The relationship of "high risk" mammographic patterns to histological risk factors for development of cancer in the human breast

No evidence for association of inherited variation in genes involved in mitosis and percent mammographic density

Introduction

Increased mammographic breast density is one of the strongest risk factors for breast cancer. While two-thirds of the variation in mammographic density appears to be genetically influenced, few variants have been identified. We examined the association of inherited variation in genes from pathways that mediate cell division with percent mammographic density (PMD) adjusted for age, body mass index (BMI) and postmenopausal hormones, in two studies of healthy postmenopausal women.

Methods

We investigated 2,058 single nucleotide polymorphisms (SNPs) in 378 genes involved in regulation of mitosis for associations with adjusted PMD among 484 unaffected postmenopausal controls (without breast cancer) from the Mayo Clinic Breast Cancer Study (MCBCS) and replicated the findings in postmenopausal controls (n = 726) from the Singapore and Sweden Breast Cancer Study (SASBAC) study. PMD was assessed in both studies by a computer-thresholding method (Cumulus) and linear regression approaches were used to assess the association of SNPs and PMD, adjusted for age, BMI and postmenopausal hormones. A P-value threshold of 4.2 × 10^-5 based on a Bonferroni correction of effective number of independent tests was used for statistical significance. Further, a pathway-level analysis was conducted of all 378 genes using the self-contained gene-set analysis method GLOSSI.

Results

A variant in PRPF4, rs10733604, was significantly associated with adjusted PMD in the MCBCS (P = 2.7 × 10^-7), otherwise, no single SNP was associated with PMD. Additionally, the pathway analysis provided no evidence of enrichment in the number of associations observed between SNPs in the mitotic genes and PMD (P = 0.60). We evaluated rs10733604 (PRPF4), and 73 other SNPs at P < 0.05 from 51 genes in the SASBAC study. There was no evidence of an association of rs10733604 (PRPF4) with adjusted PMD in SASBAC (P = 0.23). There were, however, consistent associations (P < 0.05) of variants at the putative locus, LOC375190, Aurora B kinase (AURKB), and Mini-chromosome maintenance complex component 3 (MCM3) with adjusted PMD, although these were not statistically significant.

Conclusions

Our findings do not support a role of inherited variation in genes involved in regulation of cell division and adjusted percent mammographic density in postmenopausal women.

Tissue composition of mammographically dense and non-dense breast tissue

Mammographic density is a strong risk factor for breast cancer but its underlying biology in healthy women is not well-defined. Using a novel collection of core biopsies from mammographically dense versus non-dense regions of the breasts of healthy women, we examined histologic and molecular differences between these two tissue types. Eligible participants were 40 + years, had a screening mammogram and no prior breast cancer or current endocrine therapy. Mammograms were used to identify dense and non-dense regions and ultrasound-guided core biopsies were performed to obtain tissue from these regions. Quantitative assessment of epithelium, stroma, and fat was performed on dense and non-dense cores. Molecular markers including Ki-67, estrogen receptor (ER) and progesterone receptor (PR) were also assessed for participants who had >0% epithelial area in both dense and non-dense tissue. Signed rank test was used to assess within woman differences in epithelium, stroma and fat between dense and non-dense tissue. Differences in molecular markers (Ki-67, ER, and PR) were analyzed using generalized linear models, adjusting for total epithelial area. Fifty-nine women, mean age 51 years (range: 40-82), were eligible for analyses. Dense tissue was comprised of greater mean areas of epithelium and stroma (1.1 and 9.2 mm(2) more, respectively) but less fat (6.0 mm(2) less) than non-dense tissue. There were no statistically significant differences in relative expression of Ki-67 (P = 0.82), ER (P = 0.09), or PR (P = 0.96) between dense and non-dense tissue. Consistent with prior reports, we found that mammographically dense areas of the breast differ histologically from non-dense areas, reflected in greater proportions of epithelium and stroma and lesser proportions of fat in the dense compared to non-dense breast tissue. Studies of both epithelial and stromal components are important in understanding the association between mammographic density and breast cancer risk.

Columnar cell lesions, mammographic density and breast cancer risk

BACKGROUND

Mammographic density is the third largest risk factor for ductal carcinoma in-situ (DCIS) and invasive breast cancer. However, the question of whether risk-mediating precursor histological changes, such as columnar cell lesions (CCLs), can be found in dense but non-malignant breast tissues has not been systematically addressed. We hypothesized that CCLs may be related to breast composition, in particular breast density, in non-tumour containing breast tissue.

PATIENTS AND METHODS

We examined randomly selected tissue samples obtained by bilateral subcutaneous mastectomy from a forensic autopsy series, where tissue composition was assessed, and in which there had been no selection of subjects or histological specimens for breast disease. We reviewed H&E slides for the presence of atypical and non-atypical CCLs and correlated with histological features measured using quantitative microscopy.

RESULTS

CCLs were seen in 40 out of 236 cases (17%). The presence of CCLs was found to be associated with several measures of breast tissue composition, including radiographic density: high Faxitron Wolfe Density (P = 0.037), high density estimated by percentage non-adipose tissue area (P = 0.037), high percentage collagen (P = 9.2E-05) and high percentage glandular area (P = 2E-05). DCIS was identified in two atypical CCL cases. The extent of CCL was not associated with any of the examined variables.

CONCLUSION

Our study is the first to report a possible association between CCLs and breast tissue composition, including mammographic density. Our data suggest that prospective elucidation of the strength and nature of the clinicopathological correlation may lead to an enhanced understanding of mammographic density and evidence based management strategies.

Mammographic density does not correlate with Ki-67 expression or cytomorphology in benign breast cells obtained by random periareolar fine needle aspiration from women at high risk for breast cancer

Background

Ki-67 expression is a possible risk biomarker and is currently being used as a response biomarker in chemoprevention trials. Mammographic breast density is a risk biomarker and is also being used as a response biomarker. We previously showed that Ki-67 expression is higher in specimens of benign breast cells exhibiting cytologic atypia that are obtained by random periareolar fine needle aspiration (RPFNA). It is not known whether there is a correlation between mammographic density and Ki-67 expression in benign breast ductal cells obtained by RPFNA.

Methods

Included in the study were 344 women at high risk for developing breast cancer (based on personal or family history), seen at The University of Kansas Medical Center high-risk breast clinic, who underwent RPFNA with cytomorphology and Ki-67 assessment plus a mammogram. Mammographic breast density was assessed using the Cumulus program. Categorical variables were analyzed by χ² test, and continuous variables were analyzed by nonparametric test and linear regression.

Results

Forty-seven per cent of women were premenopausal and 53% were postmenopausal. The median age was 48 years, median 5-year Gail Risk was 2.2%, and median Ki-67 was 1.9%. The median mammographic breast density was 37%. Ki-67 expression increased with cytologic abnormality (atypia versus no atypia; P ≤ 0.001) and younger age (≤50 years versus >50 years; P ≤ 0.001). Mammographic density was higher in premenopausal women (P ≤ 0.001), those with lower body mass index (P < 0.001), and those with lower 5-year Gail risk (P = 0.001). Mammographic density exhibited no correlation with Ki-67 expression or cytomorphology.

Conclusion

Given the lack of correlation of mammographic breast density with either cytomorphology or Ki-67 expression in RPFNA specimens, mammographic density and Ki-67 expression should be considered as potentially complementary response biomarkers in breast cancer chemoprevention trials.

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

BACKGROUND

Prolactin is a polypeptide hormone that promotes normal breast proliferation and differentiation, but it is also implicated in the development and growth of mammary tumors. Mammographic density is a strong, independent predictor of breast cancer and, therefore, a potential surrogate indicator of breast cancer risk.

METHODS

To test the hypothesis that serum prolactin is positively related to mammographic density, we conducted a cross-sectional analysis of baseline data from the Postmenopausal Estrogen/Progestin Interventions (PEPI) Mammographic Density Study. Based on prior work, we further hypothesized that this association would be apparent only in women who had not recently used postmenopausal hormone therapy (HT).

RESULTS

In linear regression models adjusted for age, body mass index, race, smoking, alcohol use, parity and physical activity, among the 400 women who were not recent users of HT, prolactin was positively and statistically significantly associated with mammographic density (Beta log base 2 prolactin 0.0369 [95% CI: 0.0094-0.0645]. Thus, for each doubling of serum prolactin, there was an absolute increase in mammographic density of 3.69%. Additional adjustment for serum levels of estradiol, progesterone, sex hormone binding globulin and age at first pregnancy did not affect this result. There was no association between prolactin and mammographic density among the 169 participants who had recently used HT.

CONCLUSION

The correspondence between higher prolactin and higher mammographic density is consistent with prolactin's mitogenic properties and the associations between prolactin and breast tumor promotion. These results support the thesis that prolactin deserves investigation as a target for breast cancer risk reduction.

The association of endogenous sex steroids and sex steroid binding proteins with mammographic density: results from the Postmenopausal Estrogen/Progestin Interventions Mammographic Density Study

Mammographic density is an independent risk factor for breast cancer. In postmenopausal women, higher levels of endogenous sex steroids are associated with an increased risk of breast cancer. Limited prior data suggest that endogenous sex steroids either are not associated (total estradiol and progesterone) or are negatively associated (free estradiol) with higher mammographic density. To analyze the associations between endogenous sex steroids and mammographic density, the authors conducted a 1998-2005 cross-sectional analysis of baseline clinical trial data from the Postmenopausal Estrogen/Progestin Interventions (PEPI) Trial for US women who had not used hormone therapy for at least 3.1 months prior to baseline. In models adjusted for age, body mass index, parity, prior use of hormone therapy, time since last use of hormone therapy, and the interaction between prior hormone therapy use and time since last hormone therapy use, higher levels of estrone (beta = 0.0013, p = 0.014), estradiol (beta = 0.0009, p = 0.009), and bioavailable estradiol (beta = 0.0021, p = 0.018) were statistically significantly related to greater mammographic density. (Beta coefficients express the increment in mammographic density per-unit increment (pg/ml) of each hormone.) These results suggest that some sex steroids may increase the risk of breast cancer by stimulating breast epithelial or stromal proliferation, which appears on a mammogram as higher density.

The association of measured breast tissue characteristics with mammographic density and other risk factors for breast cancer

BACKGROUND

We have examined the relationships between the measured properties of breast tissue and mammographic density and other risk factors for breast cancer, using breast tissue obtained at forensic autopsy and not selected for the presence of abnormalities.

METHODS

We used randomly selected tissue blocks taken from breast tissue slices obtained by s.c. mastectomy at the time of forensic autopsy to measure histologic features using quantitative microscopy. The proportions of the biopsy occupied by cells (estimated by nuclear area), glandular structures, and collagen were determined. These measurements were examined in relation to the percent density in the faxitron image of the tissue slice from which the biopsy was taken and other risk factors for breast cancer.

RESULTS

The percent mammographic density was associated with the proportion of the area of the biopsy occupied by nuclei, both epithelial and nonepithelial, and by collagen and the area of glandular structures. Several other risk factors for breast cancer, notably body weight, parity, and number of births, and menopausal status, that are associated with variations in mammographic density, were also associated with differences in one or more of these tissue features.

CONCLUSION

All risk factors for breast cancer must ultimately exert their influence by an effect on the breast, and these findings suggest that, for some risk factors, this influence includes an effect on the number of cells and the quantity of collagen.

Likelihood of additional work-up among women undergoing routine screening mammography: the impact of age, breast density, and hormone therapy use

BACKGROUND

Mammography screening can involve subsequent work-up to determine a final screening outcome. Understanding the likelihood of different events that follow initial screening is important if women and their health care providers are to be accurately informed about the screening process.

METHODS

We conducted an analysis of additional work-up following screening mammography to characterize use of supplemental imaging and recommendations for biopsy and/or surgical consultation and the factors associated with their use. We included all events following screening mammography performed between 1/1/1998 and 12/31/1999 on a population-based sample of 37,632 New Hampshire women. We calculated adjusted odds ratios (OR) and 95% confidence intervals (CI) for supplemental imaging and recommended biopsy and/or surgical consultation as function of age, menopausal status and HRT use, breast density, and family history of breast cancer.

RESULTS

Ninety-one percent of women (n = 34,445) did not require supplemental imaging. Among those who did (n = 3187), 84% had additional views, 9% ultrasound, and 7% received both. Supplemental imaging was affected by age (OR 0.84; 95% CI = 0.76-0.94 for 50-59; OR = 0.66; 95% CI = 0.58-0.75 for > or = 60 versus < 50), menopausal status, and HRT use (OR = 1.33; 95% CI = 1.21-1.47 for peri- or post-menopausal HRT users; OR = 1.14; 95% CI = 1.01-1.29 for premenopausal versus peri- or post-menopausal non-HRT users), breast density (OR = 1.43; 95% CI = 1.33-1.55 for dense versus fatty breasts) and family history (OR = 1.15; 95% CI = 1.06-1.25 for any versus none). In women with supplemental imaging, age (OR = 1.80; 95% CI = 1.11-2.90 for > or = 60, relative to <50) and imaging type (OR = 3.23; 95% CI = 2.38-4.38 for ultrasound with or without additional views versus additional views only) were significantly associated with biopsy and/or surgical consultation recommendation. In those with no supplemental imaging, breast density was associated with recommended biopsy and/or surgical consultation (OR = 1.53; 95% CI = 1.13-2.07 for dense versus fatty breasts).

CONCLUSIONS

Breast density and HRT use are both independent predictors of use of supplemental imaging in women. With advancing age (age 60 and older), women were less likely to require follow-up imaging but more likely to receive a recommendation for biopsy and/or surgical consultation. This information should be used to inform women about the likelihood of services received as part of the screening work-up.

Quantitative Assessment of Mammographic Breast Density: Relationship with Breast Cancer Risk

Increased mammographic breast density is a moderate independent risk factor for breast cancer, with findings of published studies in which quantitative methods of assessment were used showing a positive association. Breast density may be quantified by using visual assessment or planimetry. Although the category definitions vary, the odds ratio for developing breast cancer for the most dense compared with the least dense breast tissue categories ranges from 1.8 to 6.0, with most studies yielding an odds ratio of 4.0 or greater. Plausible explanations for the association of breast density with increased breast cancer risk may be the development of premalignant lesions such as atypical ductal hyperplasia, elevated growth factors, or increased estrogen production within the breast due to overactive aromatase. The amount of breast density may be due in part to genetic heredity. However, unlike other risk factors, breast density may be influenced. Specifically, breast density is very hormonally responsive and potentially may be influenced by lifestyle factors such as alcohol intake and diet. Assessment of breast density may become useful in risk assessment and prevention decisions.

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.

Can the stroma provide the clue to the cellular basis for mammographic density?

Mammographic density is recognised as a useful phenotypic biomarker of breast cancer risk. Deeper understanding is needed of the cellular basis, but evidence is limited because of difficulty in designing studies to validate hypotheses. The ductal epithelial components do not adequately explain the physical and dynamic features observed. The stroma is thought to interact with ductal structures in cancer initiation. Stromal tissues might account for the mammographic features, and this interplay can be hypothesised to relate risk to density. In a paper in this issue of Breast Cancer Research, Alowami has shown a relationship between density and stromal proteins, which might provide useful insight into mammographic density.

Mammographic tissue, breast cancer risk, serial image analysis, and digital mammography. Part 1. Tissue and related risk factors

This work is presented as a sequence of two parts. In this leading section, a review of the breast tissue-risk research is provided. Although controversy remains, there is substantial evidence indicating that dense mammographic tissue (a) is a breast cancer risk factor that is at least similar, if not greater, in magnitude with the other known breast cancer risk factors and (b) may be a partial biomarker for some of the other risk factors. Understanding these influences may provide a mechanism for measuring the dynamics of breast cancer risk. The totality of this work is to provide support for an automated serial mammography study under way at the authors' institution, where digital mammographic images are acquired with a full-field digital mammography system. This is a filmless imaging system, where the image is acquired in digital format. This electronic imaging acquisition system provides a prime opportunity to easily couple and manipulate the image data with patient information such as risk probability analysis or other pertinent personal history data for improved automated decision making. In this leading section, the main focus is on understanding elements that will assist in fusing risk probability analysis with automated computer-aided diagnosis. The evidence indicates that there are many factors that influence breast tissue at any given time and thus have the ability to alter the associated radiographic image appearance over time. At the initiation of the serial study it was clear that the authors did not fully understand the nature of the problem: automatically comparing similar mammographic scenes acquired at different times. In the second part of this sequence, the more time-related tissue influences are reviewed.

Parity and mammographic breast density in relation to breast cancer risk: indication of interaction

We examined whether the harmful influence of nulliparity on breast cancer risk could be mediated by high mammographic density. Another possibility is that mammographic density and nulliparity act independently or perhaps synergistically on breast cancer risk. Our study population consisted of 129 cases and 517 controls who had been participants in the Nijmegen breast cancer screening programme for 10 years. Breast density was classified with a fully automated technique on digitized mammograms from the screening examination 10 years before diagnosis. Classification was based on the proportion of the breast that was composed of high density: < 5%, 5-25% or > 25%. Data on parity and potential confounders were obtained using a questionnaire, administered at the same examination. We found that nulliparae with low breast density (< 5%) were not at increased risk compared to parous women with low density: OR 1.1 (95% CI 0.2-5.8). Parous women with < 5% density formed the reference category throughout all analyses. The risks for parous women with 5-25% or > 25% density were 2.7 (95% CI 1.3-5.6) and 3.6 (95% CI 1.7-7.7) fold increased, respectively. However, when both factors were present (nulliparity and > or = 5% density), breast cancer risk was 7.1 times higher (95% CI 3.2-15.9). This could indicate that nulliparity and high breast density might work synergistically and that breast density is not just an explanatory factor in the influence of nulliparity on breast cancer risk. It is hypothesized that high breast density (reflecting fibro-glandular tissue with increased epithelial cell proliferation) is more susceptible to carcinogenic effects in the undifferentiated epithelial breast tissue of nulliparae than in the differentiated tissue of parous women. Since there were few data, no firm conclusions can be drawn. If these findings can be confirmed in a larger study population, however, they may have important implications for the prevention and early detection of breast cancer.

Mammographic densities and the prevalence and incidence of histological types of benign breast disease. Reference Pathologists of the Canadian National Breast Screening Study

There is now a large amount of evidence indicating that women with extensive areas of mammographic densities are 4-6 times more likely to develop breast cancer than those with little or no density in the mammogram. We have examined one potential biological explanation for this association by estimating the incidence of various histological types of benign breast disease in relation to mammographic density. We studied the large cohort of women taking part in the National Breast Screening Study (NBSS), a randomized trial of screening with mammography. Mammograms from subjects with biopsies (n = 423) and from a comparison group of subjects randomly selected from the NBSS (n = 465) were included. Histological slides from biopsied subjects (n = 353) were classified independently by the pathologists of the NBSS and by a review pathologist (H.M.J.). Mammographic density in more than 75% of the breast area was associated with an increased risk of incidence of hyperplasia without atypia, and of atypical hyperplasia and/or carcinoma in situ. The classifications of the review pathologist showed that, compared to women with no density, the relative risk of incident lesions for women with density in more than 75% of breast was 13.85 (95% CI 2.65-72.49) for hyperplasia, and 9.23 (95% CI 1.66-51.48) for atypical hyperplasia and/or carcinoma in situ. These findings suggest that the association between extensive mammographic density and breast cancer risk may, at least in part, be attributable to biological processes in the breast that give rise to these histological features that are known to be related to breast cancer risk.

Wolfe's mammographic patterns in women with gross cystic disease of the breast

The epidemiologic determinants of the mammographic pattern were studied in 710 patients with aspirated gross (> 1 ml) cysts of the breast. The prevalence of the mammograms classified as P2-DY, that are considered to be associated with an increased breast cancer risk, was 636/710 or 89.6%. No relationship between mammographic patterns and characteristics of breast cyst fluid such as K+/Na+ ratio, apocrine changes and dehydroepiandrosterone sulfate concentration was observed. A significant decrease in the proportion of these patterns with increasing age (p = 0.006), Quetelet Index (p < 0.001), parity (p = 0.001), and in postmenopausal women (p = 0.026) was found. Conversely, P2-DY patterns were significantly associated with a later age at menarche (p = 0.023) and alcohol consumption (p = 0.001). In multivariate analysis, an independent association with age was not observed whereas the associations with age at menarche, parity, and relative weight were confirmed. In conclusion, the epidemiologic determinants of mammographic patterns are the same in Gross Cystic Disease patients as in unaffected women, and the lack of correlation between mammographic pattern and cyst type suggests that the latter may represent an independent predictor of breast cancer risk.

Mammographic patterns in breast cancer chemoprevention with fenretinide (4-HPR)

In 1987 a chemoprevention trial was started at the Istituto Nazionale Tumori of Milan to evaluate the efficacy of fenretinide or 4-HPR (an effective agent against carcinogen-induced epithelial tumours in experimental animals) in reducing the incidence of contralateral breast cancer in women previously treated for an early breast cancer (pT1, pT2, N-). Patients were randomised into two groups: 4-HPR 200 mg/day vs. no treatment. We reviewed the mammograms of 149 patients who received 4-HPR for at least 4 years to examine whether changes seen in the mammary glands of rats could also be seen in women. For each patient, at least five mammograms (one at baseline and four annual controls) of the contralateral breast were classified according to Wolfe's parenchymal patterns (N1, P1, P2, DY). With the daily dosage of 200 mg and after follow-up, no changes in mammographic patterns were observed.