Postmenopausal hormone therapy and change in mammographic density

Influence of different HRT regimens on mammographic density

OBJECTIVES

A prospective, randomized, open-label study was conducted to evaluate effects on mammographic density in postmenopausal and late perimenopausal women receiving continuous combined or sequential combined hormone replacement therapy (HRT).

METHODS

The subjects were randomized to treatment with low-dose continuous combined HRT containing 1 mg 17beta-estradiol plus 0.5 mg norethisterone acetate (Activelle) or a sequential combined HRT regimen consisting of 0.625 mg conjugated equine estrogens for 28 days plus 5 mg medrogestone for 14 days (Presomen). Mammograms were obtained at baseline and after 9 cycles (each 28 days) of treatment.

RESULTS

The majority of women (approximately two-thirds in each treatment group) had no changes in mammographic breast density between baseline and the final study visit. There were no marked differences between treatment groups. Approximately 20% of women in both groups had a slight increase in mammographic density. Only 10-14% of women in both groups had a pronounced increase in mammographic density. The analyses of the degree of change showed no remarkable differences between treatments.

CONCLUSION

These results indicate that the increase in mammographic density with a low-dose continuous combined HRT regimen is no greater than that with a sequential combined HRT regimen. The type of progestogen does not have an impact on the extent of mammographic density changes.

A two-by-two factorial trial comparing oral with transdermal estrogen therapy and fenretinide with placebo on breast cancer biomarkers

PURPOSE

Oral conjugated equine estrogen (CEE) and medroxyprogesterone acetate (MPA) increase breast cancer risk, whereas the effect of transdermal estradiol (E2) and MPA is less known. Fenretinide may decrease second breast malignancies in premenopausal women but not in postmenopausal women, suggesting a hormone-sensitizing effect. We compared the 6 and 12-month changes in insulin-like growth factor-I (IGF-I), IGF-binding protein-3 (IGFBP-3), IGF-I:IGFBP-3 ratio, sex-hormone binding-globulin, and computerized mammographic percent density during oral CEE or transdermal E2 with sequential MPA and fenretinide or placebo.

EXPERIMENTAL DESIGN

A total of 226 recent postmenopausal healthy women were randomly assigned in a two-by-two factorial design to either oral CEE 0.625 mg/day (n = 111) or transdermal E2, 50 microg/day (n = 115) and to fenretinide 100 mg/twice a day (n = 112) or placebo (n = 114) for 12 months. Treatment effects were investigated by the Kruskall-Wallis test and analysis of covariance. P values were two-sided.

RESULTS

After 12 months, oral CEE decreased IGF-I by 26% [95% confidence interval (CI), 22-30%] and increased sex-hormone binding-globulin by 96% (95% CI, 79-112%) relative to baseline, whereas no change occurred with transdermal E2 (P < 0.001 between groups). Fenretinide decreased IGFBP-3 relative to placebo (P = 0.04). Percentage of breast density showed an absolute increase of 3.5% (95% CI, 2.5-4.6%) during hormone therapy without differences between groups (P = 0.39).

CONCLUSIONS

Oral CEE has more favorable changes than transdermal E2 on circulating breast cancer risk biomarkers but gives similar effects on mammographic density. Fenretinide exerted little modulation on most biomarkers. The clinical implications of these findings require additional studies.

Metabolic and Hormonal Profiles: HDL Cholesterol as a Plausible Biomarker of Breast Cancer Risk. The Norwegian EBBA Study

Low serum high-density lipoprotein cholesterol (HDL-C) is an important component of the metabolic syndrome and has recently been related to increased breast cancer risk in overweight and obese women. We therefore questioned whether serum HDL-C might be a biologically sound marker of breast cancer risk. We obtained cross-sectional data among 206 healthy women ages 25 to 35 years who participated in the Norwegian EBBA study. We included salivary ovarian steroid concentrations assessed by daily samples throughout one entire menstrual cycle, metabolic profile with measures of adiposity [body mass index (BMI) and truncal fat percentage], serum concentrations of lipids and hormones (insulin, leptin, testosterone, dehydroepiandrostendione sulfate, insulin-like growth factor-I, and its principal binding protein), and mammographic parenchymal pattern. We examined how components of the metabolic syndrome, including low serum HDL-C, were related to levels of hormones, and free estradiol concentration in particular, and studied predictors of mammographic parenchymal patterns in regression models. In women with BMI ≥ 23.6 kg/m2 (median), overall average salivary estradiol concentration dropped by 2.4 pmol/L (0.7 pg/mL; 13.2% change in mean for the total population) by each 0.33 mmol/L (12.8 mg/dl; 1SD) increase in serum HDL-C (P = 0.03; Pinteraction = 0.03). A subgroup of women characterized by both relatively high BMI (≥23.6 kg/m2) and high serum LDL-C/HDL-C ratio (≥ 2.08; 75 percentile) had substantially higher levels of salivary estradiol by cycle day than other women (P = 0.001). BMI was the strongest predictor of overall average estradiol with a direct relationship (P&lt; 0.001). Serum HDL-C was inversely related to serum leptin, insulin, and dehydroepiandrostendione sulfate (P &lt; 0.001, P &lt; 0.01, and P &lt; 0.05, respectively). There was a direct relationship between breast density and healthy metabolic profiles (low BMI, high serum HDL-C; P &lt; 0.001) and salivary progesterone concentrations (P &lt; 0.05). Our findings support the hypothesis that low serum HDL-C might reflect an unfavorable hormonal profile with, in particular, increased levels of estrogens and gives further clues to biomarkers of breast cancer risk especially in overweight and obese women.

Mammographic Density and Estrogen Receptor Status of Breast Cancer

Background: The density of breast tissue on a mammogram is a strong predictor of breast cancer risk and may reflect cumulative estrogen effect on breast tissue. Endogenous and exogenous estrogen exposure increases the risk of estrogen receptor (ER)–positive breast cancer. We determined if mammographic density is associated more strongly with ER-positive breast cancer than with ER-negative breast cancer.

Methods: We analyzed data from 44,811 participants in the San Francisco Mammography Registry of whom 701 developed invasive breast cancer. Mammographic density was measured using the Breast Imaging Reporting and Data System (BI-RADS) classification system (1 = almost entirely fat, 2 = scattered fibroglandular, 3 = heterogeneously dense, 4 = extremely dense). We tested for associations between mammographic density and ER-positive and ER-negative breast cancer separately. Analyses were adjusted for age, body mass index, postmenopausal hormone use, family history of breast cancer, menopausal status, parity, and race/ethnicity.

Results: Mammographic density was strongly associated with both ER-positive and ER-negative breast cancers. Compared with women with BI-RADS 2, women with BI-RADS 1 (lowest density) had a lower risk of ER-positive cancer [adjusted hazard ratio (HR), 0.28; 95% confidence interval (95% CI), 0.16-0.50] and ER-negative cancer (adjusted HR, 0.17; 95% CI, 0.04-0.70). Women with BI-RADS 4 (highest density) had an increased risk of ER-positive breast cancer (adjusted HR, 2.21; 95% CI, 1.64-3.04) and an increased risk of ER-negative breast cancer (adjusted HR, 2.21; 95% CI, 1.16-4.18).

Conclusion: Surprisingly, women with high mammographic density have an increased risk of both ER-positive and ER-negative breast cancers. The association between mammographic density and breast cancer may be due to factors besides estrogen exposure.

Estrogen and combined estrogen–progestogen therapy in the menopause and breast cancer

Most of the data on menopausal hormone therapy (HT) and breast cancer risk available up to the mid-1990s were included in a collaborative reanalysis based on over 52,000 women with and 108,000 without breast cancer. HT increased the risk of breast cancer by about 2.3% per year of use. Subsequent studies have confirmed that breast cancer risk is elevated in current and recent (but not past) HT users and that the relative risk (RR) is higher for users of combined estrogen-progestin treatment than for users of estrogen only, and this higher RR is seen with various types of preparations and different routes of administration. With reference to intervention studies, information on combined HT derives from the Women's Health Initiative (WHI). After 7 years of follow-up, 166 breast cancer cases were recorded in the HT group, as against 124 in the placebo group, corresponding to a RR of 1.24. Data from two other, smaller, randomized studies are available. In a combined analysis of the three randomized trials, 205 cases of breast cancer were observed in the treated groups as against 154 in the placebo groups, corresponding to a pooled RR of 1.27. However, in the estrogen-only component of the WHI population, at 8 years of follow-up 94 cases were observed in the estrogen group, opposed to 124 in the placebo group (RR=0.77). The results recorded in the WHI and the Million Women Study do not confirm the suggestion that breast cancers in women using HT have a more favorable prognosis. HT has also been related to an increased risk of recurrent breast cancer.

A 2-year soy intervention in premenopausal women does not change mammographic densities

Soy consumption may be related to lower breast cancer risk as assessed by breast density. The aims of this 2-y trial were to examine the effects of soy foods and lifetime soy intake on mammographic density. After 220 premenopausal women were randomly assigned to the intervention or control group, the former group consumed 2 daily servings of soy foods equivalent to 50 mg of isoflavones and the latter consumed their regular diet. The respective dropout rates were 15.6 and 12.6%; adherence to the study regimen was high. We assessed lifetime soy intake with a questionnaire and measured breast density in screening mammograms obtained at baseline and at the end of the trial for 98 intervention and 103 control women using a computer-assisted method. None of the mammographic outcomes differed significantly by experimental group. The total area of the breast increased and the size of the dense areas decreased significantly over time in both groups. After 2 y, the mean percentage density had decreased by 2.8 and 4.1% in intervention and control women, respectively. Women who reported eating more soy during their lives had higher percentage densities than women whose diet included little soy; this difference was significant only in Caucasians. Lower soy intake during early life and higher soy intake during adulthood predicted a greater reduction in the percentage density during the study period. After 2 y of intervention, we observed no significant differences in mammographic densities by intervention status, but it appears that soy consumption throughout life may have some effect on breast density.

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.

Thérapeutiques hormonales de la ménopause : impact sur la densité mammographique

Whether qualitative-classified or quantitative-measured, mammographic density, which changes according to physiological variations, is nowadays commonly recognized as a factor increasing the relative risk of breast cancer. The present review aims at clarifying the impact of menopausal hormonal therapies on mammographic density. Neither Tibolone nor Raloxifene seem to have any negative impact on mammographic density. In some instances, oestrogens-progestin hormonal replacement therapies may increase mammographic density and thus reduce sensitivity and specificity of screening mammograms. Shorter intervals between mammographies combined with additional physical examination and breast ultrasonography appear to be the best way to reduce interval cancers.

Hormones and mammographic breast density

Mammographic density reveals information about the hormonal environment along with the heritability in which breast cancer develops. This is made possible by the widespread use of population screening by mammography. Increasingly this is an important observation not just for population studies, which reveal disease determinants, but also for the individual. Density reveals the effect of the intrinsic hormonal environment and its background genetics, and also the effect of pharmaceuticals--agents used for disease control and prevention and hormone replacement therapy (HRT) used for well-being around the menopause. Increasingly this focus on the individual will need methods of measurement of density that can be monitored with greater accuracy than the widely used BI-RADS 4 categories. For this purpose studies are under way to measure volume of dense tissue as a continuous variable. In due course, measurement of density will be used as a biomarker of risk, employed in risk models and to monitor interventions. Before this can happen more knowledge will be needed of the change occurring naturally through the menopause and the differences between individuals. This will need specific study backed up with detailed information about the patient on large numbers of women and their mammograms. Currently the widespread use of HRT has increased the prevalence of the dense patterns and potentially may adversely affect the effectiveness of mammographic screening programmes. There is a large literature recording this from which we see that combined continuous preparations of oestrogen progestin are more likely to cause increased density than oestrogen alone or tibolone. Breast density, measured more accurately, has the potential to be an important adjunct to risk estimation and to monitor interventions for breast cancer prevention with pharmaceuticals (such as SERMS) and by change in lifestyle behaviours.

Prevention of cancers of the breast, endometrium and ovary

A central epidemiological feature of cancers of the breast, endometrium and ovary is the sharp slowing down in their rate of increase with age around the time of menopause. The incidence of these tumors by the age of 70 years would be between fourfold and eightfold increased if the rapid increase with age seen in young women continued into old age. These phenomena can be explained by the different effects of ovarian hormones on cell division rates in the relevant tissues. Models of these effects provide a plausible explanation of most of the known epidemiology of each of the cancers, including the increase in breast cancer risk from menopausal estrogen-progestin therapy. Some recent epidemiological findings in endometrial and ovarian cancer suggest new avenues for possible chemoprevention of these cancers.

Interaction of dense breast patterns with other breast cancer risk factors in a case-control study

The question of interactions between breast density and other breast cancer risk factors is of interest, since it bears upon the use of density as a marker for changes in breast cancer risk. We studied breast parenchymal patterns and 13 other potential risk factors for breast cancer in 172 breast cancer cases and 338 age-matched controls in Singapore. Dense breast patterns were defined as having Tabar parenchymal pattern IV or V. We found significant interactions between dense patterns and ethnic group (P=0.046), and between dense patterns and number of deliveries (P=0.04). Among women with nondense breast patterns, the non-Chinese had lower risk than the Chinese with an odds ratio (OR) of 0.47 (95% CI 0.24, 0.88), whereas in those with dense patterns, the non-Chinese had considerably higher risks (OR=5.34, 95% CI 0.54, 52.51). Alternatively expressed, the increased risk with dense patterns was only observed in the non-Chinese (OR=13.99, 95% CI 1.33, 146.99). Among parous women, the protective effect of three or more deliveries was only observed in those with dense breast patterns (OR=0.21, 95% CI 0.06, 0.70). Suggestive but nonsignificant interactions with dense patterns were observed for ever having delivered, age at first delivery, breast feeding and body mass index. The results are consistent with dense breast patterns as a marker for hormonal modification of breast cancer risk.

Post-Treatment Change in Serum Estrone Predicts Mammographic Percent Density Changes in Women Who Received Combination Estrogen and Progestin in the Postmenopausal Estrogen/Progestin Interventions (PEPI) Trial

Purpose

Postmenopausal estrogen and progestin therapy (EPT) increases mammographic percent density and breast cancer risk substantially more than does estrogen therapy alone. We determined whether increases in serum estrone as a function of treatment predict increases in mammographic percent density.

Methods

We measured mammographic percent density and serum estrone levels in participants in the Postmenopausal Estrogen/Progestin Interventions Trial who were randomly assigned to receive conjugated equine estrogens (CEE) 0.625 mg/d; CEE and medroxyprogesterone acetate (MPA) 10 mg on days 1 to 12 per 28-day cycle; CEE and MPA 2.5 mg/d; or CEE and micronized progesterone (MP) 200 mg on days 1 to 12 per 28-day cycle. We used linear regression to determine whether serum estrone changes predicted mammographic percent density changes from baseline to 1 year.

Results

Mammographic percent density increased with increasing change in estrone level in the EPT groups, but not in the CEE group. Combined, the mammographic percent density in the three EPT groups demonstrated an absolute increase of 2.95% per 100 pg/mL increase in serum estrone level (P = .0003). The absolute increases were 4.09% (P = .0018) in the CEE + MPA continuous group, 2.79% (P = .0292) in the CEE + MPA cyclical group, and 1.40% (P = .36) in the CEE + MP group, but the differences among the EPT groups were not statistically significant.

Conclusion

Greater increase in serum estrone level as a function of treatment is a significant predictor of increase in mammographic percent density in women randomly assigned to the combination of estrogen and progestin.

Mammographic Density in Relation to Daidzein-Metabolizing Phenotypes in Overweight, Postmenopausal Women

Circulating hormones are associated with mammographic density, an intermediate marker of breast cancer risk. Differences in circulating hormones, including estrone and testosterone, have been observed in premenopausal women based on their capacity to metabolize daidzein, an isoflavone found predominantly in soybeans. Equol and O-desmethylangolensin (O-DMA) are products of intestinal bacterial metabolism of daidzein. There is interindividual variability in the capacity to produce daidzein metabolites; individuals can be equol producers or non-producers and O-DMA producers or non-producers. We tested the hypothesis that daidzein-metabolizing phenotypes are associated with mammographic density. Participants were recruited from among 92 sedentary, postmenopausal women, ages 50 to 75 years, who participated in a 1-year physical activity intervention. Pre-intervention mammographic density was determined using a computer-assisted, gray-scale thresholding technique. Fifty-five of these women consumed supplemental soy protein (&gt;10 mg daidzein/d) for 3 days and collected a first-void urine sample on the fourth day to determine daidzein-metabolizing phenotypes. Equol and O-DMA concentrations were measured using gas chromatography-mass spectrometry. Associations between daidzein-metabolizing phenotypes and percent mammographic density were adjusted for age, maximum adult weight, gravidity, family history of breast cancer, and serum follicle-stimulating hormone and free testosterone concentrations. Mammographic density was 39% lower in equol producers compared with non-producers (P = 0.04). O-DMA producers had mammographic density 69% greater than non-producers (P = 0.05). These results suggest that particular intestinal bacterial profiles are associated with postmenopausal mammographic density, and these associations are not entirely explained by differences in reproductive or anthropometric characteristics or circulating hormones.

Tamoxifen and Breast Density in Women at Increased Risk of Breast Cancer

BACKGROUND

Although mammographic breast density is associated with the risk of breast cancer and is influenced by hormone levels, the effects of tamoxifen on breast density in healthy women and whether tamoxifen-induced density changes are associated with breast cancer risk are unclear. We investigated mammographic breast density in healthy women with an increased risk of breast cancer at baseline and during 54 months of tamoxifen treatment.

METHODS

Mammograms were reviewed from 818 breast cancer-free women (388 in the tamoxifen group and 430 in the placebo group) at high risk for breast cancer, from the International Breast Cancer Intervention Study I, a trial of tamoxifen for breast cancer prevention. Breast density measurements, at baseline and during treatment, were obtained at 12- to 18-month intervals. Multivariable analysis was used to assess associations with breast density. All statistical tests were two-sided.

RESULTS

Breast density at baseline was similar in placebo (42.6%, 95% confidence interval [CI] = 39.6% to 45.6%) and tamoxifen (41.9%, 95% CI = 38.8% to 45.0%) groups. The main determinants of breast density at baseline were age, menopausal status, body mass index, and previous atypical hyperplasia. A greater density reduction in the tamoxifen group (7.9%, 95% CI = 6.9% to 8.9%) than in the placebo group (3.5%, 95% CI = 2.7% to 4.3%) was apparent within 18 months of treatment (P<.001); the reduction in density continued until 54 months of treatment. After 54 months of tamoxifen treatment, breast density was 28.2% (decrease from baseline = 13.7%, 95% CI = 12.3% to 15.1%; P<.001) in the tamoxifen group and 35.3% (decrease from baseline = 7.3%, 95% CI = 6.1% to 8.4%; P<.001) in the placebo group. The tamoxifen-associated density reduction was apparent in all subgroups, but there was a statistically significant interaction with age. In women aged 45 years or younger at entry, the net reduction with tamoxifen was 13.4% (95% CI = 8.6% to 18.1%), whereas in women older than 55 years, it was 1.1% (95% CI = -3.0% to 5.1%).

CONCLUSION

Tamoxifen treatment was associated with reduction in breast density, most of which occurred during the first 18 months of treatment.

Polymorphism in the Androgen Receptor and Mammographic Density in Women Taking and Not Taking Estrogen and Progestin Therapy

There is some evidence that women with a higher number of CAG repeat lengths on the androgen receptor (AR) gene have increased breast cancer risk. We evaluated the association between AR-CAG repeat length and mammographic density, a strong breast cancer risk factor, in 404 African-American and Caucasian breast cancer patients. In postmenopausal estrogen progestin therapy users, carriers of the less active AR-CAG had statistically significantly higher mean percentage of density (41.4%) than carriers of the more active AR-CAG (25.7%; P = 0.04). Our results raise the question of whether the number of AR-CAG repeats predicts breast cancer risk in estrogen progestin therapy users.

Prognostic Characteristics of Breast Cancer Among Postmenopausal Hormone Users in a Screened Population

Purpose: We determined the risk of breast cancer and tumor characteristics among current postmenopausal hormone therapy users compared with nonusers, by duration of use.

Methods: From January 1996 to December 2000, data were collected prospectively on 374,465 postmenopausal women aged 50 to 79 years who underwent screening mammography. We calculated the relative risk (RR) of breast cancer (invasive or ductal carcinoma-in-situ) and type of breast cancer within 12 months of postmenopausal therapy use among current hormone users with a uterus (proxy for estrogen and progestin use) and without a uterus (proxy for estrogen use), compared with nonusers.

Results: Compared with nonusers, women using estrogen and progestin for ≥ 5 years were at increased risk of breast tumors of stage 0 or I (RR, 1.51; 95% CI, 1.37 to 1.66), stage II or higher (RR, 1.46; 95% CI, 1.30 to 1.63), size ≤ 20 mm (RR, 1.59; 95% CI, 1.43 to 1.76), size greater than 20 mm (RR, 1.24; 95% CI, 1.09 to 1.42), grade 1 or 2 (RR, 1.60; 95% CI, 1.44 to 1.77), grade 3 or 4 (RR, 1.54; 95% CI, 1.37 to 1.73), and estrogen receptor-positive (RR, 1.72; 95% CI, 1.55 to 1.90). Estrogen-only users were slightly more likely to have estrogen receptor-positive breast cancer compared with nonusers (RR, 1.14; 95% CI, 1.06 to 1.23).

Conclusion: Use of estrogen and progestin postmenopausal hormone therapy for five years or more increased the likelihood of developing breast cancer, including both tumors with favorable prognostic features and tumors with unfavorable prognostic features.

A cross-sectional investigation of breast density and insulin-like growth factor I

Our study investigated the association of breast cancer risk as assessed by mammographic density with insulin-like growth factor I (IGF-I) and one of its binding proteins (IGFBP-3) in healthy premenopausal women with different ethnic backgrounds. In a cross-sectional design, we analyzed the baseline mammograms and fasting serum samples (collected 5 days after ovulation) of premenopausal women entering a nutritional intervention. Serum concentrations of IGF-I and IGFBP-3 were measured by double-antibody ELISA. Mammographic densities were assessed using a computer-assisted method. We calculated Spearman correlation coefficients between mammographic characteristics and analytes and estimated means of mammographic characteristics by quartiles of IGF-I and IGFBP-3 while adjusting for age, body mass index (BMI) and reproductive factors. In this group of 240 women, IGF-I, IGFBP-3 and percent densities did not differ significantly by ethnicity. Whereas mammographic densities were not associated with IGF-I, we found an inverse relation with IGFBP-3 (r(s) = -0.15, p = 0.02) and a positive association with the IGF-I/IGFBP-3 ratio (r(s) = 0.13, p = 0.04). The size of the dense areas was not associated with the analytes, but the size of the nondense areas was correlated directly with IGFBP-3 (r(s) = 0.20, p = 0.002) and inversely with the molar ratio (r(s) = -0.19, p = 0.004). These associations were limited to women with a BMI of less than 25 kg/m(2). These results suggest that the balance of circulating IGF-I and IGFBP-3 levels may influence the growth of the fatty part of the breast more than the epithelial and stromal breast tissue, but the exact mechanism of action needs to be explored in more detail.

Expression profiling of human breast cancers and gene regulation by progesterone receptors

Even the first expression profiling studies of breast cancers have generated new insights. They suggest for example, that information about tumor aggressiveness, prognosis, metastatic potential, or treatment outcome is encoded in, and can be deduced from, the primary tumor. On the other hand no clinical genomic array data have yet been published that deal with hormonal aspects of breast tumorigenesis, tumor progression, or therapeutics. Rather, studies have focused on experimental model systems. We review below the currently published data on array profiling in clinical breast cancer, then describe our studies in breast cancer cell lines and xenograft models dealing with progesterone receptors (PRs) and the role of progesterone. We demonstrate that the two PR isoforms, PR-A and PR-B, have mostly nonoverlapping molecular signatures when liganded by progesterone, with PR-B the more active form. Additionally, we document the surprising finding that unliganded PRs can regulate gene transcription, with PR-A the more active form. In ovariectomized mice supplemented with estradiol but lacking measurable progesterone, PR-B-expressing tumors grow to twice the size of PR-A-expressing ones. We conclude that in breast cancers, PRs are more than simple markers of estrogen receptor function. Rather, presence of PRs and the ratio of the two isoforms directly influence tumor phenotype, even in the absence of ligand.

Mammographic density is related to stroma and stromal proteoglycan expression

BACKGROUND

Mammographic density and certain histological changes in breast tissues are both risk factors for breast cancer. However, the relationship between these factors remains uncertain. Previous studies have focused on the histology of the epithelial changes, even though breast stroma is the major tissue compartment by volume. We have previously identified lumican and decorin as abundant small leucine-rich proteoglycans in breast stroma that show altered expression after breast tumorigenesis. In this study we have examined breast biopsies for a relationship between mammographic density and stromal alterations.

METHODS

We reviewed mammograms from women aged 50-69 years who had enrolled in a provincial mammography screening program and had undergone an excision biopsy for an abnormality that was subsequently diagnosed as benign or pre-invasive breast disease. The overall mammographic density was classified into density categories. All biopsy tissue sections were reviewed and tissue blocks from excision margins distant from the diagnostic lesion were selected. Histological composition was assessed in sections stained with haematoxylin and eosin, and the expression of lumican and decorin was assessed by immunohistochemistry; both were quantified by semi-quantitative scoring.

RESULTS

Tissue sections corresponding to regions of high in comparison with low mammographic density showed no significant difference in the density of ductal and lobular units but showed significantly higher collagen density and extent of fibrosis. Similarly, the expression of lumican and decorin was significantly increased.

CONCLUSION

Alteration in stromal composition is correlated with increased mammographic density. Although epithelial changes define the eventual pathway for breast cancer development, mammographic density might correspond more directly to alterations in stromal composition.