Dataset Information

Fruit and vegetable intake and risk of breast cancer by hormone receptor status.

ABSTRACT:

Background

Estrogen receptor-negative (ER(-)) breast cancer has few known or modifiable risk factors. Because ER(-) tumors account for only 15% to 20% of breast cancers, large pooled analyses are necessary to evaluate precisely the suspected inverse association between fruit and vegetable intake and risk of ER(-) breast cancer.

Methods

Among 993 466 women followed for 11 to 20 years in 20 cohort studies, we documented 19 869 estrogen receptor positive (ER(+)) and 4821 ER(-) breast cancers. We calculated study-specific multivariable relative risks (RRs) and 95% confidence intervals (CIs) using Cox proportional hazards regression analyses and then combined them using a random-effects model. All statistical tests were two-sided.

Results

Total fruit and vegetable intake was statistically significantly inversely associated with risk of ER(-) breast cancer but not with risk of breast cancer overall or of ER(+) tumors. The inverse association for ER(-) tumors was observed primarily for vegetable consumption. The pooled relative risks comparing the highest vs lowest quintile of total vegetable consumption were 0.82 (95% CI = 0.74 to 0.90) for ER(-) breast cancer and 1.04 (95% CI = 0.97 to 1.11) for ER(+) breast cancer (P (common-effects) by ER status < .001). Total fruit consumption was non-statistically significantly associated with risk of ER(-) breast cancer (pooled multivariable RR comparing the highest vs lowest quintile = 0.94, 95% CI = 0.85 to 1.04).

Conclusions

We observed no association between total fruit and vegetable intake and risk of overall breast cancer. However, vegetable consumption was inversely associated with risk of ER(-) breast cancer in our large pooled analyses.

SUBMITTER: Jung S

PROVIDER: S-EPMC3593764 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:To better understand the biology of hormone receptor-positive and negative breast cancer and to identify methylated gene markers of disease progression, we performed a genome-wide methylation array analysis on 103 primary invasive breast cancers and 21 normal breast samples using the Illumina Infinium HumanMethylation27 array that queried 27,578 CpG loci. Estrogen and/or progesterone receptor-positive tumors displayed more hypermethylated loci than ER-negative tumors. However, the hypermethylated loci in ER-negative tumors were clustered closer to the transcriptional start site compared to ER-positive tumors. An ER-classifier set of CpG loci was identified, which independently partitioned primary tumors into ER-subtypes. Forty (32 novel, 8 previously known) CpG loci showed differential methylation specific to either ER-positive or ER-negative tumors. Each of the 40 ER-subtype-specific loci was validated in silico using an independent, publicly available methylome dataset from The Cancer Genome Atlas (TCGA). In addition, we identified 100 methylated CpG loci that were significantly associated with disease progression; the majority of these loci were informative particularly in ER-negative breast cancer. Overall, the set was highly enriched in homeobox containing genes. This pilot study demonstrates the robustness of the breast cancer methylome and illustrates its potential to stratify and reveal biological differences between ER-subtypes of breast cancer. Further, it defines candidate ER-specific markers and identifies potential markers predictive of outcome within ER subgroups. Frozen breast cancer tissues that were excised from patients with Stage 1-3 disease prior to treatment (n=103) were retrieved from Surgical Pathology at Johns Hopkins Hospital (Baltimore, Maryland) and confirmed to contain > 50% epithelial cells. Normal breast organoids were prepared by enzymatic digestion of reduction mammoplasty specimens (n=15; median patient age = 52 years, range 47 to 71). Normal ducts from breast tissue > 2 cm away from the tumor (n=6) were isolated from cryosections using laser-capture micro-dissection (PALM MicroBeam, Carl Zeiss Microimaging, North America). To determine the differences in breast cancer biology/behavior between ER subtypes, we characterized methylation patterns at 8376 selected CpG loci according to ER status. These loci met two criteria: 1) showed the most variation across primary tumors (SD >0.100) and 2) had probe detection p-values <0.0001. To develop an epigenomic signature that predicts outcome in patients with breast cancer, we conducted differential methylation analysis on primary tumors from recurrent versus non-recurrent breast cancers. We used a subgroup of 82 well-annotated, invasive breast tumors derived from the discovery set of 103 tumors that included 44 ER-positive (7 recurrences) and 38 ER-negative (11 recurrences) breast cancers and independently queried the ER-positive and ER-negative tumor groups