Urinary estrogen metabolites and long-term mortality following breast cancer

Background: Estrogen metabolite concentrations of 2-hydroxyestrone (2-OHE1) and 16-hydroxyestrone (16-OHE1) may be associated with breast carcinogenesis. However, no study has investigated their possible impact on mortality after breast cancer. Methods: This population-based study was initiated in 1996–1997 with spot urine samples obtained shortly after diagnosis (mean ¼ 96 days) from 683 women newly diagnosed with first primary breast cancer and 434 age-matched women without breast cancer. We measured urinary concentrations of 2-OHE1 and 16-OHE1 using an enzyme-linked immunoassay. Vital status was determined via the National Death Index (n ¼ 244 deaths after a median of 17.7 years of follow-up). We used multivariable-adjusted Cox proportional hazards to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the estrogen metabolites-mortality association. We evaluated effect modification using likelihood ratio tests. All statistical tests were two-sided. Results: Urinary concentrations of the 2-OHE1 to 16-OHE1 ratio (>median of 1.8 vs <median) were inversely associated with all-cause mortality (HR ¼ 0.74, 95% CI ¼ 0.56 to 0.98) among women with breast cancer. Reduced hazard was also observed for breast cancer mortality (HR ¼ 0.73, 95% CI ¼ 0.45 to 1.17) and cardiovascular diseases mortality (HR ¼ 0.76, 95% CI ¼ 0.47 to 1.23), although the 95% confidence intervals included the null. Similar findings were also observed for women without breast cancer. The association with all-cause mortality was more pronounced among breast cancer participants who began chemotherapy before urine collection (n ¼ 118, HR ¼ 0.42, 95% CI ¼ 0.22 to 0.81) than among those who had not (n ¼ 559, HR ¼ 0.98, 95% CI ¼ 0.72 to 1.34; Pinteraction ¼ .008). Conclusions: The urinary 2-OHE1 to 16-OHE1 ratio may be inversely associated with long-term all-cause mortality, which may depend on cancer treatment status at the time of urine collection

Dietary intake of fish, polyunsaturated fatty acids, and survival after breast cancer: A population-based follow-up study on Long Island, New York

BACKGROUND In laboratory experiments, ω-3 polyunsaturated fatty acids (PUFAs) have been found to reduce inflammatory eicosanoids resulting from ω-6 PUFA metabolism via competitive inhibition, and the ω-3-induced cytotoxic environment increases apoptosis and reduces cell growth in breast cancer cells. To the authors' knowledge, epidemiologic investigations regarding whether dietary ω-3 PUFA intake benefits survival after breast cancer are limited and inconsistent. METHODS The authors used resources from a population-based follow-up study conducted on Long Island, New York, among 1463 women newly diagnosed with first primary breast cancer who were interviewed an average of approximately 3 months after diagnosis to assess risk and prognostic factors, including dietary intake (using a food frequency questionnaire). Vital status was determined through 2011, yielding a median follow-up of 14.7 years and 485 deaths. Adjusted hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated using Cox proportional hazards regression. RESULTS All-cause mortality was reduced among women with breast cancer reporting the highest quartile of intake (compared with never) for tuna (HR, 0.71; 95% CI, 0.55-0.92), other baked/broiled fish (HR, 0.75; 95% CI, 0.58-0.97), and the dietary long-chain ω-3 PUFAs docosahexaenoic acid (HR, 0.71; 95% CI, 0.55-0.92) and eicosapentaenoic acid (HR, 0.75; 95% CI, 0.58-0.97). CONCLUSIONS All-cause mortality was reduced by 16% to 34% among women with breast cancer who reported a high intake of fish and long-chain ω-3 PUFAs. Long-chain ω-3 PUFA intake from fish and other dietary sources may provide a potential strategy to improve survival after breast cancer. Cancer 2015;121:2244-2252

Associations of obesity and circulating insulin and glucose with breast cancer risk: a Mendelian randomization analysis.

BACKGROUND: In addition to the established association between general obesity and breast cancer risk, central obesity and circulating fasting insulin and glucose have been linked to the development of this common malignancy. Findings from previous studies, however, have been inconsistent, and the nature of the associations is unclear. METHODS: We conducted Mendelian randomization analyses to evaluate the association of breast cancer risk, using genetic instruments, with fasting insulin, fasting glucose, 2-h glucose, body mass index (BMI) and BMI-adjusted waist-hip-ratio (WHRadj BMI). We first confirmed the association of these instruments with type 2 diabetes risk in a large diabetes genome-wide association study consortium. We then investigated their associations with breast cancer risk using individual-level data obtained from 98 842 cases and 83 464 controls of European descent in the Breast Cancer Association Consortium. RESULTS: All sets of instruments were associated with risk of type 2 diabetes. Associations with breast cancer risk were found for genetically predicted fasting insulin [odds ratio (OR) = 1.71 per standard deviation (SD) increase, 95% confidence interval (CI) = 1.26-2.31, p  =  5.09  ×  10-4], 2-h glucose (OR = 1.80 per SD increase, 95% CI = 1.3 0-2.49, p  =  4.02  ×  10-4), BMI (OR = 0.70 per 5-unit increase, 95% CI = 0.65-0.76, p  =  5.05  ×  10-19) and WHRadj BMI (OR = 0.85, 95% CI = 0.79-0.91, p  =  9.22  ×  10-6). Stratified analyses showed that genetically predicted fasting insulin was more closely related to risk of estrogen-receptor [ER]-positive cancer, whereas the associations with instruments of 2-h glucose, BMI and WHRadj BMI were consistent regardless of age, menopausal status, estrogen receptor status and family history of breast cancer. CONCLUSIONS: We confirmed the previously reported inverse association of genetically predicted BMI with breast cancer risk, and showed a positive association of genetically predicted fasting insulin and 2-h glucose and an inverse association of WHRadj BMI with breast cancer risk. Our study suggests that genetically determined obesity and glucose/insulin-related traits have an important role in the aetiology of breast cancer

A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records

Background: The identification of new uses for existing drug therapies has the potential to identify treatments for comorbid conditions that have the added benefit of glycemic control while also providing a rapid, low-cost approach to drug (re)discovery. Methods: We developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically-predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug–gene pairs. These drug–gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR). Findings: After filtering on sample size, 20 candidate drug–gene pairs were validated and various medications demonstrated evidence of glycemic regulation including two anti-hypertensive classes: angiotensin-converting enzyme inhibitors as well as calcium channel blockers (CCBs). The CCBs demonstrated the strongest evidence of glycemic reduction in both validation approaches (SCCS HbA1c and glucose reduction: −0.11%, p = 0.01 and −0.85 mg/dL, p = 0.02, respectively; MR: OR = 0.84, 95% CI = 0.81, 0.87, p = 5.0 x 10–25). Interpretation: Our results support CCBs as a strong candidate medication for blood glucose reduction in addition to cardiovascular disease reduction. Further, these results support the adaptation of this approach for use in future drug-repurposing efforts for other conditions. Funding: National Institutes of Health, Medical Research Council Integrative Epidemiology Unit at the University of Bristol, UK Medical Research Council, American Heart Association, and Department of Veterans Affairs (VA) Informatics and Computing Infrastructure and VA Cooperative Studies Program. © 2023 The AuthorsOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]