

Histologically confirmed cases of breast cancer samples were obtained from 200 patients registered (2008-2009) in the Breast Service Unit. Patient's age, stage, grade, nodal status, ER and PR status were noted from the case files. Age matched (±5 years) healthy female controls were selected from patient relatives.

Inclusion criteria

All patients with histologically confirmed cases of breast cancer were taken for the study.

Exclusion criteria

A questionnaire was used to collect demographic information, personal medical history and family history from controls. Patients with other malignancies, liver problem, a history of ionizing irradiation to the chest region, family history of breast cancer were excluded. The study protocol was approved by the Institutional Ethical Committee and Informed consent was obtained from the patients/relatives of the subjects under study. All the participants of the study belonged to the same ethnic group.

A total volume of 5 ml of blood was collected from each subject after an overnight fast by routine venipuncture. The blood sample was then distributed into different tubes for the assays of various biochemical parameters.

Deoxyribonucleic acid extraction

DNA for polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis was extracted from leukocytes isolated from whole blood by using DNA extraction kit (Genei).

Genotyping of the +405G > C polymorphisms in the 5' untranslated region of the VEGF gene was determined by PCR/RFLP analysis. The method described by Buraczynska et al.,[22] was used for the detection of +405G > C polymorphism. PCR was carried out in a total volume of 30 μl, containing 200 ng genomic DNA, 1.5 μmol of each primer (Sigma, USA), IX Taq polymerase buffer (1.5 mM MgCl2) and 1U of Taq DNA polymerase (Genie, India). For the +405G > C polymorphism the forward and reverse primers were 5'-ATTTATTTTTGCTTGCCATT-3' and 5'-GTCTGTCTGTCTGTCCGTCA-3' respectively. PCR amplification was performed in a programmable thermal cycler gradient PCR system (Eppendorf AG, Hamburg, Germany).

The PCR product was digested with the BsmFI restriction endonuclease. (New England Biolabs, USA) at 65°C overnight for the +405G > C polymorphism, separated by 2% agarose gel electrophoresis and identified using ethidium bromide staining. For the VEGF +405, polymorphism the uncut fragment was 304 bp ([C allele, minor allele] and digestion products were 193 and 111 bp [G allele]) [Figure 1]a and [Figure 1]b.{Figure 1}

The method described by Han et al.,[23] was used for the detection of −1154G > A polymorphisms. For the −1154G > A polymorphism the forward and reverse primers were 5'-TCCTGCTCCCTCCTCGCCAATG-3' and 5'-GCGGGGACAGGCGAGCCTC-3' respectively. Genomic DNA was amplified in a final volume of 30 μl using the following conditions: Initial denaturation at 95°C for 10 min followed by 35 cycles at 95°C for 45 s, 62°C for 45 s and 72°C for 30 s. A final extension was at 72°C for 10 min.

The PCR product was digested with the MnlI restriction endonuclease (New England Biolabs, USA) at 37°C overnight for the −1154G > A polymorphism. PCR product of −1154G > A polymorphism has 206 base pairs. RFLP results of 1154G > A was 150 +34 +22 for (1154G allele) and 184 +22 for (1154A allele) and heterozygous having 184 + 154 + 34 + 22 bp [Figure 2]a and [Figure 2]b.{Figure 2}

Plasma VEGF levels were determined in 200 patients using commercially available enzyme-linked immunosorbent assay (ELISA) designed to measure VEGF levels (Quantikine, RandD Systems Minneapolis, MN). The assay exhibits no significant cross-reactivity with other angiogenesis factors and has a sensitivity of 9.0 pg/ml. Optical density was measured at 450 nm using a microtiter plate reader (TECAN ELISA READER). A standard curve was prepared from 2000 pg/ml stock standard VEGF by serially diluting as 31.2, 62.5, 125, 250, 500, 1000 with assay buffer and sample concentrations were determined.


Aliquot 0.1 ml/well of the 2000 pg/ml, 1000 pg/ml, 500 pg/ml, 250 pg/ml, 125 pg/ml, 62.5 pg/ml, 31.2 pg/ml human VEGF standard solutions into the precoated 96-well plate. Add 0.1 ml of the sample diluent buffer into the control well (zero well). Add 0.1 ml of each properly diluted sample of human sera, plasma, body fluids, tissue lysates or cell culture supernatants to each empty well. Seal the plate with the cover and incubate at room temperature for 2 h. Remove the cover, discard the plate content and wash the plate three times with wash buffer. Add 0.1 ml of biotinylated anti-human VEGF antibody working solution into each well and incubate the plate at room temperature for 2 h. Wash the plate three times with wash buffer and add 0.2 ml of prepared substrate solution into each well and incubate the plate at room temperature for 25 min. Wash the plate 3 times with wash buffer and add 0.2 ml of prepared stop solution into each well. The color changes into yellow immediately. Read the optical density, at 450 nm in a microplate reader within 30 min after adding the stop solution.

Statistical analysis

The data was analyzed using SPSS 16.0. The frequency of genotype was determined by direct counting. Odds ratio and 95% confidence interval were estimated as a measure of association between the genotype and breast cancer. The genotypic distribution amongst subjects was tested for Hardy-Weinberg equilibrium using Fisher's exact test. Results on continuous measurements were presented on Mean ± standard deviation (SD) (min-max) and results on categorical measurements were presented in number (%). Significance was assessed at 5% level of significance. Logistic regression analysis was used to assess the association of predictors of elevated VGEF (pg/ml) in cases.


The population consisted of 400 subjects divided into cases (n = 200) and controls (n = 200). The age limit for both populations was set at 21-81 years. The mean age for the cases was 48.80 ± 11.37 and for the control group was 47.29 ± 10.75 years. A preponderance of the patients was postmenopausal 73 (36.5%) and received no prior adjuvant therapy. Out of the 200 cases, 113 patients were node-positive and 87 cases were node-negative [Table 1]. Majority of the patients were in Stage II A followed by Stage III B. Most of the study subjects are in Grade III. Out of the 200 breast cancer cases, only 26 cases (13%) were showing distant metastasis.{Table 1}

Amongst both cases and controls, the genotypic distributions of the individual SNPs (+405G > C, −1154G > A) were all in Hardy-Weinberg equilibrium. The +405 genotype frequencies amongst the 200 cases were GG = 44.5%, GC = 44% and CC = 11.5%. The +405 genotype frequencies amongst the 200 controls were GG = 42.5%, GC = 44.5% and CC = 13%. The 'C' allele frequency for +405G > C polymorphism was 35% and 33.5% respectively for controls and cases. The genotype frequency for the homozygous wild-type and heterozygous and homozygous variant for −1154G SNP amongst cases and controls were as follows; 47.5%, 42%, 10.5% and 42.5%, 46%, 11.5% respectively. The "A" allele frequency was 31.5% and 34.5% in cases and controls respectively [Table 2].{Table 2}

We examined the effect of +405G > C, −1154G > A polymorphisms on tumor characteristics of breast cancer patients. In the present study, we did not find any significant associations between the simultaneous carriage of the +405CC and −1154AA homozygous genotypes and tumor characteristics such as TNM stage, Grade, ER/PR status of the patients at the time of diagnosis. The results are shown in [Table 3].{Table 3}

Plasma VEGF levels ranged from 31 to 876 pg/ml among breast cancer patients and among controls a range of less than minimum detectable level, i.e. <9 pg/ml to 136.0 pg/ml were shown. Mean VEGF level was significantly elevated in cases compared with control (t = 8.248; P < 0.001). Baseline concentrations of plasma VEGF were elevated (i.e. ≥123 pg/ml) in 52% (104) of the 200 evaluable patients and 48% cases were having low-levels of VEGF (VEGF < 123 pg/ml). The Mean and SD of cases was 126.58 ± 16.23 pg/ml and for controls was 71.76 ± 5.33 pg/ml. The values are showed in [Table 4].{Table 4}

Next, we studied VEGF plasma levels and VEGF genotypes in breast cancer patients and healthy subjects to assess possible functional relevance of the VEGF polymorphisms. The highest production was observed for the 405GG genotype, the intermediate production for the 405GC genotype and the lowest production was observed for the 405CC genotype.

For 1154G > A polymorphism, the highest production was observed for the GG genotype, the intermediate production for the GA genotype and the lowest production was observed for the AA genotype. Patients with −1154AA allele were showing lowest VEGF production suggesting a protective role of this allele, but this was not statistically significant (P = 0.681) [Table 5].{Table 5}

A significant association was observed between plasma VEGF and clinical stage by ANOVA (P = 0.035). No significant correlation was found between VEGF and other baseline variables such as age, menopausal status, ER/PR status etc., No statistical evaluation was carried out for metastatic pattern as there was only limited number of metastatic cases [Table 6]. By logistic regression analysis we found that +405GG and −1154GG genotypes were associated with higher levels of VEGF [Table 7].{Table 6}{Table 7}


Several studies have reported the prevalence of VEGF polymorphisms. Some have preferred to refer prevalence as genotype frequency while others refer to it as the frequency of the risk allele. The frequency of occurrence of the mutant allele (+405C) varies among different ethnic groups of the world. Lu et al.[19] reported 17.5% of homozygosity among Americans. Memariani et al.[24] have reported 12.5% 'C' allele frequency among Iranian population. Among Indians Bhanoori et al.[10] has observed VEGF homozygous genotype (4005CC) frequency of 1.9%, with a 'C' allele frequency of 18.3%.

The prevalence of the VEGF −1154G/A homozygous genotype reported was 0.7% and 13.1% among Koreans and Japanese populations respectively.[12],[23] In Europe, the frequency for homozygosity ranged from 11% in Germany [25] to 12.9% in UK [26] while in Poland [25] and Tunisia [27] the homozygosity were 10.9% and 14% respectively. Among African Americans the frequency of rare allele was 10% while in Whites the frequency is little higher, i.e. 33%.[28]

Multiple factors could be the reason for the difference between our observations in this study and results reported by others. Genetic contribution to risk susceptibility to cancer could vary between different ethnic groups with different environmental background. These include differences in ethnicity, genetic profiling techniques employed, gene-gene interaction and gene-environment interaction.

Our study has been carried out to find the prevalence of +405G > C, −1154G > A VEGF polymorphisms in our population and to find out the prognostic significance of these polymorphisms among breast cancer patients. We hypothesized that VEGF, +405G and −1154A alleles might be associated with breast cancer prognosis. In our study, significantly higher levels of VEGF (P < 0.001) were seen in cases with the '405GG' genotype (wild type) when compared with the respective control group.And the lowest production of VEGF was seen in the patient group with the "405CC" genotype. For 1154G/A polymorphism, the highest production was observed for the GG genotype and patients with −1154A allele were showing lowest VEGF production. If the individual angiogenic potential could be predicted on the basis of VEGF genotypes, the efficacy of antiangiogenic treatment in breast cancer could be further enhanced. Knowledge of the tumor level of VEGF might be helpful in the selection of optimal anticancer therapy in order to maximize the chance of good clinical response.

A high serum VEGF-A level in cancer patients is generally associated with unfavorable clinical parameters such as disease progression, lack of response to chemotherapy and poor survival. Increased serum VEGF levels may therefore be clinically useful for the prediction of increased tumor growth, recurrence or metastatic spread in individual patients.[28] Toi et al.[29] evaluated the prognostic value of VEGF expression in 103 patients with breast cancer. The authors reported that the relapse-free survival (RFS) rate of patients with VEGF-rich tumors was significantly worse than that of patients with VEGF-negative tumors (P < 0.01). Relf et al.[30] assessed the expression of VEGF messenger RNA in 64 breast cancers of patients with node-negative (n = 35) or node-positive (n = 29) disease. Univariate analysis for RFS showed that patients with high values of VEGF had significantly higher risk of relapse than those with tumors with low levels of VEGF (P = 0.03).

We have taken siblings as matched controls in our study. This may result in less variability for genetic risk factors within the matched set and hence, less confounding than using controls who are not siblings.[31] However, they may also introduce a negative bias in the study results because the controls may be too similar to cases with regard to exposure status; that is, they may not represent the true range of exposure that existed in the source population because of their similarity to the cases. Hospital-based case-control studies generally use hospital controls, that is, patients admitted to same hospital (s) for reasons other than the study disease. Although there are some advantages in terms of convenience, better recall and comparability between hospital cases and hospital controls, the chief disadvantage is that the exposure frequency may be different from that in the source population. This could lead to erroneous conclusions about the relationship between the study exposure and outcome in the target population; thus, weakening the internal validity of the study.

In our study, no significant association was found between +405G > C, −1154G > A VEGF polymorphism and breast cancer; however, we have found that some of the genotypes (+405GG, −1154GG) altered the VEGF expression. Further studies on larger populations may be necessary to confirm these observations, besides other mediators of neovascularization including interleukins, oncogenes and some growth factors may produce their effects by altering the expression of VEGF. PCR-RFLP method was used for genotyping of the subjects. RFLP is a well-established and frequently used method for genotyping and provide information on genetic diseases. This method is indirect so the process is extremely laborious and time-consuming. However, considering the higher initial cost of other genotyping assays such as Taqman, Goldengate assays, RFLP is affordable for preliminary studies like ours. We are planning to collaborate with other national institutions for future studies.


We thank Indian Council of Medical Research (ICMR) for financial assistance.


1Chopra R. The Indian scene. J Clin Oncol 2001;19:106S-11.
2Prakash S, Prasad N, Sharma RK, Faridi RM, Agrawal S. Vascular endothelial growth factor gene polymorphisms in North Indian patients with end stage renal disease. Cytokine 2012;58:261-6.
3Mittal RD, Srivastava P, Singh V, Jaiswal P, Kapoor R. Association of common variants of vascular endothelial growth factor and interleukin-18 genes with allograft survival in renal transplant recipients of North India. DNA Cell Biol 2011;30:309-15.
4Aggarwal S, Parveen F, Faridi RM, Phadke S, Borkar M, Agrawal S. Vascular endothelial growth factor gene polymorphisms in North Indian patients with recurrent miscarriages. Reprod Biomed Online 2011;22:59-64.
5Lee SJ, Lee SY, Jeon HS, Park SH, Jang JS, Lee GY, et al. Vascular endothelial growth factor gene polymorphisms and risk of primary lung cancer. Cancer Epidemiol Biomarkers Prev 2005;14:571-5.
6Tischer E, Mitchell R, Hartman T, Silva M, Gospodarowicz D, Fiddes JC, et al. The human gene for vascular endothelial growth factor. Multiple protein forms are encoded through alternative exon splicing. J Biol Chem 1991;266:11947-54.
7Brogan IJ, Khan N, Isaac K, Hutchinson JA, Pravica V, Hutchinson IV. Novel polymorphisms in the promoter and 5' UTR regions of the human vascular endothelial growth factor gene. Hum Immunol 1999;60:1245-9.
8Schultz A, Lavie L, Hochberg I, Beyar R, Stone T, Skorecki K, et al. Interindividual heterogeneity in the hypoxic regulation of VEGF: Significance for the development of the coronary artery collateral circulation. Circulation 1999;100:547-52.
9Churchill AJ, Carter JG, Lovell HC, Ramsden C, Turner SJ, Yeung A, et al. VEGF polymorphisms are associated with neovascular age-related macular degeneration. Hum Mol Genet 2006;15:2955-61.
10Bhanoori M, Arvind Babu K, Pavankumar Reddy NG, Lakshmi Rao K, Zondervan K, Deenadayal M, et al. The vascular endothelial growth factor (VEGF) +405G>C 5'-untranslated region polymorphism and increased risk of endometriosis in South Indian women: A case control study. Hum Reprod 2005;20:1844-9.
11Watson CJ, Webb NJ, Bottomley MJ, Brenchley PE. Identification of polymorphisms within the vascular endothelial growth factor (VEGF) gene: Correlation with variation in VEGF protein production. Cytokine 2000;12:1232-5.
12Awata T, Inoue K, Kurihara S, Ohkubo T, Watanabe M, Inukai K, et al. A common polymorphism in the 5'-untranslated region of the VEGF gene is associated with diabetic retinopathy in type 2 diabetes. Diabetes 2002;51:1635-9.
13Stevens A, Soden J, Brenchley PE, Ralph S, Ray DW. Haplotype analysis of the polymorphic human vascular endothelial growth factor gene promoter. Cancer Res 2003;63:812-6.
14Mohammadi M, Ollier W, Hutchinson I. A functional association study of VEGF gene polymorphisms with VEGF expression by stimulated PBM cells. Hum Immunol 2003;64:S125.
15Shahbazi M, Fryer AA, Pravica V, Brogan IJ, Ramsay HM, Hutchinson IV, et al. Vascular endothelial growth factor gene polymorphisms are associated with acute renal allograft rejection. J Am Soc Nephrol 2002;13:260-4.
16Pander J, Gelderblom H, Guchelaar HJ. Pharmacogenetics of EGFR and VEGF inhibition. Drug Discov Today 2007;12:1054-60.
17Yang B, Cross DF, Ollerenshaw M, Millward BA, Demaine AG. Polymorphisms of the vascular endothelial growth factor and susceptibility to diabetic microvascular complications in patients with type 1 diabetes mellitus. J Diabetes Complications 2003;17:1-6.
18Schneider BP, Wang M, Radovich M, Sledge GW, Badve S, Thor A, et al. Association of vascular endothelial growth factor and vascular endothelial growth factor receptor-2 genetic polymorphisms with outcome in a trial of paclitaxel compared with paclitaxel plus bevacizumab in advanced breast cancer: ECOG 2100. J Clin Oncol 2008;26:4672-8.
19Lu H, Shu XO, Cui Y, Kataoka N, Wen W, Cai Q, et al. Association of genetic polymorphisms in the VEGF gene with breast cancer survival. Cancer Res 2005;65:5015-9.
20Kataoka N, Cai Q, Wen W, Shu XO, Jin F, Gao YT, et al. Population-based case-control study of VEGF gene polymorphisms and breast cancer risk among Chinese women. Cancer Epidemiol Biomarkers Prev 2006;15:1148-52.
21Beeghly-Fadiel A, Shu XO, Lu W, Long J, Cai Q, Xiang YB, et al. Genetic variation in VEGF family genes and breast cancer risk: A report from the Shanghai breast cancer genetics study. Cancer Epidemiol Biomarkers Prev 2011;20:33-41.
22Buraczynska M, Ksiazek P, Baranowicz-Gaszczyk I, Jozwiak L. Association of the VEGF gene polymorphism with diabetic retinopathy in type 2 diabetes patients. Nephrol Dial Transplant 2007;22:827-32.
23Han SW, Kim GW, Seo JS, Kim SJ, Sa KH, Park JY, et al. VEGF gene polymorphisms and susceptibility to rheumatoid arthritis. Rheumatology (Oxford) 2004;43:1173-7.
24Memariani T, Saliminejad K, Kamali K, et al. Association of vascular endothelial growth factor (VEGF) +405G > C polymorphism with endometriosis in Iranian population. J Reprod Infertil 2010;11:33-7.
25Jin Q, Hemminki K, Enquist K, Lenner P, Grzybowska E, Klaes R, et al. Vascular endothelial growth factor polymorphisms in relation to breast cancer development and prognosis. Clin Cancer Res 2005;11:3647-53.
26McCarron SL, Edwards S, Evans PR, Gibbs R, Dearnaley DP, Dowe A, et al. Influence of cytokine gene polymorphisms on the development of prostate cancer. Cancer Res 2002;62:3369-72.
27Sfar S, Hassen E, Saad H, Mosbah F, Chouchane L. Association of VEGF genetic polymorphisms with prostate carcinoma risk and clinical outcome. Cytokine 2006;35:21-8.
28Dvorak HF, Brown LF, Detmar M, Dvorak AM. Vascular permeability factor/vascular endothelial growth factor, microvascular hyperpermeability, and angiogenesis. Am J Pathol 1995;146:1029-39.
29Toi M, Inada K, Suzuki H, Tominaga T. Tumor angiogenesis in breast cancer: Its importance as a prognostic indicator and the association with vascular endothelial growth factor expression. Breast Cancer Res Treat 1995;36:193-204.
30Relf M, LeJeune S, Scott PA, Fox S, Smith K, Leek R, et al. Expression of the angiogenic factors vascular endothelial cell growth factor, acidic and basic fibroblast growth factor, tumor growth factor beta-1, platelet-derived endothelial cell growth factor, placenta growth factor, and pleiotrophin in human primary breast cancer and its relation to angiogenesis. Cancer Res 1997;57:963-9.
31Wacholder S, McLaughlin JK, Silverman DT, Mandel JS. Selection of controls in case-control studies. I. Principles. Am J Epidemiol 1992;135:1019-28.