Literature DB >> 27647972

A case-control study about the association between vascular endothelial growth inhibitor gene polymorphisms and breast cancer risk in female patients in Northeast China.

Shaoli Han1, Lei Liu2, Fengyan Xu1, Shuang Chen1, Weiguang Yuan3, Zhenkun Fu1, Dalin Li4, Dianjun Li3.   

Abstract

OBJECTIVE: The inhibition of the neovascularization in tumors is a potential therapeutic target of cancer. Vascular endothelial growth inhibitor (VEGI) is a member of the TNF superfamily which has the ability to suppress the formation of new vessels in tumors. In order to study the association between VEGI gene polymorphisms and breast cancer risk, a case-control study was conducted in Chinese Han women in Northeast China.
METHODS: Our study involved 708 female breast cancer patients and 685 healthy volunteers. Four SNPs of VEGI gene were analyzed through the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. The association between VEGI gene polymorphisms and breast cancer risk was analyzed in our study. The relation between VEGI gene variants and clinical features of breast cancer including lymph node (LN) metastasis, estrogen receptor (ER), progestrogen receptor (PR), tumor protein 53 (p53), human epidermal growth factor receptor 2 (Her-2) and triple negative (ER-/PR-/Her-2-) status was analyzed as well.
RESULTS: We found that the CT genotype and T allele of rs6478106 were more frequent in patients than in controls. There was also a statistical difference in the distribution of Crs6478106Grs4263839 haplotype between patients and controls. In addition, SNP rs6478106 and rs4979462 were related with the Her-2 status.
CONCLUSIONS: Our results suggest that VEGI gene variants may be related to the breast cancer risk and the clinical features of breast cancer in Chinese Han women in Northeast China.

Entities:  

Keywords:  Vascular endothelial growth inhibitor (VEGI); breast cancer; single nucleotide polymorphisms (SNPs)

Year:  2016        PMID: 27647972      PMCID: PMC5018539          DOI: 10.21147/j.issn.1000-9604.2016.04.07

Source DB:  PubMed          Journal:  Chin J Cancer Res        ISSN: 1000-9604            Impact factor:   5.087


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 . Clinical features of breast cancer patients

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 -. 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.
S1

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

Agarose gel electrophoresis of rs6478106 after PCR reaction. PCR, polymerase chain reaction. 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. Agarose gel electrophoresis of rs4263839 after PCR reaction. PCR, polymerase chain reaction. 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. Agarose gel electrophoresis of rs4979462 after PCR reaction. PCR, polymerase chain reaction. 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. Agarose gel electrophoresis of rs7848647 after PCR reaction. PCR, polymerase chain reaction. 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 (mpg/haploview/">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 . 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 (). This result indicated that rs6478106 may have a strong association with breast cancer risk. The genotype frequencies of VEGI gene polymorphisms in cases and controls The allele frequencies of VEGI gene polymorphisms in cases and controls

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 (Crs6478106Ars4263839, Trs6478106Grs4263839, Crs6478106Grs4263839 and Trs6478106Ars4263839). We found that the Crs6478106Grs4263839 haplotype got a higher frequency in breast cancer patients (P=0.0136). The Trs6478106Grs4263839 haplotype and Trs6478106Ars4263839 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 Crs6478106Grs4263839 haplotype (P=0.0488). Both rs4979462 and rs7848647 belonged to block2 and constructed four haplotypes (Crs4979462Trs7848647, Trs4979462Crs7848647, Crs4979462Crs7848647 and Trs4979462Trs7848647), and they were not associated with the risk of breast cancer (). The haplotype frequencies of VEGI gene in cases and controls

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 and others were in -.
S1

Genotype and allele frequencies of VEGI gene polymorphisms and LN metastasis status

SNP ID Genotype LN (+) No. (%) LN (-) No. (%) OR (95% CI) P value
VEGI, vascular endothelial growth inhibitor; LN, lymph node.
rs6478106 CC 118 (46.46) 164 (42.60) Reference  
  CT 117 (46.06) 188 (48.83) 0.865 (0.622-1.204) 0.389
  TT 19 (7.48) 33 (8.57) 0.800 (0.434-1.476) 0.475
  Dominant     0.855 (0.622-1.176) 0.336
  Recessive     0.862 (0.479-1.553) 0.622
  Allelic     0.892 (0.701-1.135) 0.353
rs4263839 GG 59 (22.87) 116 (29.74) Reference  
  GA 149 (57.75) 209 (53.59) 1.402 (0.961-2.044) 0.079
  AA 50 (19.38) 65 (16.67) 1.512 (0.932-2.454) 0.093
  Dominant     1.428 (0.994-2.052) 0.054
  Recessive     1.202 (0.799-1.807) 0.376
  Allelic     1.213 (0.970-1.517) 0.090
rs4979462 CC 148 (58.73) 200 (51.55) Reference  
  CT 86 (34.13) 162 (41.75) 0.717 (0.512-1.005) 0.053
  TT 18 (7.14) 26 (6.70) 0.936 (0.495-1.770) 0.838
  Dominant     0.748 (0.543-1.030) 0.075
  Recessive     1.071 (0.574-1.997) 0.829
  Allelic     0.839 (0.648-1.085) 0.181
rs7848647 TT 67 (26.07) 86 (22.40) Reference  
  TC 142 (55.25) 209 (54.43) 0.872 (0.594-1.280) 0.485
  CC 48 (18.68) 89 (23.18) 0.692 (0.431-1.113) 0.128
  Dominant     0.818 (0.567-1.182) 0.285
  Recessive     0.761 (0.514-1.128) 0.173
  Allelic     0.849 (0.679-1.062) 0.151
S5

Genotype and allele frequencies of VEGI gene polymorphisms and TNBC status

SNP ID Genotype TNBC No. (%) Non-TNBC No. (%) OR (95% CI) P value
VEGI, vascular endothelial growth inhibitor; TNBC, triple negative breast cancer.
rs6478106 CC 42 (43.30) 227 (44.86) Reference  
  CT 51 (52.58) 235 (46.44) 1.173 (0.750-1.835) 0.484
  TT 4 (4.12) 44 (8.70) 0.491 (0.168-1.440) 0.265
  Dominant     1.065 (0.687-1.651) 0.777
  Recessive     0.452 (0.158-1.287) 0.153
  Allelic     0.932 (0.668-1.301) 0.680
rs4263839 GG 22 (21.57) 147 (28.65) Reference  
  GA 60 (58.82) 276 (53.80) 1.453 (0.857-2.463) 0.164
  AA 20 (19.61) 90 (17.54) 1.485 (0.768-2.873) 0.238
  Dominant     1.461 (0.878-2.430) 0.143
  Recessive     1.146 (0.669-1.965) 0.619
  Allelic     1.202 (0.890-1.624) 0.230
rs4979462 CC 49 (50.52) 276 (54.33) Reference  
  CT 43 (44.33) 196 (38.58) 1.236 (0.789-1.935) 0.355
  TT 5 (5.15) 36 (7.09) 0.782 (0.293-2.092) 0.624
  Dominant     1.165 (0.755-1.800) 0.490
  Recessive     0.713 (0.272-1.864) 0.488
  Allelic     1.049 (0.743-1.482) 0.785
rs7848647 TT 28 (28.28) 117 (23.12) Reference  
  TC 52 (52.53) 279 (55.14) 0.779 (0.469-1.299) 0.334
  CC 19 (19.19) 110 (21.74) 0.722 (0.381-1.366) 0.315
  Dominant     0.763 (0.470-1.237) 0.271
  Recessive     0.855 (0.497-1.472) 0.571
  Allelic     0.857 (0.631-1.163) 0.321
Genotype and allele frequencies of VEGI gene polymorphisms and Her-2 status

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 (-). Genotype and allele frequencies of VEGI gene polymorphisms and LN metastasis status Genotype and allele frequencies of VEGI gene polymorphisms and ER status Genotype and allele frequencies of VEGI gene polymorphisms and PR status Genotype and allele frequencies of VEGI gene polymorphisms and p53 status Genotype and allele frequencies of VEGI gene polymorphisms and TNBC status The haplotype of the VEGI gene polymorphisms and the ER status The haplotype of the VEGI gene polymorphisms and the PR status The haplotype of the VEGI gene polymorphisms and the p53 status The haplotype of the VEGI gene polymorphisms and the Her-2 status The haplotype of the VEGI gene polymorphisms and the LN metastasis status The haplotype of the VEGI gene polymorphisms and the TNBC status

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 Crs6478106Grs4263839 than healthy controls, indicating that the Crs6478106Grs4263839 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.
1

Clinical features of breast cancer patients

FeaturesCases No. (%)
ER, estrogen receptor; PR, progesterone receptor; Her-2, human epidermal growth factor receptor 2; p53, tumor protein 53; IHC, immunohistochemistry.
Tumor type
Infiltrating ductal carcinoma555 (78.39)
Intraductal carcinoma99 (13.98)
Infiltrating lobular carcinoma19 (2.68)
Mucinous carcinoma12 (1.69)
Others23 (3.25)
Lymph node metastasis
Positive261 (36.86)
Negative391 (55.23)
Unknown56 (7.91)
ER
Positive395 (55.79)
Negative225 (31.78)
Unknown88 (12.43)
PR
Positive405 (57.20)
Negative213 (30.08)
Unknown90 (12.71)
Her-2
Positive137 (19.35)
Negative482 (68.08)
Unknown89 (12.57)
p53
Positive81 (11.44)
Negative529 (74.72)
Unknown98 (13.84)
IHC type
ER or PR (+)/Her-2 (–)380 (53.67)
ER or PR (+)/Her-2 (+)86 (12.15)
ER (–)/PR (–)/Her-2 (–)102 (14.41)
ER (–)/PR (–)/Her (+)50 (7.06)
Unknown90 (12.71)
2

The genotype frequencies of VEGI gene polymorphisms in cases and controls

SNP IDGenotypeCase No. (%)Control No. (%)OR (95% CI)P value
The data was analyzed with the SPSS18.0 software. VEGI, vascular endothelial growth inhibitor.
rs6478106CC306 (44.22)361 (53.24)Reference
CT334 (48.27)274 (40.41)1.438 (1.153-1.793)0.001
TT52 (7.51)43 (6.34)1.427 (0.926-2.197)0.105
Dominant 1.437 (1.161-1.777)0.001
Recessive 1.200 (0.789-1.824)0.393
rs4263839GG194 (27.60)201 (29.65)Reference
GA381 (54.20)344 (50.74)1.148 (0.898-1.467)0.271
AA128 (18.21)133 (19.62)0.997 (0.729-1.363)0.986
Dominant1.106 (0.875-1.396)0.399
Recessive0.912 (0.697-1.194)0.504
rs4979462CC374 (54.05)325 (48.73)Reference
CT272 (39.31)287 (43.03)0.824 (0.659-1.029)0.087
TT46 (6.65)55 (8.25)0.727 (0.478-1.105)0.134
Dominant0.808 (0.653-1.000)0.050
Recessive0.792 (0.527-1.190)0.261
rs7848647TT168 (24.17)149 (22.37)Reference
TC373 (53.67)355 (53.30)0.932 (0.716-1.214)0.601
CC154 (22.16)162 (24.32)0.843 (0.617-1.152)0.283
Dominant0.904 (0.703-1.163)0.432
Recessive0.886 (0.688-1.139)0.344
3

The allele frequencies of VEGI gene polymorphisms in cases and controls

SNP IDAlleleCases No. (%)Controls No. (%)OR (95% CI)P value
P*=0.0086 after correcting the P value for multiple testing by Haploview program using 10,000 permutations. P#>0.05 after multiple testing by Haploview program using 10,000 permutations. VEGI, vascular endothelial growth inhibitor.
rs6478106C946 (68.35)996 (73.45)Reference
T438 (31.65)360 (26.55)1.281 (1.086-1.511)0.003*
rs4263839G769 (54.69)746 (55.01)Reference
A637 (45.31)610 (44.99)1.013 (0.872-1.177)0.866
rs4979462C1,020 (73.70)937 (70.24)Reference
T364 (26.30)397 (29.76)0.842 (0.712-0.996)0.045#
rs7848647T709 (51.01)653 (49.02)Reference
C681 (48.99)679 (50.98)0.924 (0.795-1.074)0.301
4

The haplotype frequencies of VEGI gene in cases and controls

HaplotypeFrequencyCasesControlsP value
P*=0.0448 after correcting the P value for multiple testing by Haploview program using 10,000 permutations. P&, P&&>0.05 after correcting the P value for multiple testing by Haploview program using 10,000 permutations. VEGI, vascular endothelial growth inhibitor.
rs6478106rs4263839
CA0.4370.4400.4330.6877
TG0.2760.2570.2950.0244&
CG0.2720.2930.2510.0136*
TA0.0160.0100.0210.0184&&
rs4979462rs7848647
CT0.4730.4620.4840.2482
TC0.2510.2660.2370.0721
CC0.2480.2420.2540.4802
TT0.0280.0300.0260.5384
5

Genotype and allele frequencies of VEGI gene polymorphisms and Her-2 status

SNP IDGenotypeHer-2 (+) No. (%)Her-2 (–) No. (%)OR (95% CI)P value
P^>0.05, P^^>0.05 after multiple testing by Haploview program using 10,000 permutations. VEGI, vascular endothelial growth inhibitor. Her-2, human epidermal growth factor receptor 2.
rs6478106CC54 (40.00)215 (45.84)Reference
CT62 (45.93)224 (47.76)1.102 (0.731-1.661)0.642
TT19 (14.07)30 (6.40)2.522 (1.320-4.818)0.004
Dominant1.270 (0.860-1.874)0.229
Recessive2.397 (1.302-4.411)0.004
Allelic1.355 (1.020-1.799)0.036^
rs4979462CC68 (50.00)257 (54.68)Reference
CT50 (36.76)189 (40.21)1.000 (0.663-1.507)0.999
TT18 (13.24)24 (5.11)2.835 (1.455-5.523)0.002
Dominant1.207 (0.823-1.768)0.335
Recessive2.835 (1.489-5.397)0.001
Allelic1.371 (1.021-1.842)0.035^^
S2

Genotype and allele frequencies of VEGI gene polymorphisms and ER status

SNP ID Genotype ER (+) No. (%) ER (-) No. (%) OR (95% CI) P value
VEGI, vascular endothelial growth inhibitor; ER, estrogen receptor.
rs6478106 CC 175 (45.45) 95 (43.18) Reference  
  CT 177 (45.97) 109 (49.55) 0.882 (0.624-1.245) 0.474
  TT 33 (8.57) 16 (7.27) 1.120 (0.586-2.139) 0.732
  Dominant     0.912 (0.653-1.273) 0.589
  Recessive     1.670 (0.894-3.119) 0.105
  Allelic     0.978 (0.760-1.257) 0.861
rs4263839 GG 113 (28.83) 57 (25.33) Reference  
  GA 203 (51.79) 134 (59.56) 0.764 (0.519-1.124) 0.172
  AA 76 (19.39) 34 (15.11) 1.128 (0.674-1.887) 0.648
  Dominant     0.841 (0.580-1.219) 0.360
  Recessive     1.351 (0.868-2.103) 0.182
  Allelic     1.016 (0.805-1.282) 0.894
rs4979462 CC 213 (54.48) 113 (52.31) Reference  
  CT 150 (38.36) 89 (41.20) 0.894 (0.632-1.266) 0.528
  TT 28 (7.16) 14 (6.48) 1.061 (0.537-2.096) 0.865
  Dominant     0.917 (0.657-1.279) 0.609
  Recessive     1.113 (0.573-2.162) 0.752
  Allelic     0.963 (0.739-1.255) 0.780
rs7848647 TT 95 (24.55) 50 (22.73) Reference  
  TC 210 (54.26) 122 (55.45) 0.906 (0.602-1.363) 0.636
  CC 82 (21.19) 48 (21.82) 0.899 (0.549-1.474) 0.673
  Dominant     0.904 (0.611-1.337) 0.613
  Recessive     0.980 (0.656-1.465) 0.922
  Allelic     0.952 (0.753-1.203) 0.681
S3

Genotype and allele frequencies of VEGI gene polymorphisms and PR status

SNP ID Genotype PR (+) No. (%) PR (-) No. (%) OR (95% CI) P value
VEGI, vascular endothelial growth inhibitor; PR, progestrogen receptor.
rs6478106 CC 176 (44.22) 93 (45.37) Reference  
  CT 187 (46.98) 99 (48.29) 0.998 (0.703-1.416) 0.992
  TT 35 (8.79) 13 (6.34) 1.423 (0.718-2.820) 0.311
  Dominant     1.047 (0.746-1.470) 0.789
  Recessive     1.424 (0.736-2.756) 0.292
  Allelic     1.087 (0.840-1.406) 0.525
rs4263839 GG 116 (28.86) 53 (24.88) Reference  
  GA 214 (53.23) 122 (57.28) 0.801 (0.541-1.188) 0.270
  AA 72 (17.91) 38 (17.84) 0.866 (0.520-1.442) 0.579
  Dominant     0.817 (0.560-1.192) 0.294
  Recessive     1.005 (0.651-1.550) 0.983
  Allelic     0.924 (0.730-1.170) 0.513
rs4979462 CC 214 (53.77) 111 (53.62) Reference  
  CT 157 (39.45) 82 (39.61) 0.993 (0.698-1.412) 0.969
  TT 27 (6.78) 14 (6.76) 1.000 (0.504-1.984) 0.999
  Dominant     0.994 (0.710-1.392) 0.973
  Recessive     1.003 (0.514-1.958) 0.992
  Allelic     0.997 (0.762-1.304) 0.981
rs7848647 TT 94 (23.62) 51 (24.64) Reference  
  TC 218 (54.77) 113 (54.59) 1.047 (0.695-1.577) 0.827
  CC 86 (21.61) 43 (20.77) 1.085 (0.658-1.789) 0.749
  Dominant     1.057 (0.715-1.564) 0.780
  Recessive     1.051 (0.696-1.587) 0.812
  Allelic     1.038 (0.818-1.316) 0.759
S4

Genotype and allele frequencies of VEGI gene polymorphisms and p53 status

SNP ID Genotype p53 (+) No. (%) p53 (-) No. (%) OR (95% CI) P value
VEGI, vascular endothelial growth inhibitor.
rs6478106 CC 36 (45.00) 229 (44.47) Reference  
  CT 37 (46.25) 245 (47.57) 0.961 (0.587-1.573) 0.873
  TT 7 (8.75) 41 (7.96) 1.086 (0.453-2.606) 0.853
  Dominant     0.979 (0.609-1.571) 0.929
  Recessive     1.109 (0.479-2.564) 0.810
  Allelic     1.006 (0.707-1.438) 0.974
rs4263839 GG 23 (28.40) 144 (27.38) Reference  
  GA 46 (56.79) 286 (54.37) 1.007 (0.587-1.726) 0.980
  AA 12 (14.81) 96 (18.25) 0.783 (0.372-1.647) 0.518
  Dominant     0.951 (0.565-1.598) 0.848
  Recessive     0.779 (0.406-1.495) 0.452
  Allelic     0.914 (0.654-1.276) 0.596
rs4979462 CC 38 (48.72) 282 (54.34) Reference  
  CT 33 (42.31) 203 (39.11) 1.206 (0.732-1.989) 0.462
  TT 7 (8.97) 34 (6.55) 1.528 (0.633-3.688) 0.343
  Dominant     1.252 (0.778-2.017) 0.354
  Recessive     1.406 (0.601-3.293) 0.430
  Allelic     1.267 (0.874-1.836) 0.210
rs7848647 TT 14 (17.72) 128 (24.71) Reference  
  TC 47 (59.49) 280 (54.05) 1.535 (0.815-2.888) 0.128
  CC 18 (22.78) 110 (21.24) 1.496 (0.711-3.147) 0.286
  Dominant     1.524 (0.827-2.807) 0.174
  Recessive     1.094 (0.621-1.928) 0.755
  Allelic     1.186 (0.848-1.659) 0.317
S6

The haplotype of the VEGI gene polymorphisms and the ER status

HaplotypeFrequencyER(+)ER(-)Pvalue
VEGI, vascular endothelial growth inhibitor; ER, estrogen receptor.
rs6478106rs4263839    
CA0.4300.4220.4340.6727
TG0.2950.2940.2960.9442
CG0.2530.2570.2510.8022
TA0.0220.0270.0190.3695
rs4979462rs7848647    
CT0.4900.4860.4920.8293
CC0.2440.2430.2450.9511
TC0.2440.2520.2390.5963
TT0.0220.0180.0240.5239
S7

The haplotype of the VEGI gene polymorphisms and the PR status

HaplotypeFrequencyPR(+)PR(-)Pvalue
VEGI, vascular endothelial growth inhibitor; PR, progestrogen receptor.
rs6478106rs4263839    
CA0.4300.4460.4220.4264
TG0.2940.2850.2990.6133
CG0.2530.2500.25550.846
TA0.0220.0190.0240.5924
rs4979462rs7848647    
CT0.4910.5030.4840.5273
CC0.2440.2320.2510.4716
TC0.2430.2480.2400.7465
TT0.0220.0160.0250.3227
S8

The haplotype of the VEGI gene polymorphisms and the p53 status

HaplotypeFrequencyp53(+)p53(-)Pvalue
VEGI, vascular endothelial growth inhibitor.
rs6478106rs4263839    
CA0.4310.4330.4140.6481
TG0.2960.2960.3000.9007
CG0.2520.2500.2680.6244
TA0.0210.0220.0180.7629
rs4979462rs7848647    
CT0.4900.4960.4520.2954
TC0.2450.2400.2770.309
CC0.2440.2430.2510.8237
TT0.0210.0210.0200.9448
S9

The haplotype of the VEGI gene polymorphisms and the Her-2 status

HaplotypeFrequencyHer-2(+)Her-2(-)Pvalue
*, P=0.0986 (P>0.05) after multiple testing by Haploview program using 10,000 permutations. VEGI, vascular endothelial growth inhibitor; Her-2, human epidermal growth factor receptor 2.
rs6478106rs4263839    
CA0.4300.4420.3860.1026
TG0.2960.2820.3430.0532
CG0.2530.2560.2430.6577
TA0.0220.0200.0290.4201
rs4979462rs7848647    
CT0.4900.5020.4490.1212
TC0.2440.2300.2950.0258*
CC0.2440.2460.2370.7719
TT0.0230.0230.0190.6911
S10

The haplotype of the VEGI gene polymorphisms and the LN metastasis status

HaplotypeFrequencyLN(+)LN(-)Pvalue
VEGI, vascular endothelial growth inhibitor; LN, lymph node.
rs6478106rs4263839    
CA0.4310.4130.4590.0998
TG0.2960.3080.2790.2654
CG0.2490.2570.2370.4136
TA0.0230.0220.0250.7551
rs4979462rs7848647    
CT0.4870.4680.5160.0865
CC0.2500.2570.2410.5062
TC0.2380.2480.2220.2755
TT0.0240.0270.0210.4978
S11

The haplotype of the VEGI gene polymorphisms and the TNBC status

HaplotypeFrequencyTNBC(+)TNBC(-)Pvalue
VEGI, vascular endothelial growth inhibitor; TNBC, triple negative breast cancer.
rs6478106rs4263839    
CA0.4300.4230.4630.2805
TG0.2950.2980.2800.5893
CG0.2530.2580.2300.3961
TA0.0220.0210.0270.5821
rs4979462rs7848647    
CT0.4900.4830.5260.2508
CC0.2440.2530.2040.1353
TC0.2440.2430.2480.866
TT0.0220.0220.0220.9737
  33 in total

1.  Modulation of endothelial cell growth arrest and apoptosis by vascular endothelial growth inhibitor.

Authors:  J Yu; S Tian; L Metheny-Barlow; L J Chew; A J Hayes; H Pan; G L Yu; L Y Li
Journal:  Circ Res       Date:  2001-12-07       Impact factor: 17.367

2.  Vascular endothelial growth inhibitor (VEGI) is an independent indicator for invasion in human pituitary adenomas.

Authors:  Wang Jia; Andrew J Sander; Guijun Jia; Ming Ni; Xiao Liu; Runchun Lu; Wen G Jiang
Journal:  Anticancer Res       Date:  2013-09       Impact factor: 2.480

3.  A genome-wide association study identifies 2 susceptibility Loci for Crohn's disease in a Japanese population.

Authors:  Keiko Yamazaki; Junji Umeno; Atsushi Takahashi; Atsushi Hirano; Todd Andrew Johnson; Natsuhiko Kumasaka; Takashi Morizono; Naoya Hosono; Takaaki Kawaguchi; Masakazu Takazoe; Tetsuhiro Yamada; Yasuo Suzuki; Hiroki Tanaka; Satoshi Motoya; Masayo Hosokawa; Yoshiaki Arimura; Yasuhisa Shinomura; Toshiyuki Matsui; Takayuki Matsumoto; Mitsuo Iida; Tatsuhiko Tsunoda; Yusuke Nakamura; Naoyuki Kamatani; Michiaki Kubo
Journal:  Gastroenterology       Date:  2012-12-22       Impact factor: 22.682

Review 4.  Epidemiology of breast cancer.

Authors:  Kristen A Ban; Constantine V Godellas
Journal:  Surg Oncol Clin N Am       Date:  2014-07       Impact factor: 3.495

5.  TL1A is a TNF-like ligand for DR3 and TR6/DcR3 and functions as a T cell costimulator.

Authors:  Thi Sau Migone; Jun Zhang; Xia Luo; Li Zhuang; Cecil Chen; Bugen Hu; June S Hong; James W Perry; Su Fang Chen; Joe X H Zhou; Yun Hee Cho; Stephen Ullrich; Palanisamy Kanakaraj; Jeffrey Carrell; Ernest Boyd; Henrik S Olsen; Gang Hu; Laurie Pukac; Ding Liu; Jian Ni; Sunghee Kim; Reiner Gentz; Ping Feng; Paul A Moore; Steve M Ruben; Ping Wei
Journal:  Immunity       Date:  2002-03       Impact factor: 31.745

6.  The T cell costimulator TL1A is induced by FcgammaR signaling in human monocytes and dendritic cells.

Authors:  John L Prehn; Lisa S Thomas; Carol J Landers; Qi T Yu; Kathrin S Michelsen; Stephan R Targan
Journal:  J Immunol       Date:  2007-04-01       Impact factor: 5.422

Review 7.  Breast cancer intratumor genetic heterogeneity: causes and implications.

Authors:  Charlotte K Y Ng; Helen N Pemberton; Jorge S Reis-Filho
Journal:  Expert Rev Anticancer Ther       Date:  2012-08       Impact factor: 4.512

8.  Expression, localization, and functional activity of TL1A, a novel Th1-polarizing cytokine in inflammatory bowel disease.

Authors:  Giorgos Bamias; Charles Martin; Marco Marini; Sharon Hoang; Margarita Mishina; William G Ross; Muhammadreza A Sachedina; Charles M Friel; James Mize; Stephen J Bickston; Theresa T Pizarro; Ping Wei; Fabio Cominelli
Journal:  J Immunol       Date:  2003-11-01       Impact factor: 5.422

Review 9.  Genetic and epigenetic aspects of breast cancer progression and therapy.

Authors:  Shannon Byler; Sarah Goldgar; Sarah Heerboth; Meghan Leary; Genevieve Housman; Kimberly Moulton; Sibaji Sarkar
Journal:  Anticancer Res       Date:  2014-03       Impact factor: 2.480

10.  Interferon-γ produced by tumor-infiltrating NK cells and CD4+ T cells downregulates TNFSF15 expression in vascular endothelial cells.

Authors:  Yi Lu; Xin Gu; Li Chen; Zhi Yao; Juan Song; Xiulong Niu; Rong Xiang; Tao Cheng; Zhihai Qin; Weimin Deng; Lu-Yuan Li
Journal:  Angiogenesis       Date:  2013-10-20       Impact factor: 9.596

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  2 in total

1.  TNFSF15 promoter polymorphisms increase the susceptibility to small cell lung cancer: a case-control study.

Authors:  Hui Gao; Zeren Niu; Zhi Zhang; Hongjiao Wu; Yuning Xie; Zhenbang Yang; Ang Li; Zhenxian Jia; Xuemei Zhang
Journal:  BMC Med Genet       Date:  2019-02-08       Impact factor: 2.103

2.  The haplotypes of various TNF related genes associated with scleritis in Chinese Han.

Authors:  Yingnan Gao; Liping Du; Fuzhen Li; Jiadong Ding; Geng Li; Qingfeng Cao; Na Li; Guannan Su; Aize Kijlstra; Peizeng Yang
Journal:  Hum Genomics       Date:  2020-12-07       Impact factor: 4.639

  2 in total

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