Abstract
Aberrant promoter methylation is recognized as an important feature of breast carcinogenesis. We hypothesized that genetic variation of genes for methylenetetrahydrofolate reductase (MTHFR) and methionine synthase (MTR), two critical enzymes in one-carbon metabolism, may alter DNA methylation levels, and thus influence DNA methylation in breast cancer. We evaluated case-control association of MTHFR C677T, A1298C, and MTR A2756G polymorphisms for cases strata defined by promoter methylation status for each of three genes, E- cadherin, p16, and RAR-β2 in breast cancer; in addition, we evaluated case-case comparisons of likelihood of promoter methylation in relation to genotypes using a population-based case-control study conducted in Western New York State. Methylation was evaluated with real time methylation-specific PCRs for 803 paraffin embedded breast tumor tissues from women with primary, incident breast cancer. We applied unordered polytomous regression and unconditional logistic regression to derive adjusted odds ratios (OR) and 95% confidence intervals (CI). We did not find any association of MTHFR and MTR polymorphisms with breast cancer risk stratified by methylation status nor between polymorphisms and likelihood of promoter methylation of any of the genes. There was no evidence of difference within strata defined by menopausal status, ER status, folate intake and lifetime alcohol consumption. Overall, we found no evidence that these common polymorphisms of the MTHFR and MTR genes are associated with promoter methylation of E- cadherin, p16, and RAR-β2 genes in breast cancer.
Keywords: promoter methylation, MTHFR, MTR, breast cancer, epidemiology, genetic polymorphisms
Introduction
Both CpG island promoter hypermethylation and global DNA hypomethylation are prominent features of breast tumors and important in the carcinogenic process (1, 2). However, the factors that result in aberrant DNA methylation in normal and neoplastic tissues are not well known. One carbon metabolism, critical in the availability of methyl groups and therefore DNA methylation, may impact both hypo- and hypermethylation (3). We examined whether common genetic variations of one carbon metabolism genes, specifically methylenetetrahydrofolate reductase (MTHFR) and methionine synthase (MTR), are associated with promoter methylation of three genes selected because they are functionally important and have been found to be methylated in breast tumors and may therefore influence breast carcinogenesis: E- cadherin, involved in cell adhesion (4), p16, important in cell cycle regulation (5), and RAR-β2 retinoic acid binding receptor- β2), important in receptor-mediated cell signaling (6). These associations were examined in a case control study of primary, incident breast cancers, examining the association between MTHFR and MTR polymorphisms and breast cancer risk by tumor methylation status as well as the likelihood of methylation in tumors by genotype.
Materials and Methods
Detailed study methods have been published previously (7). In brief, the Western New York Exposures and Breast Cancer Study (WEB Study) included 1,170 primary, histologically confirmed, incident breast cancer cases, age 35–79 at diagnosis and 2,115 randomly selected population controls, frequency-matched to cases on age and race. Extensive in-person interviews and self-administered questionnaires were administered to participants including queries on demographic factors and breast cancer risk factors. The response rates were 72% for cases and 63% for controls. Information on tumor size, histological grade, and cancer stage was abstracted from medical charts using a standard protocol. Estrogen receptor (ER) status was determined by immunohistochemistry as described previously (7). DNA was extracted from blood and mouthwash samples using the GenQuik DNA Extraction Kit (BioServe Biotechnologies Ltd., Laurel, MD). Archived tumor blocks were obtained from 920 (78.6%) breast cancer cases.
The allelic discrimination of the MTHFR C677T, A1298C and MTR A2756G polymorphisms were assessed by real time PCR with Taqman genotyping assay with primers, probes and conditions as described on the NCI’s Cancer Genome Anatomy Project SNP500 Cancer Database Website (http://snp500cancer.nci.nih.gov). Promoter methylation of E-cadherin, p16, and RAR-β2 was determined by real time methylation-specific PCR (MSP) after bisulfite modification of genomic tumor DNA isolated from archived paraffin embedded tissues of 803 breast cancer tumors (MSP, described in detailed previously (7)).
The exact χ2 goodness-of-fit test was used to test Hardy-Weinberg equilibrium of the genotypes. Characteristics of participating cases with and without promoter methylation of specific gene and controls were compared using the ANOVA test for continuous variables and χ2 test for categorical variables. For comparisons of cases with and without promoter methylation to controls, odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using polytomous logistic regression. Unconditional logistic regression was used for case-case comparisons of those with and without promoter methylation to estimate the ORs and 95% CIs for the associations of MTHFR and MTR genotypes with promoter methylation in breast cancer. Interactions between genotype and menopause, ER status, folate intake, or alcohol intake were evaluated by evaluation of a multiplicative term in the regression model. All analyses were adjusted by age and race. For case-case comparisons, we also adjusted for ER status. Potential confounding effects of other demographic factors and known breast cancer risk factors were also examined, and the results changed less than 10%. Those results are not shown. All statistical tests were based on two-sided probability. All statistical analyses were performed using SAS version 9.1 (SAS Institute, Cary, NC).
Results
The frequencies of genotypes of MTR and MTHFR polymorphisms for cases and controls and distributions of selected characteristic factors are shown in Table 1. All polymorphisms were in Hardy-Weinberg equilibrium for both cases and controls in both the whole population and in Caucasians only. The distributions of MTR and MTHFR polymorphisms were similar for cases with or without E-cadherin, p16, and RAR-β2 gene promoter methylation.
Table1.
Distribution of one-carbon metabolism genes among breast cancer cases, cases with (M) and without (UM) promoter methylation and controls, WEB Study 1996–2001*
| Controls | E-cadherin | p16 | RAR-β2 | ||||
|---|---|---|---|---|---|---|---|
| M (n = 161)§ | UM § | M (n = 208)§ | UM § | M (n = 221)§ | UM § | ||
| Age, y † | 57.8 ± 11.8 | 58.0 ± 11.8 | 57.4 ± 11.2 | 58.0 ± 11.2 | 57.4 ± 11.3 | 57.4 ± 11.3 | 57.6 ± 11.3 |
| Race/ ethnicity | |||||||
| White | 1910 (90.3%) | 148 (91.9%) | 594 (92.5%) | 192 (92.3%) | 550 (92.4%) | 210 (95.0%) | 532 (91.4%) |
| Non-white | 205 (9.7%) | 13 (8.1%) | 48 (7.5%) | 16 (7.7%) | 45 (7.6%) | 11 (5.0%) | 50 (8.6%) |
| Postmenopausal | 1503 (71.1%) | 111 (68.9%) | 455 (70.9%) | 147 (70.7%) | 419 (70.4%) | 157 (71.0%) | 409 (70.3%) |
| Folate intake (mg/day)†1 | 267.0 ±147.3 | 281.7 ± 178.4 | 280.7 ± 178.4b | 275.2 ± 143.2 | 282.9 ± 158.9 b | 285.5 ± 175.0 | 279.2 ± 146.6 |
| Lifetime alcohol (oz)†2 | 3545.6 ±12546.9 | 3509.3 ±6278.0 | 2901.8 ±4766.5 | 3049.5 ±5194.3 | 3023.3 ±5104.7 | 2626.4 ±3703.2 | 3177.4 ±5548.6 |
| ER status | |||||||
| + | 114 (71.3%) | 446 (70.0%) | 136 (65.7%) | 424 (71.9%) | 163 (74.8%) | 397 (68.6%) | |
| − | 46 (28.7%) | 191 (30%) | 71 (34.3%) | 166 (28.1%) | 55 (25.2%) | 182 (31.4%) | |
| MTR (A2756C) | |||||||
| AA | 1217 (63.1%) | 99 (65.1%) | 392 (65.0%) | 128 (65.7%) | 363 (64.8%) | 130 (63.1%) | 361 (65.8%) |
| AG | 619 (32.1%) | 47 (30.9%) | 179 (29.7%) | 56 (28.7%) | 170 (30.4%) | 66 (32.0%) | 160 (29.1%) |
| GG | 93 (4.8%) | 6 (4.0%) | 32 (5.3%) | 11 (5.6%) | 27 (4.8%) | 10 (4.9%) | 28 (5.1%) |
| χ2 test p value | 0.78 | 0.84 | 0.74 | ||||
| MTHFR (A1298C) | |||||||
| AA | 864 (47.2%) | 60 (44.8%) | 249 (47.2%) | 80 (46.3%) | 229 (46.8%) | 79 (43.4%) | 230 (47.9%) |
| AC | 779 (42.5%) | 63 (47.0%) | 224 (42.4%) | 76 (43.9%) | 211 (43.2%) | 88 (48.4%) | 199 (41.5%) |
| CC | 188 (10.3%) | 11 (8.2%) | 55 (40.4%) | 17 (9.8%) | 49 (10.0%) | 15 (8.2%) | 51 (10.6%) |
| χ2 test p value | 0.56 | 0.98 | 0.25 | ||||
| MTHFR (C677T) | |||||||
| CC | 813 (43.9%) | 63 (44.7%) | 260 (45.1%) | 83 (44.1%) | 240 (45.4%) | 93 (47.4%) | 230 (44.2%) |
| CT | 816 (44.1%) | 57 (40.4%) | 248 (43.1%) | 74 (39.4%) | 231 (43.7%) | 87 (44.4%) | 218 (41.8%) |
| TT | 223 (12.0%) | 21 (14.9%) | 68 (11.8%) | 31 (16.5%) | 58 (10.9%) | 16 (8.2%) | 73 (14.0%) |
| χ2 test p value | 0.59 | 0.13 | 0.11 | ||||
Subjects with missing values were excluded from the analysis.
M – methylated; UM – unmethylated;
Mean ± SD;
Dietary folate intake;
Among ever drinkers.
Comparison of methylated cases to controls, p < 0.05;
Comparison of unmethylated cases to controls, p < 0.05;
Comparison of methylated to unmethylated cases, p < 0.05.
The results of case-case and case-control comparisons evaluating associations between MTR A2756G and MTHFR C677T and C1298A genotypes and breast tumors with or without promoter methylation are presented in Table 2. In case-control comparisons, we did not find association of MTHFR and MTR polymorphisms with breast cancer risk stratified by methylation status. In case-case analyses, there was no association between MTR A2756G, MTHFR C677T, or C1298A polymorphisms and E-cadherin, p16, or RAR-β2 gene methylation in breast tumors for both pre- and post-menopausal women. We also analyzed the above relations using dominant and recessive models of inheritance in both case-control comparisons and case-case comparisons, however, no associations were observed. In addition, results of analyses stratified by ER status, folate intake and lifetime alcohol intake were similar; there were no interactions and all p vaules for interaction tests were > 0.05. For the joint effects of MTR and MTHFR genotypes on likelihood of promoter methylation in at least one gene, compared to the MTR 2756AA, MTHFR 677CC and 1298AA genotype, women with breast cancer with more variant alleles for either MTR 2756G, MTHFR 677 T or 1298 C alleles tend to increase likelihood of promoter methylation in at least one gene, although associations were not statistically significant and there was no trend (OR, 1.21, 1.30, and 1.45, 95% CI, 0.65–2.22, 0.70–2.41, and 0.72–2.91 for women with any one, any two, and three variant alleles, respectively).
Table 2 .
Associations of MTR and MTHFR genotypes and gene promoter methylation: ORs (95% confidence intervals) for comparisons of controls to cases with promoter methylation (M), to cases without methylation (UM), and case-case comparisons cases
| MTR A2756G (rs1805087) | MTHFR A1298C (rs1801131) | MTHFR C677T (rs1801133) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| AA | AG | GG | AA | AC | CC | CC | CT | TT | |
| Premenopausal | |||||||||
| E-cadherin | |||||||||
| M/ U/ control | 30/121/370 | 15/44/161 | 3/6/31 | 19/73/257 | 15/53/233 | 4/18/49 | 22/73/227 | 15/68/251 | 5/21/68 |
| M versus controls1 | 1.0 | 1.22 (0.64–2.31) | 1.22 (0.35–4.21) | 1.0 | 0.71 (0.37–1.35) | 0.89 (0.30–2.64) | 1.0 | 0.59 (0.31–1.13) | 0.71 (0.26–1.90) |
| U versus controls1 | 1.0 | 0.83 (0.57–1.23) | 0.57 (0.23–1.40) | 1.0 | 0.67 (0.46–0.97) | 1.07 (0.60–1.92) | 1.0 | 0.82 (0.58–1.18) | 0.92 (0.53–1.59) |
| M versus U2 | 1.0 | 1.49 (0.74–3.02) | 2.24 (0.51–9.88) | 1.0 | 1.05 (0.52–2.12) | 0.62 (0.17–2.26) | 1.0 | 0.73 (0.36–1.48) | 0.78 (0.27–2.29) |
| p16 | |||||||||
| M/ U/ control | 42/109/370 | 44/15/161 | 1/8/31 | 27/65/257 | 19/49/233 | 5/17/49 | 24/71/227 | 24/59/251 | 8/18/68 |
| M versus controls1 | 1.0 | 0.87 (0.47–1.60) | 0.28 (0.04–2.13) | 1.0 | 0.77 (0.43–1.38) | 0.95 (0.36–2.56) | 1.0 | 1.01 (0.57–1.79) | 1.21 (0.52–2.79) |
| U versus controls1 | 1.0 | 0.92 (0.62–1.36) | 0.84 (0.38–1.88) | 1.0 | 0.65 (0.44–0.94) | 1.06 (0.58–1.92) | 1.0 | 0.70 (0.49–1.01) | 0.77 (0.44–1.37) |
| M versus U2 | 1.0 | 0.93 (0.47–1.83) | 0.31 (0.04–2.61) | 1.0 | 1.16 (0.61–2.24) | 0.96 (0.32–2.84) | 1.0 | 1.45 (0.76–2.78) | 1.55 (0.60–4.00) |
| RAR-β2 | |||||||||
| M/ U/ control | 37/114/370 | 22/37/161 | 1/8/31 | 25/67/257 | 16/52/233 | 6/16/49 | 25/70/227 | 25/58/251 | 5/21/68 |
| M versus controls1 | 1.0 | 1.39 (0.80–2.42) | 0.33 (0.04–2.49) | 1.0 | 0.52 (0.28–0.95) | 0.91 (0.36–2.25) | 1.0 | 0.81 (0.47–1.41) | 0.58 (0.22–1.55) |
| U versus controls1 | 1.0 | 0.75 (0.50–1.13) | 0.80 (0.36–1.80) | 1.0 | 0.74 (0.51–1.09) | 1.09 (0.59–2.00) | 1.0 | 0.75 (0.52–1.09) | 0.99 (0.57–1.71) |
| M versus U2 | 1.0 | 1.86 (0.97–3.55) | 0.45 (0.05–3.92) | 1.0 | 0.76 (0.39–1.50) | 0.96 (0.34–2.69) | 1.0 | 1.04 (0.55–1.94) | 0.56 (0.19–1.63) |
| Postmenopausal | |||||||||
| E-cadherin | |||||||||
| M/ U/ control | 69/271/847 | 32/135/458 | 3/26/62 | 41/176/607 | 48/171/546 | 7/37/139 | 42/187/586 | 42/180/565 | 16/47/155 |
| M versus controls1 | 1.0 | 0.91 (0.59–1.39) | 0.66 (0.23–2.15) | 1.0 | 1.24 (0.83–1.86) | 0.72 (0.32–1.62) | 1.0 | 1.07 (0.70–1.63) | 1.46 (0.81–2.63) |
| U versus controls1 | 1.0 | 1.00 (0.79–1.26) | 1.47 (0.91–2.38) | 1.0 | 0.99 (0.79–1.24) | 0.85 (0.57–1.26) | 1.0 | 1.04 (0.83–1.31) | 0.98 (0.69–1.41) |
| M versus U2 | 1.0 | 0.89 (0.56–1.41) | 0.43 (0.13–1.49) | 1.0 | 1.20 (0.78–1.86) | 0.84 (0.36–2.00) | 1.0 | 1.02 (0.65–1.62) | 1.50 (0.78–2.88) |
| p16 | |||||||||
| M/ U/ control | 86/254/847 | 41/126/458 | 10/19/62 | 53/164/607 | 57/162/546 | 12/32/139 | 59/169/586 | 50/172/565 | 23/40/155 |
| M versus controls1 | 1.0 | 0.92 (0.63–1.36) | 1.76 (0.57–3.56) | 1.0 | 1.04 (0.73–1.50) | 0.87 (0.46–1.65) | 1.0 | 0.89 (0.61–1.30) | 1.47 (0.89–2.43) |
| U versus controls1 | 1.0 | 1.00 (0.78–1.27) | 0.76 (0.87–3.56) | 1.0 | 1.04 (0.82–1.31) | 0.81 (0.53–1.22) | 1.0 | 1.10 (0.88–1.39) | 0.93 (0.61–1.36) |
| M versus U2 | 1.0 | 0.90 (0.59–1.38) | 1.55 (0.69–3.50) | 1.0 | 0.97 (0.65–1.45) | 1.08 (0.53–2.22) | 1.0 | 0.82 (0.54–1.26) | 1.61 (0.89–2.89) |
| RAR-β2 | |||||||||
| M/ U/ control | 93/247/847 | 44/123/458 | 9/20/62 | 54/163/607 | 72/147/546 | 9/35/139 | 68/160/586 | 62/160/565 | 11/52/155 |
| M versus controls 1 | 1.0 | 0.92 (0.64–1.33) | 1.46 (0.70–3.03) | 1.0 | 1.35 (0.94–1.91) | 0.67 (0.33–1.37) | 1.0 | 0.96 (0.68–1.37) | 0.61 (0.43–0.88) |
| U versus controls1 | 1.0 | 1.00 (0.79–1.27) | 1.25 (0.74–2.11) | 1.0 | 0.93 (0.74–1.18) | 0.88 (0.59–1.31) | 1.0 | 1.08 (0.85–1.38) | 1.27 (0.66–2.45) |
| M versus U 2 | 1.0 | 0.90 (0.60–1.37) | 1.20 (0.52–2.75) | 1.0 | 1.45 (0.98–2.13) | 0.68 (0.30–1.54) | 1.0 | 0.87 (0.58–1.29) | 0.48 (0.24–0.97) |
Odds ratios and 95% confidence intervals adjusted for age and race.
Odds ratios and 95% confidence intervals also adjusted for estrogen receptor status.
Discussion
MTHFR and MTR are key enzymes in the biosynthesis of 5-methyl tetrahydrofolate and methionine, which are precursors for DNA methylation reactions; and these enzymes’ activities also affect availability of tetrahydrofolate for nucleotide biosynthesis (3). MTHFR C677T and A1298C variants are associated with a reduction of enzyme activity (8, 9) and MTR A2756G variant is associated with lower homocysteine concentration (10, 11), and have been investigated for their possible effect on breast carcinogenesis with inconsistent results (12–17).
Polymorphisms of MTHFR C677T and A1298C and MTR A2756G have been investigated in relation to promoter methylation of genes in breast tumors in one other study of 227 breast cancer cases. Consistent with our findings, no association was observed between MTHFR C677T and MTR A2756G polymorphisms and frequency of promoter methylation in seven, including E - cadherin, p16, and RAR-β2, genes in breast cancer (18). In our study, we also found that this association was not modified by menopausal status, ER status, folate intake or total alcohol intake.
There have been studies examining these genotypes with promoter methylation of genes in tumors from other sites with inconsistent results (19–26). Curtin et al found increased likelihood of highly CpG-methylated in colon tumors for those with one or two variant MTHFR 1298C alleles, and the association was modified by high-risk dietary profiles (low folate and methionine intake and high alcohol use) (19). In other studies these genotypes were not associated with likelihood of p16 promoter hypermethylation of colorectal cancers (20–22). Similarly, MTHFR C677T, A1298C or MTR C2756G genotypes were no associated with E – cadherin and p16 promoter methylation in esophageal (23) and cervical cancers (25).
The strengths of our study include the population-based study design and a relatively large sample size, leading to more stable risk estimates. Nevertheless, the numbers of cases were small and the confidence intervals were wide. We had 80% power to detect odds ratios of 2.5 for the association between MTR genotype and methylation and an odds ration of 2.0 for the association between MTHFR polymorphisms and methylation. Additionally, the study applied the candidate gene approach and primarily focused on potential common genetic variants (>5%) and polymorphisms with amino acid changes. We cannot rule out the possibility that genetic polymorphisms of one-carbon metabolism other than those included in our study may be related to likelihood of methylation. Given multiple genes for protein involved in one-carbon metabolism (3), the confounding and/or modifying effects of other genes also cannot be excluded. Further lack of response among cases has potential for selection bias. Compared to participated cases, those non-participants were somewhat lower education level and older. However, the two groups were similar in terms of tumor stage, distant metastases, and other breast cancer risk factors. Furthermore, our inability to obtain the paraffin embedded breast tumor tissue for all cases may have led to bias. In comparisons of cases without available archived tumor tissue to those with available tissue, those with tissue were somewhat younger at diagnosis and higher TNM stage of breast tumor. However, the two groups were similar in terms of tumor size, histological grade, nuclear grade, ER and PR status. With regard to the validity of the measure of methylation in formalin fixed paraffin embedded tissue, a recent study showed a high correlation in methylation between paraffin embedded tumor tissues and fresh samples from the same subject, measured with a similar real time PCR method as ours, concluding that paraffin embedded samples are well suited for methyaltion assessment (27).
In summary, we found no evidence that these common polymorphisms of the MTHFR and MTR genes were associated with the prevalence of promoter methylation of E - cadherin, p16, and RAR-β2 genes in breast tumors.
Acknowledgements
This study would not have been possible without the support of all the study participants and the research staff of the Western New York Exposures and Breast Cancer (WEB) Study. This work was supported in part by the Department of Defense [DAMD 179616202, DAMD 17030446], United States Public Health Service (USPHS) National Cancer Institute [R01CA 092040], and National Institute on Alcohol Abuse and Alcoholism [P50 AA09802].
Funding: This work was funded in part by United States Public Health Service (USPHS) grant number R01CA92585 from the National Cancer Institute and Department of Defense grants number DAMD 170310446 and 170010417.
Reference
- 1.Szyf M, Pakneshan P, Rabbani SA. DNA methylation and breast cancer. Biochem Pharmacol. 2004;68:1187–1197. doi: 10.1016/j.bcp.2004.04.030. [DOI] [PubMed] [Google Scholar]
- 2.Agrawal A, Murphy RF, Agrawal DK. DNA methylation in breast and colorectal cancers. Mod Pathol. 2007;20:711–721. doi: 10.1038/modpathol.3800822. [DOI] [PubMed] [Google Scholar]
- 3.Choi SW, Mason JB. Folate status: effects on pathways of colorectal carcinogenesis. J Nutr. 2002;132:2413S–2418S. doi: 10.1093/jn/132.8.2413S. [DOI] [PubMed] [Google Scholar]
- 4.Graff JR, Herman JG, Lapidus RG, et al. E-cadherin expression is silence by DNA hypermethylation in human breast and prostate carcinomas. Cancer Res. 1995;55:5195–5199. [PubMed] [Google Scholar]
- 5.Esteller M, Corn PG, Baylin SB, et al. A gene hypermethylation profile of human cancer. Cancer Res. 2001;61:3225–3229. [PubMed] [Google Scholar]
- 6.Widschwendter M, Jones PA. DNA methylation and breast carcinogenesis. Oncogene. 2002;21:5462–5482. doi: 10.1038/sj.onc.1205606. [DOI] [PubMed] [Google Scholar]
- 7.Tao MH, Shields SP, Nie J, et al. DNA hypermethylation and clinicopathological features in breast cancer: the Western New York Exposures and Breast Cancer (WEB) Study. Breast Cancer Res Treat. 2008 doi: 10.1007/s10549-008-0028-z. Epub ahead of print] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Frosst P, Blom HJ, Milos R, et al. A candidate genetic risk factor for vascular disease: a common mutation in methylenetetrahydrofolate reductase. Nat Genet. 1995;10:111–113. doi: 10.1038/ng0595-111. [DOI] [PubMed] [Google Scholar]
- 9.Weisberg IS, Jacques PF, Selhub J, et al. The 1298A-->C polymorphism in methylenetetrahydrofolate reductase (MTHFR): in vitro expression and association with homocysteine. Atherosclerosis. 2001;156:409–415. doi: 10.1016/s0021-9150(00)00671-7. [DOI] [PubMed] [Google Scholar]
- 10.Sharp L, Little J. Polymorphisms in genes involved in folate metabolism and colorectal neoplasia: a HuGE review. Am J Epidemiol. 2004;159:423–443. doi: 10.1093/aje/kwh066. [DOI] [PubMed] [Google Scholar]
- 11.Harmon DL, Shields DC, Woodside JV, et al. Methionine synthase D919G polymorphism is a significant but modest determinant of circulating homocysteine concentrations. Genetic Epidemiol. 1999;17:298–309. doi: 10.1002/(SICI)1098-2272(199911)17:4<298::AID-GEPI5>3.0.CO;2-V. [DOI] [PubMed] [Google Scholar]
- 12.Macis D, Maisonneuve P, Johansson H, et al. Methylenetetrahydrofolate reductase (MTHFR) and breast cancer risk: a nested-case-control study and a pooled meta-analysis. Breast Cancer Res Treat. 2007;106:263–271. doi: 10.1007/s10549-006-9491-6. [DOI] [PubMed] [Google Scholar]
- 13.Stevens VL, McCullough ML, Pavluck AL, et al. Association of polymorphisms in one-carbon metabolism genes and postmenopausal breast cancer incidence. Cancer Epidemiol Biomarkers Prev. 2007;16:1140–1147. doi: 10.1158/1055-9965.EPI-06-1037. [DOI] [PubMed] [Google Scholar]
- 14.Lewis SJ, Harbord RM, Harris R, et al. Meta-analyses of observational and genetic association studies of folate intakes or levels and breast cancer risk. J Natl Cancer Inst. 2006;98:1607–1622. doi: 10.1093/jnci/djj440. [DOI] [PubMed] [Google Scholar]
- 15.Lissowska J, Gaudet MM, Brinton LA, et al. Genetic polymorphisms in the one-carbon metabolism pathway and breast cancer risk: a population-based case-control study and meta-analyses. Int J Cancer. 2007;120:2696–2703. doi: 10.1002/ijc.22604. [DOI] [PubMed] [Google Scholar]
- 16.Shrubsole MJ, Gao YT, Cai Q, et al. MTR and MTRR polymorphisms, dietary intake, and breast cancer risk. Cancer Epidemiol Biomarkers Prev. 2006;15:586–588. doi: 10.1158/1055-9965.EPI-05-0576. [DOI] [PubMed] [Google Scholar]
- 17.Justenhoven C, Hamann U, Pierl CB, et al. One-carbon metabolism and breast cancer risk: no association of MTHFR, MTR, TYMS polymorphisms in the GENICA study from Germany. Cancer Epidemiol Biomarkers Prev. 2005;14:3015–3018. doi: 10.1158/1055-9965.EPI-05-0592. [DOI] [PubMed] [Google Scholar]
- 18.Li SY, Rong M, Iacopetta B. Germ-line variants in methyl-group metabolism genes and susceptibility to DNA methylation in human breast cancer. Oncol Rep. 2006;15:221–225. [PubMed] [Google Scholar]
- 19.Curtin K, Slattery ML, Ulrich CM, et al. Genetic polymorphisms in one-carbon metabolism: associations with CpG island methylator phenotype (CIMP) in colon cancer and the modifying effects of diet. Carcinogenesis. 2007;28:1672–1679. doi: 10.1093/carcin/bgm089. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Clarizia AD, Bastos-Rodrigues L, Pena H, et al. Relationship of the thylenetetrahydrofolate reductase C677T polymorphism with microsatellite instability and promoter hypermethylation in sporadic colorectal cancer. Genetics and Molecular Res. 2006;5:315–322. [PubMed] [Google Scholar]
- 21.Kawakami K, Ruszkiewicz A, Bennett G, et al. DNA hypermethylation in the normal colonic mucosa of patients with colorectal cancer. Br J Cancer. 2006;94:593–598. doi: 10.1038/sj.bjc.6602940. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.van den Donk M, van Engeland M, Pellis L, et al. Dietary folate intake in combination with MTHFR C677T genotype and promoter methylation of tumor suppressor and DNA repair genes in sporadic colorectal adenomas. Cancer Epidemiol Biomarkers Prev. 2007;16:327–333. doi: 10.1158/1055-9965.EPI-06-0810. [DOI] [PubMed] [Google Scholar]
- 23.Wang JM, Sasco AJ, Fu CW, et al. Aberrant DNA methylation of P16, MGMT, and hMLH1 genes in combination with MTHFR C677T genetic polymorphism in esophageal squamous cell carcinoma. Cancer Epidemiol Biomarkers Prev. 2008;17:118–125. doi: 10.1158/1055-9965.EPI-07-0733. [DOI] [PubMed] [Google Scholar]
- 24.Kraunz KS, Hsiung D, McClean MD, et al. Dietary folate is associated with p16INK4A methylaiton in head and neck squamous cell carcinoma. Int J Cancer. 2006;119:1553–1557. doi: 10.1002/ijc.22013. [DOI] [PubMed] [Google Scholar]
- 25.Kang S, Kim JW, Kang GH, et al. Polymorphism in folate- and methionine-metabolizing enzyme and aberrant CpG island hypermethylation in uterine cervical cancer. Gynecol Oncol. 2005;96:173–180. doi: 10.1016/j.ygyno.2004.09.031. [DOI] [PubMed] [Google Scholar]
- 26.Siraj AK, Ibrahim M, Al-Rasheed M, et al. Genetic polymorphisms of methylenetetrahydrofolate reductase and promoter methylation of MGMT and FHIT genes in diffuse large B cell lymphoma risk in Middle East. Ann Hematol. 2007;86:887–895. doi: 10.1007/s00277-007-0350-2. [DOI] [PubMed] [Google Scholar]
- 27.Harbeck N, Nimmrich I, Hartmann A, et al. Multicenter study using paraffin-embedded tumor tissue testing PITX2 DNA methylation as a marker for outcome prediction in tamoxifen-treated, node-negative breast cancer patients. J of Clin Oncol. 2008 doi: 10.1200/JCO.2007.14.1697. [Epub ahead of print]. [DOI] [PubMed] [Google Scholar]