Skip to content

Advertisement

You're viewing the new version of our site. Please leave us feedback.

Learn more

BMC Cancer

Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

Genetic analysis of the vitamin D receptor gene in two epithelial cancers: melanoma and breast cancer case-control studies

  • Eva Barroso1,
  • Lara P Fernandez1,
  • Roger L Milne2,
  • Guillermo Pita3,
  • Elena Sendagorta4,
  • Uxua Floristan4,
  • Marta Feito4,
  • Jose A Aviles5,
  • Manuel Martin-Gonzalez6,
  • Jose I Arias7,
  • Pilar Zamora7,
  • Monserrat Blanco8,
  • Pablo Lazaro5,
  • Javier Benitez1, 3 and
  • Gloria Ribas1Email author
Contributed equally
BMC Cancer20088:385

https://doi.org/10.1186/1471-2407-8-385

Received: 16 October 2008

Accepted: 23 December 2008

Published: 23 December 2008

Abstract

Background

Vitamin D serum levels have been found to be related to sun exposure and diet, together with cell differentiation, growth control and consequently, cancer risk. Vitamin D receptor (VDR) genotypes may influence cancer risk; however, no epidemiological studies in sporadic breast cancer (BC) or malignant melanoma (MM) have been performed in a southern European population. In this study, the VDR gene has been evaluated in two epithelial cancers BC and MM.

Methods

We have conducted an analysis in 549 consecutive and non-related sporadic BC cases and 556 controls, all from the Spanish population, and 283 MM cases and 245 controls. Genotyping analyses were carried out on four putatively functional SNPs within the VDR gene.

Results

An association with the minor allele A of the non-synonymous SNP rs2228570 (rs10735810, FokI, Met1Thr) was observed for BC, with an estimated odds ratio (OR) of 1.26 (95% CI = 1.02–1.57; p = 0.036). The synonymous variant rs731236 (TaqI) appeared to be associated with protection from BC (OR = 0.80, 95%CI = 0.64–0.99; p = 0.047). No statistically significant associations with MM were observed for any SNP. Nevertheless, sub-group analyses revealed an association between rs2228570 (FokI) and absence of childhood sunburns (OR = 0.65, p = 0.003), between the 3'utr SNP rs739837 (BglI) and fair skin (OR = 1.31, p = 0.048), and between the promoter SNP rs4516035 and the more aggressive tumour location in head-neck and trunk (OR = 1.54, p = 0.020).

Conclusion

In summary, we observed associations between SNPs in the VDR gene and BC risk, and a comprehensive analysis using clinical and tumour characteristics as outcome variables has revealed potential associations with MM. These associations required confirmation in independent studies.

Background

The vitamin D metabolite 1α,25-dihydroxivitamin D3 (1,25D, also known as calcitriol) is the biologically active form of vitamin D3 [1]. The concentration of vitamin D3 in natural foods is quite low, and the majority of vitamin D3 in individuals is from cholesterol metabolites in the skin upon exposure to ultraviolet (UV) radiation. 1,25D modulates the expression of specific genes in a tissue-specific manner by binding to the nuclear vitamin D receptor (VDR) and to specific DNA vitamin D response elements. The receptor and ligand induce a program of gene expression that contributes to the maintenance of the quiescent, differentiated phenotype. They are therefore able to regulate cellular proliferation, apoptosis and differentiation in many cell types [2].

Recent epidemiological studies have shown an association between low serum 1,25D levels and increased risk of breast, colorectal and prostate cancers. Furthermore, several studies have reported a possible link between polymorphic variants in the vitamin D receptor gene and increased susceptibility for primary and metastatic breast cancer, squamous cell carcinoma, colorectal cancer and prostate cancer [36]. Although the functional significance of these polymorphic variants remains unknown, there is strong evidence suggesting that they may have functional consequences in epithelial carcinogenesis and tumour progression [7, 8]. VDR polymorphisms have been widely studied in Caucasian populations in relation to breast cancer (BC) [911] and malignant melanoma (MM) susceptibility [12, 13], each finding different effects for SNPs, depending on the population analyzed and environmental factors acting upon them.

It is of general interest to study the most characterised variants in VDR in southern European countries, where sun exposure is typically higher than in northern European countries (maximum UV Index during the summer months = 9 in Spain versus 6.5 in Netherlands) [14, 15] In this study, we investigated for the first time the role of polymorphisms in VDR in two epithelial cancers, sporadic BC and MM, in the Spanish population. Additionally, clinical and tumour phenotypic variables have been taken into account to better define the involvement of VDR in these pathologies.

Methods

Study Subjects, Data Collection and DNA Extraction

BC Study

The BC case-control study included a total of 549 consecutive and non-related sporadic BC cases and 556 control women. Cases were recruited from 1st January 2002 to 31st December 2006 from three Spanish public hospitals: 258 (47%) from Monte Naranco Hospital, in Oviedo; 155 (28%) from the Fundación Jiménez Díaz, and 136 (25%) from La Paz University Hospital, both in Madrid. Controls were unaffected Spanish women, recruited at three centres in Madrid: 455 (82%) from the Menopause Research Centre at the Instituto Palacios, 82 (15%) from the Fundación Jiménez Díaz, and 19 (3%) from the Madrid College of Lawyers. All cases and controls were women and controls were selected so that their age range was comparable to that of cases. We could not frequency match due to the larger numbers of cases.

Information about personal characteristics of cases and controls (age at diagnosis for cases or age at blood sample collection for controls, age at menarche, parity and menopausal status), and clinical and tumour characteristics for cases (metastasis at diagnosis, tumour grade, type and size, nodal involvement, and immunohistochemical markers), was either collected by the treating physician or extracted by review of medical records. This information is summarised in Additional file 1.

MM Study

The MM case-control study was based on 283 consecutive and non-related sporadic MM cases that were recruited from 1st September 2004 to 15th March 2008, at the Departments of Dermatology of three hospitals in Madrid: 147 (52%) from Gregorio Marañón General University Hospital, 54 (19%) from La Paz University Hospital and 82 (29%) from Ramón y Cajal University Hospital. A total of 245 cancer-free controls, frequency matched to cases by sex and age in ten-year categories, were recruited from the Madrid College of Lawyers (218 participants, 89%) and from Gregorio Marañón General University Hospital (27 participants, 11%).

A standardised questionnaire was used to collect information on pigmentation characteristics (eye colour, hair colour, skin colour, number of nevi, presence of solar lentigines), the presence of childhood sunburns, Fitzpatrick's classification of skin type, tumour location, Breslow index (deep index), and personal and family history of cancer, as described previously [16, 17] (see Additional file 2). Fitzpatrick's classification of skin type was assessed for cases only, by review of medical records.

All participants in both studies were Caucasian and of Spanish origin. All subjects gave informed consent and the BC and MM studies were approved by the Ethics Committees of La Paz University Hospital and Gregorio Marañón General University Hospital, respectively.

Genomic DNA from cases and controls was extracted using the MagNA Pure LC Instrument according to the manufacturer's protocol as previously described [16, 18, 19].

SNP selection

Three public databases were used to collect information about SNPs in VDR: NCBI http://www.ncbi.nlm.nih.gov, Ensembl http://www.ensembl.org, and HapMap http://www.hapmap.org. Four SNPs were considered for inclusion because they have been widely analysed in previous epidemiological studies. All had minor allele frequency (MAF) greater than or equal to 10%. Two are located on exons, one is in the putative promoter region and the other in the 3'utr region. The two coding SNPs selected have been reported to be associated with breast cancer, in previous studies [11, 20, 21].

Genotyping assays

Genotyping was carried out using the TaqMan platform following the manufacturer's instructions. SNPs assays were designed using Applied Biosystems Assay-by-Design and Assay-on-Demand probes (Applied Biosystems, Foster City, CA, USA) (provided upon request). The genotype of each sample was automatically determined by measuring final allele-specific fluorescence in the ABI Prism 7900HT Detection System, using the SDS 2.1 software for allele discrimination (Applied Biosystems, Foster city, USA).

As a quality control measure, we included at least 2 sample duplicates and 1 non-template sample per 96-well plate. Genotypes were scored by two different personnel in the laboratory. We obtained a concordance rate of 100% for all four SNPs studied.

Statistical Analysis

For all polymorphisms studied, Fisher's exact test was used both to test for deviations from Hardy-Weinberg equilibrium (HWE) among controls and to compare differences in the MAF distributions between cases and controls.

In order to assess associations between genotypes, haplotypes and cancer risk, several analyses were performed. Genotype-related odds ratios (ORs), their corresponding 95% confidence intervals (CIs) and associated p-values were estimated via unconditional logistic regression. This was done for each of heterozygotes and minor-allele homozygotes relative to common-allele homozygotes, as well as under an additive model, in the latter case estimating an effect per copy of the minor allele carried. Known or suspected risk factors for BC (age, number of live births, age at menarche, and menopause status) and MM (eye colour, hair colour, skin colour, number of nevi, lentigines, and childhood sunburns) were evaluated for potential confounding effects by including them in multivariate analyses.

Associations between VDR polymorphisms genotyped and various individual, clinical and tumour characteristics were assessed via logistic regression in order to determine their potential modifying effects on BC and MM risk. This was done for cases and controls pooled for each variable. Eye colour (blue/green versus brown), hair colour (blond/red versus brown/black), skin colour (fair versus brown), number of nevi (= 50 versus < 50), presence of lentigines (yes versus no) and childhood sunburn (yes versus no) were used as the outcome variables for MM.

Among BC cases only, the presence of metastastic disease at diagnosis (yes versus no), tumour histology (invasive versus in situ), tumour grade (grade > 1 versus grade 1), tumour size (> 2 cm versus = 2 cm), nodal involvement (yes versus no), estrogen receptor status (positive versus negative) and progesterone receptor status (positive versus negative), were used in the analysis. For MM cases-only analyses, the prior diagnosis of MM (yes versus no), phototype (I/II versus III/IV), tumour location (head/neck/trunk versus extremities) and tumour depth (T2/T3/T4 versus T0/T1) were considered as the outcome variables.

SPSS v11.0 was used to carry out these analyses. All p-values were two-sided and those less than 0.05 were considered statistically significant

Results and Discussion

Associations of VDRrs731276 and rs2228570 polymorphisms with cancer risk

Allelic frequencies for each SNP and the p-value for their comparison between cases and controls are presented in Table 1. We found no evidence of departure from Hardy-Weinberg equilibrium for any of the four SNPs genotyped (all p-values > 0.05). Results from univariate and multivariate genotype analysis are shown in Table 2.
Table 1

Allelic frequencies comparison between cases and controls in the four SNPs tested, in both BC and MM pathologies

    

BREAST CANCER

MELANOMA

HapMap

 

Other names

SNP

Nucleotide

Cases (N = 549)

Controls (N = 556)

 

Cases (N = 283)

Controls (N = 245)

 

Caucasian

SNP ID

 

Location

Change*

MAF

MAF

p-value++

MAF

MAF

p-value++

MAF

rs4516035

 

5' upstrem

T > C

0.41

0.39

0.27

0.44

0.40

0.28

0.45

rs2228570

FokI. rs10735810

Met1Thr

G > A

0.37

0.34

0.08

0.31

0.33

0.33

0.44

rs731236

TaqI

Ile352

T > C

0.38

0.43

0.028

0.41

0.39

0.50

0.44

rs739837

BglI

3' utr

T > G

0.46

0.46

0.90

0.47

0.50

0.74

0.43

MAF, Minor Allele Frequency.

Statistically significant results (p < 0.05) indicated in bold.

* Correspondence of nomenclature of SNP alleles are as following: the FokI alleles G and A correspond to F and f, respectively; the TaqI alleles T and C

correspond to T and t, respectively; and BglI alleles T and G correspond to B and b, respectively.

++p-value, difference of MAF between cases and controls.

Table 2

Genotype frequencies comparison between cases and controls in the four SNPs tested, in both BC and MM pathologies

   

BREAST CANCER

MELANOMA

 

Statistical

Genotype

non-adjusted

adjusted

non-adjusted

adjusted

SNP ID

model

alleles

OR* (95% CI)

p-value

OR* (95% CI)

p-value

OR* (95% CI)

p-value

OR* (95% CI)

p-value

rs4516035

Codominant

CT

1.20 (0.92–1.56)

0.19

1.15 (0.83–1.58)

0.40

1.08 (0.73–1.60)

0.69

1.17 (0.70–1.96)

0.54

  

CC

1.16 (0.82–1.65)

0.41

0.97 (0.63–1.49)

0.88

1.51 (0.90–2.53)

0.12

1.79 (0.91–3.53)

0.09

 

Per minor allele

C-

1.09 (0.92–1.29)

0.30

1.01 (0.82–1.25)

0.91

1.20 (0.94–1.55)

0.15

1.31 (0.94–1.81)

0.11

rs2228570

Codominant

GA

1.14 (0.88–1.47)

0.32

1.26 (0.89–1.66)

0.22

1.09 (0.75–1.57)

0.66

1.23 (0.76–2.01)

0.40

  

AA

1.41 (0.96–2.08)

0.08

1.65 (1.02–2.65)

0.041

0.69 (0.38–1.25)

0.22

1.23 (0.55–2.73)

0.61

 

Per minor allele

A-

1.17 (0.98–1.40)

0.08

1.26 (1.02–1.57)

0.036

0.91 (0.70–1.19)

0.49

1.15 (0.81–1.64)

0.43

rs731236

Codominant

CT

0.84 (0.64–1.09)

0.19

0.82 (0.59–1.13)

0.22

1.26 (0.85–1.87)

0.25

1.06 (0.63–1.78)

0.81

  

CC

0.70 (0.50–0.98)

0.040

0.72 (0.48–1.09)

0.13

1.09 (0.64–1.84)

0.76

1.17 (0.57–2.39)

0.66

 

Per minor allele

C-

0.84 (0.71–0.99)

0.034

0.85 (0.69–1.03)

0.10

1.08 (0.84–1.40)

0.55

1.08 (0.77–1.52)

0.66

rs739837

Codominant

TG

0.96 (0.72–1.27)

0.76

0.96 (0.69–1.35)

0.83

0.89 (0.59–1.36)

0.60

0.64 (0.36–1.13)

0.12

  

GG

1.03 (0.74–1.44)

0.86

1.30 (0.87–1.96)

0.20

0.82 (0.50–1.36)

0.45

0.69 (0.35–1.38)

0.29

 

Per minor allele

G-

1.01 (0.86–1.20)

0.87

1.13 (0.92–1.38)

0.25

0.91 (0.71–1.17)

0.45

0.83 (0.59–1.16)

0.28

*OR: Odds Ratio estimated under codominant and log-additive models; CI: Confidence Interval.

Adjusted for age at diagnosis, number of live births, age at menarche and menopause status.

Adjusted for eye colour, hair colour, skin colour, number of nevi, lentigines, and childhood sunburn.

Statistically significant results (p < 0.05) indicated in bold.

We observed evidence of differences in minor allele frequency (MAF) between BC cases and controls for the synonymous change rs731236 (TaqI) (p = 0.028). The estimated OR per minor allele (C) in this SNP was 0.84 (95%CI 0.71–0.99, p = 0.034). This per-allele OR estimate was not substantially different in the multivariate analysis adjusting for age, number of live births, age at menarche, and menopause status (OR per allele = 0.85, 95% CI 0.69–1.03, p = 0.102). Regarding the SNP rs2228570 (FokI) (Met1Thr, formerly known as rs10735810), weak evidence of differences in MAF between BC cases and controls was observed (p = 0.080). The estimated OR per minor allele in this SNP was 1.17 (95%CI 0.98–1.40, p = 0.081), whereas the per-allele OR estimated in the multivariate analysis adjusting for potential confounding factors was higher, and statistically significant (OR per allele = 1.26, 95%CI 1.02–1.57, p = 0.036).

In general, previous studies have found no evidence of association with BC for rs731236 (TaqI) and rs2228570 (FokI) [9, 11, 2227]. All of these studies had limited statistical power to detect a moderate association. Population stratification may be another explanation for the lack of consistency in results. However, two studies with marginal statistically significant results for rs731236 (TaqI) reported contradictory results [11, 24], whereas studies using larger sample sizes from Caucasian populations have shown risk effect of rs2228570 (FokI) consistent with that detected in the present study [20, 21]. An association with rs2228570 (FokI) was observed after adjustment for established risk factors including those used in the present study. This difference may be due to the tight relationship between VDR protein function and the hormonal aspect of BC aetiology such as menarche, parity and menopause [28, 29].

In the case of MM, we did not observe any evidence of association with rs731236 (TaqI) (OR per allele = 1.08, 95%CI = 0.84–1.40, p = 0.55) or rs2228570 (FokI) (OR per allele = 0.91 95%CI = 0.70–1.19, p = 0.49). These results are consistent with the findings of smaller sample size studies [13, 30, 31] although other studies reported a protective tendency of rs731236 (TaqI) [12, 32]. Only two studies reported an association of rs2228570 (FokI) and MM risk in North-European populations, one of them being a larger sample size study [12, 32].

The rs731236 (TaqI) SNP is in linkage disequilibrium with other polymorphisms in the 3' extreme of the gene in Caucasian populations. Functional studies of these polymorphisms have evaluated their putative implication in the regulation of transcription, translation or RNA processing, but no consistent results were obtained [33]. However, functional studies of rs2228570 (FokI) have suggested a loss of the reported VDR benefits induced by the minor allele, due to its location in the first codon of the protein (Met1Thr). That is, the minor A allele appears to be associated with the use of an alternate start codon, which triggers a longer and less potent transcriptional activator protein form [7], which is consistent with it being associated with increased risk of BC. We did not observe evidence of association for any other SNP in BC or MM.

Associations of VDRpolymorphisms with personal, clinical and tumoral characteristics

We assessed whether VDR SNPs were associated with various clinical and phenotypic characteristics using cases and controls combined. We tested for associations with tumour characteristics among cases only for each disease. Results are summarised in Table 3. The rare allele in the non-synonymous SNP rs2228570 (TaqI) appeared to be strongly associated with the absence of childhood sunburns (OR per allele = 0.65, 95% CI 0.49–0.86, p = 0.003), and this was maintained among controls only (OR per allele = 0.63). There was also weak evidence that it is associated with a prior diagnosis of MM in MM patients (p = 0.060). We also observed marginally significant associations for the 3'utr SNP rs739837 (BglI) with fair skin colour (p = 0.048) and with Fitzpatrick's phototype I/II (0.070). Finally, the VDR promoter SNP rs4516035 was associated with tumours located in the head-neck or trunk (p = 0.020). No other associations were observed for BC or MM. Although we did not detect a significant effect of VDR SNPs directly on MM, the associations identified with MM phenotypic characteristics suggest that VDR SNPs may modulate MM susceptibility.
Table 3

Personal, clinical and tumoral phenotypic characteristics comparison from both BC and MM pathologies in the four SNPs tested

Tumour

 

rs4516035

 

rs2228570

 

rs731236

 

rs739837

 

Type

Characteristic

OR* (95% CI)

p-value

OR* (95% CI)

p-value

OR* (95% CI)

p-value

OR* (95% CI)

p-value

BREAST CANCER

 

Metastasis

0.53 (0.25–1.11)

0.09

1.00 (0.51–1.96)

0.99

1.20 (0.63–2.27)

0.58

1.11 (0.57–2.17)

0.75

 

Tumor histology (Invasive)

0.87 (0.57–1.32)

0.51

0.83 (0.54–1.28)

0.40

1.10 (0.72–1.69)

0.66

0.75 (0.49–1.15)

0.19

 

Tumor grade (Grade > 1)

0.93 (0.67–1.30)

0.68

1.19 (0.84–1.68)

0.33

1.22 (0.87–1.70)

0.26

0.76 (0.54–1.05)

0.09

 

Tumor size (> 2 cm)

1.02 (0.77–1.35)

0.92

0.98 (0.73–1.30)

0.88

1.14 (0.86–1.51)

0.37

0.81 (0.61–1.08)

0.15

 

Nodal involvement

0.93 (0.70–1.23)

0.61

0.95 (0.71–1.27)

0.72

0.94 (0.71–1.25)

0.69

1.09 (0.82–1.45)

0.54

 

ER positive

0.96 (0.66–1.41)

0.85

1.24 (0.84–1.84)

0.28

1.31 (0.90–1.90)

0.16

1.02 (0.71–1.46)

0.91

 

PR positive

0.92 (0.67–1.26)

0.60

1.12 (0.80–1.55)

0.51

0.91 (0.67–1.24)

0.56

1.12 (0.83–1.51)

0.48

MELANOMA

 

Light Eye Colour+

1.03 (0.79–1.34)

0.82

0.91 (0.69–1.21)

0.52

0.92 (0.70–1.21)

0.56

1.06 (0.81–1.39)

0.64

 

Blond/Red Hair Colour+

0.99 (0.71–1.40)

0.99

0.78 (0.55–1.13)

0.19

1.02 (0.73–1.44)

0.89

1.45 (0.89–1.74)

0.20

 

Fair Skin Colour+

0.97 (0.75–1.26)

0.83

1.08 (0.82–1.42)

0.57

0.86 (0.66–1.12)

0.25

1.31 (1.00–1.70)

0.048

 

N° of Nevi = 50+

0.97 (0.66–1.40)

0.85

1.00 (0.67–1.49)

0.99

1.06 (0.72–1.54)

0.77

1.34 (0.90–1.97)

0.15

 

Presence of Lentigines+

1.03 (0.79–1.34)

0.84

0.79 (0.59–1.05)

0.11

1.20 (0.91–1.58)

0.21

0.90 (0.69–1.18)

0.45

 

Presence of Childhood Sunburns+

1.12 (0.87–1.45)

0.39

0.65 (0.49–0.86)

0.003

1.10 (0.84–1.43)

0.49

0.91 (0.70–1.19)

0.50

 

Other MM

1.26 (0.52–3.03)

0.61

2.43 (0.95–6.19)

0.060

1.83 (0.73–4.56)

0.19

0.70 (0.26–1.85)

0.47

 

Fitzpatrick's photoype I/II

0.74 (0.51–1.09)

0.13

0.85 (0.63–1.46)

0.89

0.91 (0.62–1.34)

0.63

1.43 (0.97–2.12)

0.070

 

Tumor Location (Head/Neck/Trunk)

1.54 (1.08–2.20)

0.020

1.16 (0.79–1.72)

0.45

1.16 (0.81–1.65)

0.42

1.17 (0.82–1.67)

0.38

 

Breslow Index (T2/T3/T4)

1.04 (0.72–1.51)

0.82

1.20 (0.80–1.79)

0.38

0.84 (0.57–1.24)

0.38

1.01 (0.69–1.47)

0.96

*OR: Odds Ratio per minor allele; CI: Confidence Interval, unadjusted p-values.

+Cases and controls pooled for each variable.

Cases only considered.

Statistically significant results (p < 0.05) indicated in bold.

Further considerations

The strength of our study is the ability to control for the many established risk factors for BC and MM, although we recognize that there was potential for misclassification of phenotypic characteristics due to the subjective nature of the phenotypic attributes considered. Controls participated on a volunteer basis which may have introduced some selection bias. However, the fact that they were frequency matched to cases on age and sex for melanoma and that breast cancer controls were selected so that their age range was comparable to that of cases and that the variable of primary interest was genetic would have kept such bias to a minimum. It should be noted that, the sample size of both studies was relatively limited and so associations can not be ruled out for rs731236 (TaqI), and rs2228570 (FokI), particularly in MM. The association of rs731236 (TaqI) and BC, was not statistically significant under a multivariate model. However, the estimated relative risk did not change substantially, indicating that the increase in p-value was due to the reduced sample size (with available covariate data), rather than due to confounding. Finally, conclusions are based on nominal p-values at 5% statistical significance and therefore require replication in independent studies.

Conclusion

BC and MM tumour pathologies may be influenced by the effect of variation in vitamin D intake through diet and sun exposure, together with VDR polymorphisms. Therefore, in a sunny region such as Spain, the effect of VDR polymorphisms on cancer risk may be more apparent than in other Caucasian populations. The results obtained in this study add to the evidence for a role of VDR as an important mediator in the development of cancer. We found evidence of association with BC for the non-synonymous variant rs2228570 (FokI), and for the synonymous SNP rs731236 (TaqI). These findings require replication in large samples and the role of these variants needs to be clarified by functional studies. We have also reported several associations among VDR SNPs and phenotypic risk factors that influence MM susceptibility, indicating their potential effect in disease development. The characterization of these and other polymorphisms in the VDR gene may help to better understand the aetiology and development of cancer, and to define risk groups to better target prevention strategies.

Notes

Abbreviations

VDR: 

Vitamin D receptor

BC: 

Breast cancer

MM: 

Malignant melanoma

SNP: 

Single nucleotide polymorphism

OR: 

Odds ratio

UV: 

Ultraviolet

DNA: 

Deoxyribonucleic acid

MAF: 

Minor alelle frequency

HWE: 

Hardy-Weinberg equilibrium

CIs: 

Confidence Intervals

Declarations

Acknowledgements

This study was supported by grants BFI2003-03852 and SAF2007-65542-C02-01 from the Ministerio de Educación y Ciencia (MEC) and Fundación Mútua Madrileña, Spain (GR). EB is funded by the Comunidad Autónoma de Madrid and LPF is funded by the Ministerio de Sanidad y Consumo under a grant form the Fondo de Investigación Sanitaria FI05/00918. We would like to thank Álvaro Ruibal (University Hospital, Santiago de Compostela), and Santiago Palacios (Instituto Palacios, Madrid), Mariano Casado, Angel Pizarro and Matias Mayor (Hospital La Paz), Angeles de la Riva Grandal (Hospital Ramón y Cajal) and staff at the Hospital Gregorio Marañon and Madrid College of Lawyers for the access to samples of cases and controls. We would also like to thank Fátima Mercadillo, Alicia Barroso, Victoria Fernández and Rocío Letón for their expert technical skills.

Authors’ Affiliations

(1)
Human Genetics Group; Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO)
(2)
Genetic and Molecular Epidemiology Group; Human Cancer Genetics Program, CNIO
(3)
National Genotyping Centre (CeGen), Human Cancer Genetics Program, CNIO
(4)
Department of Dermatology, La Paz Hospital
(5)
Department of Dermatology, Gregorio Marañon Hospital
(6)
Department of Dermatology, Ramon y Cajal Hospital
(7)
Service of Surgery, Monte Naranco
(8)
Department of Oncology, La Paz Hospital

References

  1. Trang HM, Cole DE, Rubin LA, Pierratos A, Siu S, Vieth R: Evidence that vitamin D3 increases serum 25-hydroxyvitamin D more efficiently than does vitamin D2. Am J Clin Nutr. 1998, 68 (4): 854-858.PubMedGoogle Scholar
  2. Jurutka PW, Whitfield GK, Hsieh JC, Thompson PD, Haussler CA, Haussler MR: Molecular nature of the vitamin D receptor and its role in regulation of gene expression. Rev Endocr Metab Disord. 2001, 2 (2): 203-216. 10.1023/A:1010062929140.View ArticlePubMedGoogle Scholar
  3. Deeb KK, Trump DL, Johnson CS: Vitamin D signalling pathways in cancer: potential for anticancer therapeutics. Nat Rev Cancer. 2007, 7 (9): 684-700. 10.1038/nrc2196.View ArticlePubMedGoogle Scholar
  4. Bikle DD, Oda Y, Xie Z: Vitamin D and skin cancer: a problem in gene regulation. J Steroid Biochem Mol Biol. 2005, 97 (1–2): 83-91. 10.1016/j.jsbmb.2005.06.001.View ArticlePubMedGoogle Scholar
  5. Cui Y, Rohan TE: Vitamin D, calcium, and breast cancer risk: a review. Cancer Epidemiol Biomarkers Prev. 2006, 15 (8): 1427-1437. 10.1158/1055-9965.EPI-06-0075.View ArticlePubMedGoogle Scholar
  6. Guy M, Lowe LC, Bretherton-Watt D, Mansi JL, Peckitt C, Bliss J, Wilson RG, Thomas V, Colston KW: Vitamin D receptor gene polymorphisms and breast cancer risk. Clin Cancer Res. 2004, 10 (16): 5472-5481. 10.1158/1078-0432.CCR-04-0206.View ArticlePubMedGoogle Scholar
  7. Arai H, Miyamoto K, Taketani Y, Yamamoto H, Iemori Y, Morita K, Tonai T, Nishisho T, Mori S, Takeda E: A vitamin D receptor gene polymorphism in the translation initiation codon: effect on protein activity and relation to bone mineral density in Japanese women. J Bone Miner Res. 1997, 12 (6): 915-921. 10.1359/jbmr.1997.12.6.915.View ArticlePubMedGoogle Scholar
  8. Colin EM, Weel AE, Uitterlinden AG, Buurman CJ, Birkenhager JC, Pols HA, van Leeuwen JP: Consequences of vitamin D receptor gene polymorphisms for growth inhibition of cultured human peripheral blood mononuclear cells by 1, 25-dihydroxyvitamin D3. Clin Endocrinol (Oxf). 2000, 52 (2): 211-216. 10.1046/j.1365-2265.2000.00909.x.View ArticleGoogle Scholar
  9. McCullough ML, Stevens VL, Diver WR, Feigelson HS, Rodriguez C, Bostick RM, Thun MJ, Calle EE: Vitamin D pathway gene polymorphisms, diet, and risk of postmenopausal breast cancer: a nested case-control study. Breast Cancer Res. 2007, 9 (1): R9-10.1186/bcr1642.View ArticlePubMedPubMed CentralGoogle Scholar
  10. Trabert B, Malone KE, Daling JR, Doody DR, Bernstein L, Ursin G, Marchbanks PA, Strom BL, Humphrey MC, Ostrander EA: Vitamin D receptor polymorphisms and breast cancer risk in a large population-based case-control study of Caucasian and African-American women. Breast Cancer Res. 2007, 9 (6): R84-10.1186/bcr1833.View ArticlePubMedPubMed CentralGoogle Scholar
  11. Abbas S, Nieters A, Linseisen J, Slanger T, Kropp S, Mutschelknauss EJ, Flesch-Janys D, Chang-Claude J: Vitamin D receptor gene polymorphisms and haplotypes and postmenopausal breast cancer risk. Breast Cancer Res. 2008, 10 (2): R31-10.1186/bcr1994.View ArticlePubMedPubMed CentralGoogle Scholar
  12. Hutchinson PE, Osborne JE, Lear JT, Smith AG, Bowers PW, Morris PN, Jones PW, York C, Strange RC, Fryer AA: Vitamin D receptor polymorphisms are associated with altered prognosis in patients with malignant melanoma. Clin Cancer Res. 2000, 6 (2): 498-504.PubMedGoogle Scholar
  13. Santonocito C, Capizzi R, Concolino P, Lavieri MM, Paradisi A, Gentileschi S, Torti E, Rutella S, Rocchetti S, Di Carlo A, et al: Association between cutaneous melanoma, Breslow thickness and vitamin D receptor BsmI polymorphism. Br J Dermatol. 2007, 156 (2): 277-282. 10.1111/j.1365-2133.2006.07620.x.View ArticlePubMedGoogle Scholar
  14. Den Outer PN, Slaper H, Tax RB: UV radiation in the Netherlands: Assessing long-term variability and trends in relation to ozone and vlouds. Journal of geophysical research. 2005, 110: D02203-10.1029/2004JD004824. 02201-02211View ArticleGoogle Scholar
  15. Marin MJ, Sola Y, Tena F, Utrillas MP, Campmany E, de Cabo X, Lorente J, Martinez-Lozano JA: The UV index on the Spanish Mediterranean coast. Photochemistry and photobiology. 81 (3): 659-665. 10.1562/2004-11-25-RA-380.1.Google Scholar
  16. Fernandez L, Milne R, Bravo J, Lopez J, Aviles J, Longo M, Benitez J, Lazaro P, Ribas G: MC1R: three novel variants identified in a malignant melanoma association study in the Spanish population. Carcinogenesis. 2007, 28 (8): 1659-1664. 10.1093/carcin/bgm084.View ArticlePubMedGoogle Scholar
  17. Fernandez LP, Milne RL, Pita G, Aviles JA, Lazaro P, Benitez J, Ribas G: SLC45A2: a novel malignant melanoma-associated gene. Hum Mutat. 2008, 29 (9): 1161-1167. 10.1002/humu.20804.View ArticlePubMedGoogle Scholar
  18. Kessler HH, Muhlbauer G, Stelzl E, Daghofer E, Santner BI, Marth E: Fully automated nucleic acid extraction: MagNA Pure LC. Clin Chem. 2001, 47 (6): 1124-1126.PubMedGoogle Scholar
  19. Barroso E, Milne RL, Fernandez LP, Zamora P, Arias JI, Benitez J, Ribas G: FANCD2 associated with sporadic breast cancer risk. Carcinogenesis. 2006, 27 (9): 1930-1937. 10.1093/carcin/bgl062.View ArticlePubMedGoogle Scholar
  20. Chen WY, Bertone-Johnson ER, Hunter DJ, Willett WC, Hankinson SE: Associations between polymorphisms in the vitamin D receptor and breast cancer risk. Cancer Epidemiol Biomarkers Prev. 2005, 14 (10): 2335-2339. 10.1158/1055-9965.EPI-05-0283.View ArticlePubMedGoogle Scholar
  21. Gapska P, Scott RJ, Serrano-Fernandez P, Huzarski T, Byrski T, Kladny J, Gronwald J, Gorski B, Cybulski C, Lubinski J, et al: Vitamin D receptor variants and breast cancer risk in the Polish population. Breast Cancer Res Treat. 2008Google Scholar
  22. Hou MF, Tien YC, Lin GT, Chen CJ, Liu CS, Lin SY, Huang TJ: Association of vitamin D receptor gene polymorphism with sporadic breast cancer in Taiwanese patients. Breast Cancer Res Treat. 2002, 74 (1): 1-7. 10.1023/A:1016048900049.View ArticlePubMedGoogle Scholar
  23. Buyru N, Tezol A, Yosunkaya-Fenerci E, Dalay N: Vitamin D receptor gene polymorphisms in breast cancer. Exp Mol Med. 2003, 35 (6): 550-555.View ArticlePubMedGoogle Scholar
  24. Curran JE, Vaughan T, Lea RA, Weinstein SR, Morrison NA, Griffiths LR: Association of A vitamin D receptor polymorphism with sporadic breast cancer development. Int J Cancer. 1999, 83 (6): 723-726. 10.1002/(SICI)1097-0215(19991210)83:6<723::AID-IJC4>3.0.CO;2-3.View ArticlePubMedGoogle Scholar
  25. Bretherton-Watt D, Given-Wilson R, Mansi JL, Thomas V, Carter N, Colston KW: Vitamin D receptor gene polymorphisms are associated with breast cancer risk in a UK Caucasian population. Br J Cancer. 2001, 85 (2): 171-175. 10.1054/bjoc.2001.1864.View ArticlePubMedPubMed CentralGoogle Scholar
  26. Ingles SA, Garcia DG, Wang W, Nieters A, Henderson BE, Kolonel LN, Haile RW, Coetzee GA: Vitamin D receptor genotype and breast cancer in Latinas (United States). Cancer Causes Control. 2000, 11 (1): 25-30. 10.1023/A:1008979417618.View ArticlePubMedGoogle Scholar
  27. John EM, Schwartz GG, Koo J, Wang W, Ingles SA: Sun exposure, vitamin D receptor gene polymorphisms, and breast cancer risk in a multiethnic population. Am J Epidemiol. 2007, 166 (12): 1409-1419. 10.1093/aje/kwm259.View ArticlePubMedGoogle Scholar
  28. Gilad LA, Bresler T, Gnainsky J, Smirnoff P, Schwartz B: Regulation of vitamin D receptor expression via estrogen-induced activation of the ERK 1/2 signaling pathway in colon and breast cancer cells. J Endocrinol. 2005, 185 (3): 577-592. 10.1677/joe.1.05770.View ArticlePubMedGoogle Scholar
  29. Gilad LA, Schwartz B: Association of estrogen receptor beta with plasma-membrane caveola components: implication in control of vitamin D receptor. J Mol Endocrinol. 2007, 38 (6): 603-618. 10.1677/JME-06-0040.View ArticlePubMedGoogle Scholar
  30. Halsall JA, Osborne JE, Potter L, Pringle JH, Hutchinson PE: A novel polymorphism in the 1A promoter region of the vitamin D receptor is associated with altered susceptibilty and prognosis in malignant melanoma. Br J Cancer. 2004, 91 (4): 765-770.PubMedPubMed CentralGoogle Scholar
  31. Han J, GA Colditz, DJ Hunter: Polymorphisms in the MTHFR and VDR genes and skin cancer risk. Carcinogenesis. 2007, 28: 390-7. 10.1093/carcin/bgl156.View ArticlePubMedGoogle Scholar
  32. Li C, Z Liu, LE Wang, JE Gershenwald, JE Lee, VG Prieto, et al: Haplotype and genotypes of the VDR gene and cutaneous melanoma risk in non-Hispanic whites in Texas: a case-control study. International Journal of Cancer. 2008, 122: 2077-84. 10.1002/ijc.23357.View ArticlePubMedPubMed CentralGoogle Scholar
  33. Durrin LK, Haile RW, Ingles SA, Coetzee GA: Vitamin D receptor 3'-untranslated region polymorphisms: lack of effect on mRNA stability. Biochim Biophys Acta. 1999, 1453 (3): 311-320.View ArticlePubMedGoogle Scholar
  34. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/8/385/prepub

Copyright

© Barroso et al; licensee BioMed Central Ltd. 2008

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 (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement