Introduction

Breast cancer is one of the most frequent malignant tumors worldwide and the second leading cause of cancer death in women (1). Research showed that significant percentage of breast cancer patients experienced a delayed treatment because of their misconceptions about breast cancer (2). As cases of breast cancer are increasing year by year, a better understanding of the causes leading to breast cancer is necessary. Although, there are many possible factors contributing to the cause, development, and prognosis of breast cancer (3), genetic factors have an extremely important influence on the risk of breast cancer (4). In addition, many studies have shown that the SNPs in some genes can affect the susceptibility to breast cancer (5, 6). As is well known, the endothelium plays an important role in maintaining vascular homeostasis. The endothelial cells proliferate, migrate and interact with other cells such as stromal cells to form new capillaries during the cancer angiogenesis. The new blood vessels are extremely important for the growth of cancer cells. Therefore, to a certain extent, the inhibition of endothelial cell proliferation can suppress the angiopoiesis of cancer cells. However, some studies have indicated that VEGI, also known as TNFSF15 or TNF ligand-related molecule, can inhibit the proliferation of endothelial cells and exert an anti-angiogenic effect on the endothelial cells (7). VEGI-192, an isoform of VEGI, has been reported to be able to eliminate the endothelial cells in tumors and suppress the development of tumors (8). VEGI always acts as a co-stimulator to induce T cell proliferation and cytokine secretion (9, 10).

Many studies have shown that VEGI is related to various diseases including bowel disease (11), lung cancer (12), prostate cancer (13), and breast cancer (14). Except for its ability to inhibit the endothelial cells, VEGI could influence the development of diseases through participating in various pathways. Research results indicated that VEGI plays an essential role in activating the transcription factor κB and caspase-3, leading to PARP cleavage (15). Moreover, VEGI was also involved in immune response by inducing the secretion of GM-CSF and IFN-γ (10). In cancers or wounds, VEGI gene expression also decreased at the inflammation and angiogenesis sites (16). Other studies have demonstrated that VEGI is mediated by DR3 to inhibit the growth and migration of tumor cells (17). Studies that involved cell cycle suggested that VEGI maintained early G1 arrest in the G0/G1 cells and induced the programmed death in the endothelial cell cycle (7).

VEGI is a member of the TNF superfamily firstly discovered in 1999. It is mainly produced by vessel endothelial cells and also expressed on antigen-presenting cells and lymphocytes such as T cells and dendritic cells. VEGI maps to human chromosome 9q32 and contains 4 exons and 3 introns. VEGI gene polymorphisms have exhibited a connection with certain inflammatory and autoimmune diseases, such as Crohn's Disease (18), inflammatory bowel disease (19), and psoriatic arthritis (20). However, the association between VEGI gene polymorphisms and breast cancer in Chinese people has never been studied. The purpose of this paper is to discuss the association of VEGI gene polymorphism with breast cancer in northeast China. We selected four SNPs located at the VEGI gene (rs4263839, rs6478106, rs4979462, rs7848647) that had been reported before and examined whether these SNPs are associated with the development of breast cancer in Chinese Han women.

Materials and methods

Blood sample preparation

In total, 708 patients and 685 healthy volunteers were involved in our research. The cases and controls are all females and age matched (cases, 50.02±9.80 years old; controls, 49.32±9.56 years old). We used Chi-squared test and independent-samples T test to detect the difference between the ages of cases and controls and P>0.05. Blood samples of breast cancer patients were obtained from the Third Affiliated Hospital of Harbin Medical University. Diagnostic indicators including tumor size, human epidermal growth factor receptor 2 (Her-2), p53, estrogen receptor (ER), progestrogen receptor (PR), and lymph node (LN) metastasis were all collected from the patients' medical records. The ER and PR positivity was defined by a 10% positively staining of nuclei. The p53 positive status was defined as p53>25% in the cell staining. The IHC scores of 3+ or 2+ were considered positive for Her-2 (0, negative; 1+, <25%; 2+, 25-50%; 3+, >50%). Blood samples of healthy controls were collected from neighborhood volunteers without a history of cancer or autoimmune diseases. The clinical features of patients with breast cancer were shown in Table 1.

Table 1 Clinical features of breast cancer patients
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Ethics statement

This study was conducted at the department of immunology in Harbin Medical University. The patients and healthy volunteers were not genetically related. Before recruitment, a written informed consent was signed by each participant and the study was approved by the institutional ethical review board. The ethics approval was obtained from Harbin Medical University.

DNA extraction from blood samples

Three-milliliter blood samples were taken from the Third Affiliated Hospital to the laboratory, the blood samples were mixed with anticoagulant and stored at -20 ℃. The lymphocytes were obtained through centrifugation. We used the Universal Genomic DNA Extraction Kit Ver. 3.0 (TaKaRa, Japan) to extract DNA according to the manufacturer's protocol.

Genotyping

Genotyping was conducted using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay. The primers were designed by using Gene Runner software, and the primer sequences of each SNP were: rs6478106 (F: 5′-ACTTCATCCACTTCTCCTC-3′, R: 5′-AGACGTTCTGACTACTATTCC-3′), rs4264839 (F: 5′-GGACCCTGATTGCTACATG-3′, R: 5′-GTTACAGACCAGGGAGGATC-3′), rs4979462 (F: 5′-AAGGGCTCTCAGACATCATC-3′, R: 5′-TCAAAGCATAGACACCACAAG-3′), rs7848647 (F: 5′-ACAGAGGAGCTAGGAAGATG-3′, R: 5′-TCCTGGCTCTACCACTTG-3′). All the primers were produced by Invitrogen Company. The PCR reaction mixture contained 0.4 µg DNA, 2.5 mM dNTP mix (TaKaRa, Japan), 2.5 µL 10× PCR reaction buffer including 10 mM Tris-HCl, 50 nM KCl and 2.5 nM MgCL₂ (TaKaRa, Japan), 4 µM primers (Invitrogen, China), 2.5 U Taq DNA polymerase (TaKaRa, Japan), and added sterile double distilled water to a final volume of 25 µL. The PCR program consisted of an initial melting step at 94 ℃ for 15 minutes, 35 cycles of 30 seconds at 94 ℃, 30 seconds at annealing temperatures, 1 minute at 72 ℃, and a terminal step at 72 ℃ for 5 minutes. The annealing temperatures for each SNP were rs6478106 (56.0 ℃), rs4263839 (57.0 ℃), rs4979462 (56.5 ℃), and rs7848647 (57.2 ℃). The PCR products contained the SNP sites and were examined in 2% agarose gel electrophoresis. The RFLP was conducted in a final volume of 10 µL, including 5 µL PCR products, 1× NEB buffer (50 Mm, Tris-HCl, 100 mM NaCl, 10 mM MgCl₂, 1 mM dithiothreitol), and 0.25 µL restriction enzyme (NEB, UK). The reaction mix was incubated in water bath according to the optimal temperature for each restriction enzyme for 4-6 hours, and the digested fragments were separated by 2% (rs4263839, rs4979462, rs7848647) or 3% (rs6478106) agarose gel electrophoresis as the difference in length among the restricted fragments was smaller than other three SNPs. The restriction enzymes for each SNP were as follows: rs6478106 (Eco53KI), rs4263839 (ApoI), rs4979462 (MscI), and rs7848647 (CviQI). The digested fragments were 105 bp and 151 bp with T allele and 256 bp with C allele in rs6478106, 132 bp and 213 bp with A allele and 345 bp with G allele in rs4263839, 101 bp and 306 bp with C allele and 407 bp with T allele in rs4979462, 120 bp and 296 bp with C allele, and 416 bp with T allele in rs7848647. The results of PCR-RFLP products for each SNP is shown in the Figures S1-S8. Direct sequencing of random samples was conducted to verify the accuracy of the genotyping results. About 10% of our samples were tested by direct sequencing and the results were in accord with our PCR-RFLP analysis results.

Figure S1 Agarose gel electrophoresis of rs6478106 after PCR reaction. PCR, polymerase chain reaction.

Figure S2 Agarose gel electrophoresis of rs6478106 digested by Eco53KI. Lane 1 is DNA marker; lanes 4, 21 are TT homozygote; lanes 6, 8, 11,12, 15, 19, 22-24 are CC homozygote; lanes 2, 3, 5, 7, 9, 10, 13, 14, 16-18, 20, 25 are CT heterozygote.

Figure S3 Agarose gel electrophoresis of rs4263839 after PCR reaction. PCR, polymerase chain reaction.

Figure S4 Agarose gel electrophoresis of rs4263839 digested by ApoI. Lane 1 is DNA marker; lanes 2, 10, 14, 17, 18, 20, 24, 25 are GG homozygote; lanes 5, 13, 15, 16, 22 are AA homozygote; lanes 3, 4, 6-9, 11, 12, 19, 21, 23 are GA heterozygote.

Figure S5 Agarose gel electrophoresis of rs4979462 after PCR reaction. PCR, polymerase chain reaction.

Figure S6 Agarose gel electrophoresis of rs4979462 digested by MscI. Lane 1 is DNA marker; lanes 7, 18 are TT homozygote; lanes 6, 9, 10, 12, 13, 16, 17, 21, 22, 25 are CC homozygote; lanes 2-5, 8, 11, 14, 15, 19, 20, 23, 24 are CT heterozygote.

Figure S7 Agarose gel electrophoresis of rs7848647 after PCR reaction. PCR, polymerase chain reaction.

Figure S8 Agarose gel electrophoresis of rs7848647 digested by CviQI. Lane 1 is DNA marker; lanes 2, 4-7, 12, 19, 20, 23, 25, 33 are TT homozygote; lanes 9, 10, 13, 14, 17, 18, 24 are CC homozygote; lanes 3, 8, 11, 15, 16, 21, 22, 26-32, 34 are TC heterozygote.

Statistical analysis

We tested the genotype frequencies of these SNPs for Hardy Weinberg equilibrium (HWE) among healthy controls. The genotype frequencies in the breast cancer cases and healthy controls were analyzed in different genetic models (codominant model, dominant model, and recessive model) using the chi-squared test or Fisher′s test. In the codominant model, the major allele homozygotes were used as the reference group, and the heterozygotes and minor allele homozygotes were compared to the reference group, respectively. The dominant model was the combination of minor homozygotes and heterozygotes compared to the major allele homozygotes. In the recessive model, the minor homozygotes were compared to the combination of heterozygotes and major allele homozygotes. The P value, estimated odds ratios (ORs) and 95% confidence intervals (95% CIs) were all calculated using the statistical software SPSS version 18.0 and Haploview 4.1 (http://www.broad.mit.edu/mpg/haploview/) was used to tag all the common haplotypes and their frequencies in the breast cancer cases and healthy controls. Haplotypes were constructed based on D′ values using our own data. The linkage disequilibrium (LD) was constructed by D' and r². The statistical significance was set at P<0.05, and 10, 000 permutations were run to evaluate the P values using Haploview 4.1 to verify the correctness of the significance.

Results

VEGI gene polymorphisms with the risk of breast cancer

We have chosen four SNPs at VEGI gene to test the association between VEGI gene polymorphisms and breast cancer risk. The genotype frequencies of these four SNPs are shown in Table 2. The distributions of genotypes of these four SNPs we selected were in Hardy Weinberg equilibrium in healthy control group. Based on the data, in rs6478106, compared to the CC genotype, the CT genotype was related to an increased risk in breast cancer (P=0.001, OR=1.438, 95% CI, 1.153-1.793). There was also a significant difference in genotype distribution in rs6478106 under dominant model (P=0.001, OR=1.437, 95% CI, 1.161-1.777). Furthermore, compared with the C allele, the T allele of rs6478106 also increased the risk of breast cancer (Table 3). This result indicated that rs6478106 may have a strong association with breast cancer risk.

Table 2 The genotype frequencies of VEGI gene polymorphisms in cases and controls
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Table 3 The allele frequencies of VEGI gene polymorphisms in cases and controls
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Haplotypes of the SNPs in the VEGI gene in cases and controls

The association between the haplotype and breast cancer risk was analyzed using Haploview 4.1 version software. Two blocks were constructed based on the solid spin of LD method. Block 1 contained rs6478106 and rs4263839, and there were four haplotypes in this block (C_rs6478106A_rs4263839, T_rs6478106G_rs4263839, C_rs6478106G_rs4263839 and T_rs6478106A_rs4263839). We found that the C_rs6478106G_rs4263839 haplotype got a higher frequency in breast cancer patients (P=0.0136). The T_rs6478106G_rs4263839 haplotype and T_rs6478106A_rs4263839 haplotype had lower frequencies in cases (P=0.0244; P=0.0184). However, after correcting the P value for multiple testing, significant differences were only found for the C_rs6478106G_rs4263839 haplotype (P=0.0488). Both rs4979462 and rs7848647 belonged to block2 and constructed four haplotypes (C_rs4979462T_rs7848647, T_rs4979462C_rs7848647, C_rs4979462C_rs7848647 and T_rs4979462T_rs7848647), and they were not associated with the risk of breast cancer (Table 4).

Table 4 The haplotype frequencies of VEGI gene in cases and controls
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Clinical features and VEGI gene polymorphisms

The association between VEGI gene polymorphisms and the clinical features of breast cancer including ER, PR, p53, Her-2, LN metastasis and triple negative breast cancer (TNBC) status were also analyzed in our study. We found an association only between VEGI gene polymorphisms and Her-2 status. In comparison with the CC genotype, patients with the TT genotype of rs6478106 may exhibit increased expression of Her-2 (P=0.004, OR=2.522, 95% CI, 1.320-4.818), and this association was also significant in the recessive model (P=0.004, OR=2.397, 95% CI, 1.302-4.411). Moreover, compared to the CC genotype of rs4979462, the TT genotype had higher frequencies in Her-2 positive patients (P=0.002, OR=2.835, 95% CI, 1.455-5.523), and in the recessive model, the distribution of the genotype of rs4979462 was also associated with Her-2 expression (P=0.001, OR=2.835, 95% CI, 1.489-3.397). The T allele of rs6478106 and the T allele of rs4979462 appeared more frequently in Her-2 positive cases (P=0.0356, P=0.0354), but after correcting the P value for multiple testing, no significant difference was found. The positive results are shown in Table 5 and others were in Tables S1-S5.

Table 5 Genotype and allele frequencies of VEGI gene polymorphisms and Her-2 status
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Clinical features and haplotypes of VEGI SNPs

The analysis results of the association between the haplotypes and the clinical features did not show a significant difference (Tables S6-S11).

Table S1 Genotype and allele frequencies of VEGI gene polymorphisms and LN metastasis status
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Table S2 Genotype and allele frequencies of VEGI gene polymorphisms and ER status
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Table S3 Genotype and allele frequencies of VEGI gene polymorphisms and PR status
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Table S4 Genotype and allele frequencies of VEGI gene polymorphisms and p53 status
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Table S5 Genotype and allele frequencies of VEGI gene polymorphisms and TNBC status
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Table S6 The haplotype of the VEGI gene polymorphisms and the ER status
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Table S7 The haplotype of the VEGI gene polymorphisms and the PR status
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Table S8 The haplotype of the VEGI gene polymorphisms and the p53 status
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Table S9 The haplotype of the VEGI gene polymorphisms and the Her-2 status
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Table S10 The haplotype of the VEGI gene polymorphisms and the LN metastasis status
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Table S11 The haplotype of the VEGI gene polymorphisms and the TNBC status
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Discussion

The growth and development of tumors rely on many factors, and the growth of new vessels in tumors is extremely important. The nutrients and oxygen that tumor cells need are transported by blood vessels, and the spread of cancer cells also depends on blood vessels. Therefore, the suppression of vessel formation can act as a potential therapeutic target in cancers. In recent research, VEGI has been identified as an inhibitory protein that inhibits the growth of vascular endothelial cells in cancers (21). VEGI is mediated by DR3 and modulates neovascularization and inflammation (22, 23). VEGF receptor 1 could also be regulated by VEGI to inhibit the angiogenesis (24). Decreased expression of VEGI can promote tumor development (25). Recent studies showed that tumor vasculature could be suppressed by a new NGR-VEGI fusion protein (26). In addition to its ability to inhibit neovascularization, VEGI can play an important role in immune response. VEGI can induce dendritic cell maturation (27), and the interaction between VEGI and DR3 can modulate the adaptive immune response by suppressing the proliferation of human activated B cells (28). In Crohn's disease, VEGI has been shown to down-regulate the activation of T helper-1 cells and T helper-17 cells (29).

The expression of VEGI can affect the vessel formation of breast tumor (30). The mRNA and protein levels of VEGI in breast cancer patients were lower compared to the controls and patients with breast cancer who expressed more VEGI protein had a more favorable prognosis than patients who expressed less VEGI protein (14). Thus, the gene variants of VEGI may play a very important role in the development of breast cancer. Our study indicates that some SNPs in the VEGI gene may affect the development of breast cancer in Chinese Han women.

Our data indicates that rs6478106 is related to the risk of breast cancer in Chinese Han women. The CT genotype and T allele of rs6478106 were related to an increased risk of breast cancer. In the Crohn's disease, rs6478106 was proven to be a really significant locus (31). It is noteworthy that rs6478106 is located in the 3'-flanking region of the VEGI gene, and the 3' flanking region of gene often contains sequences that can influence the formation of 3' end of the message. It may also contain the sites where proteins may bind or enhancers. Thus, the genetic variants in these regions may affect the transcription of the gene. The T allele of rs6478106 can be treated as a potential marker to inform the prognosis of breast cancer patients. In addition, breast cancer patients have a higher frequency of expression of C_rs6478106G_rs4263839 than healthy controls, indicating that the C_rs6478106G_rs4263839 haplotype might also have potential to predict breast cancer development. The intron 1 of gene contains many splicing control elements and regulatory elements that can affect the expression of genes. The SNP in this location may affect its alternative splicing function. The location of rs4979462 is in intron 1 of VEGI gene. In our research, no significant difference was found in the genotype distribution of rs4979462 between healthy controls and breast cancer patients. However, based on the analysis of the association between gene polymorphisms in VEGI and the clinical features of breast cancer patients, we found that rs4979462 and rs6478106 are related to the expression of Her-2. The TT genotype of rs4979462 and rs6478106 was more frequent in the Her-2 (+) patients. According to researches involved Her-2 indicated that Her-2 could regulate cell growth and proliferation through many pathways in different diseases (32). It acts as a key marker in diagnosis and predicts the prognosis of cancers (33). The TT genotype in rs6478106 and rs4979462 may be a potential indicator to predict the prognosis of breast cancer patients.

In summary, we have found an association between VEGI gene polymorphisms and the risk of breast cancer and the clinical pathologic features of breast cancer in Chinese Han women.

Conclusions

Our study indicates that VEGI gene polymorphisms may be associated with the risk of breast cancer in Chinese Han women in northeast China. Our results show an association between VEGI gene polymorphisms and the Her-2 status of breast cancer patients as well. This analysis was the first to involve VEGI gene polymorphisms and breast cancer risk in Chinese Han women. However, further functional studies need to be conducted in our subsequent research.

Acknowledgements

We thank all patients and healthy volunteers for providing blood samples. We are grateful for the collaboration of the participating hospitals and their staff.

Funding: This study was supported by a grant from the National Natural Science Foundation of China (31070780) and the Major Project of Technology Department, Heilongjiang Province (GB05C402).

Footnote

Conflicts of Interest: The authors have no conflicts of interest to declare.

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Cite this article as: Han S, Liu L, Xu F, Chen S, Yuan W, Fu Z, Li D, Li D. A case-control study about the association between vascular endothelial growth inhibitor gene polymorphisms and breast cancer risk in female patients in Northeast China. Chin J Cancer Res 2016;28(4):435-443. doi: 10.21147/j.issn.1000-9604.2016.04.07