Inclusion of endogenous hormone levels in risk prediction models of postmenopausal breast cancer

Update on breast cancer risk prediction and prevention

PURPOSE OF REVIEW

Breast cancer is the most common cancer in women worldwide. This review will focus on current prevention strategies for women at high risk.

RECENT FINDINGS

The identification of women who are at high risk of developing breast cancer is key to breast cancer prevention. Recent findings have shown that the inclusion of breast density and a panel of low-penetrance genetic polymorphisms can improve risk estimation compared with previous models. Preventive therapy with aromatase inhibitors has produced large reductions in breast cancer incidence in postmenopausal women. Tamoxifen confers long-term protection and is the only proven preventive treatment for premenopausal women. Several other agents, including metformin, bisphosphonates, aspirin and statins, have been found to be effective in nonrandomized settings.

SUMMARY

There are many options for the prevention of oestrogen-positive breast cancer, in postmenopausal women who can be given a selective oestrogen receptor modulator or an aromatase inhibitor. It still remains unclear how to prevent oestrogen-negative breast cancer, which occurs more often in premenopausal women. Identification of women at high risk of the disease is crucial, and the inclusion of breast density and a panel of genetic polymorphisms, which individually have low penetrance, can improve risk assessment.

The relationship between bilateral oophorectomy and plasma hormone levels in postmenopausal women

Oophorectomy prior to natural menopause reduces breast cancer risk. We evaluated whether timing of oophorectomy (during premenopause vs. postmenopause) or hysterectomy was associated with hormone levels, specifically estradiol, estrone, estrone sulfate, testosterone, sex hormone binding globulin (SHBG), dehydroepiandrosterone sulfate (DHEAS), and prolactin, using data from the Nurses' Health Study. We included 2,251 postmenopausal women not using hormones who provided blood samples in 1989-1990 and/or 2000-2002, and who were controls in various nested case-control studies. We used multivariate linear mixed-effects models to assess geometric mean hormone levels by surgery status. Bilateral oophorectomy was associated with 25% lower testosterone levels versus women with natural menopause (20.8 vs. 15.5 ng/dL) (P < 0.0001) with no effect of timing of surgery (P = 0.80). SHBG levels were lower among women with a premenopausal oophorectomy (52.2 nmol/L) versus those with natural menopause (58.1 nmol/L) or a postmenopausal oophorectomy (62.0 nmol/L) (P = 0.02). There was no significant association of oophorectomy with estradiol, estrone, estrone sulfate, DHEAS, or prolactin levels (P ≥ 0.23). A simple hysterectomy was associated with a significant 8% lower testosterone (P = 0.03) and 14 % lower DHEAS (P = 0.02) levels compared with women with natural menopause but not with other hormone levels. Although limited by small numbers, our findings suggest no differential influence of timing of surgery on sex hormone levels. The reduction of testosterone levels in women with oophorectomy or hysterectomy suggests a possible role of this hormone in postmenopausal breast cancer development.

Gene variations in oestrogen pathways, CYP19A1, daily 17β-estradiol and mammographic density phenotypes in premenopausal women

INTRODUCTION

High mammographic density is an established breast cancer risk factor, and circulating oestrogen influences oestrogen-regulating gene expression in breast cancer development. However, less is known about the interrelationships of common variants in the CYP19A1 gene, daily levels of oestrogens, mammographic density phenotypes and body mass index (BMI) in premenopausal women.

METHODS

Based on plausible biological mechanisms related to the oestrogen pathway, we investigated the association of single nucleotide polymorphisms (SNPs) in CYP19A1, 17β-estradiol and mammographic density in 202 premenopausal women. DNA was genotyped using the Illumina Golden Gate platform. Daily salivary 17β-estradiol concentrations were measured throughout an entire menstrual cycle. Mammographic density phenotypes were assessed using a computer-assisted method (Madena). We determined associations using multivariable linear and logistic regression models.

RESULTS

The minor alleles of rs749292 were positively (P = 0.026), and the minor alleles of rs7172156 were inversely (P = 0.002) associated with daily 17β-estradiol. We observed an 87% lower level of daily 17β-estradiol throughout a menstrual cycle in heavier women (BMI >23.6 kg/m(2)) of rs7172156 with minor genotype aa compared with major genotype AA. Furthermore, the rs749292 minor alleles were inversely associated with absolute mammographic density (P = 0.032). Lean women with rs749292 minor alleles had 70 to 80% lower risk for high absolute mammographic density (>32.4 cm(2)); Aa: odds ratio (OR) = 0.23 (95% CI 0.07 to 0.75). Lean women with rs7172156 minor homozygous genotype had OR 5.45 for high absolute mammographic density (aa: OR = 5.45 (95% CI 1.13 to 26.3)).

CONCLUSION

Our findings suggest that two SNPs in CYP19A1, rs749292 and rs7172156, are associated with both daily oestrogen levels and mammographic density phenotypes. BMI may modify these associations, but larger studies are needed.

Risk determination and prevention of breast cancer

Breast cancer is an increasing public health problem. Substantial advances have been made in the treatment of breast cancer, but the introduction of methods to predict women at elevated risk and prevent the disease has been less successful. Here, we summarize recent data on newer approaches to risk prediction, available approaches to prevention, how new approaches may be made, and the difficult problem of using what we already know to prevent breast cancer in populations. During 2012, the Breast Cancer Campaign facilitated a series of workshops, each covering a specialty area of breast cancer to identify gaps in our knowledge. The risk-and-prevention panel involved in this exercise was asked to expand and update its report and review recent relevant peer-reviewed literature. The enlarged position paper presented here highlights the key gaps in risk-and-prevention research that were identified, together with recommendations for action. The panel estimated from the relevant literature that potentially 50% of breast cancer could be prevented in the subgroup of women at high and moderate risk of breast cancer by using current chemoprevention (tamoxifen, raloxifene, exemestane, and anastrozole) and that, in all women, lifestyle measures, including weight control, exercise, and moderating alcohol intake, could reduce breast cancer risk by about 30%. Risk may be estimated by standard models potentially with the addition of, for example, mammographic density and appropriate single-nucleotide polymorphisms. This review expands on four areas: (a) the prediction of breast cancer risk, (b) the evidence for the effectiveness of preventive therapy and lifestyle approaches to prevention, (c) how understanding the biology of the breast may lead to new targets for prevention, and (d) a summary of published guidelines for preventive approaches and measures required for their implementation. We hope that efforts to fill these and other gaps will lead to considerable advances in our efforts to predict risk and prevent breast cancer over the next 10 years.