Skip to main content

Genetic polymorphism of the OPG gene associated with breast cancer



The receptor activator of NF-κB (RANK), its ligand (RANKL) and osteoprotegerin (OPG) have been reported to play a role in the pathophysiological bone turnover and in the pathogenesis of breast cancer. Based on this we investigated the role of single nucleotide polymorphisms (SNPs) within RANK, RANKL and OPG and their possible association to breast cancer risk.


Genomic DNA was obtained from Caucasian participants consisting of 307 female breast cancer patients and 396 gender-matched healthy controls. We studied seven SNPs in the genes of OPG (rs3102735, rs2073618), RANK (rs1805034, rs35211496) and RANKL (rs9533156, rs2277438, rs1054016) using TaqMan genotyping assays. Statistical analyses were performed using the χ2-tests for 2 x 2 and 2 x 3 tables.


The allelic frequencies (OR: 1.508 CI: 1.127-2.018, p=0.006) and the genotype distribution (p=0.019) of the OPG SNP rs3102735 differed significantly between breast cancer patients and healthy controls. The minor allele C and the corresponding homo- and heterozygous genotypes are more common in breast cancer patients (minor allele C: 18.4% vs. 13.0%; genotype CC: 3.3% vs. 1.3%; genotype CT: 30.3% vs. 23.5%). No significantly changed risk was detected in the other investigated SNPs. Additional analysis showed significant differences when comparing patients with invasive vs. non-invasive tumors (OPG rs2073618) as well as in terms of tumor localization (RANK rs35211496) and body mass index (RANKL rs9533156 and rs1054016).


This is the first study reporting a significant association of the SNP rs3102735 (OPG) with the susceptibility to develop breast cancer in the Caucasian population.

Peer Review reports


Breast cancer is one of the most common malignancies in women, leading to distant metastases in patients with advanced disease, particularly in liver, lung and bone. Bone metastases are associated with hypercalcemia, pathologic fracture, spinal cord compression, pain and reduced quality of life [1]. The discovery of receptor activator of NF-κB (RANK), its ligand RANKL and osteoprotegerin (OPG) has contributed significantly to the understanding of the physiological bone turnover. A functional interaction between RANKL, a member of the tumor necrosis factor (TNF) ligand superfamily and RANK, its cognate TNF-receptor is essential for osteoclast differentiation, survival and activation [2].

RANKL, a type II homotrimeric transmembrane protein, is expressed by osteoblasts, osteocytes, bone marrow stromal cells, Tcells and various tumor cells, e. g. myeloma and breast cancer [36]. The type-I homotrimeric transmembrane protein RANK is not only expressed by osteoclast, Tcells, dendritic cells, endothelial cells, and mammary glands but also by cancer cells including prostate and breast [711]. RANKL- or RANK-deficient mice develop osteopetrosis resulting from a lack of osteoclasts and absence of bone resorption [12, 13]. OPG is a secreted homodimeric glycoprotein from the TNF receptor family, lacking a transmembrane domain and has homology to the CD40 protein [14]. OPG neutralizes RANKL, which leads to a reduced RANK-RANKL interaction, thus inhibiting osteoclastogenesis [6, 15]. Transgenic mice overexpressing OPG show increased bone mass (osteopetrosis) as a result of reduced osteoclasts [14], whereas OPG-deficient mice are characterized by massive osteoclast activity and osteoporosis [16]. With regard to tumor development, OPG is discussed to be a positive regulator of microvessel formation and to promote neovascularisation [17] and might therefore have an influence on tumor progression. Moreover OPG overexpression by breast cancer cells increased cell proliferation and tumor growth in vivo[18].

A disturbed RANKL/OPG ratio was found in a spectrum of skeletal diseases (e. g. rheumatoid arthritis, osteoporosis, bone metastases) characterized by extensive osteoclast activity. Additionally, the RANK/RANKL pathway has intrinsic functionality in mammary epithelium development. Mice that are deficient for RANK or RANKL did not develop lactating mammary gland [8]. Recently, two groups have found that RANKL has not only a fundamental role in the normal physiology of the mammary gland, but may also be crucial for breast cancer development [19, 20]. These data support earlier results, where RANKL was shown to play a role in breast cancer cell migration into bone [21] and underscore the potential use of RANKL inhibition in the prevention of breast cancer development. Based on its pivotal role in the bone remodeling process, RANKL has become a therapeutic target. A monoclonal antibody against RANKL, denosumab, has been approved for the treatment of postmenopausal osteoporosis and bone metastasis in breast cancer [22, 23].

In summary, the functional properties of the RANK/RANKL/OPG pathway suggest an important effect of the genes on the pathogenesis of breast cancer. These findings led us to investigate the link between seven single nucleotide polymorphisms (SNPs) in the genes of RANK, RANKL and OPG, all possibly associated with functional alterations, and breast cancer risk.


Study populations

A total of 703 participants consisting of 307 female breast cancer patients and 396 gender-matched healthy controls were enrolled in this study (Table 1). All patients and controls were of central European Caucasian ethnicity. Breast cancer patients were collected from the Department of Gynecology, Obstetrics and Reproductive Medicine of Saarland University Medical School, Homburg/Saar, Germany. Controls were either recruited from the Departments of Gynecology, Obstetrics and Reproductive Medicine (n=47), Internal Medicine II (n=163) or the Institute for Transfusion Medicine (n=186) of Saarland University Medical School, Homburg/Saar, Germany. The local ethics committee of the Medical Association from the Saarland (reference number: 162/11) approved the study and all individuals in the study gave written informed consent. The study was carried out in compliance with the Helsinki Declaration.

Table 1 Characteristics of study population

Case patients were diagnosed as unambiguously having breast cancer through standard clinical and histological findings. Specific cancer characteristics such as histological subtypes, grading, metastasis were not used as a criterion for the inclusion or exclusion of samples.

SNP selection

The three genes of interest together span more than 120 kb pairs and show only weak to moderate linkage-disequilibrium patterns according to the HapMap data. We have preferentially selected SNPs which might be functionally relevant, either by their location within a potentially regulatory region (3’ untranslated or promoter region, intron-exon boundary) or by altering the amino acid sequence (missense mutation). A total of seven SNPs were analyzed, two within the OPG (rs3102735, rs2073618) and RANK (rs1805034, rs35211496) gene, respectively, and three within the RANKL gene (rs9533156, rs2277438, rs1054016). Table 2 summarizes the chromosomal position and function of the selected SNPs.

Table 2 Selected SNPs for genotyping

Genomic DNA extraction and Genotyping

Genomic DNA was isolated from peripheral blood lymphocytes using QIAamp DNA Blood Mini Kit according to the manufacturer’s protocols (Qiagen, Hilden, Germany). DNA quantity was assessed spectrophotometrically with the Nanodrop ND 1000 (Peqlab, Erlangen, Germany). All SNPs were genotyped using commercial TaqMan assays (assay IDs: rs3102735: C_1971046_10; rs2073618: C_1971047_1; rs1805034: C_8685532_20; rs35211496: C_25473190_10; rs9533156: C_30009803_10; rs2277438: C_25473654_10; rs1054016: C_7444426_10) with TaqMan Genotyping Master Mix on a 7500 real-time PCR cycler (Life Technologies, Darmstadt, Germany) by following the manufacturer’s instructions.

Statistical analyses

Hardy-Weinberg equilibrium was assessed in each cohort by comparing the observed genotype distribution with the expected one using a χ2-test (Institute of Human Genetic, Munich, Germany: The difference in allele and genotype frequencies between patients and healthy controls (as well as between different subgroups) were analyzed using χ2-tests for 2 x 2 and 2 x 3 tables, respectively, with Fisher’s exact test. Differences in allele frequencies were quantified by odds ratios (OR) and 95% confidence intervals (CI). With regard to significantly elder breast cancer patients than healthy controls age-adjusted covariate analysis was performed. All p-values are two-sided and p-values <0.05 were considered as statistically significant. All statistical analyses were performed using the SPSS statistical software. Finally, a power analysis was performed using the G power 3.1.3 software. To the best of our knowledge no adjustment for multiple testing was made because analyses were considered exploratory and needing confirmation by an independent set of data. Previous studies have demonstrated that the analyzed SNPs only show a weak to moderate linkage-disequilibrium patterns according to the HapMap data.


Subject characteristics

The mean age was 56 years (range 22-91) for the breast cancer patients and 45 (range 18-88) for the healthy controls showing significant difference. Clinical data (e. g. menopausal status, body mass index (BMI)) and specific cancer characteristics such as localization, histological subtypes, tumor size, metastasis, grading, proliferation index as well as hormone receptor and Her2 expression are listed in Table 1. The tumor markers carcinoembryonic antigen (CEA) and CA15-3 were measured routinely in the blood of preoperative patients. Invasive ductal carcinomas (74%) with a size smaller 2 cm (T1, 62%) and without metastases (nodal negative: 70%, no distant metastases: 95%) at first diagnosis were most frequently. Additionally, most tumors expressed estrogen (81%) and progesterone receptors (70%), as expected, while Her2 was negative in most cases (80%) (Table 1).

Allele and genotype frequencies and risk of breast cancer

The genotype distributions for all seven SNPs were in the Hardy-Weinberg equilibrium. Table 3 summarizes the results of all SNP analyses in the genes encoding for OPG (rs3102735, rs2073618), RANK (rs1805034, rs35211496) and RANKL (rs9533156, rs2277438, rs1054016). Allelic and genotype frequencies in breast cancer patients were compared to healthy controls.

Table 3 Association of allele and genotype frequencies of OPG , RANK and RANKL in patients with breast cancer and healthy controls

The allelic frequencies (OR: 1.508 CI: 1.127-2.018, p=0.006) as well as the genotype distribution (p=0.019) of the OPG SNP rs3102735 differed significantly between breast cancer patients and healthy controls. The minor allele C was more frequent in breast cancer patients (18.4%) compared to the control group (13.0%). In addition, the homozygous genotype CC of the minor allele as well as the heterozygous genotype CT were more frequent in the breast cancer group (3.3% and 30.3%) compared to the controls (1.3% and 23.5%) (Table 3). The power analysis revealed a power of 0.79 for the allele frequency and 0.72 for the genotype distribution to detect dependencies (α = 0.05) (Additional file 1: Figure S1). Further statistical analysis revealed that the heterozygous genotype CT as well as the homozygous genotype CC together with the heterozygous genotype CT versus the homozygous genotype TT of the major allele significantly differed between breast cancer patients and controls (CT vs. TT: OR: 1.462, CI 1.042-2.052, p=0.030; [CC + CT] vs. TT: OR: 1.536, CI 1.104-2.135, p=0.011). Due to significantly differences in the median age between controls and breast cancer patients (Table 1) we confirmed these data with a logistic regression using age as a covariate (p=0.005).

No significant differences in the allele frequencies and genotype distributions were found, when the breast cancer patients were compared with the controls for the other SNPs analyzed in this study.

Association between SNPs within different breast cancer subgroups

Next we examined the association between the distribution of genotypes and allelic frequencies of all analyzed SNPs and clinicopathological data including tumor localization, histological subtypes, tumor size, metastasis, grading, proliferation index, hormone receptor expression, Her2 expression, tumor marker level, menopausal status as well as body mass index at the time of diagnosis (Table 1).

Regarding the two OPG SNPs the most interesting result was the significant difference in genotype distribution and allelic frequency of OPG rs2073618 between invasive versus non invasive tumors. The homozygous major genotype GG (31.3% vs. 21.4%, p=0.006) as well as the major allele G (57.5% vs. 39.3%, OR 2.088 CI 1.189-3.663, p=0.011) were more frequent in patients with invasive tumors in contrast to non-invasive ones (Table 4).

Table 4 Association of allele and genotype frequencies within selected breast cancer subgroups

Another important difference was found with respect to the genotype distribution as well as the allelic frequency comparing the tumor localization (right breast vs. left breast) for the RANK SNP rs35211496. The homozygous minor allele T (25.2% vs. 15.3% OR 1.863 CI 1.236-2.808, p=0.003) and the minor allele genotype TT (7.3% vs. 1.7%, p=0.009) were more frequent in patients with tumor involvement of the right breast in contrast to the left side (Table 4).

The allelic frequencies (rs9533156: OR 1.543 CI 1.029-2.315, p=0.038; rs1054016: OR 1.630 CI 1.083-2.453, p=0.021) as well as the genotype distribution (rs9533156: p=0.032; rs1054016: p=0.018) of the RANKL SNPs rs9533156 and rs1054016 differed significantly between patients with a higher BMI (>/= 28) compared to patients with a lower BMI (< 28) at the first diagnosis. The minor allele C for SNP rs9533156 and T concerning the SNP rs1054016 were more frequent in patients with a BMI >/= 28 (rs9533156: 50.7%; rs1054016: 47.8%) compared to patients with a lower BMI (rs9533156: 40%, rs1054016: 36%; Table 4).

No significant differences in the allele frequencies and genotype distributions were found in the different subgroup analyses (including distant metastases) for the remaining analyzed SNPs (data not shown).


To the best of our knowledge, this is the first study showing a significant association between the SNP rs3102735 of the OPG gene and the susceptibility of breast cancer in Caucasian populations. For the SNP rs3102735 containing the minor allele C as well as for the homo- and heterozygous genotype with the minor allele C, we observed a 1.5-fold increased risk of breast cancer. All other SNPs were not associated with an increased risk for breast cancer. These results suggest a role for the OPG gene polymorphism in relation to breast cancer development.

Previous studies showed that genetic variants in the OPG locus have been associated with differences in bone mineral density (BMD; [2433], osteoporotic fractures [28, 34], bone turnover [31], bisphosphonate-induced osteonecrosis of the jaw [35], calcaneal quantitative ultrasound (velocity of sound) [36], ankylosing spondylitis development [37] and diabetic charcot neuroarthropathy [38].

In detail, concerning the rs3102735 SNP the G allele was more common among fracture patients [28, 34] and patients with lower BMD at the distal radius [30]. Furthermore, there is an association within a subgroup of postmenopausal patients carrying the minor allele and a lower calcaneal velocity of sound [36]. In an earlier study the variation (rs3102735) within the OPG gene showed a trend with higher frequency of the minor allele (p=0.076) and responding genotypes (p=0.097) in patients with psoriasis compared to controls without reaching significance [39].

Recently, several genome wide association studies or studies of specific candidate SNPs revealed additional loci to be associated with breast cancer including the same chromosomal region 8q24 as for the OPG gene [4049]. The majority of the association on chromosome 8q24 lies at approximately 128 Mb and is related to several tumor entities (prostate [50], colon [51]) in addition to breast cancer. Each locus within the 128 Mb bears epigenetic enhancer elements and forms chromatin loops with the myc proto-oncogene located several hundred kilobases telomeric [52]. A recent meta-analysis revealed an additional locus around 120 Mb on chromosome 8 associated with cancer development [53]. This region is close to the locus of OPG rs3102735 SNP (chromosome 8q24 119.965.070), which is associated with breast cancer in our study.

In this context we found a second genetic variation within the rs2073618 SNP of the OPG gene when stratifying our breast cancer patients into the subgroups of invasive or non-invasive tumors. However, the impact of the SNPs rs3102735 (5’ near promoter region) and rs2073618, located in the first exon, which encodes the signal peptide of OPG, are still unclear. Zhao et al. discussed that the change of the third amino acid from lysine (basic amino acid) to asparagine (uncharged polar amino acid) may have an influence of the OPG secretion from the cells. In their study they found that patients carrying the CC genotype had lower serum level of OPG [33]. In another study, a mutation in a basic amino acid (arginin) in the signal peptide of angiotensinogen drastically affected the secretory kinetics [54]. However, the exact mechanism that the SNP rs2073618 possibly affects the secretory characteristics of OPG needs to be elucidated by further functional studies. Genetic variation within the promoter region of OPG (rs3102735) could have an effect on the OPG gene expression and thus an influence on tumor development.

Further subgroup analyses according to clinical parameters showed an association with BMI (<28 or >/=28). In general, increased BMI is associated with the risk of some cancers and might differ between sexes and different ethnic populations such as breast cancer [55]. Combined studies revealed that the increase in breast cancer risk with increasing BMI among postmenopausal women is mostly depending on associated increase in bioavailable estradiol [56]. Here we show that the minor allele as well as the genotype of the minor allele of the RANKL SNPs rs9533156 and rs1054016 were strongly associated with a higher BMI (>/= 28) in the breast cancer group. Whether obese patients carrying the minor allele from one of the two RANKL SNPs have an additionally a higher risk of developing breast cancer remains open in this study due to the lack of BMI data from the control group.

Moreover, we confirmed an asymmetry of breast carcinoma to the left side (57% vs. 40%, Table 1) in accordance with several other studies, which revealed asymmetries in paired organs including breast [57, 58], the lungs [59], kidney [60] and testes [61]. Especially for the unsymmetric incidence of breast cancer in favour of the left side, several possible explanations are discussed, including the sleeping habit [62], handedness [63], the preference for breast feeding [64] or breast size [63]. We found that a genetic variation within the rs35211496 RANK SNP could have an influence on the tumor localization. Whether this polymorphism has a direct effect on the unsymmetric incidence or indirectly via the breast size can not be answered from this study.

The subgroup analyses stratified into metastatic disease at initial diagnosis showed no significant differences in genotype or allelic distribution. Only 10 of 292 patients were primarily diagnosed with bone metastases. Further studies focusing on skeletal metastases with respect to genetic background are required.

Other genetic variants at the RANK locus and/or functionally related genes, including RANKL have been associated with differences in bone mineral density [31], rheumatoid arthritis [65, 66], aortic calcification [67], age at menarche [68] or Paget′s disease of bone [69]. There is one recent study which showed a genetic variant near the 5′-end of RANK (rs7226991) associated with a breast cancer risk [70].


Our case-control study points to an association of the OPG SNP rs3102735 with an increased risk of developing breast cancer. These results could extend the constellation of possible breast cancer risk and might affect early diagnosis.

Future studies are needed, including confirmation of our observation in an independent validation set, to determine the relationship between OPG rs3102735 SNP and breast cancer risk in other ethnic groups. Whether this SNP leads to a functional alteration of OPG expression and consequently to an altered RANKL level remains to be shown.



bone mineral density


body mass index


carcinoembryonic antigen


confidence intervals


degree of freedom


estrogen receptor


fluorescence in situ hybridization


tumor grading


human epidermal growth factor receptor 2


distant metastases


nodal status




odds ratio


progesterone receptor


receptor activator of NF-κB


receptor activator of NF-κB ligand


single nucleotide polymorphism


tumor size


tumor necrosis factor.


  1. Coleman RE: Clinical features of metastatic bone disease and risk of skeletal morbidity. Clin Cancer Res. 2006, 12: 6243s-6249s. 10.1158/1078-0432.CCR-06-0931.

    Article  PubMed  Google Scholar 

  2. Wittrant Y, Theoleyre S, Chipoy C, Padrines M, Blanchard F, Heymann D, Redini F: RANKL/RANK/OPG: new therapeutic targets in bone tumours and associated osteolysis. Biochim Biophys Acta. 2004, 1704: 49-57.

    CAS  PubMed  Google Scholar 

  3. Bhatia P, Sanders MM, Hansen MF: Expression of receptor activator of nuclear factor-kappaB is inversely correlated with metastatic phenotype in breast carcinoma. Clin Cancer Res. 2005, 11: 162-165.

    CAS  PubMed  Google Scholar 

  4. Heider U, Langelotz C, Jakob C, Zavrski I, Fleissner C, Eucker J, Possinger K, Hofbauer LC, Sezer O: Expression of receptor activator of nuclear factor kappaB ligand on bone marrow plasma cells correlates with osteolytic bone disease in patients with multiple myeloma. Clin Cancer Res. 2003, 9: 1436-1440.

    CAS  PubMed  Google Scholar 

  5. Kong YY, Feige U, Sarosi I, Bolon B, Tafuri A, Morony S, Capparelli C, Li J, Elliott R, McCabe S, Wong T, Campagnuolo G, Moran E, Bogoch ER, Van G, Nguyen LT, Ohashi PS, Lacey DL, Fish E, Boyle WJ, Penninger JM: Activated T cells regulate bone loss and joint destruction in adjuvant arthritis through osteoprotegerin ligand. Nature. 1999, 402: 304-309. 10.1038/46303.

    Article  CAS  PubMed  Google Scholar 

  6. Lacey DL, Timms E, Tan HL, Kelley MJ, Dunstan CR, Burgess T, Elliott R, Colombero A, Elliott G, Scully S, Hsu H, Sullivan J, Hawkins N, Davy E, Capparelli C, Eli A, Qian YX, Kaufman S, Sarosi I, Shalhoub V, Senaldi G, Guo J, Delaney J, Boyle WJ: Osteoprotegerin ligand is a cytokine that regulates osteoclast differentiation and activation. Cell. 1998, 93: 165-176. 10.1016/S0092-8674(00)81569-X.

    Article  CAS  PubMed  Google Scholar 

  7. Anderson DM, Maraskovsky E, Billingsley WL, Dougall WC, Tometsko ME, Roux ER, Teepe MC, DuBose RF, Cosman D, Galibert L: A homologue of the TNF receptor and its ligand enhance T-cell growth and dendritic-cell function. Nature. 1997, 390: 175-179. 10.1038/36593.

    Article  CAS  PubMed  Google Scholar 

  8. Fata JE, Kong YY, Li J, Sasaki T, Irie-Sasaki J, Moorehead RA, Elliott R, Scully S, Voura EB, Lacey DL, Boyle WJ, Khokha R, Penninger JM: The osteoclast differentiation factor osteoprotegerin-ligand is essential for mammary gland development. Cell. 2000, 103: 41-50. 10.1016/S0092-8674(00)00103-3.

    Article  CAS  PubMed  Google Scholar 

  9. Hsu H, Lacey DL, Dunstan CR, Solovyev I, Colombero A, Timms E, Tan HL, Elliott G, Kelley MJ, Sarosi I, Wang L, Xia XZ, Elliott R, Chiu L, Black T, Scully S, Capparelli C, Morony S, Shimamoto G, Bass MB, Boyle WJ: Tumor necrosis factor receptor family member RANK mediates osteoclast differentiation and activation induced by osteoprotegerin ligand. Proc Natl Acad Sci U S A. 1999, 96: 3540-3545. 10.1073/pnas.96.7.3540.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Min JK, Kim YM, Kim YM, Kim EC, Gho YS, Kang IJ, Lee SY, Kong YY, Kwon YG: Vascular endothelial growth factor up-regulates expression of receptor activator of NF-kappa B (RANK) in endothelial cells. Concomitant increase of angiogenic responses to RANK ligand. J Biol Chem. 2003, 278: 39548-39557. 10.1074/jbc.M300539200.

    Article  CAS  PubMed  Google Scholar 

  11. Santini D, Perrone G, Roato I, Godio L, Pantano F, Grasso D, Russo A, Vincenzi B, Fratto ME, Sabbatini R, Della Pepa C, Porta C, Del Conte A, Schiavon G, Berruti A, Tomasino RM, Papotti M, Papapietro N, Onetti Muda A, Denaro V, Tonini G: Expression pattern of receptor activator of NFkappaB (RANK) in a series of primary solid tumors and related bone metastases. J Cell Physiol. 2011, 226: 780-784. 10.1002/jcp.22402.

    Article  CAS  PubMed  Google Scholar 

  12. Dougall WC, Glaccum M, Charrier K, Rohrbach K, Brasel K, De Smedt T, Daro E, Smith J, Tometsko ME, Maliszewski CR, Armstrong A, Shen V, Bain S, Cosman D, Anderson D, Morrissey PJ, Peschon JJ, Schuh J: RANK is essential for osteoclast and lymph node development. Genes Dev. 1999, 13: 2412-2424. 10.1101/gad.13.18.2412.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Kong YY, Yoshida H, Sarosi I, Tan HL, Timms E, Capparelli C, Morony S, Oliveira-dos-Santos AJ, Van G, Itie A, Khoo W, Wakeham A, Dunstan CR, Lacey DL, Mak TW, Boyle WJ, Penninger JM: OPGL is a key regulator of osteoclastogenesis, lymphocyte development and lymph-node organogenesis. Nature. 1999, 397: 315-323. 10.1038/16852.

    Article  CAS  PubMed  Google Scholar 

  14. Simonet WS, Lacey DL, Dunstan CR, Kelley M, Chang MS, Luthy R, Nguyen HQ, Wooden S, Bennett L, Boone T, Shimamoto G, DeRose M, Elliott R, Colombero A, Tan HL, Trail G, Sullivan J, Davy E, Bucay N, Renshaw-Gegg L, Hughes TM, Hill D, Pattison W, Campbell P, Sander S, Van G, Tarpley J, Derby P, Lee R, Boyle WJ: Osteoprotegerin: a novel secreted protein involved in the regulation of bone density. Cell. 1997, 89: 309-319. 10.1016/S0092-8674(00)80209-3.

    Article  CAS  PubMed  Google Scholar 

  15. Yasuda H, Shima N, Nakagawa N, Yamaguchi K, Kinosaki M, Mochizuki S, Tomoyasu A, Yano K, Goto M, Murakami A, Tsuda E, Morinaga T, Higashio K, Udagawa N, Takahashi N, Suda T: Osteoclast differentiation factor is a ligand for osteoprotegerin/osteoclastogenesis-inhibitory factor and is identical to TRANCE/RANKL. Proc Natl Acad Sci U S A. 1998, 95: 3597-3602. 10.1073/pnas.95.7.3597.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Bucay N, Sarosi I, Dunstan CR, Morony S, Tarpley J, Capparelli C, Scully S, Tan HL, Xu W, Lacey DL, Boyle WJ, Simonet WS: Osteoprotegerin-deficient mice develop early onset osteoporosis and arterial calcification. Genes Dev. 1998, 12: 1260-1268. 10.1101/gad.12.9.1260.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. McGonigle JS, Giachelli CM, Scatena M: Osteoprotegerin and RANKL differentially regulate angiogenesis and endothelial cell function. Angiogenesis. 2009, 12: 35-46. 10.1007/s10456-008-9127-z.

    Article  CAS  PubMed  Google Scholar 

  18. Fisher JL, Thomas-Mudge RJ, Elliott J, Hards DK, Sims NA, Slavin J, Martin TJ, Gillespie MT: Osteoprotegerin overexpression by breast cancer cells enhances orthotopic and osseous tumor growth and contrasts with that delivered therapeutically. Cancer Res. 2006, 66: 3620-3628. 10.1158/0008-5472.CAN-05-3119.

    Article  CAS  PubMed  Google Scholar 

  19. Gonzalez-Suarez E, Jacob AP, Jones J, Miller R, Roudier-Meyer MP, Erwert R, Pinkas J, Branstetter D, Dougall WC: RANK ligand mediates progestin-induced mammary epithelial proliferation and carcinogenesis. Nature. 2010, 468: 103-107. 10.1038/nature09495.

    Article  CAS  PubMed  Google Scholar 

  20. Schramek D, Leibbrandt A, Sigl V, Kenner L, Pospisilik JA, Lee HJ, Hanada R, Joshi PA, Aliprantis A, Glimcher L, Pasparakis M, Khokha R, Ormandy CJ, Widschwendter M, Schett G, Penninger JM: Osteoclast differentiation factor RANKL controls development of progestin-driven mammary cancer. Nature. 2010, 468: 98-102. 10.1038/nature09387.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Jones DH, Nakashima T, Sanchez OH, Kozieradzki I, Komarova SV, Sarosi I, Morony S, Rubin E, Sarao R, Hojilla CV, Komnenovic V, Kong YY, Schreiber M, Dixon SJ, Sims SM, Khokha R, Wada T, Penninger JM: Regulation of cancer cell migration and bone metastasis by RANKL. Nature. 2006, 440: 692-696. 10.1038/nature04524.

    Article  CAS  PubMed  Google Scholar 

  22. Eastell R, Christiansen C, Grauer A, Kutilek S, Libanati C, McClung MR, Reid IR, Resch H, Siris E, Uebelhart D, Wang A, Weryha G, Cummings SR: Effects of denosumab on bone turnover markers in postmenopausal osteoporosis. J Bone Miner Res. 2011, 26: 530-537. 10.1002/jbmr.251.

    Article  CAS  PubMed  Google Scholar 

  23. Stopeck AT, Lipton A, Body JJ, Steger GG, Tonkin K, de Boer RH, Lichinitser M, Fujiwara Y, Yardley DA, Viniegra M, Fan M, Jiang Q, Dansey R, Jun S, Braun A: Denosumab compared with zoledronic acid for the treatment of bone metastases in patients with advanced breast cancer: a randomized, double-blind study. J Clin Oncol. 2010, 28: 5132-5139. 10.1200/JCO.2010.29.7101.

    Article  CAS  PubMed  Google Scholar 

  24. Choi JY, Shin A, Park SK, Chung HW, Cho SI, Shin CS, Kim H, Lee KM, Lee KH, Kang C, Cho DY, Kang D: Genetic polymorphisms of OPG, RANK, and ESR1 and bone mineral density in Korean postmenopausal women. Calcif Tissue Int. 2005, 77: 152-159. 10.1007/s00223-004-0264-0.

    Article  CAS  PubMed  Google Scholar 

  25. Eun IS, Park WW, Suh KT, Kim JI, Lee JS: Association between osteoprotegerin gene polymorphism and bone mineral density in patients with adolescent idiopathic scoliosis. Eur Spine J. 2009, 18: 1936-1940. 10.1007/s00586-009-1145-z.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Hsu YH, Niu T, Terwedow HA, Xu X, Feng Y, Li Z, Brain JD, Rosen CJ, Laird N, Xu X: Variation in genes involved in the RANKL/RANK/OPG bone remodeling pathway are associated with bone mineral density at different skeletal sites in men. Hum Genet. 2006, 118: 568-577. 10.1007/s00439-005-0062-4.

    Article  CAS  PubMed  Google Scholar 

  27. Kim JG, Kim JH, Kim JY, Ku SY, Jee BC, Suh CS, Kim SH, Choi YM: Association between osteoprotegerin (OPG), receptor activator of nuclear factor-kappaB (RANK), and RANK ligand (RANKL) gene polymorphisms and circulating OPG, soluble RANKL levels, and bone mineral density in Korean postmenopausal women. Menopause. 2007, 14: 913-918. 10.1097/gme.0b013e31802d976f.

    Article  PubMed  Google Scholar 

  28. Langdahl BL, Carstens M, Stenkjaer L, Eriksen EF: Polymorphisms in the osteoprotegerin gene are associated with osteoporotic fractures. J Bone Miner Res. 2002, 17: 1245-1255. 10.1359/jbmr.2002.17.7.1245.

    Article  CAS  PubMed  Google Scholar 

  29. Mencej-Bedrac S, Prezelj J, Marc J: TNFRSF11B gene polymorphisms 1181 G > C and 245 T > G as well as haplotype CT influence bone mineral density in postmenopausal women. Maturitas. 2011, 69: 263-267. 10.1016/j.maturitas.2011.02.010.

    Article  CAS  PubMed  Google Scholar 

  30. Piedra M, Garcia-Unzueta MT, Berja A, Paule B, Lavin BA, Valero C, Riancho JA, Amado JA: Single nucleotide polymorphisms of the OPG/RANKL system genes in primary hyperparathyroidism and their relationship with bone mineral density. BMC Med Genet. 2011, 12: 168-10.1186/1471-2350-12-168.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Roshandel D, Holliday KL, Pye SR, Boonen S, Borghs H, Vanderschueren D, Huhtaniemi IT, Adams JE, Ward KA, Bartfai G, Casanueva F, Finn JD, Forti G, Giwercman A, Han TS, Kula K, Lean ME, Pendleton N, Punab M, Silman AJ, Wu FC, Thomson W, O'Neill TW: Genetic variation in the RANKL/RANK/OPG signaling pathway is associated with bone turnover and bone mineral density in men. J Bone Miner Res. 2010, 25: 1830-1838. 10.1002/jbmr.78.

    Article  CAS  PubMed  Google Scholar 

  32. Roshandel D, Holliday KL, Pye SR, Ward KA, Boonen S, Vanderschueren D, Borghs H, Huhtaniemi IT, Adams JE, Bartfai G, Casanueva FF, Finn JD, Forti G, Giwercman A, Han TS, Kula K, Lean ME, Pendleton N, Punab M, Silman AJ, Wu FC, Thomson W: TW ON: Influence of polymorphisms in the RANKL/RANK/OPG signaling pathway on volumetric bone mineral density and bone geometry at the forearm in men. Calcif Tissue Int. 2011, 89: 446-455. 10.1007/s00223-011-9532-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Zhao HY, Liu JM, Ning G, Zhao YJ, Zhang LZ, Sun LH, Xu MY, Uitterlinden AG, Chen JL: The influence of Lys3Asn polymorphism in the osteoprotegerin gene on bone mineral density in Chinese postmenopausal women. Osteoporos Int. 2005, 16: 1519-1524. 10.1007/s00198-005-1865-9.

    Article  CAS  PubMed  Google Scholar 

  34. Jorgensen HL, Kusk P, Madsen B, Fenger M, Lauritzen JB: Serum osteoprotegerin (OPG) and the A163G polymorphism in the OPG promoter region are related to peripheral measures of bone mass and fracture odds ratios. J Bone Miner Metab. 2004, 22: 132-138. 10.1007/s00774-003-0461-3.

    Article  CAS  PubMed  Google Scholar 

  35. Katz J, Gong Y, Salmasinia D, Hou W, Burkley B, Ferreira P, Casanova O, Langaee TY, Moreb JS: Genetic polymorphisms and other risk factors associated with bisphosphonate induced osteonecrosis of the jaw. Int J Oral Maxillofac Surg. 2011, 40: 605-611. 10.1016/j.ijom.2011.02.002.

    Article  CAS  PubMed  Google Scholar 

  36. Zajickova K, Zemanova A, Hill M, Zofkova I: Is A163G polymorphism in the osteoprotegerin gene associated with heel velocity of sound in postmenopausal women?. Physiol Res. 2008, 57 (Suppl 1): S153-157.

    CAS  PubMed  Google Scholar 

  37. Huang CH, Wei JC, Hung PS, Shiu LJ, Tsay MD, Wong RH, Lee HS: Osteoprotegerin genetic polymorphisms and age of symptom onset in ankylosing spondylitis. Rheumatology (Oxford). 2011, 50: 359-365. 10.1093/rheumatology/keq306.

    Article  CAS  Google Scholar 

  38. Pitocco D, Zelano G, Gioffre G, Di Stasio E, Zaccardi F, Martini F, Musella T, Scavone G, Galli M, Caputo S, Mancini L, Ghirlanda G: Association between osteoprotegerin G1181C and T245G polymorphisms and diabetic charcot neuroarthropathy: a case-control study. Diabetes Care. 2009, 32: 1694-1697. 10.2337/dc09-0243.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Assmann G, Pfoehler C, Simon P, Pfreundschuh M, Tilgen W, Wieczorek S: Genetic variations in the genes encoding receptor activator nuclear factor kappa B (RANK), receptor activator nuclear factor kappa B ligand (RANKL) and osteoprotegerin (OPG) in patients with psoriasis and psoriatic arthritis: a case-control study. J Dermatol. 2011, 38: 519-523. 10.1111/j.1346-8138.2010.01055.x.

    Article  CAS  PubMed  Google Scholar 

  40. Campa D, Kaaks R, Le Marchand L, Haiman CA, Travis RC, Berg CD, Buring JE, Chanock SJ, Diver WR, Dostal L, Fournier A, Hankinson SE, Henderson BE, Hoover RN, Isaacs C, Johansson M, Kolonel LN, Kraft P, Lee IM, McCarty CA, Overvad K, Panico S, Peeters PH, Riboli E, Sanchez MJ, Schumacher FR, Skeie G, Stram DO, Thun MJ, Trichopoulos D, et al: Interactions between genetic variants and breast cancer risk factors in the breast and prostate cancer cohort consortium. J Natl Cancer Inst. 2011, 103: 1252-1263. 10.1093/jnci/djr265.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Easton DF, Pooley KA, Dunning AM, Pharoah PD, Thompson D, Ballinger DG, Struewing JP, Morrison J, Field H, Luben R, Wareham N, Ahmed S, Healey CS, Bowman R, Meyer KB, Haiman CA, Kolonel LK, Henderson BE, Le Marchand L, Brennan P, Sangrajrang S, Gaborieau V, Odefrey F, Shen CY, Wu PE, Wang HC, Eccles D, Evans DG, Peto J, Fletcher O, et al: Genome-wide association study identifies novel breast cancer susceptibility loci. Nature. 2007, 447: 1087-1093. 10.1038/nature05887.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Fanale D, Amodeo V, Corsini LR, Rizzo S, Bazan V, Russo A: Breast cancer genome-wide association studies: there is strength in numbers. Oncogene. 2012, 31: 2121-2128. 10.1038/onc.2011.408.

    Article  CAS  PubMed  Google Scholar 

  43. He C, Chasman DI, Dreyfus J, Hwang SJ, Ruiter R, Sanna S, Buring JE, Fernandez-Rhodes L, Franceschini N, Hankinson SE, Hofman A, Lunetta KL, Palmieri G, Porcu E, Rivadeneira F, Rose LM, Splansky GL, Stolk L, Uitterlinden AG, Chanock SJ, Crisponi L, Demerath EW, Murabito JM, Ridker PM, Stricker BH, Hunter DJ: Reproductive aging associated common genetic variants and the risk of breast cancer. Breast Cancer Res. 2012, 14: R54-10.1186/bcr3155.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Hunter DJ, Kraft P, Jacobs KB, Cox DG, Yeager M, Hankinson SE, Wacholder S, Wang Z, Welch R, Hutchinson A, Wang J, Yu K, Chatterjee N, Orr N, Willett WC, Colditz GA, Ziegler RG, Berg CD, Buys SS, McCarty CA, Feigelson HS, Calle EE, Thun MJ, Hayes RB, Tucker M, Gerhard DS, Fraumeni JF, Hoover RN, Thomas G, Chanock SJ: A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer. Nat Genet. 2007, 39: 870-874. 10.1038/ng2075.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Long J, Cai Q, Sung H, Shi J, Zhang B, Choi JY, Wen W, Delahanty RJ, Lu W, Gao YT, Shen H, Park SK, Chen K, Shen CY, Ren Z, Haiman CA, Matsuo K, Kim MK, Khoo US, Iwasaki M, Zheng Y, Xiang YB, Gu K, Rothman N, Wang W, Hu Z, Liu Y, Yoo KY, Noh DY, Han BG, et al: Genome-wide association study in East asians identifies novel susceptibility Loci for breast cancer. PLoS Genet. 2012, 8: e1002532-10.1371/journal.pgen.1002532.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Sehrawat B, Sridharan M, Ghosh S, Robson P, Cass CE, Mackey JR, Greiner R, Damaraju S: Potential novel candidate polymorphisms identified in genome-wide association study for breast cancer susceptibility. Hum Genet. 2011, 130: 529-537. 10.1007/s00439-011-0973-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Stacey SN, Manolescu A, Sulem P, Rafnar T, Gudmundsson J, Gudjonsson SA, Masson G, Jakobsdottir M, Thorlacius S, Helgason A, Aben KK, Strobbe LJ, Albers-Akkers MT, Swinkels DW, Henderson BE, Kolonel LN, Le Marchand L, Millastre E, Andres R, Godino J, Garcia-Prats MD, Polo E, Tres A, Mouy M, Saemundsdottir J, Backman VM, Gudmundsson L, Kristjansson K, Bergthorsson JT, Kostic J, et al: Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor-positive breast cancer. Nat Genet. 2007, 39: 865-869. 10.1038/ng2064.

    Article  CAS  PubMed  Google Scholar 

  48. Teraoka SN, Bernstein JL, Reiner AS, Haile RW, Bernstein L, Lynch CF, Malone KE, Stovall M, Capanu M, Liang X, Smith SA, Mychaleckyj J, Hou X, Mellemkjaer L, Boice JD, Siniard A, Duggan D, Thomas DC: Single nucleotide polymorphisms associated with risk for contralateral breast cancer in the Women's Environment, Cancer, and Radiation Epidemiology (WECARE) Study. Breast Cancer Res. 2011, 13: R114-10.1186/bcr3057.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Vega A, Salas A, Milne RL, Carracedo B, Ribas G, Ruibal A, de Leon AC, Gonzalez-Hernandez A, Benitez J, Carracedo A: Evaluating new candidate SNPs as low penetrance risk factors in sporadic breast cancer: a two-stage Spanish case-control study. Gynecol Oncol. 2009, 112: 210-214. 10.1016/j.ygyno.2008.09.012.

    Article  CAS  PubMed  Google Scholar 

  50. Chu LW, Meyer TE, Li Q, Menashe I, Yu K, Rosenberg PS, Huang WY, Quraishi SM, Kaaks R, Weiss JM, Hayes RB, Chanock SJ, Hsing AW: Association between genetic variants in the 8q24 cancer risk regions and circulating levels of androgens and sex hormone-binding globulin. Cancer Epidemiol Biomarkers Prev. 2010, 19: 1848-1854. 10.1158/1055-9965.EPI-10-0101.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Zanke BW, Greenwood CM, Rangrej J, Kustra R, Tenesa A, Farrington SM, Prendergast J, Olschwang S, Chiang T, Crowdy E, Ferretti V, Laflamme P, Sundararajan S, Roumy S, Olivier JF, Robidoux F, Sladek R, Montpetit A, Campbell P, Bezieau S, O'Shea AM, Zogopoulos G, Cotterchio M, Newcomb P, McLaughlin J, Younghusband B, Green R, Green J, Porteous ME, Campbell H, et al: Genome-wide association scan identifies a colorectal cancer susceptibility locus on chromosome 8q24. Nat Genet. 2007, 39: 989-994. 10.1038/ng2089.

    Article  CAS  PubMed  Google Scholar 

  52. Ahmadiyeh N, Pomerantz MM, Grisanzio C, Herman P, Jia L, Almendro V, He HH, Brown M, Liu XS, Davis M, Caswell JL, Beckwith CA, Hills A, Macconaill L, Coetzee GA, Regan MM, Freedman ML: 8q24 prostate, breast, and colon cancer risk loci show tissue-specific long-range interaction with MYC. Proc Natl Acad Sci U S A. 2010, 107: 9742-9746. 10.1073/pnas.0910668107.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Brisbin AG, Asmann YW, Song H, Tsai YY, Aakre JA, Yang P, Jenkins RB, Pharoah P, Schumacher F, Conti DV, Duggan DJ, Jenkins M, Hopper J, Gallinger S, Newcomb P, Casey G, Sellers TA, Fridley BL: Meta-analysis of 8q24 for seven cancers reveals a locus between NOV and ENPP2 associated with cancer development. BMC Med Genet. 2011, 12: 156-10.1186/1471-2350-12-156.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Nakajima T, Cheng T, Rohrwasser A, Bloem LJ, Pratt JH, Inoue I, Lalouel JM: Functional analysis of a mutation occurring between the two in-frame AUG codons of human angiotensinogen. J Biol Chem. 1999, 274: 35749-35755. 10.1074/jbc.274.50.35749.

    Article  CAS  PubMed  Google Scholar 

  55. Renehan AG, Tyson M, Egger M, Heller RF, Zwahlen M: Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet. 2008, 371: 569-578. 10.1016/S0140-6736(08)60269-X.

    Article  PubMed  Google Scholar 

  56. Key TJ, Appleby PN, Reeves GK, Roddam A, Dorgan JF, Longcope C, Stanczyk FZ, Stephenson HE, Falk RT, Miller R, Schatzkin A, Allen DS, Fentiman IS, Key TJ, Wang DY, Dowsett M, Thomas HV, Hankinson SE, Toniolo P, Akhmedkhanov A, Koenig K, Shore RE, Zeleniuch-Jacquotte A, Berrino F, Muti P, Micheli A, Krogh V, Sieri S, Pala V, Venturelli E, et al: Body mass index, serum sex hormones, and breast cancer risk in postmenopausal women. J Natl Cancer Inst. 2003, 95: 1218-1226.

    Article  CAS  PubMed  Google Scholar 

  57. Perkins CI, Hotes J, Kohler BA, Howe HL: Association between breast cancer laterality and tumor location, United States, 1994-1998. Cancer Causes Control. 2004, 15: 637-645.

    Article  PubMed  Google Scholar 

  58. Roychoudhuri R, Putcha V, Moller H: Cancer and laterality: a study of the five major paired organs (UK). Cancer Causes Control. 2006, 17: 655-662. 10.1007/s10552-005-0615-9.

    Article  PubMed  Google Scholar 

  59. Parkash O: Lung cancer. A statistical study based on autopsy data from 1928 to 1972. Respiration. 1977, 34: 295-304. 10.1159/000193839.

    Article  CAS  PubMed  Google Scholar 

  60. Delahunt B, Bethwaite P, Nacey JN: Renal cell carcinoma in New Zealand: a national survival study. Urology. 1994, 43: 300-309. 10.1016/0090-4295(94)90070-1.

    Article  CAS  PubMed  Google Scholar 

  61. Stone JM, Cruickshank DG, Sandeman TF, Matthews JP: Laterality, maldescent, trauma and other clinical factors in the epidemiology of testis cancer in Victoria. Australia. Br J Cancer. 1991, 64: 132-138. 10.1038/bjc.1991.256.

    Article  CAS  PubMed  Google Scholar 

  62. Hallberg O, Johansson O: Sleep on the right side-Get cancer on the left?. Pathophysiology. 2010, 17: 157-160. 10.1016/j.pathophys.2009.07.001.

    Article  PubMed  Google Scholar 

  63. Hsieh CC, Trichopoulos D: Breast size, handedness and breast cancer risk. Eur J Cancer. 1991, 27: 131-135. 10.1016/0277-5379(91)90469-T.

    Article  CAS  PubMed  Google Scholar 

  64. Ing R, Petrakis NL, Ho JH: Unilateral breast-feeding and breast cancer. Lancet. 1977, 2: 124-127.

    Article  CAS  PubMed  Google Scholar 

  65. Assmann G, Koenig J, Pfreundschuh M, Epplen JT, Kekow J, Roemer K, Wieczorek S: Genetic variations in genes encoding RANK, RANKL, and OPG in rheumatoid arthritis: a case-control study. J Rheumatol. 2010, 37: 900-904. 10.3899/jrheum.091110.

    Article  CAS  PubMed  Google Scholar 

  66. Furuya T, Hakoda M, Ichikawa N, Higami K, Nanke Y, Yago T, Kamatani N, Kotake S: Associations between HLA-DRB1, RANK, RANKL, OPG, and IL-17 genotypes and disease severity phenotypes in Japanese patients with early rheumatoid arthritis. Clin Rheumatol. 2007, 26: 2137-2141. 10.1007/s10067-007-0745-4.

    Article  PubMed  Google Scholar 

  67. Rhee EJ, Yun EJ, Oh KW, Park SE, Park CY, Lee WY, Park SW, Kim SW, Baek KH, Kang MI: The relationship between Receptor Activator of Nuclear Factor-kappaB Ligand (RANKL) gene polymorphism and aortic calcification in Korean women. Endocr J. 2010, 57: 541-549. 10.1507/endocrj.K10E-015.

    Article  CAS  PubMed  Google Scholar 

  68. Pan R, Liu YZ, Deng HW, Dvornyk V: Association analyses suggest the effects of RANK and RANKL on age at menarche in Chinese women. Climacteric. 2012, 15: 75-81. 10.3109/13697137.2011.587556.

    Article  PubMed  Google Scholar 

  69. Chung PY, Beyens G, Riches PL, Van Wesenbeeck L, de Freitas F, Jennes K, Daroszewska A, Fransen E, Boonen S, Geusens P, Vanhoenacker F, Verbruggen L, Van Offel J, Goemaere S, Zmierczak HG, Westhovens R, Karperien M, Papapoulos S, Ralston SH, Devogelaer JP, Van Hul W: Genetic variation in the TNFRSF11A gene encoding RANK is associated with susceptibility to Paget's disease of bone. J Bone Miner Res. 2010, 25: 2592-2605. 10.1002/jbmr.162.

    Article  PubMed  Google Scholar 

  70. Bonifaci N, Palafox M, Pellegrini P, Osorio A, Benitez J, Peterlongo P, Manoukian S, Peissel B, Zaffaroni D, Roversi G, Barile M, Viel A, Mariette F, Bernard L, Radice P, Kaufman B, Laitman Y, Milgrom R, Friedman E, Saez ME, Climent F, Soler MT, Diez O, Balmana J, Lasa A, Ramon Y, Cajal T, Miramar MD, De la Hoya M, Perez-Segura P, Caldes T, et al: Evidence for a link between TNFRSF11A and risk of breast cancer. Breast Cancer Res Treat. 2011, 129: 947-954. 10.1007/s10549-011-1546-7.

    Article  CAS  PubMed  Google Scholar 

Pre-publication history

Download references


We thank Wilhelmine Daub for her technical assistance and Miriam Langhirt for her expert advice for the implementation of the genotyping assays. We also thank the Center of Pediatrics and Neonatology, University Medical School of Saarland, especially Dominik Monz, PhD, for providing of laboratory equipment and helpful discussions. We thank Sebastian Wieczorek for providing healthy controls.

This work was supported in part by research grants from Abbott (Wiesbaden, Germany) and research grants from the Universitiy of Saarland (Saarbruecken, Germany).

Author information

Authors and Affiliations


Corresponding author

Correspondence to Jasmin Teresa Ney.

Additional information

Competing interests

JT Ney holds a consultancy position at Novartis. EF Solomayer holds a consultancy position at Novartis and Amgen and received compensation from Novartis, Amgen and Roche. I Juhasz-Boess, F Gruenhage, S Graeber, RM Bohle, M Pfreundschuh and G Assmann declare that they have no competing interests.

Authors’ contributions

JTN designed and performed the research, collected the clinical data, analyzed data, performed statistical analyses and wrote the paper. IJB helped to design the research and to provide study material. FG provided study material and analyzed data. SG analyzed data and supervised the statistical analyses. RMB provided pathological data of tumor samples and participated in manuscript revision. MP participated in critical manuscript revision and data interpretation. EFS participated in the design of the study, provided study material and financial support for the study. GA designed the research, analyzed data, provided study material, helped to draft the manuscript and provided financial support for the study. All authors read and approved the final manuscript.

Electronic supplementary material


Additional file 1: Power analysis of the Χ 2 -tests for the allele frequency (2 x 2 contingency table, a, degree of freedom (DF) = 1) and the genotype distribution (2 x 3 contingency table, b, DF = 2) concerning the rs3102735 OPG SNP. Power was calculated by given effect size w, α (0.05) and total sample size (a: 1398; b: 699).(PDF 226 KB)

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Ney, J.T., Juhasz-Boess, I., Gruenhage, F. et al. Genetic polymorphism of the OPG gene associated with breast cancer. BMC Cancer 13, 40 (2013).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: