Utilizing data from a population-based cohort of breast cancer cases, we found inverse associations between several micronutrients and genotypes in the one-carbon metabolism and all-cause mortality. To the best of our knowledge, our study is the first to systematically evaluate pre-diagnostic intake of B vitamins involved in one-carbon metabolism pathway in relation to breast cancer survival. This study is based on a strong biological rationale because one-carbon metabolism not only involves in regulation of prognosis-predictive genes in breast cancer but also is the major target for treatment of the disease (). Considering the high prevalence of these polymorphisms in the general population, results from the study can help us to identify factors that may influence disease outcomes.
B vitamins (B1
, thiamin; B2
, riboflavin; B3
, niacin; B6
, pyridoxine; B9
, folate; B12
, cobalamin) play important roles in cell metabolism, and some of them are cofactors involved in the one-carbon pathway. In a previous report (29
), we found that increased dietary intakes of B vitamins were associated with reduced risk of developing breast cancer. Herein, we reported a beneficial effect of B vitamins, B1
in particular, on survival in the same population of breast cancer cases. These findings imply that a healthy diet reduces a woman's risk of developing breast cancer, but should a breast cancer occur, the tumor would also display characteristics associated with a more favorable prognosis.
In this study, we found two genetic polymorphisms, MTHFR C677T
and BHMT G742A
, were inversely associated with all-cause mortality. MTHFR catalyzes an irreversible reaction and it is the rate-limiting step in folate metabolism. Changes in MTHFR activity may tilt the balance of one-carbon metabolism in favor of DNA synthesis at the expense of methyl supply (i.e. S-Adenosylmethionine) for methylation reactions. The C677T
polymorphism of MTHFR
results in an alanine
substitution and has been correlated with enzyme thermolability and reduced enzyme activity (34
). Lower MTHFR activity has been shown to decrease DNA methylation in animal experiments (35
). DNA methylation has been implicated in the silencing of ER, a prognosis-predictive gene (12
). Consistent with this reasoning, the TT
genotype was associated with ER+/PR+ tumors in our study population () leading to improved survival. This finding is based on a small sample size, and replication is warranted.
Although not directly involved in folate metabolism, BHMT is involved in the metabolism of homocysteine. BHMT may play a critical role in the remethylation of homocysteine when the folate-dependent pathway is compromised by either genetic or dietary factors (36
). The BHMT G742A
polymorphism was associated with overall survival in our study population; it is unknown whether homocysteine level correlates with breast cancer prognosis in our study population.
Many studies have been conducted to examine the effects of one-carbon metabolism polymorphisms on breast cancer risk, but reports of effects on subsequent survival are relatively sparse. There are two other studies that examined the effect of MTHFR
genotypes on breast cancer survival. Results from the Shanghai Breast Cancer study showed that MTHFR
genotypes were not associated with all-cause mortality, but the 677TT
genotype was associated with poor survival among those with late stage disease (37
). In our study, we observed a beneficial effect of the MTHFR677
T allele on all-cause mortality. Difference among these reports could be due to the difference in study populations, given that our population is overwhelmingly Caucasian, whereas the Shanghai Breast Cancer Study is restricted to Chinese women. Factors that may influence the MTHFR
-survival relationship, such as treatment modality, may also be different in these two populations. Results from a small cohort reported by Martin et al. showed that MTHFR1298
C allele was associated with worse survival compared to the AA genotype; furthermore, this effect was stronger in ER- patients (38
). This latter study is based on a cohort containing a mixture of Caucasian and African-American women and the sample size was relatively small (~250).
We did not observe any survival differences by genotype stratified by chemotherapy. Although our sample size is much larger than previous studies, statistical power is still limited in stratified analyses. In addition, because the LIBCSP is a population-based study, the breast cancer patients were treated in multiple institutions with non-standardized protocols. The majority of women in our study received adjuvant chemotherapy as part of their regular treatment for breast cancer. Specific information such as chemotherapy dose and duration were not available for all our study subjects, which limited our ability to examine the potential interaction between one-carbon metabolism and chemotherapy. Investigation of such relationships in the context of a larger population of breast cancer patients with more complete information on treatment modality is warranted, since it is plausible that these factors could potentially be used to tailor treatment and ultimately improve survival.
In our study, we did not find any substantial differences in terms of associations of one-carbon metabolism with all-cause mortality and breast cancer specific mortality. Vitamin B3
intake and BHMT (G742A
) polymorphism were associated with all-cause mortality but did not reach statistical significance for breast cancer specific mortality. Given the point estimates are similar, the wide confidence interval could be a result of limited study outcome (~130 death). Results on breast cancer-specific mortality may help us better understand the role of one-carbon metabolism in breast cancer progression and to develop more efficient treatment for this disease. Accurate assessment on cause of death is crucial in this type of investigation (39
). The reliability of the cause of death listed on the death certificate, particularly when looking at a specific cancer site may be questionable, e.g. sometimes a metastatic site may be recorded as the cause of death (42
). Thus, our findings based on all-cause mortality may be more valid. In addition, estimation of overall survival (with death as the end point regardless of the specific cause) is of public health significance and provides us with better power for detecting associations (44
We utilized the dietary information collected at the baseline interview, which reflects intake patterns one year prior to the interview including the months just prior to and at diagnosis. Recall of this information was ascertained prior to the study outcome (i.e. death), thus any possible misclassification is likely to be non-differential. However, it is possible that patients change their lifestyle after a diagnosis of cancer (45
). Consequently, our results should be interpreted with caution. Studies have indicated that after breast cancer diagnosis, women are motivated to change their diet, but this is observed primarily in younger women (47
); our study population, on the other hand, is primarily composed of postmenopausal women. Interestingly, a substantial percentage (50%) of cancer survivors has been reported to continue to engage in health-risk behaviors (45
). As discussed in a recent review, supplement use among breast cancer patients is high and frequently increases after diagnosis (49
). We were unable to identify studies that specifically address the issue of whether breast cancer survivors change their dietary intake of foods containing B vitamins after diagnosis. If women in our study continued to follow their pre-diagnostic diets after their breast cancer diagnosis, then the implications of our results are that women in the general population should be encouraged to consume more B vitamins.
One potential issue to consider in interpreting our results is whether our analyses should have considered the potential confounding effects of tumor stage (or its surrogates tumor size and first course of treatment). However, because tumor stage is more likely a causal intermediate (e.g. the biological link between the exposure with the outcome), it would be epidemiologically inappropriate to include tumor stage in the model. However, in sub-analyses we did consider the potential confounding effects of tumor size and first course of treatment (as surrogates for tumor stage, which was not reliably recorded on the medical record for all cases), and found that our results remain unchanged.
A potential limitation of our study is that we focused solely on the dominant model in our genetic association analyses. Consideration of other models would be of interest, but because our study power was constrained by the number of deaths (about 130) in our cohort of breast cancer cases, the results would be unstable and perhaps misleading. Another limitation of our study is its limited power for testing potential gene-gene and gene-diet interactions. Thus we did not investigate these interactions in our analysis.
In summary, results from our population-based study suggest that in addition to its role in breast cancer etiology, one-carbon metabolism may be an important pathway that can be targeted to improve breast cancer survival among women with breast cancer.