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Carcinogenesis Advance Access originally published online on July 9, 2007
Carcinogenesis 2007 28(9):1985-1990; doi:10.1093/carcin/bgm160
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

MGMT germline polymorphism is associated with somatic MGMT promoter methylation and gene silencing in colorectal cancer

Shuji Ogino1,2,3,*, Aditi Hazra4, Gregory J. Tranah5, Gregory J. Kirkner6, Takako Kawasaki1, Katsuhiko Nosho1, Mutsuko Ohnishi1, Yuko Suemoto1, Jeffrey A. Meyerhardt1,6, David J. Hunter4,6 and Charles S. Fuchs1,6

1 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
2 Department of Pathology, Brigham and Women's Hospital, Boston, MA 02115, USA
3 Department of Pathology, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA
4 Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
5 California Pacific Medical Center, San Francisco, CA 94107, USA
6 Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA

* To whom correspondence should be addressed. Tel: +1 617 632 3978; Fax: +1 617 277 9015; Email: shuji_ogino{at}dfci.harvard.edu


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 Funding
 References
 
O-6-methylguanine-DNA methyltransferase (MGMT) repairs inappropriately methylated guanine residues in DNA. MGMT promoter methylation and gene silencing are common events in colorectal cancer, and may or may not co-exist with the CpG island methylator phenotype (CIMP). To date, no study has examined the relationship between MGMT promoter methylation and common MGMT single nucleotide polymorphisms (SNPs), which have been associated with colorectal cancer risk. Utilizing real-time polymerase chain reaction (MethyLight technology), we quantified DNA methylation in MGMT and eight other markers (a CIMP diagnostic panel including CACNA1G, CDKN2A, CRABP1, IGF2, MLH1, NEUROG1, RUNX3 and SOCS1 in 182 colorectal cancers collected from two prospective cohorts, the Nurses’ Health Study and the Health Professionals Follow-up Study. We genotyped four MGMT germline SNPs in normal DNA and assessed microsatellite instability (MSI), 18q loss of heterozygosity and KRAS and BRAF status in tumors. The presence of a common MGMT promoter SNP (NM_002412 [GenBank] .2:c.-56C>T) (rs16906252) was strongly associated with MGMT methylation (multivariate odds ratio 18.0; 95% confidence interval, 6.2–52.1, P < 0.0001). The presence of the c.-56C>T SNP was also associated with loss of MGMT expression in tumors (assessed by immunohistochemistry) (P = 0.009). This promoter SNP was not correlated with KRAS, BRAF, CIMP or MSI status. None of the other three non-promoter SNPs was significantly associated with any molecular changes tested. In conclusion, we have found a strong association between the germline polymorphism (c.-56C>T) of the MGMT promoter and promoter methylation/silencing of MGMT in colorectal cancer. Our data provide compelling evidence for common susceptibility for MGMT promoter CpG island methylation.

Abbreviations: CACNA1 G, calcium channel, voltage-dependent, T type alpha-1 G subunit; CDKN2A, cyclin-dependent kinase inhibitor 2A (pl6/INK4A); CI, confidence interval; CIMP, CpG island methylator phenotype; CRABP1, cellular retinoic acid binding protein 1; IGF2, insulin-like growth factor 2; LOH, loss of heterozygosity; MGMT, O-6-methylguanine-DNA methyltransferase; MSI, microsatellite instability; MSS, microsatellite stable; NEUROG1, neurogenin 1; OR, odds ratio; PCR, polymerase chain reaction; PMR, percentage of methylated reference (degree of methylation); RUNX3, runt-related transcription factor 3; SNP, single nucleotide polymorphism; SOCS1, suppressor of cytokine signaling 1


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 Funding
 References
 
O-6-methylguanine-DNA methyltransferase (MGMT) acts to repair inappropriately methylated guanine residues in DNA. Chronic exposure to alkylating/methylating agents can lead to increased MGMT activity (1), and MGMT expression protects from spontaneous G:C to A:T transition mutations (2). Inactivation of MGMT increases efficacy of alkylating agent against cancer (3–5). MGMT promoter methylation is present in approximately 30–40% of colorectal cancers, and may co-exist with widespread CpG methylation known as the CpG island methylator phenotype (CIMP) (6). In addition, promoter methylation and gene silencing of MGMT are associated with G > A transition mutations in colorectal cancer (7,8). MGMT promoter methylation in normal-appearing colonic mucosa (perhaps as a field effect) may be a predisposing factor for the development of cancer (9), and MGMT promoter methylation may be an early event in colorectal carcinogenesis (10–12). MGMT methylation is a poor predictor of CIMP-high in colorectal cancer compared with selected CpG island methylation markers (13), suggesting that MGMT methylation may be somewhat independent of CIMP status.

Inter-individual variation in MGMT activity may be attributable to genetic variations in the MGMT gene (14). Three common, non-synonymous single nucleotide polymorphisms (SNPs), Leu84Phe, Ile143Val and Lys178Arg, have been reported in the coding region of MGMT (15,16). These MGMT SNPs have been associated with increased or decreased risks for various cancers (17–20), including colorectal cancer (21).

The relation between germline genetic variations and somatic epigenetic events has been an emerging area of investigation. Certainly, germline genetic variants are quite common in the general population, in contrast to heritable germline epimutations which are probably rare events (22). A possible relationship between germline SNPs and loss of methylation in an imprinted gene, IGF2 has been shown (23). Recently, a study has shown a weak association between a promoter SNP and promoter methylation of the MLH1 gene in colorectal and endometrial cancers (24). However, the possibility of potential interference with the methylation assay by the SNP was not excluded, and loss of MLH1 expression was not examined (24). Another case–control study has demonstrated a higher frequency of an MLH1 promoter SNP in microsatellite instability (MSI) cancer patients than control subjects; however, promoter methylation or silencing of the MLH1 gene has not been examined (25). Therefore, there has been no compelling evidence for the relationship between a promoter SNP and promoter methylation (and silencing) of the same gene.

In this study, using quantitative DNA methylation analysis (MethyLight technology) and immunohistochemistry, we examined MGMT promoter methylation and loss of expression in relation to four known MGMT SNPs including one promoter SNP. Our data provide compelling evidence for the relationship between a common MGMT promoter SNP and promoter methylation and silencing of the MGMT gene.


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 Funding
 References
 
Study group
We utilized the databases of two large prospective cohort studies; the Nurses’ Health Study (N = 121 700 women followed since 1976) (26), and the Health Professional Follow-up Study (N = 51 500 men followed since 1986) (21). Informed consent was obtained from all participants prior to inclusion in the cohorts. We also collected blood specimens from a subset of cohort participants (21). A subset of the cohort participants developed colorectal cancers during prospective follow-up. Thus, these colorectal cancers represented population-based, relatively unbiased samples (compared with retrospective or single-hospital-based samples). Tumor location and staging information were obtained through reviewing medical records. Previous studies in the Nurses’ Health Study and Health Professionals Follow-up Study have described baseline characteristics of cohort participants and incident colorectal cancer cases and confirmed that our colorectal cancer cases were well representative as a population-based sample (26,27). We collected paraffin-embedded tissue blocks from hospitals where cohort participants with colorectal cancers had undergone resections of primary tumors. We excluded cases if adequate paraffin-embedded tumor tissue was not available for DNA methylation analysis, if tumors were previously treated by chemotherapy or radiation or if MGMT germline SNP data were not available. As a result, a total of 182 colorectal cancer cases (100 from the men's cohort and 82 from the women's cohort) were included. Clinical characteristics of the 182 cases are described in Table I. Most of the cases were previously characterized for status of CIMP MSI, KRAS, BRAF and MGMT methylation (13,28) and status of MGMT germline SNPs (21). However, we have not examined MGMT germline SNPs in relation to any molecular features in colorectal cancer cells. Germline SNP analyses and tumor tissue analyses were approved by the Institutional Review Boards of the Harvard School of Public Health, Dana-Farber Cancer Institute and Brigham and Women's Hospital.


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  		Table I. Clinical characteristics of colorectal cancer cases

 
Genotyping of MGMT germline SNPs
Venous blood samples were separated into plasma, buffy coat, and red blood cells and stored in liquid nitrogen. Genomic DNA was extracted from 50 µl of buffy coat diluted with 150 µl of phosphate-buffered saline using the QIAmp (Qiagen, Chatsworth, CA) 96-spin blood protocol according to the manufacturer's protocol. Concentrations of genomic DNA were measured in 96-well format with PicoGreen technology (Molecular Probes, Eugene, OR).

The MGMT SNPs, rs16906252 (NM_002412 [GenBank] .2:c.-56C>T), rs12917 (NM_002412 [GenBank] .2:c.250C>T or p.Leu84Phe), rs2308327 (NM_002412 [GenBank] .2:c.533A>G or p.Lys178Arg) and rs2296675 (NT_008818 [GenBank] .15:g.2798929A>G or ‘so-called IVS3-54A>G’), in the MGMT gene were evaluated by the Illumina GoldenGate® oligo pool assay (29), which included 1412 successfully genotyped unique SNPs (A. Hazra, S. Chanock, E. Giovanucci, D.G. Cox, T. Niu, C.S. Fuchs, W.C. Wilett and D.J. Hunter, unpublished data) in candidate genes identified in the SNP500 Cancer project. Briefly, whole genome amplification (WGA) of genomic DNA was queried with probes (two allele-specific and one locus-specific oligonucleotide) to create DNA fragments that could be amplified by standard polymerase chain reaction (PCR) methods with three universal primers. Fluorescently labeled strands were hybridized to the appropriate probe on the microbead array, which allowed identification of a particular SNP (29). Laboratory personnel were blinded to clinical features and molecular status in tumor.

Tumor genomic DNA extraction and WGA
Genomic DNA was extracted from paraffin-embedded tumor tissue sections using QIAmp DNA Mini Kit (Qiagen, Valencia, CA) as previously described (30). Normal DNA was obtained from colonic tissue at resection margins. WGA of genomic DNA was performed by PCR using random 15mer primers for subsequent MSI analysis and KRAS and BRAF sequencing as previously described (30). Previous studies showed that WGA did not significantly affect downstream genetic analysis (30,31).

MSI and 18q loss of heterozygosity analyses
Methods to analyze for MSI and 18q loss of heterozygosity (LOH) status have been previously described (32). In addition to the recommended MSI panel consisting of D2S123, D5S346, D17S250, BAT25 and BAT26 (33), we also used BAT40, D18S55, D18S56, D18S67 and D18S487 (i.e. 10-marker panel) (32). A ‘high degree of MSI’ was defined as the presence of instability in ≥30% of the markers. A low degree of MSI was defined as the presence of instability in <30% of the markers and ‘microsatellite stable’ tumors were defined as tumors without an unstable marker.

For 18q LOH analysis, we duplicated PCR reactions and electrophoresis in each sample for D18S55, D18S56, D18S67 and D18S487 to exclude allele dropouts of one of two alleles. LOH at each locus (D18S55, D18S56, D18S67 or D18S487) was defined as 40% or greater reduction of one of two allele peaks in two duplicated runs in tumor DNA relative to normal DNA. Overall, 18q LOH positivity was defined as the presence of at least one informative marker with LOH, and 18q LOH negativity as the presence of at least one informative marker and the absence of LOH in all informative markers.

Sequencing of KRAS and BRAF
Methods of PCR and sequencing targeted for KRAS codons 12 and 13, and BRAF codon 600 have been previously described (30,34). Pyrosequecing was performed using the PSQ96 HS System (Biotage AB and Biosystems, Uppsala, Sweden) according to the manufacturer's instructions.

Real-time PCR (MethyLight) for quantitative DNA methylation analysis
Sodium bisulfite treatment on genomic DNA was performed as previously described (35). Real-time PCR to measure DNA methylation (MethyLight) was performed as previously described (36). Utilizing ABI 7300 (Applied Biosystems, Foster City, CA) for quantitative real-time PCR, we amplified MGMT and eight other CIMP markers CACNA1G, CDKN2A, CRABP1, IGF2, MLH1, NEUROG1, RUNX3 and SOCS1 (13,37)]; methylation in the latter eight promoters has been shown to be sensitive and specific for CIMP (38), and thus we used these eight markers as a CIMP diagnostic panel. COL2A1 (the collagen 2A1 gene) was used to normalize for the amount of input bisulfite-converted DNA (35). Primers and probes were previously described (37). The percentage of methylated reference (PMR, i.e. degree of methylation) at a specific locus was calculated by dividing the GENE:COL2A1 ratio of template amounts in a sample by the GENE:COL2A1 ratio of template amounts in SssI-treated human genomic DNA (presumably fully methylated) and multiplying this value by 100 (36). A PMR cutoff value of 4 (except a cut-off of 6 for CRABP1 and IGF2) was based on previously validated data (13,35). In particular, we validated MGMT PMR cut-off of 4, by examining PMR values in relation to loss of expression, using a larger number of tumors including those without available SNP data, and the frequencies of MGMT loss were as follows: 14% (46/331) in tumors with PMR = 0; 18% (5/28) in tumors with PMR of 0–1; 33% (3/9) in tumors with PMR of 1–4; 60% (6/10) in tumors with PMR of 4–10 and 79% (150/189) in tumors with PMR > 10 (28). Precision and performance characteristics of bisulfite conversion and subsequent MethyLight assays have been previously evaluated and the assays have been validated (35). CIMP-high was defined as the presence of ≥6/8 methylated CIMP markers (excluding MGMT) (38).

Immunohistochemistry for MGMT
Detailed methods for MGMT immunohistochemistry have been previously described (28). Normal colonic epithelial cells and inflammatory cells served as internal positive controls when a tumor lost MGMT expression (Figure 1). Appropriate positive and negative controls were included in each run of immunohistochemistry. All immunohistochemically stained slides were interpreted by a pathologist (S.O.) blinded from clinical and other molecular data.


Figure 1
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  		Fig. 1. MGMT expression and loss in colorectal cancer. (A) Colorectal cancer with intact MGMT expression (arrow). (B) Colorectal cancer with loss of MGMT expression (empty arrow). Normal colonic mucosa (solid arrowhead) and lymphocytes (empty arrowhead) show intact MGMT expression.

 
Statistical analysis
For analysis of the main effect of genotype, logistic regression was used to compute odds ratios (ORs) and 95% confidence intervals (CIs). In multivariate analyses, ORs were adjusted for age, sex, tumor location and tumor stage. For categorical data, a chi-square test (or Fisher's exact test when the number in any category was <10) was performed. All statistical analyses were performed using SAS (Version 9.1, SAS Institute, Cary, NC). All P values were two-sided, and statistical significance was set at P ≤ 0.05.


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 Funding
 References
 
MGMT germline SNPs
We analyzed MGMT germline SNPs in a total of 182 cohort participants who developed colorectal cancer. Table II summarizes overall distribution of genotypes for each SNP on the left. A minor allele frequency for each SNP was as follows: c.-56C>T (rs16906252), T allele 9.2% ( = 33/358); c.250C>T (p.Leu84Phe, rs12917), T allele 15% ( = 52/358); c.533A>G (p.Lys178Arg, rs2308327), G allele 7.6% ( = 27/356) and g.2798929A>G (rs2296675), G allele 16% ( = 56/354). Distributions of these SNPs were conformed to the Hardy–Weinberg equilibrium in our control population in the Nurses’ Health Study and Health Professionals Follow-up Study (A. Hazra, S. Chanock, E. Giovanucci, D.G. Cox, T. Niu, C.S. Fuchs, W.C. Wilett and D.J. Hunter, unpublished data).


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  		Table II. MGMT germline SNPs and promoter methylation in colorectal cancer

 
MGMT SNPs and promoter methylation/gene silencing in tumor
Utilizing MethyLight technology, we quantified DNA methylation in MGMT in colorectal cancers. Among the 182 tumors, 63 (35%) showed MGMT promoter methylation. The c.-56C>T SNP was tightly correlated with MGMT methylation (Table II). Compared with the C/C genotype (with MGMT methylation frequency 24%), the combined C/T and T/T genotypes showed very high frequencies of MGMT methylation (84%) with a univariate OR of 16.2 (95% CI, 5.8–45.2; P < 0.0001) and a multivariate OR of 18.0 (95% CI, 6.2–52.1; P < 0.0001) (adjusted for age, sex, tumor location and tumor stage).

Figure 2 shows the relationship between the c.-56C>T SNP, CpG island and MethyLight primers and probe. The c.-56C>T SNP did not interfere with MethyLight assay; because it was not located within a CpG site, both alleles C and T became T after bisulfite conversion.


Figure 2
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  		Fig. 2. Relationship between the c.-56C>T SNP, CpG island and MethyLight primers and probe for MGMT. All of the other three SNPs are intragenic and not shown. The c.-56C>T SNP is present within the MGMTpromoter CpG island. However, the SNP would not interfere with methylation assay. Since this SNP is not in a CpG site, C allele was converted to T, so that both alleles C and T were T after bisulfite treatment. Note that sequence shown is native before bisulfite conversion; actual sequences of MethyLight primers and probe match with bisulfite-converted nucleotide sequence assuming all methylated CpG sites.

 
Nonetheless, we examined whether the c.-56C>T SNP showed a positive correlation with MGMT loss of expression assessed by immunohistochemistry. Among the 103 tumors with valid MGMT expression data, 32 (31%) tumors showed loss of MGMT expression. As in Table III, the c.-56 C/T genotype showed a significantly higher frequency of MGMT loss than the c.-56 C/C genotype (70 versus 27%; OR = 6.4, 95% CI, 1.5–26.5; P = 0.009), corroborating the MGMT methylation results.


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  		Table III. MGMT germline SNPs and loss of MGMT expression in colorectal cancer

 
None of the other three SNPs were significantly correlated with MGMT methylation or loss of expression.

MGMT SNPs and 18q LOH
We examined the relationship between MGMT SNPs and 18q LOH, because, within colorectal cancers, MGMT methylation and loss have been inversely correlated with 18q LOH (28). Compared with the c.-56 C/C genotype (with 53% of tumors showing18q LOH), the c.-56 C/T and T/T genotypes showed a lower frequency of 18q LOH (33%) (Table IV). In a multivariate analysis, the inverse relationship between 18q LOH and the combined c.-56 C/T and T/T genotypes was significant (OR = 0.29; 95% CI, 0.097–0.85, P = 0.02). As we expected, the association between MGMT SNP and 18q LOH was not as strong as the association between the MGMT promoter SNP and MGMT methylation.


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  		Table IV. MGMT germline SNPs and the frequencies of 18q LOH,KRAS and BRAF mutations, CIMP-high and MSI-high in colorectal cancer

 
MGMT germline SNPs and CIMP
We examined CIMP status in tumors to examine whether the effect of the MGMT SNP on promoter methylation was more than a local phenomenon. By MethyLight, we quantified DNA methylation in a panel of eight promoters (CACNA1G, CDKN2A, CRABP1, IGF2, MLH1, NEUROG1, RUNX3 and SOCS1) all of which showed methylation patterns correlated positively with widespread CpG island methylation (13,37). None of the MGMT SNPs was significantly correlated with CIMP status (Table IV).

MGMT SNPs, KRAS/BRAF mutations and MSI status in tumor
We also examined KRAS/BRAF mutations and MSI status in relation to MGMT SNPs because of known associations between MGMT loss and KRAS mutations (in particular, G > A mutations) and between KRAS/BRAF, CIMP and MSI. None of the MGMT SNPs showed a significant association with KRAS or BRAF mutation, MSI-high (Table IV) or MSI-low (data not shown).


   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
Funding
 References
 
We conducted this study to examine the relationship with MGMT germline SNPs and MGMT promoter methylation in colorectal cancer. We used quantitative PCR assays (MethyLight) to determine the degree of DNA methylation, which is essential to reproducibly differentiate high-level from low-level methylation (35). We have shown that the c.-56C>T MGMT promoter SNP is tightly associated with MGMT promoter methylation (multivariate OR 18.0, 95% CI, 6.2–52.1, for the dominant genetic model). The association is unlikely caused by interference with the MethyLight assay by this SNP because the SNP is also significantly correlated with loss of MGMT expression, which is a consequence of MGMT promoter methylation. As illustrated in Figure 2, the SNP is not located within a CpG site (since both C and T alleles become T alleles after bisulfite conversion), and the MethyLight probe binds in the same manner regardless of germline genotype.

Our data provide compelling evidence for the strong relationship between an MGMT promoter SNP, MGMT promoter methylation and gene silencing. We cannot exclude a possibility that another SNP which shows a strong linkage disequilibrium with the c.-56C>T SNP may cause MGMT promoter methylation. Nonetheless, if such a SNP exists, it is likely present around the promoter CpG island close to the c.-56C>T SNP. A potential correlation between promoter SNP and methylation in MLH1 has recently been proposed (24); however, the authors have shown much weaker associations (univariate ORs up to 2.0 compared with the multivariate ORs of 16.7 and 18.0 in our current study) and did not exclude interference with their combined bisulfite restriction analysis assay by the promoter SNP. Neither a detailed map of the SNP in relation to the combined bisulfite restriction analysis assay primer/restriction sites nor protein expression data are provided (24).

The mechanistic explanation for the strong association between the c.-56C>T MGMT promoter SNP and CpG island methylation is speculative at this time. Studies have suggested that site-specific repressors of transcription may recruit DNA methyltransferases, leading to de novo DNA methylation and epigenetic gene silencing (39,40). It is possible that the c.-56C>T SNP in the regulatory region could contribute to abnormal CpG island methylation by recruiting DNA methyltransferases. The effect of the MGMT promoter SNP appears to be limited to the local CpG island since there is no significant correlation between the MGMT promoter SNP and CIMP. Further studies are necessary to elucidate the mechanisms of the effect of SNP on CpG island methylation.

The exact effect of the MGMT c.-56C>T SNP is currently unknown; however, it is located within a 59 bp enhancer that has been described within the first exon–intron boundary of the MGMT gene (41). The 59 bp enhancer is required for efficient MGMT promoter function (41). Sequential deletion from the 5' end of the MGMT promoter resulted in a gradual reduction of activity in a reporter gene assay (42), suggesting that the majority of the sequence contained within this area (including the c.-56 position) is required for efficient MGMT gene expression. In these experiments, 5' extension that includes the c.-56 position increases promoter activity by 60% (42), suggesting that this region of the exon–intron boundary contains elements important for the modulation of gene transcription. The c.-56C>T SNP has been shown to enhance transcriptional activity using reporter constructs (43); however, the relationship between this SNP and transcript levels in vivo has not been examined.

Potential implications of the discovery of the relationship between this SNP and methylation warrant discussion. This discovery provides compelling evidence for heritable susceptibility for promoter CpG island methylation, at least in MGMT. We have shown that the MGMT c.-56C>T promoter SNP is not correlated with CIMP. Thus, the effect of the MGMT c.-56C>T promoter SNP on CpG island methylation appears to be local without genome-wide effect on CpG island methylation. It remains to be investigated whether the effect of a promoter SNP on CpG island methylation is generalizable or limited to a smaller set of genes including MGMT. As possible measures of cancer prevention in the future, screening for various promoter SNPs may be used to stratify individuals according to risks of developing colorectal cancer with promoter methylation in the specific tumor suppressor genes.

In conclusion, we provide compelling evidence for the relationship between the MGMT c.-56C>T promoter SNP, MGMT promoter methylation and gene silencing. The effect of the MGMT c.-56C>T promoter SNP on DNA methylation is limited to the local CpG island; this SNP does not appear to exhibit genome-wide effect on CIMP. The mechanism of this effect of a promoter SNP on CpG island methylation needs to be elucidated by additional studies.


   Funding
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Funding
References
 
US National Institute of Health (P01 CA87969, P01 CA55075 and U54 CA100971 [GenBank] ); Bennett Family Fund for Targeted Therapies Research; Entertainment Industry Foundation (EIF) through the EIF National Colorectal Cancer Research Alliance.


   Acknowledgments
 
We deeply thank the Nurses’ Health Study and Health Professionals Follow-up Study cohort participants who have generously agreed to provide us with biological specimens and information through responses to questionnaires. We thank Walter Willett, Sue Hankinson and many other staff members who implemented and have maintained the cohort studies. We thank Peter Laird, Daniel Weisenberger and Mihaela Campan for assisting in the development of the MethyLight assay.

Conflict of Interest Statement: None declared.


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Funding
 References
 

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Received May 16, 2007; revised June 19, 2007; accepted July 3, 2007.


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