- Email: [email protected]
Genetic markers of immunoglobulin G and susceptibility to breast cancer
Human Immunology 73 (2012) 1155–1158
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Genetic markers of immunoglobulin G and susceptibility to breast cancer Janardan P. Pandey a,⇑, Emily Kistner-Griffin b, Motoki Iwasaki c, Shizhong Bu a, Ray Deepe a, Laurel Black a, Yoshio Kasuga d, Gerson S. Hamada e, Shoichiro Tsugane c a
Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, SC, United States Department of Medicine, Medical University of South Carolina, Charleston, SC, United States c Epidemiology and Prevention Division, Research Center for Cancer Prevention and Screening, National Cancer Center, Tokyo, Japan d Department of Surgery, Nagano Matsushiro General Hospital, Nagano, Japan e Nikkei Disease Prevention Center, São Paulo, Brazil b
a r t i c l e
i n f o
Article history: Received 6 June 2012 Accepted 30 July 2012 Available online 9 August 2012
a b s t r a c t Immunoglobulin GM allotypes, antigenic determinants of c chains, are encoded by three very closely linked codominant genes on chromosome 14q32. Particular GM alleles/haplotypes are associated with antibody responses to certain tumor antigens and contribute to the cytotoxicity of breast cancer cells, but their possible role in susceptibility to this malignancy has not been adequately examined. Using a matched case-control design, we genotyped a large (1710 subjects) study population from Japan and Brazil for several GM alleles to determine whether these determinants are associated with susceptibility to breast cancer. After adjusting for the potential confounders, the GM 3 allele of IgG1 was significantly associated with susceptibility to breast cancer in white subjects from Brazil (OR = 2.07, CI 1.16–3.71; p = 0.0147). These data show that Caucasians with the GM 3 allele are over twice as likely to develop breast cancer as those who lack this allele. Since this allele modulates an immune evasion strategy of cytomegalovirus, the results also shed light on the possible mechanism underlying the reported involvement of this virus in the etiology of breast cancer. Ó 2012 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.
1. Introduction
2. Materials and methods
Polymorphic hereditary antigenic determinants expressed on immunoglobulin c chains are called GM allotypes. Encoded by three very closely linked and highly homologous codominant genes on chromosome 14q32, they are expressed on the constant region of c1, c2, and c3 chains [1]. Linkage disequilibrium in the GM system within a racial group is almost absolute and major races are characterized by a unique array of GM haplotypes [2]. GM allotypes are associated with many cancers [3–7], but their role in susceptibility to breast cancer has not been adequately examined. Using a matched case-control study design and a large study population from Japan and Brazil, we aimed to determine whether or not GM alleles are risk factors for the development of breast cancer. Since the majority of the GM alleles are expressed in the Fc region of c chains, we also wished to investigate whether particular Fc (GM), FccRIIa, and FccRIIIa alleles epistatically contribute to the risk of breast cancer.
2.1. Study subjects
⇑ Corresponding author. Address: Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, SC 29425-2230, United States. Fax: +1 843 792 4882. E-mail address: [email protected] (J.P. Pandey).
The experimental design, recruitment criteria, and the demographics of the study population have been described in detail elsewhere [8]. Briefly, breast cancer patients were recruited between 2001 and 2005 at four hospitals in Nagano, Japan, and between 2001 and 2006 at eight hospitals in São Paulo, Brazil. Cancer-free controls were matched to case patients by ethnicity, residential area during the study period, and age (within 3–5 years). Detailed data were collected on family history of cancer, menstrual and reproductive history, anthropometric factors, physical activity, and smoking habits. Estrogen and progesterone hormone receptor status was also determined. The study protocol was approved by the Institutional Review Boards of the respective institutions. Blood from cases and controls was collected after informed consent. The study population consisted of the following: 258 case-control pairs of Caucasian descent (Brazil), 40 case-control pairs of African descent (Brazil), 80 case-control pairs of Japanese descent (Brazil), 80 case-control pairs from the Brazilian mulatto population, 397 case-control pairs from Nagano, Japan.
0198-8859/$36.00 - see front matter Ó 2012 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.humimm.2012.07.340
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J.P. Pandey et al. / Human Immunology 73 (2012) 1155–1158
2.2. GM genotyping DNA for genotyping was isolated from peripheral blood using a standard protocol (Qiagen-Kit method). For the determination of IgG1 markers GM 3 and 17 (arginine to lysine, a G to A substitution in the CH1 region of the c1 gene), we used a pre-designed TaqManÒ genotyping assay from Applied Biosystems Inc. (Foster City, CA). The probe specific to GM 3 allele was labeled with FAM fluorescent at the 50 end and with nonfluorescent quencher at the 30 end. The probe specific to GM 17 allele was labeled with VIC fluorescent at the 50 end and with nonfluorescent quencher at the 30 end. GM 23—valine to methionine, a G to A substitution in the CH2 region of the c2 gene—was determined by a nested PCR-RFLP method. In brief, a 915 bp region of the c2 gene that incorporates the sites for the allelic substitutions was amplified as described by Brusco et al. [9], using the following primers: 50 AAATGTTGTGTCGAGTGCCC 30 and 50 GGCTTGCCGGCCGTGGCAC 30 . A 197 bp segment was further amplified from this 915 bp fragment using the following primers: 50 GCACCACCTGTGGCAGGACC 30 and 50 TTGAACTGCTCCTCCCG TGG 30 . After digestion of the amplified product with the restriction enzyme NlaIII, the following products corresponding to the three genotypes were obtained: GM 23+ GM 23 GM 23+,23
90 bp, 63 bp, 44 bp 134 bp, 63 bp 134 bp, 90 bp, 63 bp, 44 bp
For the determination of IgG3 markers GM 5 and 21, the c3 gene containing the allelic sites was amplified [10] using the following primers: 50 ACCCAAGGATACCCTTATGATT 30 and 50 GAGGCTCTTCTGCGTG AAGC 30 . The amplified product (685 bp) was digested with the restriction enzyme MspA1I. The resulting products corresponding to the three genotypes are as follows: GM 21 GM 5 GM 5,21
327 bp, 295 bp, 63 bp 171 bp, 158 bp, 156 bp, 137 bp, 63 bp 327 bp, 295 bp, 171 bp, 158 bp, 156 bp, 137 bp, 63 bp
In addition to the controls representing the three genotypes for the marker, we also used a blank (no genomic DNA, only primers and the PCR master mix) control and a DNA molecular weight marker. 2.3. FccR genotyping The activating receptors FccRIIa and FccRIIIa are genetically polymorphic: a change in the nucleotide at position 497 of FccRIIa gene from A to G results in change of amino acid histidine to arginine (H/R131); a change in the nucleotide at position 559 of the FccRIIIa gene from T to G results in phenylalanine to valine substitution (F/V158). The single nucleotide polymorphisms (SNP) responsible for the allelic variation were previously determined by the TaqManÒ genotyping assays from Applied Biosystems Inc. [8]. Genotyping was done blinded to the case-control and group status of the subjects. 2.4. Statistical analysis Genotype frequencies were in Hardy–Weinberg equilibrium in all groups except the mulatto population, which could be due to
population admixture. This group was excluded from further analyses. Conditional logistic regression models were constructed within each population group. Potential confounders—family history of breast cancer, history of benign breast disease, menopausal status and age at menopause, number of births, age at first birth, breast feeding, alcohol drinking, smoking status, moderate physical activity in the past 5 years, vitamin supplement use, age at menarche, body mass index—were considered for inclusion as covariates in the models of genetic association, and a backwards regression approach with an a = 0.10 inclusion level was implemented. Tests of genotype models (2df tests with no assumptions about inheritance models) as well as tests of additive effects (1df) were constructed. In all models, statistical significance was defined as p < 0.05. All reported p values are two-sided. 3. Results The results of the tests of associations between GM genotypes and risk of breast cancer in various population groups are presented in Tables 1–4. Allelic variation at the IgG1 GM 3/17 locus contributed to the risk of developing breast cancer in white subjects from Brazil (Table 1). The association was significant for both the genotype model, which assumed no particular mode of inheritance, and the additive model, which assumed that the alleles contribute to the risk additively on the logit scale. Compared to subjects who were homozygous for GM 17, the GM 3 homozygotes were over twice as likely to develop breast cancer (OR = 2.07, CI 1.16–3.71; p = 0.0147). This association would remain significant even after a conservative correction for multiple testing [p = 0.0441 (0.0147 3)]. The GM 5 allele, which is in significant linkage disequilibrium with the GM 3 allele in whites, was also associated with breast cancer at a borderline significance (OR = 2.14, CI 1.04–4.41; p = 0.0526), which would become nonsignificant if adjusted for multiple testing. GM genotypes were not associated with susceptibility to breast cancer in other groups (Tables 2–4). In our previous investigations involving this study population, we did not find a significant association between any FccRIIa and FccRIIIa genotypes and susceptibility to breast cancer [8]. In the present investigation, we tested the possibility that FccR genotypes do contribute to the development of breast cancer, but only in the presence of certain Fcc (GM) alleles. An interaction analysis between GM and FccR genotypes showed that in the Japanese living in Brazil, this appears to be the case (Table 5). GM 23 genotypes interacted epistatically with FccRIIIa (V/F) genotypes and contributed to the risk of breast cancer (p = 0.0390). This apparent association is driven by the contrasting (protective and risk) effects of GM 23 genotypes in the presence of FccRIIIa V allele: The OR associated with the inheritance of one copy of the V allele for individuals carrying the heterozygous GM 23+/GM 23 genotype is 0.13 (protective), while the OR associated with the inheritance of one copy of the V allele for individuals carrying the homozygous GM 23/GM 23 genotype is 1.48 (susceptibility). No other interactive effects were found (data not shown). 4. Discussion The results presented here show a distinct association between the GM 3 allele of IgG1 and susceptibility to breast cancer in a Brazilian white population. This allele acts additively to increase the risk of breast cancer over two fold compared to the alternative GM 17 allele at this locus. There are at least two potential mechanisms through which GM alleles could be associated with susceptibility to breast cancer. The GM 3 allele could itself modulate the risk of breast cancer, possibly through its effect on immunity to self
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J.P. Pandey et al. / Human Immunology 73 (2012) 1155–1158 Table 1 Tests of associations between GM genotypes and breast cancer risk in whites (Brazil). GM genotypes
(3/3, 3/17, 17/17) (23+/+,23+/,23/) (5/5,5 /21,21/21)
Odds ratiosa (95% CI)
Genotype counts
P-values
Cases
Control
1 Copy
2 Copies
Genotype
Additive
92/123/43 48/110/100 143/93/20
73/120/65 35/105/118 125/103/29
1.61 (0.94–2.74) 1.28 (0.84–1.96) 1.80 (0.86–3.79)
2.07 (1.16–3.71) 1.70 (0.93–3.08) 2.14 (1.04–4.41)
0.0457 0.1906 0.1140
0.0147 0.0687 0.0526
a Reference allele (17/17,23/,21/21), constructed from the genotype model; regression models included number of births, alcohol consumption, smoking status, and BMI as covariates.
Table 2 Tests of associations between GM genotypes and breast cancer risk in blacks (Brazil). GM genotypes
(3/3, 3/17, 17/17) (23+/+,23+/,23/) (5/5,5 /21,21/21) a
Odds ratiosa (95% CI)
Genotype counts
P-values
Cases
Control
1 Copy
2 Copies
Genotype
Additive
2/17/21 0/12/28 24/13/2
4/16/20 2/11/27 24/13/3
0.84 (0.31–2.30) 0.89 (0.34–2.30) 1.95 (0.17–21.95)
0.44 (0.07–2.76) NA 2.10 (0.18–24.99)
0.6858 0.9710 0.8420
0.4363 0.3978 0.6836
Reference allele (17/17,23/,21/21), constructed from the genotype model; no covariates met the p < 0.10 significance level for inclusion in the model.
Table 3 Tests of associations between GM genotypes and breast cancer risk in Japanese (Nagano). GM genotypes
(3/3, 3/17, 17/17) (23+/+,23+/,23/) (5/5,5 /21,21/21)
Odds ratiosa (95% CI)
Genotype counts
P-values
Cases
Control
1 Copy
2 Copies
Genotype
Additive
4/69/324 4/63/330 8/70/318
3/56/338 3/56/338 5/62/330
1.26 (0.80–1.98) 1.17 (0.74–1.86) 1.16 (0.75–1.80)
1.39 (0.18–10.58) 1.36 (0.18–10.39) 1.55 (0.40–6.02)
0.5859 0.7776 0.6779
0.3038 0.4782 0.3871
a Reference allele (17/17,23/,21/21), constructed from the genotype model; regression models included family history, number of births, menopausal status, age at menopause, breast feeding, moderate physical activity in the past five years, and smoking status as covariates.
Table 4 Tests of associations between GM genotypes and breast cancer risk in subjects of Japanese descent living in Brazil. GM genotypes
(3/3, 3/17, 17/17) (23+/+,23+/,23/) (5/5,5 /21,21/21) a
Odds ratiosa (95% CI)
Genotype counts
P-values
Cases
Control
1 Copy
2 Copies
Genotype
Additive
1/13/66 0/9/71 0/14/66
0/13/67 0/11/69 0/16/64
0.81 (0.33–1.97) 0.65 (0.23–1.82) 0.81 (0.34–1.93)
NA NA NA
0.8995 0.4109 0.6329
0.9933 0.4109 0.6329
Reference allele (17/17,23/,21/21), constructed from the genotype model; regression models included number of births as a covariate.
Table 5 Tests of interactions between GM and FccR genotypes in subjects of Japanese descent living in Brazil. GM genotypes
FccR locus
P-valuesa
(3/3, 3/17, 17/17)
FccRIIa FccRIIIa FccRIIa FccRIIIa FccRIIa FccRIIIa
0.4871 0.1853 0.6666 0.0390 0.7843 0.4372
(23+/+,23+/,23/) (5/5,5/21,21/21)
a Reference allele (17/17,23/,21/21), constructed from the genotype model; regression models included number of births as a covariate.
and non-self antigens that may be relevant to the etiopathogenesis of this malignancy. Alternatively, there may be another locus for susceptibility to breast cancer on chromosome 14, distinct from GM, whose alleles are in significant linkage disequilibrium with those of the GM loci. This putative linkage disequilibrium could give rise to the associations observed. The most relevant among the self-antigens, immunity to which is influenced by GM alleles, is epidermal growth factor receptor 2
(HER2). This tumor antigen is overexpressed in 25 to 30% of breast cancer patients, and is associated with poor prognosis. Particular GM alleles, including GM 3 and 5, are associated with natural antibody responsiveness to this antigen [11]. The most relevant among the non-self factors, immunity to which is influenced by GM alleles, is human cytomegalovirus (HCMV). Increasing evidence implicates HCMV in the etiopathogenesis of breast cancer. Elevation in serum HCMV IgG antibody levels is reported to precede the development of breast cancer [12]. Evidence of viral expression has been found in over 97% of neoplastic breast epithelium [13]. HCMV is endemic, affecting 50–100% of the world population. The question arises: How could such a common virus cause breast cancer in only a subset of those infected? The GM alleles could, at least in part, explain the vast discrepancy in HCMV seroprevalence and the prevalence of breast cancer. These determinants modulate certain viral immune evasion strategies [14], a property that could explain their involvement in susceptibility to breast cancer. HCMV has evolved a large repertoire of immune evasion strategies. One strategy involves generating two proteins—encoded by genes TRL11/IRL11 and UL119-UL118—that have functional properties of FccR [15], which may enable the virus to evade host immu-
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nosurveillance by evading the effector consequences of antibody binding, such as antibody-dependent cellular cytotoxicity (ADCC), complement-dependent neutralization, and phagocytosis. Interestingly, HCMV TRL11/IRL11-encoded FccR has significantly higher affinity for IgG1 proteins expressing the GM 3+,1,2 allotypes than for those expressing the allelic GM 17+,1+,2+ allotypes [14]. It follows that subjects with the GM 3+,1,2 allotypes would be more likely to have their Fc domains scavenged, thereby reducing their immunological competence to eliminate the virus and virallyinfected cells through ADCC and other Fc-mediated effector mechanisms. Consequently, these subjects would be more likely to be susceptible to HCMV-spurred diseases. Our finding of a significant association between the GM 3 allele and susceptibility to breast cancer is consistent with this prediction. An additional mechanism could involve the influence of GM allotypes on humoral immunity to HCMV. These determinants influence antibody responsiveness to HCMV epitopes in patients with scleroderma, an autoimmune disease with suspected HCMV etiology [16]. Whether this relationship also holds for breast cancer needs to be investigated. As mentioned above, the association observed here can also be explained by postulating the presence of a breast cancer susceptibility locus whose alleles are in significant linkage disequilibrium with those of the GM loci. It is interesting to note that breast cancer metastasis-related genes have been localized in chromosome 14q32, the region that also harbors GM genes [17]. Additionally, genome-wide association studies (GWAS) have identified breast cancer risk genes on this chromosome in several different population groups. Such GWAS [18], however, cannot evaluate the involvement of GM alleles, as these determinants are not included in the current genotyping platforms. To our knowledge, they are not being tagged by any SNPs that are included in the platforms. Furthermore, GM alleles cannot even be imputed because they were not genotyped in the HapMap panel [19]. IgG gene segments harboring GM genes are highly homologous and apparently not amenable to the high throughput genotyping technology; this attribute may have contributed to their exclusion from the genotyping panels. Although we did not find a strong interactive/epistatic effect of Fcc (GM) and FccR alleles on breast cancer in this study, there is a sound biological rationale for extending this investigation at a larger scale in future studies: Particular alleles at these loci jointly contribute to the cytotoxicity of breast cancer cells by ADCC [20], a major host immunosurveillance mechanism against tumors as well as the leading mechanism underlying the clinical efficacy of therapeutic antibodies such as trastuzumab, which targets HER2. Detection of epistasis requires a large sample size, and the present investigation was most likely underpowered. We found a significant association between GM alleles and breast cancer in white subjects from Brazil but not in other groups. The lack of association in the Japanese population is consistent with a previous report in this group [3]. The reasons for these racial differences in disease associations are not clear. Linkage disequilibrium between GM alleles in the Japanese is different from that in whites or blacks, resulting in distinct arrays of GM haplotypes in various groups. It follows that linkage disequilibrium between any putative risk-conferring genes for breast cancer and GM alleles might also be different in these groups, contributing to the ethnic differences in genetic associations. Multiple genetic and non-genetic factors probably contribute to the risk of breast cancer, and racial differences in these factors may contribute to the differ-
ences in the observed associations. To our knowledge, this is the first report implicating GM genes in susceptibility to breast cancer. It needs to be replicated in a large multiethnic study population. Acknowledgments This work was supported in part by a Grant from the US Department of Defense (W81XWH-08-1-0373) and by a Grant-in-Aid for Research on Risk of Chemical Substances from the Ministry of Health, Labor and Welfare of Japan, and Grants-in-Aid for Scientific Research on Priority Areas (17015049). References [1] Jefferis R, Lefranc MP. Human immunoglobulin allotypes: possible implications for immunogenicity. MAbs 2009;1:332–8. [2] Dugoujon JM, Hazout S, Loirat F, Mourrieras B, Crouau-Roy B, Sanchez-Mazas A. GM haplotype diversity of 82 populations over the world suggests a centrifugal model of human migrations. Am J Phys Anthropol 2004;125:175–92. [3] Nakao Y, Matsumoto H, Miyazaki T, Watanabe S, Mukojima T, Kawashima R, et al. Immunoglobulin G heavy-chain allotypes as possible genetic markers for human cancer. J Natl Cancer Inst 1981;67:47–50. [4] Ilic´ V, Milosevic´-Jovcic´ N, Markovic´ D, Petrovic´ S, Stefanovic´ G. A biased Gm haplotype and Gm paraprotein allotype in multiple myeloma suggests a role for the Gm system in myeloma development. Int J Immunogenet 2007;34:119–25. [5] Pandey JP, Johnson AH, Fudenberg HH, Amos DB, Gutterman JU, Hersh EM. HLA antigens and immunoglobulin allotypes in patients with malignant melanoma. Hum Immunol 1981;2:185–90. [6] Morell A, Scherz R, Käser H, Skvaril F. Evidence for an association between uncommon Gm phenotypes and neuroblastoma. Lancet 1977;1:23–4. [7] Pandey JP, Ebbesen P, Bülow S, Svendsen LB, Fudenberg HH. IgG heavy-chain (Gm) allotypes in familial polyposis coli. Am J Hum Genet 1986;39:133–6. [8] Iwasaki M, Shimada N, Kasuga Y, Yokoyama S, Onuma H, Nishimura H, et al. Fragment c gamma receptor gene polymorphisms and breast cancer risk in case-control studies in Japanese, Japanese Brazilians, and non-Japanese Brazilians. Breast Cancer Res Treat 2011;126:497–505. [9] Brusco A, de Lange GG, Boccazzi C, Carbonara AO. Molecular characterization of G2m(n+) and G2m(n) allotypes. Immunogenetics 1995;42:414–7. [10] Balbín M, Grubb A, de Lange GG, Grubb R. DNA sequences specific for Caucasian G3m(b) and (g) allotypes: allotyping at the genomic level. Immunogenetics 1994;39:187–93. [11] Pandey JP, Namboodiri AM, Kurtenkov O, Nietert PJ. Genetic regulation of antibody responses to human epidermal growth factor receptor 2 (HER-2) in breast cancer. Hum Immunol 2010;71:1124–7. [12] Cox B, Richardson A, Graham P, Gislefoss RE, Jellum E, Rollag H. Breast cancer, cytomegalovirus and Epstein-Barr virus: a nested case-control study. Br J Cancer 2010;102:1665–9. [13] Harkins LE, Matlaf LA, Soroceanu L, Klemm K, Britt WJ, Wang W, et al. Detection of human cytomegalovirus in normal and neoplastic breast epithelium. Herpesviridae 2010;1:8. [14] Namboodiri AM, Pandey JP. The human cytomegalovirus TRL11/IRL11encoded FccR binds differentially to allelic variants of immunoglobulin G1. Arch Virol 2011;156:907–10. [15] Atalay R, Zimmermann A, Wagner M, Borst E, Benz C, Messerle M, et al. Identification and expression of human cytomegalovirus transcription units coding for two distinct Fcgamma receptor homologs. J Virol 2002;76: 8596–608. [16] Pandey JP, Immunoglobulin GM. Genes and IgG antibodies to cytomegalovirus in patients with systemic sclerosis. Clin Exp Rheumatol 2004;22:S35–7. [17] O’Connell P, Fischbach K, Hilsenbeck S, Mohsin SK, Fuqua SA, Clark GM, et al. Loss of heterozygosity at D14S62 and metastatic potential of breast cancer. J Natl Cancer Inst 1999;91:1391–7. [18] Figueroa JD, Garcia-Closas M, Humphreys M, Platte R, Hopper JL, Southey MC, Van’t Veer LJ, et al. Associations of common variants at 1p11.2 and 14q24.1 (RAD51L1) with breast cancer risk and heterogeneity by tumor subtype: findings from the Breast Cancer Association Consortium. Hum Mol Genet 2011;20:4693–706. [19] Pandey JP. Genomewide association studies and assessment of the risk of disease. N Engl J Med 2010;363:2076–7. [20] Namboodiri AM, Pandey JP. Differential inhibition of trastuzumab and cetuximab induced cytotoxicity of cancer cells by IgG1 expressing different GM allotypes. Clin Exp Immunol 2011;166:361–5.
Contents lists available at SciVerse ScienceDirect
www.ashi-hla.org
journal homepage: www.elsevier.com/locate/humimm
Genetic markers of immunoglobulin G and susceptibility to breast cancer Janardan P. Pandey a,⇑, Emily Kistner-Griffin b, Motoki Iwasaki c, Shizhong Bu a, Ray Deepe a, Laurel Black a, Yoshio Kasuga d, Gerson S. Hamada e, Shoichiro Tsugane c a
Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, SC, United States Department of Medicine, Medical University of South Carolina, Charleston, SC, United States c Epidemiology and Prevention Division, Research Center for Cancer Prevention and Screening, National Cancer Center, Tokyo, Japan d Department of Surgery, Nagano Matsushiro General Hospital, Nagano, Japan e Nikkei Disease Prevention Center, São Paulo, Brazil b
a r t i c l e
i n f o
Article history: Received 6 June 2012 Accepted 30 July 2012 Available online 9 August 2012
a b s t r a c t Immunoglobulin GM allotypes, antigenic determinants of c chains, are encoded by three very closely linked codominant genes on chromosome 14q32. Particular GM alleles/haplotypes are associated with antibody responses to certain tumor antigens and contribute to the cytotoxicity of breast cancer cells, but their possible role in susceptibility to this malignancy has not been adequately examined. Using a matched case-control design, we genotyped a large (1710 subjects) study population from Japan and Brazil for several GM alleles to determine whether these determinants are associated with susceptibility to breast cancer. After adjusting for the potential confounders, the GM 3 allele of IgG1 was significantly associated with susceptibility to breast cancer in white subjects from Brazil (OR = 2.07, CI 1.16–3.71; p = 0.0147). These data show that Caucasians with the GM 3 allele are over twice as likely to develop breast cancer as those who lack this allele. Since this allele modulates an immune evasion strategy of cytomegalovirus, the results also shed light on the possible mechanism underlying the reported involvement of this virus in the etiology of breast cancer. Ó 2012 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.
1. Introduction
2. Materials and methods
Polymorphic hereditary antigenic determinants expressed on immunoglobulin c chains are called GM allotypes. Encoded by three very closely linked and highly homologous codominant genes on chromosome 14q32, they are expressed on the constant region of c1, c2, and c3 chains [1]. Linkage disequilibrium in the GM system within a racial group is almost absolute and major races are characterized by a unique array of GM haplotypes [2]. GM allotypes are associated with many cancers [3–7], but their role in susceptibility to breast cancer has not been adequately examined. Using a matched case-control study design and a large study population from Japan and Brazil, we aimed to determine whether or not GM alleles are risk factors for the development of breast cancer. Since the majority of the GM alleles are expressed in the Fc region of c chains, we also wished to investigate whether particular Fc (GM), FccRIIa, and FccRIIIa alleles epistatically contribute to the risk of breast cancer.
2.1. Study subjects
⇑ Corresponding author. Address: Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, SC 29425-2230, United States. Fax: +1 843 792 4882. E-mail address: [email protected] (J.P. Pandey).
The experimental design, recruitment criteria, and the demographics of the study population have been described in detail elsewhere [8]. Briefly, breast cancer patients were recruited between 2001 and 2005 at four hospitals in Nagano, Japan, and between 2001 and 2006 at eight hospitals in São Paulo, Brazil. Cancer-free controls were matched to case patients by ethnicity, residential area during the study period, and age (within 3–5 years). Detailed data were collected on family history of cancer, menstrual and reproductive history, anthropometric factors, physical activity, and smoking habits. Estrogen and progesterone hormone receptor status was also determined. The study protocol was approved by the Institutional Review Boards of the respective institutions. Blood from cases and controls was collected after informed consent. The study population consisted of the following: 258 case-control pairs of Caucasian descent (Brazil), 40 case-control pairs of African descent (Brazil), 80 case-control pairs of Japanese descent (Brazil), 80 case-control pairs from the Brazilian mulatto population, 397 case-control pairs from Nagano, Japan.
0198-8859/$36.00 - see front matter Ó 2012 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.humimm.2012.07.340
1156
J.P. Pandey et al. / Human Immunology 73 (2012) 1155–1158
2.2. GM genotyping DNA for genotyping was isolated from peripheral blood using a standard protocol (Qiagen-Kit method). For the determination of IgG1 markers GM 3 and 17 (arginine to lysine, a G to A substitution in the CH1 region of the c1 gene), we used a pre-designed TaqManÒ genotyping assay from Applied Biosystems Inc. (Foster City, CA). The probe specific to GM 3 allele was labeled with FAM fluorescent at the 50 end and with nonfluorescent quencher at the 30 end. The probe specific to GM 17 allele was labeled with VIC fluorescent at the 50 end and with nonfluorescent quencher at the 30 end. GM 23—valine to methionine, a G to A substitution in the CH2 region of the c2 gene—was determined by a nested PCR-RFLP method. In brief, a 915 bp region of the c2 gene that incorporates the sites for the allelic substitutions was amplified as described by Brusco et al. [9], using the following primers: 50 AAATGTTGTGTCGAGTGCCC 30 and 50 GGCTTGCCGGCCGTGGCAC 30 . A 197 bp segment was further amplified from this 915 bp fragment using the following primers: 50 GCACCACCTGTGGCAGGACC 30 and 50 TTGAACTGCTCCTCCCG TGG 30 . After digestion of the amplified product with the restriction enzyme NlaIII, the following products corresponding to the three genotypes were obtained: GM 23+ GM 23 GM 23+,23
90 bp, 63 bp, 44 bp 134 bp, 63 bp 134 bp, 90 bp, 63 bp, 44 bp
For the determination of IgG3 markers GM 5 and 21, the c3 gene containing the allelic sites was amplified [10] using the following primers: 50 ACCCAAGGATACCCTTATGATT 30 and 50 GAGGCTCTTCTGCGTG AAGC 30 . The amplified product (685 bp) was digested with the restriction enzyme MspA1I. The resulting products corresponding to the three genotypes are as follows: GM 21 GM 5 GM 5,21
327 bp, 295 bp, 63 bp 171 bp, 158 bp, 156 bp, 137 bp, 63 bp 327 bp, 295 bp, 171 bp, 158 bp, 156 bp, 137 bp, 63 bp
In addition to the controls representing the three genotypes for the marker, we also used a blank (no genomic DNA, only primers and the PCR master mix) control and a DNA molecular weight marker. 2.3. FccR genotyping The activating receptors FccRIIa and FccRIIIa are genetically polymorphic: a change in the nucleotide at position 497 of FccRIIa gene from A to G results in change of amino acid histidine to arginine (H/R131); a change in the nucleotide at position 559 of the FccRIIIa gene from T to G results in phenylalanine to valine substitution (F/V158). The single nucleotide polymorphisms (SNP) responsible for the allelic variation were previously determined by the TaqManÒ genotyping assays from Applied Biosystems Inc. [8]. Genotyping was done blinded to the case-control and group status of the subjects. 2.4. Statistical analysis Genotype frequencies were in Hardy–Weinberg equilibrium in all groups except the mulatto population, which could be due to
population admixture. This group was excluded from further analyses. Conditional logistic regression models were constructed within each population group. Potential confounders—family history of breast cancer, history of benign breast disease, menopausal status and age at menopause, number of births, age at first birth, breast feeding, alcohol drinking, smoking status, moderate physical activity in the past 5 years, vitamin supplement use, age at menarche, body mass index—were considered for inclusion as covariates in the models of genetic association, and a backwards regression approach with an a = 0.10 inclusion level was implemented. Tests of genotype models (2df tests with no assumptions about inheritance models) as well as tests of additive effects (1df) were constructed. In all models, statistical significance was defined as p < 0.05. All reported p values are two-sided. 3. Results The results of the tests of associations between GM genotypes and risk of breast cancer in various population groups are presented in Tables 1–4. Allelic variation at the IgG1 GM 3/17 locus contributed to the risk of developing breast cancer in white subjects from Brazil (Table 1). The association was significant for both the genotype model, which assumed no particular mode of inheritance, and the additive model, which assumed that the alleles contribute to the risk additively on the logit scale. Compared to subjects who were homozygous for GM 17, the GM 3 homozygotes were over twice as likely to develop breast cancer (OR = 2.07, CI 1.16–3.71; p = 0.0147). This association would remain significant even after a conservative correction for multiple testing [p = 0.0441 (0.0147 3)]. The GM 5 allele, which is in significant linkage disequilibrium with the GM 3 allele in whites, was also associated with breast cancer at a borderline significance (OR = 2.14, CI 1.04–4.41; p = 0.0526), which would become nonsignificant if adjusted for multiple testing. GM genotypes were not associated with susceptibility to breast cancer in other groups (Tables 2–4). In our previous investigations involving this study population, we did not find a significant association between any FccRIIa and FccRIIIa genotypes and susceptibility to breast cancer [8]. In the present investigation, we tested the possibility that FccR genotypes do contribute to the development of breast cancer, but only in the presence of certain Fcc (GM) alleles. An interaction analysis between GM and FccR genotypes showed that in the Japanese living in Brazil, this appears to be the case (Table 5). GM 23 genotypes interacted epistatically with FccRIIIa (V/F) genotypes and contributed to the risk of breast cancer (p = 0.0390). This apparent association is driven by the contrasting (protective and risk) effects of GM 23 genotypes in the presence of FccRIIIa V allele: The OR associated with the inheritance of one copy of the V allele for individuals carrying the heterozygous GM 23+/GM 23 genotype is 0.13 (protective), while the OR associated with the inheritance of one copy of the V allele for individuals carrying the homozygous GM 23/GM 23 genotype is 1.48 (susceptibility). No other interactive effects were found (data not shown). 4. Discussion The results presented here show a distinct association between the GM 3 allele of IgG1 and susceptibility to breast cancer in a Brazilian white population. This allele acts additively to increase the risk of breast cancer over two fold compared to the alternative GM 17 allele at this locus. There are at least two potential mechanisms through which GM alleles could be associated with susceptibility to breast cancer. The GM 3 allele could itself modulate the risk of breast cancer, possibly through its effect on immunity to self
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J.P. Pandey et al. / Human Immunology 73 (2012) 1155–1158 Table 1 Tests of associations between GM genotypes and breast cancer risk in whites (Brazil). GM genotypes
(3/3, 3/17, 17/17) (23+/+,23+/,23/) (5/5,5 /21,21/21)
Odds ratiosa (95% CI)
Genotype counts
P-values
Cases
Control
1 Copy
2 Copies
Genotype
Additive
92/123/43 48/110/100 143/93/20
73/120/65 35/105/118 125/103/29
1.61 (0.94–2.74) 1.28 (0.84–1.96) 1.80 (0.86–3.79)
2.07 (1.16–3.71) 1.70 (0.93–3.08) 2.14 (1.04–4.41)
0.0457 0.1906 0.1140
0.0147 0.0687 0.0526
a Reference allele (17/17,23/,21/21), constructed from the genotype model; regression models included number of births, alcohol consumption, smoking status, and BMI as covariates.
Table 2 Tests of associations between GM genotypes and breast cancer risk in blacks (Brazil). GM genotypes
(3/3, 3/17, 17/17) (23+/+,23+/,23/) (5/5,5 /21,21/21) a
Odds ratiosa (95% CI)
Genotype counts
P-values
Cases
Control
1 Copy
2 Copies
Genotype
Additive
2/17/21 0/12/28 24/13/2
4/16/20 2/11/27 24/13/3
0.84 (0.31–2.30) 0.89 (0.34–2.30) 1.95 (0.17–21.95)
0.44 (0.07–2.76) NA 2.10 (0.18–24.99)
0.6858 0.9710 0.8420
0.4363 0.3978 0.6836
Reference allele (17/17,23/,21/21), constructed from the genotype model; no covariates met the p < 0.10 significance level for inclusion in the model.
Table 3 Tests of associations between GM genotypes and breast cancer risk in Japanese (Nagano). GM genotypes
(3/3, 3/17, 17/17) (23+/+,23+/,23/) (5/5,5 /21,21/21)
Odds ratiosa (95% CI)
Genotype counts
P-values
Cases
Control
1 Copy
2 Copies
Genotype
Additive
4/69/324 4/63/330 8/70/318
3/56/338 3/56/338 5/62/330
1.26 (0.80–1.98) 1.17 (0.74–1.86) 1.16 (0.75–1.80)
1.39 (0.18–10.58) 1.36 (0.18–10.39) 1.55 (0.40–6.02)
0.5859 0.7776 0.6779
0.3038 0.4782 0.3871
a Reference allele (17/17,23/,21/21), constructed from the genotype model; regression models included family history, number of births, menopausal status, age at menopause, breast feeding, moderate physical activity in the past five years, and smoking status as covariates.
Table 4 Tests of associations between GM genotypes and breast cancer risk in subjects of Japanese descent living in Brazil. GM genotypes
(3/3, 3/17, 17/17) (23+/+,23+/,23/) (5/5,5 /21,21/21) a
Odds ratiosa (95% CI)
Genotype counts
P-values
Cases
Control
1 Copy
2 Copies
Genotype
Additive
1/13/66 0/9/71 0/14/66
0/13/67 0/11/69 0/16/64
0.81 (0.33–1.97) 0.65 (0.23–1.82) 0.81 (0.34–1.93)
NA NA NA
0.8995 0.4109 0.6329
0.9933 0.4109 0.6329
Reference allele (17/17,23/,21/21), constructed from the genotype model; regression models included number of births as a covariate.
Table 5 Tests of interactions between GM and FccR genotypes in subjects of Japanese descent living in Brazil. GM genotypes
FccR locus
P-valuesa
(3/3, 3/17, 17/17)
FccRIIa FccRIIIa FccRIIa FccRIIIa FccRIIa FccRIIIa
0.4871 0.1853 0.6666 0.0390 0.7843 0.4372
(23+/+,23+/,23/) (5/5,5/21,21/21)
a Reference allele (17/17,23/,21/21), constructed from the genotype model; regression models included number of births as a covariate.
and non-self antigens that may be relevant to the etiopathogenesis of this malignancy. Alternatively, there may be another locus for susceptibility to breast cancer on chromosome 14, distinct from GM, whose alleles are in significant linkage disequilibrium with those of the GM loci. This putative linkage disequilibrium could give rise to the associations observed. The most relevant among the self-antigens, immunity to which is influenced by GM alleles, is epidermal growth factor receptor 2
(HER2). This tumor antigen is overexpressed in 25 to 30% of breast cancer patients, and is associated with poor prognosis. Particular GM alleles, including GM 3 and 5, are associated with natural antibody responsiveness to this antigen [11]. The most relevant among the non-self factors, immunity to which is influenced by GM alleles, is human cytomegalovirus (HCMV). Increasing evidence implicates HCMV in the etiopathogenesis of breast cancer. Elevation in serum HCMV IgG antibody levels is reported to precede the development of breast cancer [12]. Evidence of viral expression has been found in over 97% of neoplastic breast epithelium [13]. HCMV is endemic, affecting 50–100% of the world population. The question arises: How could such a common virus cause breast cancer in only a subset of those infected? The GM alleles could, at least in part, explain the vast discrepancy in HCMV seroprevalence and the prevalence of breast cancer. These determinants modulate certain viral immune evasion strategies [14], a property that could explain their involvement in susceptibility to breast cancer. HCMV has evolved a large repertoire of immune evasion strategies. One strategy involves generating two proteins—encoded by genes TRL11/IRL11 and UL119-UL118—that have functional properties of FccR [15], which may enable the virus to evade host immu-
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nosurveillance by evading the effector consequences of antibody binding, such as antibody-dependent cellular cytotoxicity (ADCC), complement-dependent neutralization, and phagocytosis. Interestingly, HCMV TRL11/IRL11-encoded FccR has significantly higher affinity for IgG1 proteins expressing the GM 3+,1,2 allotypes than for those expressing the allelic GM 17+,1+,2+ allotypes [14]. It follows that subjects with the GM 3+,1,2 allotypes would be more likely to have their Fc domains scavenged, thereby reducing their immunological competence to eliminate the virus and virallyinfected cells through ADCC and other Fc-mediated effector mechanisms. Consequently, these subjects would be more likely to be susceptible to HCMV-spurred diseases. Our finding of a significant association between the GM 3 allele and susceptibility to breast cancer is consistent with this prediction. An additional mechanism could involve the influence of GM allotypes on humoral immunity to HCMV. These determinants influence antibody responsiveness to HCMV epitopes in patients with scleroderma, an autoimmune disease with suspected HCMV etiology [16]. Whether this relationship also holds for breast cancer needs to be investigated. As mentioned above, the association observed here can also be explained by postulating the presence of a breast cancer susceptibility locus whose alleles are in significant linkage disequilibrium with those of the GM loci. It is interesting to note that breast cancer metastasis-related genes have been localized in chromosome 14q32, the region that also harbors GM genes [17]. Additionally, genome-wide association studies (GWAS) have identified breast cancer risk genes on this chromosome in several different population groups. Such GWAS [18], however, cannot evaluate the involvement of GM alleles, as these determinants are not included in the current genotyping platforms. To our knowledge, they are not being tagged by any SNPs that are included in the platforms. Furthermore, GM alleles cannot even be imputed because they were not genotyped in the HapMap panel [19]. IgG gene segments harboring GM genes are highly homologous and apparently not amenable to the high throughput genotyping technology; this attribute may have contributed to their exclusion from the genotyping panels. Although we did not find a strong interactive/epistatic effect of Fcc (GM) and FccR alleles on breast cancer in this study, there is a sound biological rationale for extending this investigation at a larger scale in future studies: Particular alleles at these loci jointly contribute to the cytotoxicity of breast cancer cells by ADCC [20], a major host immunosurveillance mechanism against tumors as well as the leading mechanism underlying the clinical efficacy of therapeutic antibodies such as trastuzumab, which targets HER2. Detection of epistasis requires a large sample size, and the present investigation was most likely underpowered. We found a significant association between GM alleles and breast cancer in white subjects from Brazil but not in other groups. The lack of association in the Japanese population is consistent with a previous report in this group [3]. The reasons for these racial differences in disease associations are not clear. Linkage disequilibrium between GM alleles in the Japanese is different from that in whites or blacks, resulting in distinct arrays of GM haplotypes in various groups. It follows that linkage disequilibrium between any putative risk-conferring genes for breast cancer and GM alleles might also be different in these groups, contributing to the ethnic differences in genetic associations. Multiple genetic and non-genetic factors probably contribute to the risk of breast cancer, and racial differences in these factors may contribute to the differ-
ences in the observed associations. To our knowledge, this is the first report implicating GM genes in susceptibility to breast cancer. It needs to be replicated in a large multiethnic study population. Acknowledgments This work was supported in part by a Grant from the US Department of Defense (W81XWH-08-1-0373) and by a Grant-in-Aid for Research on Risk of Chemical Substances from the Ministry of Health, Labor and Welfare of Japan, and Grants-in-Aid for Scientific Research on Priority Areas (17015049). References [1] Jefferis R, Lefranc MP. Human immunoglobulin allotypes: possible implications for immunogenicity. MAbs 2009;1:332–8. [2] Dugoujon JM, Hazout S, Loirat F, Mourrieras B, Crouau-Roy B, Sanchez-Mazas A. GM haplotype diversity of 82 populations over the world suggests a centrifugal model of human migrations. Am J Phys Anthropol 2004;125:175–92. [3] Nakao Y, Matsumoto H, Miyazaki T, Watanabe S, Mukojima T, Kawashima R, et al. Immunoglobulin G heavy-chain allotypes as possible genetic markers for human cancer. J Natl Cancer Inst 1981;67:47–50. [4] Ilic´ V, Milosevic´-Jovcic´ N, Markovic´ D, Petrovic´ S, Stefanovic´ G. A biased Gm haplotype and Gm paraprotein allotype in multiple myeloma suggests a role for the Gm system in myeloma development. Int J Immunogenet 2007;34:119–25. [5] Pandey JP, Johnson AH, Fudenberg HH, Amos DB, Gutterman JU, Hersh EM. HLA antigens and immunoglobulin allotypes in patients with malignant melanoma. Hum Immunol 1981;2:185–90. [6] Morell A, Scherz R, Käser H, Skvaril F. Evidence for an association between uncommon Gm phenotypes and neuroblastoma. Lancet 1977;1:23–4. [7] Pandey JP, Ebbesen P, Bülow S, Svendsen LB, Fudenberg HH. IgG heavy-chain (Gm) allotypes in familial polyposis coli. Am J Hum Genet 1986;39:133–6. [8] Iwasaki M, Shimada N, Kasuga Y, Yokoyama S, Onuma H, Nishimura H, et al. Fragment c gamma receptor gene polymorphisms and breast cancer risk in case-control studies in Japanese, Japanese Brazilians, and non-Japanese Brazilians. Breast Cancer Res Treat 2011;126:497–505. [9] Brusco A, de Lange GG, Boccazzi C, Carbonara AO. Molecular characterization of G2m(n+) and G2m(n) allotypes. Immunogenetics 1995;42:414–7. [10] Balbín M, Grubb A, de Lange GG, Grubb R. DNA sequences specific for Caucasian G3m(b) and (g) allotypes: allotyping at the genomic level. Immunogenetics 1994;39:187–93. [11] Pandey JP, Namboodiri AM, Kurtenkov O, Nietert PJ. Genetic regulation of antibody responses to human epidermal growth factor receptor 2 (HER-2) in breast cancer. Hum Immunol 2010;71:1124–7. [12] Cox B, Richardson A, Graham P, Gislefoss RE, Jellum E, Rollag H. Breast cancer, cytomegalovirus and Epstein-Barr virus: a nested case-control study. Br J Cancer 2010;102:1665–9. [13] Harkins LE, Matlaf LA, Soroceanu L, Klemm K, Britt WJ, Wang W, et al. Detection of human cytomegalovirus in normal and neoplastic breast epithelium. Herpesviridae 2010;1:8. [14] Namboodiri AM, Pandey JP. The human cytomegalovirus TRL11/IRL11encoded FccR binds differentially to allelic variants of immunoglobulin G1. Arch Virol 2011;156:907–10. [15] Atalay R, Zimmermann A, Wagner M, Borst E, Benz C, Messerle M, et al. Identification and expression of human cytomegalovirus transcription units coding for two distinct Fcgamma receptor homologs. J Virol 2002;76: 8596–608. [16] Pandey JP, Immunoglobulin GM. Genes and IgG antibodies to cytomegalovirus in patients with systemic sclerosis. Clin Exp Rheumatol 2004;22:S35–7. [17] O’Connell P, Fischbach K, Hilsenbeck S, Mohsin SK, Fuqua SA, Clark GM, et al. Loss of heterozygosity at D14S62 and metastatic potential of breast cancer. J Natl Cancer Inst 1999;91:1391–7. [18] Figueroa JD, Garcia-Closas M, Humphreys M, Platte R, Hopper JL, Southey MC, Van’t Veer LJ, et al. Associations of common variants at 1p11.2 and 14q24.1 (RAD51L1) with breast cancer risk and heterogeneity by tumor subtype: findings from the Breast Cancer Association Consortium. Hum Mol Genet 2011;20:4693–706. [19] Pandey JP. Genomewide association studies and assessment of the risk of disease. N Engl J Med 2010;363:2076–7. [20] Namboodiri AM, Pandey JP. Differential inhibition of trastuzumab and cetuximab induced cytotoxicity of cancer cells by IgG1 expressing different GM allotypes. Clin Exp Immunol 2011;166:361–5.