Vitamin D Receptor Polymorphisms and Breast Cancer Risk: Results from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium

Background: Vitamin D is hypothesized to lower the risk of breast cancer by inhibiting cell proliferation via the nuclear vitamin D receptor (VDR). Two common single nucleotide polymorphisms (SNP) in the VDR gene ( VDR ), rs1544410 ( Bsm I), and rs2228570 ( Fok I), have been inconsistently associated with breast cancer risk. Increased risk has been reported for the Fok I ff genotype, which encodes a less transcriptionally active isoform of VDR , and reduced risk has been reported for the Bsm I BB genotype, a SNP in strong linkage disequilibrium with a 3′-untranslated region, which may influence VDR mRNA stability. Methods: We pooled data from 6 prospective studies in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium to examine associations between these SNPs and breast cancer among >6,300 cases and 8,100 controls for each SNP using conditional logistic regression. Results: The odds ratio (OR) for the rs2228570 ( Fok I) ff versus FF genotype in the overall population was statistically significantly elevated [OR, 1.16; 95% confidence interval (95% CI), 1.04-1.28] but was weaker once data from the cohort with previously published positive findings were removed (OR, 1.10; 95% CI, 0.98-1.24). No association was noted between rs1544410 ( Bsm I) BB and breast cancer risk overall (OR, 0.98; 95% CI, 0.89-1.09), but the BB genotype was associated with a significantly lower risk of advanced breast cancer (OR, 0.74; 95% CI, 0.60-0.92). Conclusions: Although the evidence for independent contributions of these variants to breast cancer susceptibility remains equivocal, future large studies should integrate genetic variation in VDR with biomarkers of vitamin D status. (Cancer Epidemiol Biomarkers Prev 2009;18(1):297–305

Added value of serum hormone measurements in risk prediction models for breast cancer for women not using exogenous hormones : Results from the EPIC cohort

PURPOSE: Circulating hormone concentrations are associated with breast cancer risk, with well-established associations for postmenopausal women. Biomarkers may represent minimally invasive measures to improve risk prediction models. EXPERIMENTAL DESIGN: We evaluated improvements in discrimination gained by adding serum biomarker concentrations to risk estimates derived from risk prediction models developed by Gail et al. and Pfeiffer et al. using a nested case-control study within the EPIC cohort including 1217 breast cancer cases and 1976 matched controls. Participants were pre- or postmenopausal at blood collection. Circulating sex steroids, prolactin, insulin-like growth factor I, IGF binding protein 3 and sex hormone binding globulin (SHBG) were evaluated using backward elimination separately in women pre- and postmenopausal at blood collection. Improvement in discrimination was evaluated as the change in C-statistic from a modified Gail or Pfeiffer risk score alone vs. models including the biomarkers and risk score. Internal validation with bootstrapping (1000-fold) was used to adjust for over-fitting. RESULTS: Among women postmenopausal at blood collection, estradiol, testosterone and SHBG were selected into the prediction models. For breast cancer overall, discrimination was 5.3 percentage points higher than the modified Gail model alone, and 3.4 percentage points higher than the Pfeiffer model alone, after accounting for over-fitting. Discrimination was more markedly improved for estrogen receptor (ER)+ disease (percentage point change in C-statistic: 7.2, Gail; 4.8 Pfeiffer). We observed no improvement in discrimination among women premenopausal at blood collection. CONCLUSIONS: Integration of hormone measurements in clinical risk prediction models may represent a strategy to improve breast cancer risk stratification

Vitamin D receptor polymorphisms and breast cancer risk: results from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium. Cancer Epidemiol

Abstract Background: Vitamin D is hypothesized to lower the risk of breast cancer by inhibiting cell proliferation via the nuclear vitamin D receptor (VDR). Two common single nucleotide polymorphisms (SNP) in the VDR gene (VDR), rs1544410 (BsmI), and rs2228570 (FokI), have been inconsistently associated with breast cancer risk. Increased risk has been reported for the FokI ff genotype, which encodes a less transcriptionally active isoform of VDR, and reduced risk has been reported for the BsmI BB genotype, a SNP in strong linkage disequilibrium with a 3 ¶-untranslated region, which may influence VDR mRNA stability. Methods: We pooled data from 6 prospective studies in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium to examine associations between these SNPs and breast cancer among >6,300 cases and 8,100 controls for each SNP using conditional logistic regression

Body mass index and breast cancer survival:a Mendelian randomization analysis

Abstract Background: There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival from breast cancer. Methods: We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis. Results: BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER)-positive cases [hazard ratio (HR) = 1.11, per one-unit increment of GRS, 95% confidence interval (CI) 1.01–1.22, P = 0.03). We observed no association for ER-negative cases (HR = 1.00, per one-unit increment of GRS, 95% CI 0.89–1.13, P = 0.95). Conclusions: Our findings suggest a causal effect of increased BMI on reduced breast cancer survival for ER-positive breast cancer. There is no evidence of a causal effect of higher BMI on survival for ER-negative breast cancer cases