Serum prolactin levels are positively associated with mammographic density in postmenopausal women

Reproductive Factors Related to Childbearing and a Novel Automated Mammographic Measure, V

BACKGROUND

We investigated the associations between several reproductive factors related to childbearing and the variation (V) measure (a novel, objective, single summary measure of breast image intensity) by menopausal status.

METHODS

Our study included 3,814 cancer-free women within the Nurses' Health Study (NHS) and NHSII cohorts. The data on reproductive variables and covariates were obtained from biennial questionnaires closest to the mammogram date. V-measures were obtained from mammographic images using a previously developed algorithm capturing the standard deviation of pixel values. We used multivariate linear regression to examine the associations of parity, age at first birth, time between menarche and first birth, time since last pregnancy, and lifetime breastfeeding duration with V-measure, adjusting for breast cancer risk factors, including the percentage of mammographic density (PMD). We further examined whether these associations were statistically accounted for (mediated) by PMD.

RESULTS

Among premenopausal women, none of the reproductive factors were associated with V. Among postmenopausal women, inverse associations of parity and positive associations of age at first birth with V were mediated by PMD (percent mediated: nulliparity: 66.7%, P < 0.0001; parity: 50.5%, P < 0.01; age at first birth 76.1%, P < 0.001) and were no longer significant in PMD-adjusted models. Lifetime duration of breastfeeding was positively associated with V [>36 vs. 0 ≤1 months β = 0.29; 95% confidence interval (CI) 0.07; 0.52, Ptrend < 0.01], independent of PMD.

CONCLUSIONS

Parity, age at first birth, and breastfeeding were associated with postmenopausal V.

IMPACT

This study highlights associations of reproductive factors with mammographic image intensity.

The association between mammographic density and breast cancer molecular subtypes: a systematic review and meta-analysis

AIM

To conduct a systematic review and meta-analysis to evaluate the whether high mammographic density (MD) is differentially associated with all subtypes of breast cancer.

MATERIALS AND METHODS

The PubMed, Cochrane Library, and Embase databases were searched systematically in October 2022 to include all studies that investigated the association between MD and breast cancer subtype. Aggregate data of 17,193 breast cancer cases from 23 studies were selected, including five cohort/case-control and 18 case-only studies. The relative risk (RR) of MD were combined using random/fixed effects models for case-control studies, and for case-only studies, relative risk ratios (RRRs) were a combination of luminal A, luminal B, and HER2-positive versus triple-negative tumours.

RESULTS

Women in the highest density category in case-control/cohort studies had a 2.24-fold (95% confidence interval [CI] 1.53, 3.28), 1.81-fold (95% CI 1.15, 2.85), 1.44-fold (95% CI 1.14, 1.81), and 1.59-fold (95% CI 0.89, 2.85) higher risk of triple-negative, HER-2 (human epidermal growth factor receptor 2) positive, luminal A, and luminal B breast cancer compared to women in the lowest density category. RRRs for breast tumours being luminal A, luminal B, and HER-2 positive versus triple-negative in case-only studies were 1.62 (95% CI 1.14, 2.31), 1.81 (95% CI 1.22, 2.71) and 2.58 (95% CI 1.63, 4.08), respectively, for BIRADS 4 versus BIRADS 1.

CONCLUSION

The evidence indicates MD is a potent risk factor for the majority of breast cancer subtypes to different degrees. Increased MD is more strongly linked to HER-2-positive cancers compared to other breast cancer subtypes. The application of MD as a subtype-specific risk marker may facilitate the creation of personalised risk prediction models and screening procedures.

Hormone and receptor activator of NF-κB (RANK) pathway gene expression in plasma and mammographic breast density in postmenopausal women

Background

Hormones impact breast tissue proliferation. Studies investigating the associations of circulating hormone levels with mammographic breast density have reported conflicting results. Due to the limited number of studies, we investigated the associations of hormone gene expression as well as their downstream mediators within the plasma with mammographic breast density in postmenopausal women.

Methods

We recruited postmenopausal women at their annual screening mammogram at Washington University School of Medicine, St. Louis. We used the NanoString nCounter platform to quantify gene expression of hormones (prolactin, progesterone receptor (PGR), estrogen receptor 1 (ESR1), signal transducer and activator of transcription (STAT1 and STAT5), and receptor activator of nuclear factor-kB (RANK) pathway markers (RANK, RANKL, osteoprotegerin, TNFRSF18, and TNFRSF13B) in plasma. We used Volpara to measure volumetric percent density, dense volume, and non-dense volume. Linear regression models, adjusted for confounders, were used to evaluate associations between gene expression (linear fold change) and mammographic breast density.

Results

One unit increase in ESR1, RANK, and TNFRSF18 gene expression was associated with 8% (95% CI 0–15%, p value = 0.05), 10% (95% CI 0–20%, p value = 0.04) and % (95% CI 0–9%, p value = 0.04) higher volumetric percent density, respectively. There were no associations between gene expression of other markers and volumetric percent density. One unit increase in osteoprotegerin and PGR gene expression was associated with 12% (95% CI 4–19%, p value = 0.003) and 7% (95% CI 0–13%, p value = 0.04) lower non-dense volume, respectively.

Conclusion

These findings provide new insight on the associations of plasma hormonal and RANK pathway gene expression with mammographic breast density in postmenopausal women and require confirmation in other studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-022-01522-2.

Prolactin: The Third Hormone in Breast Cancer

Prolactin coordinates with the ovarian steroids to orchestrate mammary development and lactation, culminating in nourishment and an increasingly appreciated array of other benefits for neonates. Its central activities in mammary epithelial growth and differentiation suggest that it plays a role(s) in breast cancer, but it has been challenging to identify its contributions, essential for incorporation into prevention and treatment approaches. Large prospective epidemiologic studies have linked higher prolactin exposure to increased risk, particularly for ER+ breast cancer in postmenopausal women. However, it has been more difficult to determine its actions and clinical consequences in established tumors. Here we review experimental data implicating multiple mechanisms by which prolactin may increase the risk of breast cancer. We then consider the evidence for role(s) of prolactin and its downstream signaling cascades in disease progression and treatment responses, and discuss how new approaches are beginning to illuminate the biology behind the seemingly conflicting epidemiologic and experimental studies of prolactin actions across diverse breast cancers.

Mammographic breast density and IGF-1 gene polymorphisms rs1520220, rs2946834 and rs6219 in Polish women

Aim of the study

The aim of the study was to analyze three single nucleotide polymorphisms – rs1520220, rs2946834, rs6219 – of the IGF-1 gene in the context of breast mammographic density.

Material and methods

The research material included 202 samples of the peripheral blood of women with increased mammographic breast density and 238 samples of the epithelium from the oral mucosa of women without diagnosed pathological changes of the breast and with no family history of breast and/or ovarian cancer. The real-time polymerase chain reaction method was applied for analysis of polymorphisms.

Results

rs1520220 polymorphism was associated with increased mammographic density of the breasts. The presence of the CC genotype in the IGF-1 gene increased the risk of developing higher breast density visible in mammography by 2.43-fold. CC homozygotes (rs1520220) correlated with higher Breast Imaging-Reporting and Data System scale (3 vs. 4 and 5) (OR = 5.6; 95% CI: 1.82–16.3, p = 0.001). In the present study no relationship was detected between rs6219 and rs2946834 polymorphism and mammographic breast density.

Conclusions

The results suggest that the rs1520220 polymorphism of the IGF-1 gene plays an important role in the occurrence of increased mammographic breast density.

Single nucleotide polymorphisms of insulin-like growth factor gene and mammographic breast density

Aim of the study

To analyze six single nucleotide polymorphisms (SNPs): rs1520220, rs2945834, rs5747694, rs6214, rs6219, rs5742678. An attempt was made to assess the significance of the above IGF-1 gene polymorphisms as prognostic and predictive factors in Polish women with diagnosed increased breast mammographic density.

Material and methods

The study included women diagnosed with an increased breast mammographic density (n = 98), breast cancer (n = 135) and women as a control group (n = 60). The method used to detect polymorphisms in the IGF-1 gene was the analysis of single-stranded DNA conformation polymorphism (SSCP-PCR) and Sanger’s sequencing.

Results

In the case of rs1520220 polymorphism, the genotype CC was found to increase the risk of breast cancer (OR = 2.6 95% CI 1.01-6.5, p = 0.04). Analysis of the rs2945834 polymorphism revealed that the occurrence of the G allele reduced the risk of breast cancer, while the occurrence of the A allele increased the risk of disease almost twice (OR = 0.55 95% CI). Among women who are heterozygous in terms of rs5747694 polymorphism (TG), the risk of breast cancer is twice as high as in the control group. The SNPs in the study group did not correlate with mammographic breast density.

Conclusions

The results obtained in the course of the analysis indicate that polymorphisms rs1520220, rs2946834, rs5747694 gene IGF-1 are associated with the occurrence of breast cancer but not with increased mammographic density. Summing up, the association between the polymorphisms of IGF-1 and the risk of developing breast cancer is independent of mammographic density.

Hormonal determinants of mammographic density and density change

Background

Mammographic density (MD) is a strong risk factor for breast cancer. We examined how endogenous plasma hormones are associated with average MD area (cm²) and annual MD change (cm²/year).

Methods

This study within the prospective KARMA cohort included analyses of plasma hormones of 1040 women. Hormones from the progestogen (n = 3), androgen (n = 7), oestrogen (n = 2) and corticoid (n = 5) pathways were analysed by ultra-performance supercritical fluid chromatography-tandem mass spectrometry (UPSFC-MS/MS), as well as peptide hormones and proteins (n = 2). MD was measured as a dense area using the STRATUS method (mean over the left and right breasts) and mean annual MD change over time.

Results

Greater baseline mean MD was associated with overall higher concentrations of progesterone (average + 1.29 cm² per doubling of hormone concentration), 17OH-progesterone (+ 1.09 cm²), oesterone sulphate (+ 1.42 cm²), prolactin (+ 2.11 cm²) and SHBG (+ 4.18 cm²), and inversely associated with 11-deoxycortisol (− 1.33 cm²). The association between MD and progesterone was confined to the premenopausal women only. The overall annual MD change was − 0.8 cm². Hormones from the androgen pathway were statistically significantly associated with MD change. The annual MD change was − 0.96 cm² and − 1.16 cm² lesser, for women in the highest quartile concentrations of testosterone and free testosterone, respectively, compared to those with the lowest concentrations.

Conclusions

Our results suggest that, whereas hormones from the progestogen, oestrogen and corticoid pathways drive baseline MD, MD change over time is mainly driven by androgens. This study emphasises the complexity of risk factors for breast cancer and their mechanisms of action.

Is mammographic density a marker of breast cancer phenotypes?

PURPOSE

To investigate the association between mammographic density (MD) phenotypes and both clinicopathologic features of breast cancer (BC) and tumor location.

METHODS

MD was measured for 297 BC-affected females using qualitative (visual method) and quantitative (fully automated area-based method) approaches. Radiologists' description, visible external markers, and surgical scar were used to establish the location of tumors. Binary logistic regression models were used to assess the association between MD phenotypes and BC clinicopathologic features.

RESULTS

Categorical and numerical MD measures showed no association with clinicopathologic features of BC (p > 0.05). Participants with higher BI-RADS scores [(51-75% glandular) and (> 75% glandular)] (p < 0.001), and percent density (PD) categories [PD (21-49%) and PD ≥ 50%] (p = 0.01) were more likely to have tumors emanating from dense areas. Additionally, tumors were commonly found in dense regions of the breast among patients with higher medians of PD (p = 0.001), dense area (DA) (p = 0.02), and lower medians of non-dense area (NDA) (p < 0.001). Adjusted logistic regression models showed that high BI-RADS density (> 75% glandular) has an almost fivefold increased odds of tumors developing within dense areas (OR 4.99, 95% CI 0.93-25.9; p = 0.05. PD (OR 1.02, 95% CI 1-1.03, p = 0.002) and NDA (OR 0.99, 95% CI 0.991-0.997, p < 0.001) had very small effect on tumor location. Compared to tumors within non-dense areas, tumors in dense areas tended to exhibit human epidermal growth factor receptor 2 positive (p = 0.05) and carcinoma in situ (p = 0.01) characteristics.

CONCLUSION

MD shows no significant association with clinicopathologic features of BC. However, BC was more likely to originate from dense tissue, with tumors in dense regions having human epidermal growth receptor 2 positive and carcinoma in situ characteristics.

Association between mammographic density and tumor marker-defined breast cancer subtypes: a case-control study

High mammographic density (MD) is the most important risk factor for breast cancer. This study aimed to clarify the relationship between MD and breast cancer subtypes defined by tumor markers. We enrolled 642 women with breast cancer (69% premenopausal) and 1241 controls matched for age and menopausal status. Absolute mammographic dense area (ADA), percent mammographic dense area (PDA), and nondense area were assessed using a computer-assisted thresholding technique. We classified breast cancer cases into four subtypes using information on tumor marker expression such as estrogen receptor (ER), progesterone receptor (PR), and Cerb2 receptor (HER2); luminal A (ER+ and/or PR+, HER2-), luminal B (ER+ and/or PR+, HER2+), HER2-overexpressing (ER-, PR-, and HER2+), and triple-negative (ER-, PR-, and HER2-). Analysis was carried out using a conditional logistic regression model with adjustment for covariates. ADA and PDA were associated positively with the risk of breast cancer overall. Both ADA and PDA tended to have a positive association with breast cancer with any ER, any PR, or HER2-, but not for HER2+. The risk of luminal A breast cancer increased significantly 1.11 times (95% confidence interval: 1.01-1.23) for ADA and 1.12 times (95% confidence interval: 1.01-1.24) for PDA, estimated per 1 SD of the age and BMI-adjusted MD. However, the risk of breast cancer with luminal B, HER2-overexpressing, and triple-negative subtypes did not differ (P>0.10). Differential associations between MD measures and breast cancer by tumor marker status or tumor marker-defined subtypes were not detected. These findings suggested that the association between MD and breast cancer subtype may be because of other causal pathways.

Inclusion of Plasma Prolactin Levels in Current Risk Prediction Models of Premenopausal and Postmenopausal Breast Cancer

Background

Circulating plasma prolactin is associated with breast cancer risk and may improve our ability to identify high-risk women. Mammographic density is a strong risk factor for breast cancer, but the association with prolactin is unclear. We studied the association between breast cancer, established breast cancer risk factors and plasma prolactin, and improvement of risk prediction by adding prolactin.

Methods

We conducted a nested case-control study including 721 breast cancer patients and 1400 age-matched controls. Plasma prolactin levels were assayed using immunoassay and mammographic density measured by STRATUS. Odds ratios (ORs) were calculated by multivariable adjusted logistic regression, and improvement in the area under the curve for the risk of breast cancer by adding prolactin to established risk models. Statistical tests were two-sided.

Results

In multivariable adjusted analyses, prolactin was associated with risk of premenopausal (OR, top vs bottom quintile = 1.9; 1.88 (95% confidence interval [CI] = 1.08 to 3.26) but not with postmenopausal breast cancer. In postmenopausal cases prolactin increased by 10.6% per cBIRADS category (P_trend = .03). In combined analyses of prolactin and mammographic density, ORs for women in the highest vs lowest tertile of both was 3.2 (95% CI = 1.3 to 7.7) for premenopausal women and 2.44 (95% CI = 1.44 to 4.14) for postmenopausal women. Adding prolactin to current risk models improved the area under the curve of the Gail model (+2.4 units, P = .02), Tyrer-Cuzick model (+3.8, P = .02), and the CAD2Y model (+1.7, P = .008) in premenopausal women.

Conclusion

Circulating plasma prolactin and mammographic density appear independently associated with breast cancer risk among premenopausal women, and prolactin may improve risk prediction by current risk models.

Prolactin signaling through focal adhesion complexes is amplified by stiff extracellular matrices in breast cancer cells

Estrogen receptor α positive (ERα+) breast cancer accounts for most breast cancer deaths. Both prolactin (PRL) and extracellular matrix (ECM) stiffness/density have been implicated in metastatic progression of this disease. We previously demonstrated that these factors cooperate to fuel processes involved in cancer progression. Culture of ERα+ breast cancer cells in dense/stiff 3D collagen-I matrices shifts the repertoire of PRL signals, and increases crosstalk between PRL and estrogen to promote proliferation and invasion. However, previous work did not distinguish ECM stiffness and collagen density. In order to dissect the ECM features that control PRL signals, we cultured T47D and MCF-7 cells on polyacrylamide hydrogels of varying elastic moduli (stiffness) with varying collagen-I concentrations (ligand density). Increasing stiffness from physiological to pathological significantly augmented PRL-induced phosphorylation of ERK1/2 and the SFK target, FAK-Y925, with only modest effects on pSTAT5. In contrast, higher collagen-I ligand density lowered PRL-induced pSTAT5 with no effect on pERK1/2 or pFAK-Y925. Disrupting focal adhesion signaling decreased PRL signals and PRL/estrogen-induced proliferation more efficiently in stiff, compared to compliant, extracellular environments. These data indicate that matrix stiffness shifts the balance of PRL signals from physiological (JAK2/STAT5) to pathological (FAK/SFK/ERK1/2) by increasing PRL signals through focal adhesions. Together, our studies suggest that PRL signaling to FAK and SFKs may be useful targets in clinical aggressive ERα+ breast carcinomas.

Breast cancer risk factors and mammographic density among high-risk women in urban China

Elevated mammographic density (MD) is an established breast cancer risk factor. Studies examining relationships between MD and breast cancer risk factors are limited in China, where established breast cancer risk factors are less prevalent but dense breasts are more prevalent than Western countries. This study included 11,478 women (45-69 years; 36% premenopausal) participating in an ongoing national cancer screening program in 11 urban provinces in China and predicted as having high-risk for breast cancer. Polytomous logistic regression was performed to assess associations between MD and risk factors by comparing each higher Breast Imaging Reporting and Data System (BI-RADS) category (2, 3, or 4) to the lowest category (BI-RADS, 1). We found associations of increasing age, body mass index, weight, postmenopausal status, and parity with lower MD. Higher levels of education, increasing height, and later first birth were associated with higher MD. These associations did not vary by menopausal status. Additionally, the association between longer period of breastfeeding and lower MD was seen among postmenopausal women only (P_interaction = 0.003). Having first-degree relatives with breast cancer diagnosed before 50 years was associated with lower MD only among premenopausal women (P_interaction = 0.061). We found effects of established breast cancer risk factors on MD showed similar directions in Chinese and Western women, supporting the hypothesis that MD represents cumulative exposure to breast cancer risk factors over the life course. Our findings help to understand the biological basis of the association of MD with breast cancer risk and have implications for breast cancer prevention research in China.

Progesterone receptors (PR) mediate STAT actions: PR and prolactin receptor signaling crosstalk in breast cancer models

Estrogen is the major mitogenic stimulus of mammary gland development during puberty wherein ER signaling acts to induce abundant PR expression. PR signaling, in contrast, is the primary driver of mammary epithelial cell proliferation in adulthood. The high circulating levels of progesterone during pregnancy signal through PR, inducing expression of the prolactin receptor (PRLR). Cooperation between PR and prolactin (PRL) signaling, via regulation of downstream components in the PRL signaling pathway including JAKs and STATs, facilitates the alveolar morphogenesis observed during pregnancy. Indeed, these pathways are fully integrated via activation of shared signaling pathways (i.e. JAKs, MAPKs) as well as by the convergence of PRs and STATs at target genes relevant to both mammary gland biology and breast cancer progression (i.e. proliferation, stem cell outgrowth, tissue cell type heterogeneity). Thus, rather than a single mediator such as ER, transcription factor cascades (ER>PR>STATs) are responsible for rapid proliferative and developmental programming in the normal mammary gland. It is not surprising that these same mediators typify uncontrolled proliferation in a majority of breast cancers, where ER and PR are most often co-expressed and may cooperate to drive malignant tumor progression. This review will primarily focus on the integration of PR and PRL signaling in breast cancer models and the importance of this cross-talk in cancer progression in the context of mammographic density. Components of these PR/PRL signaling pathways could offer alternative drug targets and logical complements to anti-ER or anti-estrogen-based endocrine therapies.

Elevated collagen-I augments tumor progressive signals, intravasation and metastasis of prolactin-induced estrogen receptor alpha positive mammary tumor cells

Background

The development and progression of estrogen receptor alpha positive (ERα+) breast cancer has been linked epidemiologically to prolactin. However, activation of the canonical mediator of prolactin, STAT5, is associated with more differentiated cancers and better prognoses. We have reported that density/stiffness of the extracellular matrix potently modulates the repertoire of prolactin signals in human ERα + breast cancer cells in vitro: stiff matrices shift the balance from the Janus kinase (JAK)2/STAT5 cascade toward pro-tumor progressive extracellular regulated kinase (ERK)1/2 signals, driving invasion. However, the consequences for behavior of ERα + cancers in vivo are not known.

Methods

In order to investigate the importance of matrix density/stiffness in progression of ERα + cancers, we examined tumor development and progression following orthotopic transplantation of two clonal green fluorescent protein (GFP) + ERα + tumor cell lines derived from prolactin-induced tumors to 8-week-old wild-type FVB/N (WT) or collagen-dense (col1a1^tm1Jae/+) female mice. The latter express a mutant non-cleavable allele of collagen 1a1 “knocked-in” to the col1a1 gene locus, permitting COL1A1 accumulation. We evaluated the effect of the collagen environment on tumor progression by examining circulating tumor cells and lung metastases, activated signaling pathways by immunohistochemistry analysis and immunoblotting, and collagen structure by second harmonic generation microscopy.

Results

ERα + primary tumors did not differ in growth rate, histologic type, ERα, or prolactin receptor (PRLR) expression between col1a1^tm1Jae/+ and WT recipients. However, the col1a1^tm1Jae/+ environment significantly increased circulating tumor cells and the number and size of lung metastases at end stage. Tumors in col1a1^tm1Jae/+ recipients displayed reduced STAT5 activation, and higher phosphorylation of ERK1/2 and AKT. Moreover, intratumoral collagen fibers in col1a1^tm1Jae/+ recipients were aligned with tumor projections into the adjacent fat pad, perpendicular to the bulk of the tumor, in contrast to the collagen fibers wrapped around the more uniformly expansive tumors in WT recipients.

Conclusions

A collagen-dense extracellular matrix can potently interact with hormonal signals to drive metastasis of ERα + breast cancers.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-017-0801-1) contains supplementary material, which is available to authorized users.

Prolactin receptor in breast cancer: marker for metastatic risk

Prolactin and prolactin receptor signaling and function are complex in nature and intricate in function. Basic, pre-clinical and translational research has opened up our eyes to the understanding that prolactin and prolactin receptor signaling function differently within different cellular contexts and microenvironmental conditions. Its multiple roles in normal physiology are subverted in cancer initiation and progression, and gradually we are teasing out the intricacies of function and therapeutic value. Recently, we observed that prolactin has a role in accelerating the time to bone metastasis in breast cancer patients and identified the mechanism by which prolactin stimulated breast cancer cell-mediated lytic osteoclast formation. The possibility that the prolactin receptor is a marker for metastasis, and specifically bone metastasis, is one that may have to be put into the context of the different variants of prolactin, different prolactin receptor isoforms and intricate signaling pathways that are regulated by the microenvironment. The more complete the picture, the better one can test biomarker identity and design clinical trials to test therapeutic intervention. This review will cover the recent advances and highlight the complexity of prolactin receptor biology.

Gigantomastia and Macroprolactinemia Responding to Cabergoline Treatment: A Case Report and Minireview of the Literature

Background. Macroprolactinemia is defined as predominance of high molecular weight prolactin forms in the circulation. Although macroprolactin is considered as a biologically inactive molecule, some authorities suggest treatment in symptomatic cases. Gigantomastia is defined as excess breast tissue and most cases in the literature were treated by surgical intervention. Case. A 44-year-old woman was admitted to our clinic with gigantomastia and galactorrhea. The patient had a demand for surgical therapy. In laboratory examination, she had hyperprolactinemia and macroprolactinemia. Pituitary imaging revealed 6 mm microadenoma in right side of the hypophysis. Since she was symptomatic, cabergolin treatment was started. Macroprolactin became negative, breast circumference decreased significantly, and galactorrhea resolved after treatment. Conclusion. Gigantomastia might be the presenting symptom in patients with macroprolactinemia. In these patients medical treatment with cabergoline may be used initially as an alternative to surgical approach.

Plasma prolactin and breast cancer risk: a meta- analysis

Breast cancer is the most common cancer among women, and its incidence is on a constant rise. Previous studies suggest that higher levels of plasma prolactin are associated with escalated risk of breast cancer, however, these results are contradictory and inconclusive. PubMed and Medline were used to search and identify published observational studies that assessed the relationship between plasma prolactin levels and the risk of breast cancer. The pooled relative risks (RRs) with 95% confidence intervals (CIs) were calculated using a fixed-effects or random-effects model. A total of 7 studies were included in our analysis. For the highest versus lowest levels of plasma prolactin, the pooled RR (95% CI) of breast cancer were 1.16 (1.04, 1.29). In subgroup analyses, we found a positive association between plasma prolactin levels and the risk of breast cancer among the patients who were postmenopausal, ER(+)/PR(+) or in situ and invasive carcinoma. However, this positive association was not detected in the premenopausal and ER(-)/PR(-) patients. In conclusion, the present study provides evidence supporting a significantly positive association between plasma prolactin levels and the risk of breast cancer.

Relationship between prolactin, breast cancer risk, and antipsychotics in patients with schizophrenia: a critical review

OBJECTIVE

A recent meta-analysis showed that breast cancer probably is more common in female patients with schizophrenia than in the general population (effect size = 1.25, P < 0.05). Increasing experimental and epidemiological data have alerted researchers to the influence of prolactin (PRL) in mammary carcinogenesis. We therefore investigated the possible relationship between antipsychotic-induced hyperprolactinemia (HPRL) and breast cancer risk in female patients with schizophrenia.

METHOD

A literature search (1950 until January 2015), using the MEDLINE database, was conducted for English-language published clinical trials to identify and synthesize data of the current state of knowledge concerning breast cancer risk (factors) in women with schizophrenia and its (their) relationship between HPRL and antipsychotic medication.

RESULTS

Although an increasing body of evidence supports the involvement of PRL in breast carcinogenesis, results of human prospective studies are limited, equivocal, and correlative (with risk ratios ranging from 0.70 to 1.9 for premenopausal women and from 0.76 to 2.03 for postmenopausal women). Moreover, these studies equally do not take into account the local production of PRL in breast epithelium, although amplification or overexpression of the local autocrine/paracrine PRL loop may be a more important mechanism in tumorigenesis. Until now, there is also no conclusive evidence that antipsychotic medication can increase the risk of breast malignancy and mortality.

CONCLUSION

Other breast risk factors than PRL, such as nulliparity, obesity, diabetes mellitus, and unhealthy lifestyle behaviours (alcohol dependence, smoking, low physical activity), probably are of greater relevance in individual breast cancer cases within the population of female patients with schizophrenia.

A comprehensive evaluation of interaction between genetic variants and use of menopausal hormone therapy on mammographic density

INTRODUCTION

Mammographic density is an established breast cancer risk factor with a strong genetic component and can be increased in women using menopausal hormone therapy (MHT). Here, we aimed to identify genetic variants that may modify the association between MHT use and mammographic density.

METHODS

The study comprised 6,298 postmenopausal women from the Mayo Mammography Health Study and nine studies included in the Breast Cancer Association Consortium. We selected for evaluation 1327 single nucleotide polymorphisms (SNPs) showing the lowest P-values for interaction (P int) in a meta-analysis of genome-wide gene-environment interaction studies with MHT use on risk of breast cancer, 2541 SNPs in candidate genes (AKR1C4, CYP1A1-CYP1A2, CYP1B1, ESR2, PPARG, PRL, SULT1A1-SULT1A2 and TNF) and ten SNPs (AREG-rs10034692, PRDM6-rs186749, ESR1-rs12665607, ZNF365-rs10995190, 8p11.23-rs7816345, LSP1-rs3817198, IGF1-rs703556, 12q24-rs1265507, TMEM184B-rs7289126, and SGSM3-rs17001868) associated with mammographic density in genome-wide studies. We used multiple linear regression models adjusted for potential confounders to evaluate interactions between SNPs and current use of MHT on mammographic density.

RESULTS

No significant interactions were identified after adjustment for multiple testing. The strongest SNP-MHT interaction (unadjusted P int <0.0004) was observed with rs9358531 6.5kb 5' of PRL. Furthermore, three SNPs in PLCG2 that had previously been shown to modify the association of MHT use with breast cancer risk were found to modify also the association of MHT use with mammographic density (unadjusted P int <0.002), but solely among cases (unadjusted P int SNP×MHT×case-status <0.02).

CONCLUSIONS

The study identified potential interactions on mammographic density between current use of MHT and SNPs near PRL and in PLCG2, which require confirmation. Given the moderate size of the interactions observed, larger studies are needed to identify genetic modifiers of the association of MHT use with mammographic density.

Anti-metastatic outcome of isoform-specific prolactin receptor targeting in breast cancer

Controversy exists concerning the role of the long prolactin receptor (PRLR) in the progression of breast cancer. By targeting pre-mRNA splicing, we succeeded in knocking down only the long PRLR in vivo, leaving the short forms unaffected. Using two orthotopic and highly-metastatic models of breast cancer, one of which was syngeneic (mouse 4T1) to allow assessment of tumor-immune interactions and one of which was endocrinologically humanized (human BT-474) to activate human PRLRs, we examined the effect of long PRLR knockdown on disease progression. In both models, knockdown dramatically inhibited metastatic spread to the lungs and liver and resulted in increased central death in the primary tumor. In the syngeneic model, immune infiltrates in metastatic sites were changed from innate inflammatory cells to lymphocytes, with an increase in the incidence of tumor-specific cytotoxic T cells. Long PRLR knockdown in three-dimensional culture induced apoptosis of tumor-initiating/cancer stem cells (death of 95% of cells displaying stem cell markers in 15 days). We conclude that the long PRLR plays an important role in breast cancer metastasis.

Dense collagen-I matrices enhance pro-tumorigenic estrogen-prolactin crosstalk in MCF-7 and T47D breast cancer cells

Breast cancers that express estrogen receptor alpha (ERα+) constitute the majority of breast tumors. Estrogen is a major driver of their growth, and targeting ER-mediated signals is a largely successful primary therapeutic strategy. Nonetheless, ERα+ tumors also result in the most breast cancer mortalities. Other factors, including altered characteristics of the extracellular matrix such as density and orientation and consequences for estrogen crosstalk with other hormones such as prolactin (PRL), may contribute to these poor outcomes. Here we employed defined three dimensional low density/compliant and high density/stiff collagen-I matrices to investigate the effects on 17β-estradiol (E2) activity and PRL/E2 interactions in two well-characterized ERα+/PRLR+ luminal breast cancer cell lines in vitro. We demonstrate that matrix density modulated E2-induced transcripts, but did not alter the growth response. However, matrix density was a potent determinant of the behavioral outcomes of PRL/E2 crosstalk. High density/stiff matrices enhanced PRL/E2-induced growth mediated by increased activation of Src family kinases and insensitivity to the estrogen antagonist, 4-hydroxytamoxifen. It also permitted these hormones in combination to drive invasion and modify the alignment of collagen fibers. In contrast, low density/compliant matrices allowed modest if any cooperation between E2 and PRL to growth and did not permit hormone-induced invasion or collagen reorientation. Our studies demonstrate the power of matrix density to determine the outcomes of hormone actions and suggest that stiff matrices are potent collaborators of estrogen and PRL in progression of ERα+ breast cancer. Our evidence for bidirectional interactions between these hormones and the extracellular matrix provides novel insights into the regulation of the microenvironment of ERα+ breast cancer and suggests new therapeutic approaches.

Immunoassay and Nb2 lymphoma bioassay prolactin levels and mammographic density in premenopausal and postmenopausal women the Nurses' Health Studies

Higher circulating prolactin levels have been associated with higher percent mammographic density among postmenopausal women in some, but not all studies. However, few studies have examined associations with dense area and non-dense breast area breast or considered associations with prolactin Nb2 lymphoma cell bioassay levels. We conducted a cross-sectional study among 1,124 premenopausal and 890 postmenopausal women who were controls in breast cancer case-control studies nested in the Nurses' Health Study (NHS) and NHSII. Participants provided blood samples in 1989-1990 (NHS) or 1996-1999 (NHSII) and mammograms were obtained from around the time of blood draw. Multivariable linear models were used to assess the associations between prolactin levels (measured by immunoassay or bioassay) with percent density, dense area, and non-dense area. Among 1,124 premenopausal women, percent density, dense area, and non-dense area were not associated with prolactin immunoassay levels in multivariable models (p trends = 0.10, 0.18, and 0.69, respectively). Among 890 postmenopausal women, those with prolactin immunoassay levels in the highest versus lowest quartile had modestly, though significantly, higher percent density (difference = 3.01 percentage points, 95 % CI 0.22, 5.80) as well as lower non-dense area (p trend = 0.02). Among women with both immunoassay and bioassay levels, there were no consistent differences in the associations with percent density between bioassay and immunoassay levels. Postmenopausal women with prolactin immunoassay levels in the highest quartile had significantly higher percent density as well as lower non-dense area compared to those in the lowest quartile. Future studies should examine the underlying biologic mechanisms, particularly for non-dense area.

Circulating prolactin and breast cancer risk among pre- and postmenopausal women in the EPIC cohort

BACKGROUND

Experimental and epidemiological evidence suggests that prolactin might play a role in the etiology of breast cancer. We analyzed the relationship of prediagnostic circulating prolactin levels with the risk of breast cancer by menopausal status, use of postmenopausal hormone replacement therapy (HRT) at blood donation, and by estrogen and progesterone receptor status of the breast tumors.

PATIENTS AND METHODS

Conditional logistic regression was used to analyze the data from a case-control study nested within the prospective European EPIC cohort, including 2250 invasive breast cancer and their matched control subjects.

RESULTS

Statistically significant heterogeneity in the association of prolactin levels with breast cancer risk between women who were either pre- or postmenopausal at the time of blood donation was observed (Phet = 0.04). Higher serum levels of prolactin were associated with significant increase in the risk of breast cancer among postmenopausal women [odds ratio (OR)Q4-Q1 = 1.29 (95% confidence interval, CI, 1.05-1.58), Ptrend = 0.09]; however, this increase in risk seemed to be confined to women who used postmenopausal HRT at blood donation [ORQ4-Q1 = 1.45 (95% CI 1.08-1.95), Ptrend = 0.01], whereas no statistically significant association was found for the non-users of HRT [ORQ4-Q1 = 1.11 (95%CI 0.83-1.49), Ptrend = 0.80] (Phet = 0.08). Among premenopausal women, a statistically non-significant inverse association was observed [ORQ4-Q1 = 0.70 (95% CI 0.48-1.03), Ptrend = 0.16]. There was no heterogeneity in the prolactin-breast cancer association by hormone receptor status of the tumor.

CONCLUSION

Our study indicates that higher circulating levels of prolactin among the postmenopausal HRT users at baseline may be associated with increased breast cancer risk.

Combined effects of endogenous sex hormone levels and mammographic density on postmenopausal breast cancer risk: results from the Breakthrough Generations Study

BACKGROUND

Mammographic density and sex hormone levels are strong risk factors for breast cancer, but it is unclear whether they represent the same aetiological entity or are independent risk factors.

METHODS

Within the Breakthrough Generations Study cohort, we conducted a case-control study of 265 postmenopausal breast cancer cases and 343 controls with prediagnostic mammograms and blood samples. Plasma was assayed for oestradiol, testosterone and sex hormone-binding globulin (SHBG) concentrations and mammographic density assessed by Cumulus.

RESULTS

Oestradiol and testosterone were negatively and SHBG positively associated with percentage density and absolute dense area, but after adjusting for body mass index the associations remained significant only for SHBG. Breast cancer risk was independently and significantly positively associated with percentage density (P=0.002), oestradiol (P=0.002) and testosterone (P=0.007) levels. Women in the highest tertile of both density and sex hormone level were at greatest risk, with an odds ratio of 7.81 (95% confidence interval (CI): 2.89-21.1) for oestradiol and 4.57 (95% CI: 1.75-11.9) for testosterone and high density compared with those who were in the lowest tertiles. The cumulative risk of breast cancer in the highest oestradiol and density tertiles, representing 8% of controls, was estimated as 12.8% at ages 50-69 years and 19.4% at ages 20-79 years, and in the lowest tertiles was 1.7% and 4.3%, respectively. Associations of breast cancer risk with tertiles of mammographic dense area were less strong than for percentage density.

CONCLUSIONS

Endogenous sex hormone levels and mammographic density are independent risk factors for postmenopausal breast cancer, which in combination can identify women who might benefit from increased frequency of screening and chemoprophylaxis.

Stiff collagen matrices increase tumorigenic prolactin signaling in breast cancer cells

Clinically, circulating prolactin levels and density of the extracellular matrix (ECM) are individual risk factors for breast cancer. As tumors develop, the surrounding stroma responds with increased deposition and cross-linking of the collagen matrix (desmoplasia). In mouse models, prolactin promotes mammary carcinomas that resemble luminal breast cancers in women, and increased collagen density promotes tumor metastasis and progression. Although the contributions of the ECM to the physiologic actions of prolactin are increasingly understood, little is known about the functional relationship between the ECM and prolactin signaling in breast cancer. Here, we examined consequences of increased ECM stiffness on prolactin signals to luminal breast cancer cells in three-dimensional collagen I matrices in vitro. We showed that matrix stiffness potently regulates a switch in prolactin signals from physiologic to protumorigenic outcomes. Compliant matrices promoted physiological prolactin actions and activation of STAT5, whereas stiff matrices promoted protumorigenic outcomes, including increased matrix metalloproteinase-dependent invasion and collagen scaffold realignment. In stiff matrices, prolactin increased SRC family kinase-dependent phosphorylation of focal adhesion kinase (FAK) at tyrosine 925, FAK association with the mitogen-activated protein kinase mediator GRB2, and pERK1/2. Stiff matrices also increased co-localization of prolactin receptors and integrin-activated FAK, implicating altered spatial relationships. Together, these results demonstrate that ECM stiffness is a powerful regulator of the spectrum of prolactin signals and that stiff matrices and prolactin interact in a feed-forward loop in breast cancer progression. Our study is the first reported evidence of altered ECM-prolactin interactions in breast cancer, suggesting the potential for new therapeutic approaches.

Is mammographic density differentially associated with breast cancer according to receptor status? A meta-analysis

Mammographic density (MD) is a strong marker of breast cancer risk, but it is debated whether the association holds, and is of a similar magnitude, for different subtypes of breast cancer defined by receptor status or gene expression profiles. A literature search conducted in June 2012 was used to identify all studies that had investigated the association of MD with subtype-specific breast cancer, independent of age. 7 cohort/case-control and 12 case-only studies were included, comprising a total of >24,000 breast cancer cases. Random effects meta-analysis models were used to combine relative risks (RR) of MD with subtype-specific breast cancer for case-control studies, and in case-only studies to combine relative risk ratios (RRR) of receptor positive versus negative breast tumors. In case-control/cohort studies, relative to women in the lowest density category, women in the highest density category had 3.1-fold (95 % confidence interval [CI] 2.2, 4.2) and 3.2-fold (1.7, 5.9) increased risk of estrogen receptor positive (ER+) and ER- breast cancer, respectively. In case-only analyses, RRRs of breast tumors being ER+ versus ER- were 1.13 (95 % CI 0.89, 1.42) for medium versus minimal MD. MD remained associated with screen-detected ER+ tumors, despite the expectation of this association to be attenuated due to masking bias and overdiagnoses of ER+ tumors. In eight contributing studies, the association of MD did not differ by HER2 status. This combined evidence strengthens the importance of MD as a strong marker of overall and of subtype-specific risk, and confirms its value in overall breast cancer risk assessment and monitoring for both research and clinical purposes.

Rotating night shift work and mammographic density

BACKGROUND

An increased risk of breast cancer has been observed in night shift workers. Exposure to artificial light at night and disruption of the endogenous circadian rhythm with suppression of the melatonin synthesis have been suggested mechanisms. We investigated the hypothesis that rotating night shift work is associated with mammographic density.

METHODS

We conducted a cross-sectional study on the association between rotating night shift work characteristics, 6-sulfatoxymelatonin (MT6s) creatinine adjusted in a spot morning urine sample, and a computer-assisted measure of mammographic density in 640 nurses and midwives ages 40 to 60 years. The associations were evaluated using regression models adjusted for age, body mass index, menopausal status, age at menopause, age at menarche, smoking, and the calendar season of the year when mammography was conducted.

RESULTS

The adjusted means of percentage of mammographic density and absolute density were slightly higher among women working rotating night shifts but not statistically significant [percentage of mammographic density = 23.6%, 95% confidence interval (CI), 21.9%-25.4% vs. 22.5%, 95% CI, 20.8%-24.3%; absolute density = 23.9 cm(2), 95% CI, 21.4-26.4 cm(2) vs. 21.8 cm(2), 95% CI, 19.4-24.3 cm(2) in rotating night shift and day shift nurses, respectively). There were no significant associations between the current or cumulative rotating night shift work exposure metrics and mammographic density. No association was observed between morning MT6s and mammographic density.

CONCLUSIONS

The hypothesis on the link between rotating night shift work, melatonin synthesis disruption, and mammographic density is not supported by the results of the present study.

IMPACT

It is unlikely that the development of breast cancer in nurses working rotating night shifts is mediated by an increase in mammographic density.

Breast density, body mass index, and risk of tumor marker-defined subtypes of breast cancer

PURPOSE

Breast density and body mass index (BMI) are correlated attributes and are both potentially modifiable risk factors for breast cancer. However, relationships between these factors and risk of molecularly-defined subtypes of breast cancer have not been established.

METHODS

We used breast density and BMI data collected by the Breast Cancer Surveillance Consortium from 1,054,466 women ages 40 to 84 years receiving mammography, including 13,797 women subsequently diagnosed with breast cancer. Cases were classified into three groups on the basis of expression of the estrogen receptor (ER), progesterone receptor (PR), and HER2:1) ER-positive (ER+, n = 10,026), 2) HER2-expressing (ER-negative/PR-negative/HER2-positive, n = 308), or triple-negative (ER-negative/PR-negative/HER2-negative, n = 705). Using Cox regression, we evaluated subtype-specific associations with breast density and BMI.

RESULTS

Breast density was similarly positively associated with risk of all subtypes, especially among women ages 40 to 64 years. BMI was positively associated with risks of ER+ and triple-negative breast cancer in women ages 50 to 84 who were not users of hormone therapy.

CONCLUSIONS

Breast density is positively associated with breast cancer risk, regardless of disease subtype. Associations with BMI appear to vary more by breast cancer subtype. Additional studies are needed to confirm and further characterize risk factors for HER2-expressing and triple-negative breast cancer.

Obstetric history and mammographic density: a population-based cross-sectional study in Spain (DDM-Spain)

High mammographic density (MD) is used as a phenotype risk marker for developing breast cancer. During pregnancy and lactation the breast attains full development, with a cellular-proliferation followed by a lobular-differentiation stage. This study investigates the influence of obstetric factors on MD among pre- and post-menopausal women. We enrolled 3,574 women aged 45–68 years who were participating in breast cancer screening programmes in seven screening centers. To measure MD, blind anonymous readings were taken by an experienced radiologist, using craniocaudal mammography and Boyd’s semiquantitative scale. Demographic and reproductive data were directly surveyed by purpose-trained staff at the date of screening. The association between MD and obstetric variables was quantified by ordinal logistic regression, with screening centre introduced as a random effect term. We adjusted for age, number of children and body mass index, and stratified by menopausal status. Parity was inversely associated with density, the probability of having high MD decreased by 16% for each new birth (P value < 0.001). Among parous women, a positive association was detected with duration of lactation [>9 months: odds ratio (OR) = 1.33; 95% confidence interval (CI) = 1.02–1.72] and weight of first child (>3,500 g: OR = 1.32; 95% CI = 1.12–1.54). Age at first birth showed a different effect in pre- and post-menopausal women (P value for interaction = 0.030). No association was found among pre-menopausal women. However, in post-menopausal women the probability of having high MD increased in women who had their first child after the age of 30 (OR = 1.53; 95% CI = 1.17–2.00). A higher risk associated with birth of twins was also mainly observed in post-menopausal women (OR = 2.02; 95% CI = 1.18–3.46). Our study shows a greater prevalence of high MD in mothers of advanced age at first birth, those who had twins, those who have breastfed for longer periods, and mothers whose first child had an elevated birth weight. These results suggest the influence of hormones and growth factors over the proliferative activity of the mammary gland.

Hypothesis: prolactin is tumorigenic to human breast: dispelling the myth that prolactin-induced mammary tumors are rodent-specific

The commonly held assumption that rodent mammary tumors resulting from elevated prolactin are species-specific, or not biologically relevant to humans, is incorrect. Substantial epidemiological, clinical, and biological evidence now exists confirming the role of prolactin in human breast cancer. This evidence is evaluated and the argument presented that the tumorigenic risk from prolactin is therefore not species-specific to rodents but directly applies to humans. Further, as the mechanisms of prolactin-induced mammary tumor promotion and development appear analogous between rodents and humans, mammary tumorigenic findings in rodent carcinogenicity bioassays are both predictive and biologically relevant to the human response. Toxicologists and regulators need to consider this in carcinogenicity risk assessments.

Mammographic density and risk of second breast cancer after ductal carcinoma in situ

BACKGROUND

We examined whether mammographic density predicts risk of second breast cancers among patients with ductal carcinoma in situ (DCIS).

METHODS

The study included DCIS patients diagnosed during 1990 to 1997 and treated with breast-conserving surgery at Kaiser Permanente Northern California. Medical records were reviewed for clinical factors and subsequent breast cancers (DCIS and invasive). Ipsilateral mammograms from the index DCIS were assessed for density without knowledge of subsequent cancer status. Cox regression modeling was used to examine the association between mammographic density and risk of breast cancer events.

RESULTS

Of the 935 eligible DCIS patients, 164 (18%) had a subsequent ipsilateral breast cancer, and 59 (6%) had a new primary cancer in the contralateral breast during follow-up (median, 103 mo). Those with the greatest total area of density (upper 20% of values) were at increased risk for invasive disease in either breast [hazard ratio (HR), 2.1; 95% confidence interval (95% CI), 1.2-3.8] or any cancer (DCIS or invasive) in the ipsilateral (HR, 1.7; 95% CI, 1.0-2.9) or contralateral (HR, 3.0; 95% CI, 1.3-6.9) breast compared with those with the smallest area of density (bottom 20%). HRs for these same end points comparing those in the highest with those in the lowest American College of Radiology Breast Imaging Reporting and Data System category were 1.6 (95% CI, 0.7-3.6), 1.3 (95% CI, 0.7-2.6), and 5.0 (95% CI, 1.4-17.9), respectively. There was a suggestion of increasing risk of contralateral, but not ipsilateral, cancer with increasing percent density.

CONCLUSIONS

Women with mammographically dense breasts may be at higher risk of subsequent breast cancer, especially in the contralateral breast.

IMPACT

Information about mammographic density may help with DCIS treatment decisions.

Plasma prolactin level and risk of incident hypertension in postmenopausal women

BACKGROUND

Laboratory and cross-sectional human studies suggest a potential role for prolactin in the pathogenesis of hypertension; however, the prospective association between prolactin and hypertension has not been previously reported.

METHODS

We prospectively examined the association between daytime plasma prolactin levels and the risk of incident hypertension among 874 postmenopausal women who were participants of the Nurses' Health Study. Cox proportional hazards regression models were used to adjust for potential confounders.

RESULTS

We identified 183 incident cases of hypertension during 8 years of follow-up. After adjusting for potential confounders, the relative risk of hypertension for a 1-standard deviation higher plasma prolactin was 1.31 (95% confidence interval 1.05-1.62). Compared with women with plasma prolactin levels of 8.0 ng/ml or below, the multivariable relative risk of incident hypertension for those with prolactin levels above 8.0 ng/ml was 1.34 (95% confidence interval 0.90-1.99).

CONCLUSION

A higher daytime plasma prolactin level is independently associated with an increased risk of incident hypertension among postmenopausal women.

Cellular and hormonal content of breast nipple aspirate fluid in relation to the risk of breast cancer

In research settings, the measurement of serum and urine hormone concentrations has shown modest positive relationships with breast cancer risk in postmenopausal women. However, the local production of sex steroids in the breast is a significant contributor to the hormonal environment of the breast. Nipple aspiration fluid provides a window into this environment and allows the measurement of hormone and protein content which may show stronger relations to breast cancer risk, and therefore enable both more accurate risk assessment, and the use of preventive measures directed to the lowering of local breast hormonal exposure.

Association of body size measurements and mammographic density in Korean women: the Healthy Twin study

BACKGROUND

Both greater body size and higher mammographic density seem to be associated with a risk of breast cancer. To understand a mechanism through which body size confers a higher risk of breast cancer, associations between mammographic measures and various measures of body size were examined.

METHOD

Study subjects were 730 Korean women selected from the Healthy Twin study. Body size measurements were completed according to standard protocol. Mammographic density was measured from digital mammograms using a computer-assisted method from which the total area and the dense area of the breast were calculated, and nondense area and percent of dense area were straightforwardly derived. Linear mixed models considering familial correlations were used for analyses.

RESULTS

Total and nondense areas were positively associated with current body mass index (BMI), BMI at 35 years, total fat percent, waist circumference, and waist-hip ratio, whereas percent dense area was inversely associated with these characteristics in both premenopausal and postmenopausal women. Height was not associated with any mammographic measure. Total and nondense areas had strong positive genetic correlations with current BMI, total fat percent, waist circumference, and waist-hip ratio, whereas percent dense area had strong inverse genetic correlations with these body size measurements.

CONCLUSION

Mammographic density and obesity are inversely associated with each other possibly from common genetic influences that have opposite effects on mammographic density and obesity in Korean women.

IMPACT

The association between obesity and breast cancer does not seem to be mediated through mammographic density.

Sex steroids, growth factors and mammographic density: a cross-sectional study of UK postmenopausal Caucasian and Afro-Caribbean women

Introduction

Sex steroids, insulin-like growth factors (IGFs) and prolactin are breast cancer risk factors but whether their effects are mediated through mammographic density, one of the strongest risk factors for breast cancer, is unknown. If such a hormonal basis of mammographic density exists, hormones may underlie ethnic differences in both mammographic density and breast cancer incidence rates.

Methods

In a cross-sectional study of 270 postmenopausal Caucasian and Afro-Caribbean women attending a population-based breast screening service in London, UK, we investigated whether plasma biomarkers (oestradiol, oestrone, sex hormone binding globulin (SHBG), testosterone, prolactin, leptin, IGF-I, IGF-II and IGF binding protein 3 (IGFBP3)) were related to and explained ethnic differences in mammographic percent density, dense area and nondense area, measured in Cumulus using the threshold method.

Results

Mean levels of oestrogens, leptin and IGF-I:IGFBP3 were higher whereas SHBG and IGF-II:IGFBP3 were lower in Afro-Caribbean women compared with Caucasian women after adjustment for higher mean body mass index (BMI) in the former group (by 3.2 kg/m² (95% confidence interval (CI): 1.8, 4.5)). Age-adjusted percent density was lower in Afro-Caribbean compared with Caucasian women by 5.4% (absolute difference), but was attenuated to 2.5% (95% CI: -0.2, 5.1) upon BMI adjustment. Despite ethnic differences in biomarkers and in percent density, strong ethnic-age-adjusted inverse associations of oestradiol, leptin and testosterone with percent density were completely attenuated upon adjustment for BMI. There were no associations of IGF-I, IGF-II or IGFBP3 with percent density or dense area. We found weak evidence that a twofold increase in prolactin and oestrone levels were associated, respectively, with an increase (by 1.7% (95% CI: -0.3, 3.7)) and a decrease (by 2.0% (95% CI: 0, 4.1)) in density after adjustment for BMI.

Conclusions

These findings suggest that sex hormone and IGF levels are not associated with BMI-adjusted percent mammographic density in cross-sectional analyses of postmenopausal women and thus do not explain ethnic differences in density. Mammographic density may still, however, be influenced by much higher premenopausal hormone levels.

Normal breast tissue implanted into athymic nude mice identifies biomarkers of the effects of human pregnancy levels of estrogen

We have generated a novel model system for the study of estrogen intervention in normal breast tissue. Nulliparous human breast tissue was implanted into immunocompromised nude mice and treated with high-dose estrogen to simulate the effects of pregnancy. Treatment of mice with human mid-pregnancy levels of 17beta-estradiol for a period of 4 weeks was followed by 4 weeks of withdrawal to mimic involution. Gene expression in the xenograft tissue was then analyzed by real-time reverse transcription-PCR to identify differences between treated and control tissues. Ten genes previously identified as altered by pregnancy in rodent models were found to be differentially expressed in human breast tissue with a > or =1.8-fold up-regulation of CDC42, TGFbeta3, DCN, KRT14, LTF, and AREG and a > or =0.7-fold down-regulation of STAT1, CTGF, IGF1, and VAMP1. Immunohistochemical analysis of archival paraffin-embedded adult premenopausal human breast tissue specimens identified a significantly lower level of expression of STAT1 (P < 0.05, Mann-Whitney U test) in parous compared with age-matched nulliparous tissue (median of 24% compared with 42% epithelial cells positive). We conclude that many of the pregnancy-induced breast cancer-protective changes observed in rodent models also occur in human breast tissue following intervention using human pregnancy levels of estrogen and that STAT1 expression is a potential biomarker of parity-induced breast cancer protection in the human breast.

Antidepressant medications and change in mammographic density in postmenopausal women

BACKGROUND

Several studies suggest antidepressant medications can increase prolactin levels. Some, but not all, studies suggest prolactin levels are positively associated with mammographic breast density, an established risk factor for breast cancer.

METHODS

We evaluated 29,284 women with two routine screening mammograms 9 to 28 months apart between 1996 to 2006 to examine whether antidepressant use was associated with changes in mammographic breast density. Mammographic breast density was assigned by radiologists and coded according the Breast Imaging Reporting and Data System classification. Exposure to antidepressants was ascertained based on electronic pharmacy dispensing data, including dispensings from claims data. We used polytomous logistic regression to estimate the odds of an increase or decrease in density categories between mammograms associated with antidepressant initiation, continuation, and discontinuation compared with nonusers of any antidepressants.

RESULTS

Initiation, continuation, and discontinuation of antidepressant medications were not associated with changes in mammographic density.

CONCLUSIONS

The lack of association between antidepressant use and breast density is consistent with recent studies that do not suggest an association between antidepressant use and breast cancer risk.

Exogenous and endogenous hormones, mammographic density and breast cancer risk: can mammographic density be considered an intermediate marker of risk?

Elevated mammographic density measures are a well-established, relatively strong risk factor for breast cancer development. A systematic review of prospective cohort studies and cross-sectional studies strikingly establishes parallels between the associations of combined postmenopausal estrogen and progestin replacement therapy with, on the one hand, mammographic densities and, on the other hand, breast cancer risk. Other parallel observations were the inverse associations of both mammographic density and breast cancer risk with the selective estrogen receptor modulator tamoxifen, and direct associations with prolactin. Paradoxically, however, high mammographic density has been found associated with higher risks of both estrogen- and progesterone-receptor positive (ER+/ PR+) and negative (ER-/PR-) breast cancers, while hormone replacement therapy (HRT) use, but also circulating (blood) levels of androgens, estrogens, and prolactin appear to be associated more specifically to the risk of ER+ tumors. The effects of aromatase inhibitors and gonadotropin-releasing hormone agonists on breast density, as well as on breast cancer risk, still require further investigation. Regarding circulating levels of insulin-like growth factor (IGF)-I or IGFBP-3, studies did not show fully consistent relationships with mammographic density measures and breast cancer risk. In view of these various findings, it is impossible, at present, to propose mammographic density measures as an intermediate risk-related phenotype, integrating the effects of exogenous and/or endogenous hormones on the risk of developing breast cancer.

Prolactin and breast cancer etiology: an epidemiologic perspective

A number of epidemiologic studies of prolactin and breast cancer etiology have recently become available. Retrospective case-control studies have suggested a modest positive or null relationship between circulating prolactin concentrations and risk of breast cancer. However these studies are limited by small sample sizes and the collection of blood after case diagnosis. Several large prospective studies, in which blood was collected prior to diagnosis, have observed modest positive associations between prolactin and risk. In a pooled analysis of approximately 80% of the world's prospective data, the relative risk (RR) comparing women in the top vs bottom quartile of prolactin levels was 1.3 (95% confidence interval (CI): 1.1, 1.6, p-trend = 0.002). The results were similar for premenopausal and postmenopausal women. Most notably, high prolactin levels were associated with a 60% increased risk of estrogen receptor (ER) positive tumors, but not with ER negative tumors. Limited genetic data suggest a role of polymorphisms in the prolactin and prolactin receptor genes in risk of breast cancer. Studies of survival have suggested that high pretreatment prolactin levels were associated with treatment failure, earlier recurrence, and worse overall survival. Parity and certain medications are the only confirmed factors associated with prolactin levels in women. Overall, epidemiologic data suggest that prolactin is involved in breast cancer etiology. Further research to better elucidate these associations and their underlying mechanisms is warranted.

Adverse effects of prolactin in rodents and humans: breast and prostate cancer

Drugs and chemicals shown to induce mammary carcinogenesis in the rat/rodent via prolactin excess have traditionally been argued to pose little or no risk to humans in a regulatory toxicology context. The basis for this assumption is reviewed and placed into context with new evidence in humans that prolactin may be a tumour promoter in the breast and prostate. This evidence includes epidemiology, patient studies involving endocrine evaluation and molecular biology in human cells. It is concluded that hyperprolactinaemia is associated with an increase in breast cancer risk in both post and premenopausal women, that rat carcinogenicity studies are predictive of the human response, and that in a regulatory toxicology context prolactin-induced mammary tumours from nongenotoxic drugs and chemicals are an adverse effect that should not be ignored. More evidence is required concerning prostate cancer risk but molecular biology indicates that prolactin also induces prostate cell proliferation and inhibits apoptosis, which are similar to the responses observed in breast cancer cells.

Mammographic density. Potential mechanisms of breast cancer risk associated with mammographic density: hypotheses based on epidemiological evidence

There is now extensive evidence that mammographic density is an independent risk factor for breast cancer that is associated with large relative and attributable risks for the disease. The epidemiology of mammographic density, including the influences of age, parity and menopause, is consistent with it being a marker of susceptibility to breast cancer, in a manner similar to the concept of 'breast tissue age' described by the Pike model. Mammographic density reflects variations in the tissue composition of the breast. It is associated positively with collagen and epithelial and nonepithelial cells, and negatively with fat. Mammographic density is influenced by some hormones and growth factors as well as by several hormonal interventions. It is also associated with urinary levels of a mutagen. Twin studies have shown that most of the variation in mammographic density is accounted for by genetic factors. The hypothesis that we have developed from these observations postulates that the combined effects of cell proliferation (mitogenesis) and genetic damage to proliferating cells by mutagens (mutagenesis) may underlie the increased risk for breast cancer associated with extensive mammographic density. There is clearly a need for improved understanding of the specific factors that are involved in these processes and of the role played by the several breast tissue components that contribute to density. In particular, identification of the genes that are responsible for most of the variance in percentage density (and of their biological functions) is likely to provide insights into the biology of the breast, and may identify potential targets for preventative strategies in breast cancer.

Strong Evidence of a Genetic Determinant for Mammographic Density, a Major Risk Factor for Breast Cancer

Increased mammographic density (MD), the proportion of dense tissue visible on a mammogram, is a strong risk factor for breast cancer, common in the population and clusters in families. We conducted the first genome-wide linkage scan to identify genes influencing MD. DNA was obtained from 889 relatives (756 women, 133 men) from 89 families. Percent MD was estimated on 618 (82%) female family members using a validated computer-assisted thresholding method. The genome-wide scan included 403 microsatellite DNA markers with an average spacing of 9 cM. Fine mapping of a region of chromosome 5p (5p13.1-5p15.1) was done using 21 additional closely spaced DNA markers. Linkage analyses were conducted to quantify the evidence for a gene responsible for MD across the genome. The maximum log odds for linkage (LOD) score from the genome-wide scan was on chromosome 5p (LOD = 2.9, supporting linkage by a factor of 10(2.9) or 794 to 1) with a 1-LOD interval spanning 28.6 cM. Two suggestive regions for linkage were also identified on chromosome 12 (LOD = 2.6, 1-LOD interval of 14.8 cM; and LOD = 2.5, 1-LOD interval of 17.2 cM). Finer mapping of the region surrounding the maximum LOD on chromosome 5p resulted in stronger and statistically significant evidence for linkage (LOD = 4.2) and a narrowed 1-LOD interval (13.4 cM). The putative locus on chromosome 5p is likely to account for up to 22% of variation in MD. Hence, 1 or more of the 45 candidate genes in this region could explain a large proportion of MD and, potentially, breast cancer.

Mammographic density and breast cancer after ductal carcinoma in situ

Women with ductal carcinoma in situ (DCIS) are at substantially increased risk for a second breast cancer, but few strong predictors for these subsequent tumors have been identified. We used Cox regression modeling to examine the association between mammographic density at diagnosis of DCIS of 504 women from the National Surgical Adjuvant Breast and Bowel Project B-17 trial and risk of subsequent breast cancer events. In this group of patients, mostly 50 years old or older, approximately 6.6% had breasts categorized as highly dense (i.e., > or =75% of the breast occupied by dense tissue). After adjusting for treatment with radiotherapy, age, and body mass index, women with highly dense breasts had 2.8 (95% confidence interval [CI] = 1.3 to 6.1) times the risk of subsequent breast cancer (DCIS or invasive), 3.2 (95% CI = 1.2 to 8.5) times the risk of invasive breast cancer, and 3.0 (95% CI = 1.2 to 7.5) times the risk of any ipsilateral breast cancer, compared with women with less than 25% of the breast occupied by dense tissue. Our results provide initial evidence that the risk of second breast cancers may be increased among DCIS patients with highly dense breasts.