Benign Breast Disease and Breast Cancer Risk in the Percutaneous Biopsy Era

Importance

Benign breast disease (BBD) comprises approximately 75% of breast biopsy diagnoses. Surgical biopsy specimens diagnosed as nonproliferative (NP), proliferative disease without atypia (PDWA), or atypical hyperplasia (AH) are associated with increasing breast cancer (BC) risk; however, knowledge is limited on risk associated with percutaneously diagnosed BBD.

Objectives

To estimate BC risk associated with BBD in the percutaneous biopsy era irrespective of surgical biopsy.

Design, Setting, and Participants

In this retrospective cohort study, BBD biopsy specimens collected from January 1, 2002, to December 31, 2013, from patients with BBD at Mayo Clinic in Rochester, Minnesota, were reviewed by 2 pathologists masked to outcomes. Women were followed up from 6 months after biopsy until censoring, BC diagnosis, or December 31, 2021.

Exposure

Benign breast disease classification and multiplicity by pathology panel review.

Main Outcomes

The main outcome was diagnosis of BC overall and stratified as ductal carcinoma in situ (DCIS) or invasive BC. Risk for presence vs absence of BBD lesions was assessed by Cox proportional hazards regression. Risk in patients with BBD compared with female breast cancer incidence rates from the Iowa Surveillance, Epidemiology, and End Results (SEER) program were estimated.

Results

Among 4819 female participants, median age was 51 years (IQR, 43-62 years). Median follow-up was 10.9 years (IQR, 7.7-14.2 years) for control individuals without BC vs 6.6 years (IQR, 3.7-10.1 years) for patients with BC. Risk was higher in the cohort with BBD than in SEER data: BC overall (standard incidence ratio [SIR], 1.95; 95% CI, 1.76-2.17), invasive BC (SIR, 1.56; 95% CI, 1.37-1.78), and DCIS (SIR, 3.10; 95% CI, 2.54-3.77). The SIRs increased with increasing BBD severity (1.42 [95% CI, 1.19-1.71] for NP, 2.19 [95% CI, 1.88-2.54] for PDWA, and 3.91 [95% CI, 2.97-5.14] for AH), comparable to surgical cohorts with BBD. Risk also increased with increasing lesion multiplicity (SIR: 2.40 [95% CI, 2.06-2.79] for ≥3 foci of NP, 3.72 [95% CI, 2.31-5.99] for ≥3 foci of PDWA, and 5.29 [95% CI, 3.37-8.29] for ≥3 foci of AH). Ten-year BC cumulative incidence was 4.3% for NP, 6.6% for PDWA, and 14.6% for AH vs an expected population cumulative incidence of 2.9%.

Conclusions and Relevance

In this contemporary cohort study of women diagnosed with BBD in the percutaneous biopsy era, overall risk of BC was increased vs the general population (DCIS and invasive cancer combined), similar to that in historical BBD cohorts. Development and validation of pathologic classifications including both BBD severity and multiplicity may enable improved BC risk stratification.

Impact of Artificial Intelligence System and Volumetric Density on Risk Prediction of Interval, Screen-Detected, and Advanced Breast Cancer

PURPOSE

Artificial intelligence (AI) algorithms improve breast cancer detection on mammography, but their contribution to long-term risk prediction for advanced and interval cancers is unknown.

METHODS

We identified 2,412 women with invasive breast cancer and 4,995 controls matched on age, race, and date of mammogram, from two US mammography cohorts, who had two-dimensional full-field digital mammograms performed 2-5.5 years before cancer diagnosis. We assessed Breast Imaging Reporting and Data System density, an AI malignancy score (1-10), and volumetric density measures. We used conditional logistic regression to estimate odds ratios (ORs), 95% CIs, adjusted for age and BMI, and C-statistics (AUC) to describe the association of AI score with invasive cancer and its contribution to models with breast density measures. Likelihood ratio tests (LRTs) and bootstrapping methods were used to compare model performance.

RESULTS

On mammograms between 2-5.5 years prior to cancer, a one unit increase in AI score was associated with 20% greater odds of invasive breast cancer (OR, 1.20; 95% CI, 1.17 to 1.22; AUC, 0.63; 95% CI, 0.62 to 0.64) and was similarly predictive of interval (OR, 1.20; 95% CI, 1.13 to 1.27; AUC, 0.63) and advanced cancers (OR, 1.23; 95% CI, 1.16 to 1.31; AUC, 0.64) and in dense (OR, 1.18; 95% CI, 1.15 to 1.22; AUC, 0.66) breasts. AI score improved prediction of all cancer types in models with density measures (PLRT values < .001); discrimination improved for advanced cancer (ie, AUC for dense volume increased from 0.624 to 0.679, Δ AUC 0.065, P = .01) but did not reach statistical significance for interval cancer.

CONCLUSION

AI imaging algorithms coupled with breast density independently contribute to long-term risk prediction of invasive breast cancers, in particular, advanced cancer.

Comparison of breast density assessments between synthesized C-View™ & intelligent 2D™ mammography

OBJECTIVE

To compare breast density assessments between C-View™ and Intelligent 2D™, different generations of synthesized mammography (SM) from Hologic.

METHODS

In this retrospective study, we identified a subset of females between March 2017 and December 2019 who underwent screening digital breast tomosynthesis (DBT) with C-View followed by DBT with Intelligent 2D. Clinical Breast Imaging Reporting and Database System breast density was obtained along with volumetric breast density measures (including density grade, breast volume, percentage volumetric density, dense volume) using VolparaTM. Differences in density measures by type of synthesized image were calculated using the pairwise t-test or McNemar's test, as appropriate.

RESULTS

67 patients (avg age 62.7; range 40-84) were included with an average of 13.3 months between the two exams. No difference was found in Breast Imaging Reporting and Database System density between the SM reconstructions (p = 0.74). Similarly, there was no difference in VolparaTM mean density grade (p = 0.71), mean breast volume (p = 0.48), mean dense volume (p = 0.43) or mean percent volumetric density (p = 0.12) between the exams.

CONCLUSION

We found no significant differences in clinical and automated breast density assessments between these two versions of SM.

ADVANCES IN KNOWLEDGE

Lack of differences in density estimates between the two SM reconstructions is important as density assignment impacts risk stratification and adjunct screening recommendations.

Fully Automated Volumetric Breast Density Estimation from Digital Breast Tomosynthesis

Background While digital breast tomosynthesis (DBT) is rapidly replacing digital mammography (DM) in breast cancer screening, the potential of DBT density measures for breast cancer risk assessment remains largely unexplored. Purpose To compare associations of breast density estimates from DBT and DM with breast cancer. Materials and Methods This retrospective case-control study used contralateral DM/DBT studies from women with unilateral breast cancer and age- and ethnicity-matched controls (September 19, 2011-January 6, 2015). Volumetric percent density (VPD%) was estimated from DBT using previously validated software. For comparison, the publicly available Laboratory for Individualized Breast Radiodensity Assessment software package, or LIBRA, was used to estimate area-based percent density (APD%) from raw and processed DM images. The commercial Quantra and Volpara software packages were applied to raw DM images to estimate VPD% with use of physics-based models. Density measures were compared by using Spearman correlation coefficients (r), and conditional logistic regression was performed to examine density associations (odds ratios [OR]) with breast cancer, adjusting for age and body mass index. Results A total of 132 women diagnosed with breast cancer (mean age ± standard deviation [SD], 60 years ± 11) and 528 controls (mean age, 60 years ± 11) were included. Moderate correlations between DBT and DM density measures (r = 0.32-0.75; all P < .001) were observed. Volumetric density estimates calculated from DBT (OR, 2.3 [95% CI: 1.6, 3.4] per SD for VPD%_DBT) were more strongly associated with breast cancer than DM-derived density for both APD% (OR, 1.3 [95% CI: 0.9, 1.9] [P < .001] and 1.7 [95% CI: 1.2, 2.3] [P = .004] per SD for LIBRA raw and processed data, respectively) and VPD% (OR, 1.6 [95% CI: 1.1, 2.4] [P = .01] and 1.7 [95% CI: 1.2, 2.6] [P = .04] per SD for Volpara and Quantra, respectively). Conclusion The associations between quantitative breast density estimates and breast cancer risk are stronger for digital breast tomosynthesis compared with digital mammography. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Yaffe in this issue.

Conformational rearrangements enable iterative backbone N-methylation in RiPP biosynthesis

Peptide backbone α-N-methylations change the physicochemical properties of amide bonds to provide structural constraints and other favorable characteristics including biological membrane permeability to peptides. Borosin natural product pathways are the only known ribosomally encoded and posttranslationally modified peptides (RiPPs) pathways to incorporate backbone α-N-methylations on translated peptides. Here we report the discovery of type IV borosin natural product pathways (termed 'split borosins'), featuring an iteratively acting α-N-methyltransferase and separate precursor peptide substrate from the metal-respiring bacterium Shewanella oneidensis. A series of enzyme-precursor complexes reveal multiple conformational states for both α-N-methyltransferase and substrate. Along with mutational and kinetic analyses, our results give rare context into potential strategies for iterative maturation of RiPPs.

Association of Daily Alcohol Intake, Volumetric Breast Density, and Breast Cancer Risk

High alcohol intake and breast density increase breast cancer (BC) risk, but their interrelationship is unknown. We examined whether volumetric density modifies and/or mediates the alcohol-BC association. BC cases (n = 2233) diagnosed from 2006 to 2013 in the San Francisco Bay area had screening mammograms 6 or more months before diagnosis; controls (n = 4562) were matched on age, mammogram date, race or ethnicity, facility, and mammography machine. Logistic regression was used to estimate alcohol-BC associations adjusted for age, body mass index, and menopause; interaction terms assessed modification. Percent mediation was quantified as the ratio of log (odds ratios [ORs]) from models with and without density measures. Alcohol consumption was associated with increased BC risk (2-sided P_trend = .004), as were volumetric percent density (OR = 1.45 per SD, 95% confidence interval [CI] = 1.36 to 1.56) and dense volume (OR = 1.30, 95% CI = 1.24 to 1.37). Breast density did not modify the alcohol-BC association (2-sided P > .10 for all). Dense volume mediated 25.0% (95% CI = 5.5% to 44.4%) of the alcohol-BC association (2-sided P = .01), suggesting alcohol may partially increase BC risk by increasing fibroglandular tissue.

Abstract PS7-11: Benign breast disease: Temporal trends from 1967 to 2013

Background: Women with benign breast disease (BBD) are at increased risk of breast cancer (BC). Classic studies based on film-based mammographic screening and pathology diagnosis of surgical biopsies conducted in the 1980s established a hierarchy of increasing BC risk: non-proliferative (NP) BBD, proliferative BBD without atypia (PDWA) and atypical hyperplasia (AH). Given changes in epidemiological BC risk factors and introduction of percutaneous core needle biopsy (CNB) in mid-1990s, and later, digital mammography, we hypothesized that the patient characteristics and relative frequency of BBD diagnoses have changed over time. Accordingly, we performed a longitudinal analysis of the frequency of patient characteristics and BBD diagnoses in the Mayo BBD cohort.

Methods: Utilizing the Mayo Clinic Surgical and Pathology Indices, women ages 18 to 85 who had a BBD biopsy between 1/1/67 and 12/31/13 were identified. Breast pathologists reviewed biopsies masked to diagnoses of incident BC diagnosed in follow-up. Demographic characteristics and BC events were obtained by query of institutional data sources and participant surveys. Trends were evaluated for the following eras: 1: pre-mammogram (1967-1981), 2: pre-CNB (1982-1992), 3: CNB Transition (1993-2001), and 4: CNB (2002-2013). Demographics were formally compared across eras using chi-square tests for categorical variables and analyses of variance (ANOVAs) for continuous variables.

Results: From 1967-2013, the cohort includes 19,582 unique women with BBD. The frequency of CNB increased from eras 1-4: 0.04%, 0.6%, 51.3 %, and 88.9%, respectively. Mean age at BBD diagnosis was younger in era 1 (48.0 years) vs eras 2-4 (53.2, 52.0, and 51.8, respectively, p&lt;0.001). The percentage of biopsies diagnosed as PDWA increased from era 1-4 (25.7%, 34.3%, 35.2%, 46.2%, p&lt;0.001), as did the percentage with AH (2.4%, 5.1%, 8.6%, 12.3%, p&lt;0.001). Over eras 1-4, the percentages of women with a strong family history of BC increased (9.9%, 12.7%, 17.1%, and 29.0%, p&lt;0.001) as did mean BMI (24.8, 26.4, 27.4, and 28.6, p&lt;0.001). With a median follow-up of 10.9 years, 1,719 breast cancers have developed, with increasing proportion of noninvasive (DCIS-only) disease across eras 1-4: 15.0%, 21.1%, 21.2%, and 33.2%, p&lt; 0.001.

Conclusions: Analysis of this large, single institution BBD cohort for the 46 year period 1967-2013 demonstrates that BC risk factors among BBD patients has changed over time, with subjects demonstrating increasing age, BMI, and family history, and that the percentages of BBD classified as PDWA and AH have increased. Impact on BC risk will be further investigated.

Citation Format: Amy Degnim, Karthik Ghosh, Jodi M Carter, Robert A Vierkant, Matthew R Jensen, Stacey J Winham, Tanya L Hoskin, Marlene Frost, Teresa M Allers, Denise L Gehling, Mindy J Kern, Laura M Pacheco-Spann, Celine M Vachon, Derek C Radisky, Daniel W Visscher, Mark E Sherman. Benign breast disease: Temporal trends from 1967 to 2013 [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-11.

Abstract PD10-10: Epithelial proliferation score as an independent breast cancer risk predictor in benign breast disease

Background: Women with benign breast disease (BBD) experience an increased risk of breast cancer (BC). Histologic classification of BBD, as non-proliferative disease (NP), proliferative disease without atypia (PDWA) or atypical hyperplasia (AH), stratifies groups of patients into progressively higher categories of BC risk. However, this classification does not comprehensively assess the proliferative state of the epithelium throughout the biopsy. In addition, while AH is considered the most high-risk class of BBD, it is not always a highly proliferative lesion; atypical ductal lesions may reflect focal cytologic and architectural changes. We evaluated the association of an alternative classification of BBD severity and BC risk based on subjective grading of: 1) the maximal degree of epithelial proliferation and 2) multifocality of epithelial proliferation. Methods: Pathologists reviewed biopsies from participants aged 18 to 85 years in the Mayo BBD cohort (2002-2013), masked to BC outcomes, ascertained via questionnaires, tumor registry data and medical record review. Biopsies were classified as NP, PDWA or AH and semi-quantitatively scored for: 1) maximal degree of epithelial proliferation within a focus (DP) (0-3; none to severe) and 2) multifocality of proliferation (MP) (0-3; none to multiple foci). DP and MP scores were also summed to give a DP+MP score (0-6). Associations of DP and MP with BC risk were examined using Cox proportional hazards regression analyses, adjusting for age at BBD biopsy. Women were followed from date of initial biopsy to date of BC, death or last follow-up. Results: Of the 1529 assessable biopsies, 544 (35.6%) were classified as NP, 708 (46.3%) as PDWA and 277 (18.1%) as AH. Both DP and MP scores had significant positive correlation with increasing BBD severity (DP: r=0.51, p&lt; 0.001; MP: r=0.52, p&lt; 0.001). Mean (SD) DP scores were 0.6 (0.6) for NP, 1.6 (0.9) for PDWA, and 1.8 (0.7) for AH (ANOVA p&lt;0.001). Mean (SD) for MP scores were 0.6 (0.6) for NP, 1.4 (0.8) for PDWA, and 1.8 (0.8) for AH (ANOVA p&lt;0.001). Mean (SD) for DP+MP scores were 1.2 (1.2) for NP, 2.9 (1.5) for PDWA, and 3.6 (1.2) for AH (ANOVA p&lt;0.001). With median follow-up of 8.8 years for controls and 5.3 years for cases, 10.6% of the women in the cohort developed BC. Compared to those with DP scores of 0, women with DP scores of 3 had significantly increased BC risk (HR 1.42, 95% CI: 1.16, 1.74, p=0.003). MP was associated with a non-significant increase in BC risk for scores of 3 versus 0 (HR: 1.20, 95% CI: 0.97,1.49, p=0.11). DP+MP scores of 6 conferred the highest BC risk (HR (score 6 vs. 0): 1.62, 95% CI 1.18,2.21, p=0.02). Results did not substantively differ after adjusting for BBD severity as NP, PDWA or AH. Conclusions: In this preliminary analysis within the Mayo BBD cohort, both proliferative degree (DP) and multifocality (MP) scores were correlated with histologic severity of BBD. DP and DP+MP scores were each associated with increased BC risk. We conclude that improved characterization of epithelial proliferation in BBD biopsies may enable refined prediction of individual BC risk.

Citation Format: Jodi M Carter, Matthew R Jensen, Robert A Vierkant, Stacey J Winham, Tanya L Hoskin, Marlene Frost, Karthik Ghosh, Derek C Radisky, Amy C Degnim, Mark E Sherman. Epithelial proliferation score as an independent breast cancer risk predictor in benign breast disease [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD10-10.

Association of mammographic density measures and breast cancer "intrinsic" molecular subtypes

PURPOSE

We evaluated the association of percent mammographic density (PMD), absolute dense area (DA), and non-dense area (NDA) with risk of "intrinsic" molecular breast cancer (BC) subtypes.

METHODS

We pooled 3492 invasive BC and 10,148 controls across six studies with density measures from prediagnostic, digitized film-screen mammograms. We classified BC tumors into subtypes [63% Luminal A, 21% Luminal B, 5% HER2 expressing, and 11% as triple negative (TN)] using information on estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and tumor grade. We used polytomous logistic regression to calculate odds ratio (OR) and 95% confidence intervals (CI) for density measures (per SD) across the subtypes compared to controls, adjusting for age, body mass index and study, and examined differences by age group.

RESULTS

All density measures were similarly associated with BC risk across subtypes. Significant interaction of PMD by age (P = 0.001) was observed for Luminal A tumors, with stronger effect sizes seen for younger women < 45 years (OR = 1.69 per SD PMD) relative to women of older ages (OR = 1.53, ages 65-74, OR = 1.44 ages 75 +). Similar but opposite trends were seen for NDA by age for risk of Luminal A: risk for women: < 45 years (OR = 0.71 per SD NDA) was lower than older women (OR = 0.83 and OR = 0.84 for ages 65-74 and 75 + , respectively) (P < 0.001). Although not significant, similar patterns of associations were seen by age for TN cancers.

CONCLUSIONS

Mammographic density measures were associated with risk of all "intrinsic" molecular subtypes. However, findings of significant interactions between age and density measures may have implications for subtype-specific risk models.

Breast Cancer Risk and Use of Nonsteroidal Anti-inflammatory Agents After a Benign Breast Biopsy

Over one million women in the United States receive biopsy diagnoses of benign breast disease (BBD) each year, which confer a 1.5-4.0-fold increase in breast cancer risk. Studies in the general population suggest that nonsteroidal anti-inflammatory agents (NSAID) lower breast cancer risk; however, associations among women with BBD are unknown. We assessed whether NSAID use among women diagnosed with BBD is associated with lower breast cancer risk. Participants included 3,080 women (mean age = 50.3 ± 13.5 years) in the Mayo BBD surgical biopsy cohort diagnosed between January 1, 1992 and December 31, 2001 who completed breast cancer risk factor questionnaires that assessed NSAID use, and whose biopsies underwent detailed pathology review, masked to outcome. Women were followed from date of BBD biopsy to breast cancer diagnosis (main outcome) or censoring (death, prophylactic mastectomy, reduction mammoplasty, lobular carcinoma in situ or last contact). Median follow-up time was 16.4 ± 6.0 years. Incident breast cancer was diagnosed among 312 women over a median follow-up of 9.9 years. Regular non-aspirin NSAID use was associated with lower breast cancer risk [HR = 0.63; 95% confidence interval (CI) = 0.46-0.85; P = 0.002] with trends of lower risk (highest tertiles of use vs. nonuse) for greater number of years used [HR = 0.55; 95% CI = 0.31-0.97; P _trend = 0.003), days used per month (HR = 0.51; 95% CI = 0.33-0.80; P _trend = 0.001) and lifetime number of doses taken (HR = 0.53; 95% CI = 0.31-0.89; P _trend = 0.003). We conclude that nonaspirin NSAID use is associated with statistically significant lower breast cancer risk after a BBD biopsy, including a dose-response effect, suggesting a potential role for NSAIDs in breast cancer prevention among patients with BBD.

Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction

Background The associations of density measures from the publicly available Laboratory for Individualized Breast Radiodensity Assessment (LIBRA) software with breast cancer have primarily focused on estimates from the contralateral breast at the time of diagnosis. Purpose To evaluate LIBRA measures on mammograms obtained before breast cancer diagnosis and compare their performance to established density measures. Materials and Methods For this retrospective case-control study, full-field digital mammograms in for-processing (raw) and for-presentation (processed) formats were obtained (March 2008 to December 2011) in women who developed breast cancer an average of 2 years later and in age-matched control patients. LIBRA measures included absolute dense area and area percent density (PD) from both image formats. For comparison, dense area and PD were assessed by using the research software (Cumulus), and volumetric PD (VPD) and absolute dense volume were estimated with a commercially available software (Volpara). Density measures were compared by using Spearman correlation coefficients (r), and conditional logistic regression (odds ratios [ORs] and 95% confidence intervals [CIs]) was performed to examine the associations of density measures with breast cancer by adjusting for age and body mass index. Results Evaluated were 437 women diagnosed with breast cancer (median age, 62 years ± 17 [standard deviation]) and 1225 matched control patients (median age, 61 years ± 16). LIBRA PD showed strong correlations with Cumulus PD (r = 0.77-0.84) and Volpara VPD (r = 0.85-0.90) (P < .001 for both). For LIBRA, the strongest breast cancer association was observed for PD from processed images (OR, 1.3; 95% CI: 1.1, 1.5), although the PD association from raw images was not significantly different (OR, 1.2; 95% CI: 1.1, 1.4; P = .25). Slightly stronger breast cancer associations were seen for Cumulus PD (OR, 1.5; 95% CI: 1.3, 1.8; processed images; P = .01) and Volpara VPD (OR, 1.4; 95% CI: 1.2, 1.7; raw images; P = .004) compared with LIBRA measures. Conclusion Automated density measures provided by the Laboratory for Individualized Breast Radiodensity Assessment from raw and processed mammograms correlated with established area and volumetric density measures and showed comparable breast cancer associations. © RSNA, 2020 Online supplemental material is available for this article.

Abstract P5-08-02: Association of daily alcohol intake, volumetric density and breast cancer risk

Background: Alcohol intake and breast density are established risk factors for breast cancer (BC). A few studies suggest breast density is on the causal pathway between alcohol and BC but the literature is not consistent. We examine the interrelationship between alcohol, volumetric breast density and BC risk, specifically whether there is a stronger alcohol and BC association among women with dense breasts and/or whether breast density mediates the alcohol and BC association.

Methods: We conducted a nested case-control study within the San Francisco Mammography Registry consisting of four breast screening centers. From 2006-2013, through linkages with the California cancer registry, we identified 2572 women diagnosed with BC who had screening mammograms performed at least six months prior to diagnosis. Controls (5119) were matched to cases on age, date of earliest mammogram, race/ethnicity, facility, and mammography machine. We obtained the raw format of digital mammograms on average 3.1 (standard deviation (SD) =1.7) years prior to diagnosis or corresponding date for controls. We ascertained usual daily alcohol intake and other risk factors from a clinical questionnaire at time of mammography. We obtained BI-RADS density from clinical records and used VolparaTM to assess volumetric percent density, dense volume and non-dense volume from the mammogram. We examined the associations of daily alcohol intake (none, one or less, two or more drinks per day) and volumetric density phenotypes (per 1 SD) with BC risk using logistic regression (odds ratios, OR; 95% confidence intervals, CI; and trend tests). We examined deviation from multiplicative interaction using chi-squared tests. We evaluated mediation of the alcohol and BC association by volumetric density measures using logistic regression to estimate the association between alcohol use and BC with and without adjustment for density measures. Percent mediation was estimated using the differences in the log OR estimates from the two models. All models were adjusted for age, 1/BMI and menopause and matching factors. Analyses were also stratified by menopausal status.

Results: Alcohol intake was available on 2233 cases and 4562 controls, 88% of those eligible. BC cases and controls had similar age (57.2 years (SD=11.5) vs. 57.1 years (SD=11.5)), BMI (25.3 kg/m2 (SD=5.3) vs. 24.9 kg/ m2 (SD=5.1)) and race (69.0% vs. 68.2% Caucasian). Cases were more likely to drink alcohol daily than controls (52.1% vs. 49.0%), in particular two or more drinks per day (14.8% vs. 13.2%). Alcohol was associated with increased BC risk (OR=1.14, 95% CI:1.02-1.27, for one or less drinks per day and OR=1.22, 95% CI:1.05-1.42 for 2 or more drinks per day) compared to non-drinkers (p-trend=0.004). Percent volumetric density (OR=1.45 per SD, 95%CI: 1.36-1.56,) and dense volume (OR=1.30, 95% CI: 1.24-1.37) were also positively associated with BC risk; non-dense volume was inversely associated (OR=0.93, 95%CI: 0.86-1.01). Associations were similar by menopausal subgroup. There was no evidence for a differential association of alcohol and breast cancer risk by dense breasts assessed using any of the density phenotypes examined (all P’s&gt;0.1). However, the association between alcohol and overall risk of BC was partially mediated by dense volume among all women (percent mediated=25%, P=0.01) and postmenopausal women (percent mediated=19%, P=0.03).

Conclusions: The association of daily alcohol intake and breast cancer risk was similar among women with dense and non-dense breasts. However, dense volume partially mediated the association between alcohol and risk of breast cancer, particularly among postmenopausal women, suggesting that alcohol partially influences breast cancer risk through changes in breast tissue composition.

Citation Format: Celine Marie Vachon, Christopher G. Scott, Stacey J Winham, John A Shepherd, Kathleen R Brandt, Matthew R Jensen, Carrie B Hruska, John J Heine, V. Shane Pankratz, Karla Kerlikowske. Association of daily alcohol intake, volumetric density and breast cancer risk [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-08-02.

Automated volumetric breast density measures: differential change between breasts in women with and without breast cancer

BACKGROUND

Given that breast cancer and normal dense fibroglandular tissue have similar radiographic attenuation, we examine whether automated volumetric density measures identify a differential change between breasts in women with cancer and compare to healthy controls.

METHODS

Eligible cases (n = 1160) had unilateral invasive breast cancer and bilateral full-field digital mammograms (FFDMs) at two time points: within 2 months and 1-5 years before diagnosis. Controls (n = 2360) were matched to cases on age and date of FFDMs. Dense volume (DV) and volumetric percent density (VPD) for each breast were assessed using Volpara™. Differences in DV and VPD between mammograms (median 3 years apart) were calculated per breast separately for cases and controls and their difference evaluated by using the Wilcoxon signed-rank test. To simulate clinical practice where cancer laterality is unknown, we examined whether the absolute difference between breasts can discriminate cases from controls using area under the ROC curve (AUC) analysis, adjusting for age, BMI, and time.

RESULTS

Among cases, the VPD and DV between mammograms of the cancerous breast decreased to a lesser degree (- 0.26% and - 2.10 cm³) than the normal breast (- 0.39% and - 2.74 cm³) for a difference of 0.13% (p value < 0.001) and 0.63 cm³ (p = 0.002), respectively. Among controls, the differences between breasts were nearly identical for VPD (- 0.02 [p = 0.92]) and DV (0.05 [p = 0.77]). The AUC for discriminating cases from controls using absolute difference between breasts was 0.54 (95% CI 0.52, 0.56) for VPD and 0.56 (95% CI, 0.54, 0.58) for DV.

CONCLUSION

There is a small relative increase in volumetric density measures over time in the breast with cancer which is not found in the normal breast. However, the magnitude of this difference is small, and this measure alone does not appear to be a good discriminator between women with and without breast cancer.

Associations of mammographic breast density with breast stem cell marker-defined breast cancer subtypes

PURPOSE

High mammographic breast density is a strong, well-established breast cancer risk factor. Whether stem cells may explain high breast cancer risk in dense breasts is unknown. We investigated the association between breast density and breast cancer risk by the status of stem cell markers CD44, CD24, and ALDH1A1 in the tumor.

METHODS

We included 223 women with primary invasive or in situ breast cancer and 399 age-matched controls from Mayo Clinic Mammography Study. Percent breast density (PD), absolute dense area (DA), and non-dense area (NDA) were assessed using computer-assisted thresholding technique. Immunohistochemical analysis of the markers was performed on tumor tissue microarrays according to a standard protocol. We used polytomous logistic regression to quantify the associations of breast density measures with breast cancer risk across marker-defined tumor subtypes.

RESULTS

Of the 223 cancers in the study, 182 were positive for CD44, 83 for CD24 and 52 for ALDH1A1. Associations of PD were not significantly different across t marker-defined subtypes (51% + vs. 11-25%: OR 2.83, 95% CI 1.49-5.37 for CD44+ vs. OR 1.87, 95% CI 0.47-7.51 for CD44-, p-heterogeneity = 0.66; OR 2.80, 95% CI 1.27-6.18 for CD24+ vs. OR 2.44, 95% CI 1.14-5.22 for CD24-, p-heterogeneity = 0.61; OR 3.04, 95% CI 1.14-8.10 for ALDH1A1+ vs. OR 2.57. 95% CI 1.30-5.08 for ALDH1A1-, p-heterogeneity = 0.94). Positive associations of DA and inverse associations of NDA with breast cancer risk were similar across marker-defined subtypes.

CONCLUSIONS

We found no evidence of differential associations of breast density with breast cancer risk by the status of stem cell markers. Further studies in larger study populations are warranted to confirm these associations.

Longitudinal Changes in Volumetric Breast Density in Healthy Women across the Menopausal Transition

BACKGROUND

Mammographic breast density declines during menopause. We assessed changes in volumetric breast density across the menopausal transition and factors that influence these changes.

METHODS

Women without a history of breast cancer, who had full field digital mammograms during both pre- and postmenopausal periods, at least 2 years apart, were sampled from four facilities within the San Francisco Mammography Registry from 2007 to 2013. Dense breast volume (DV) was assessed using Volpara on mammograms across the time period. Annualized change in DV from pre- to postmenopause was estimated using linear mixed models adjusted for covariates and per-woman random effects. Multiplicative interactions were evaluated between premenopausal risk factors and time to determine whether these covariates modified the annualized changes.

RESULTS

Among the 2,586 eligible women, 1,802 had one premenopausal and one postmenopausal mammogram, 628 had an additional perimenopausal mammogram, and 156 had two perimenopausal mammograms. Women experienced an annualized decrease in DV [-2.2 cm³ (95% confidence interval, -2.7 to -1.7)] over the menopausal transition. Declines were greater among women with a premenopausal DV above the median (54 cm³) versus below (DV, -3.5 cm³ vs. -1.0 cm³; P < 0.0001). Other breast cancer risk factors, including race, body mass index, family history, alcohol, and postmenopausal hormone therapy, had no effect on change in DV over the menopausal transition.

CONCLUSIONS

High premenopausal DV was a strong predictor of greater reductions in DV across the menopausal transition.

IMPACT

We found that few factors other than premenopausal density influence changes in DV across the menopausal transition, limiting targeted prevention efforts.

Combined effect of volumetric breast density and body mass index on breast cancer risk

BACKGROUND

Breast density and body mass index (BMI) are used for breast cancer risk stratification. We evaluate whether the positive association between volumetric breast density and breast cancer risk is strengthened with increasing BMI.

METHODS

The San Francisco Mammography Registry and Mayo Clinic Rochester identified 781 premenopausal and 1850 postmenopausal women with breast cancer diagnosed between 2007 and 2015 that had a screening digital mammogram at least 6 months prior to diagnosis. Up to three controls (N = 3535) were matched per case on age, race, date, mammography machine, and state. Volumetric percent density (VPD) and dense volume (DV) were measured with Volpara™. Breast cancer risk was assessed with logistic regression stratified by menopause status. Multiplicative interaction tests assessed whether the association of density measures was differential by BMI categories.

RESULTS

The increased risk of breast cancer associated with VPD was strengthened with higher BMI for both premenopausal (p_interaction = 0.01) and postmenopausal (p_interaction = 0.0003) women. For BMI < 25, 25-30, and ≥ 30 kg/m², ORs for breast cancer for a 1 SD increase in VPD were 1.24, 1.65, and 1.97 for premenopausal, and 1.20, 1.55, and 2.25 for postmenopausal women, respectively. ORs for breast cancer for a 1 SD increase in DV were 1.39, 1.33, and 1.51 for premenopausal (p_interaction = 0.58), and 1.31, 1.34, and 1.65 (p_interaction = 0.03) for postmenopausal women for BMI < 25, 25-30 and ≥ 30 kg/m², respectively.

CONCLUSIONS

The effect of volumetric percent density on breast cancer risk is strongest in overweight and obese women. These associations have clinical relevance for informing prevention strategies.

Body mass index, mammographic density, and breast cancer risk by estrogen receptor subtype

Background

Obesity and elevated breast density are common risk factors for breast cancer, and their effects may vary by estrogen receptor (ER) subtype. However, their joint effects on ER subtype-specific risk are unknown. Understanding this relationship could enhance risk stratification for screening and prevention. Thus, we assessed the association between breast density and ER subtype according to body mass index (BMI) and menopausal status.

Methods

We conducted a case-control study nested within two mammography screening cohorts, the Mayo Mammography Health Study and the San Francisco Bay Area Breast Cancer SPORE/San Francisco Mammography Registry. Our pooled analysis contained 1538 ER-positive and 285 ER-negative invasive breast cancer cases and 4720 controls matched on age, menopausal status at time of mammogram, and year of mammogram. Percent density was measured on digitized film mammograms using computer-assisted techniques. We used polytomous logistic regression to evaluate the association between percent density and ER subtype by BMI subgroup (normal/underweight, < 25 kg/m² versus overweight/obese, ≥ 25 kg/m²). We used Wald chi-squared tests to assess for interactions between percent density and BMI. Our analysis was stratified by menopausal status and hormone therapy usage at the time of index mammogram.

Results

Percent density was associated with increased risk of overall breast cancer regardless of menopausal status or BMI. However, when analyzing breast cancer across ER subtype, we found a statistically significant (p = 0.008) interaction between percent density and BMI in premenopausal women only. Specifically, elevated percent density was associated with a higher risk of ER-negative than ER-positive cancer in overweight/obese premenopausal women [OR per standard deviation increment 2.17 (95% CI 1.50–3.16) vs 1.33 (95% CI 1.11–1.61) respectively, P_{heterogeneity} = 0.01]. In postmenopausal women, elevated percent density was associated with similar risk of ER-positive and ER-negative cancers, and no substantive differences were seen after accounting for BMI or hormone therapy usage.

Conclusions

The combination of overweight/obesity and elevated breast density in premenopausal women is associated with a higher risk of ER-negative compared with ER-positive cancer. Eighteen percent of premenopausal women in the USA have elevated BMI and breast density and may benefit from lifestyle modifications involving weight loss and exercise.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1129-9) contains supplementary material, which is available to authorized users.

Synthesis of Functionalized N-Acetyl Muramic Acids To Probe Bacterial Cell Wall Recycling and Biosynthesis

Uridine diphosphate N-acetyl muramic acid (UDP NAM) is a critical intermediate in bacterial peptidoglycan (PG) biosynthesis. As the primary source of muramic acid that shapes the PG backbone, modifications installed at the UDP NAM intermediate can be used to selectively tag and manipulate this polymer via metabolic incorporation. However, synthetic and purification strategies to access large quantities of these PG building blocks, as well as their derivatives, are challenging. A robust chemoenzymatic synthesis was developed using an expanded NAM library to produce a variety of 2 -N-functionalized UDP NAMs. In addition, a synthetic strategy to access bio-orthogonal 3-lactic acid NAM derivatives was developed. The chemoenzymatic UDP synthesis revealed that the bacterial cell wall recycling enzymes MurNAc/GlcNAc anomeric kinase (AmgK) and NAM α-1 phosphate uridylyl transferase (MurU) were permissive to permutations at the two and three positions of the sugar donor. We further explored the utility of these derivatives in the fluorescent labeling of both Gram (-) and Gram (+) PG in whole cells using a variety of bio-orthogonal chemistries including the tetrazine ligation. This report allows for rapid and scalable access to a variety of functionalized NAMs and UDP NAMs, which now can be used in tandem with other complementary bio-orthogonal labeling strategies to address fundamental questions surrounding PG's role in immunology and microbiology.

Abstract 3226: Overweight and obese women with high volumetric breast density at high breast cancer risk

Purpose: Volumetric breast density and body mass index (BMI) are increasingly used for breast cancer risk stratification. We examine if the effect of volumetric breast density on breast cancer risk increases with increasing BMI.

Methods: Participants were from two case-control studies within mammography practices, the San Francisco Mammography Registry and the Mayo Clinic Rochester, Breast Screening Practice. Breast cancers were included if diagnosed between January 2007 and 2015 and with a screening full-field digital mammogram at least 6 months prior to diagnosis; the earliest mammogram within 5 years of diagnosis was selected. Up to three controls were matched to each case on age, race, date, mammography machine, and state of residence. Volumetric percent density (VPD), dense volume (DV) and non-dense volume (NDV) were measured using VolparaTM software. Breast cancer risk was assessed using logistic regression stratified by menopause status and adjusted for matching factors, family history of breast cancer, parity/age at first birth, and postmenopausal hormone therapy. Models for DV were additionally adjusted for NDV, and NDV models for DV. Multiplicative interactions were fit between BMI categories [&lt;25 (underweight), 25-30 (normal weight) and &gt;30 (overweight/obese) kg/m2] and VPD, DV, and NDV, and trend tests assessed for increasing odds ratios (OR) with increasing BMI.

Results: A total of 781 premenopausal and 1850 postmenopausal breast cancers and 3535 controls were included in the analysis. Median age of premenopausal women was 45 years (IQR: 6.1) and 63.3 years (IQR: 14) for postmenopausal women. Cases vs. controls had greater VPD and DV for both premenopausal (VPD: 14.9% vs. 12.0%, DV: 74.1 cm3 vs. 64.4 cm3) and postmenopausal women (VPD: 6.8% vs. 6.1%, DV: 53.4 cm3 vs. 48.0 cm3)(all p's&lt;0.001). Trends between increasing BMI and VPD were evident for both pre (ptrend=0.0007) and postmenopausal (ptrend=0.0005) women. Among premenopausal women, the odds ratio (OR) for breast cancer associated with a 10% increase in VPD was of 1.39, 2.19 and 2.88 for BMI &lt;25, 25-30 and &gt;30 kg/m2 (p-trend=0.0007), respectively. For DV, OR's were 1.39, 1.33 and 1.51 for a 1 SD increase in DV, respectively, though the interaction with DV was not significant (ptrend=0.68). Among postmenopausal women, a 10% increase in VPD was associated with OR's of 1.35, 2.03, 3.6 for BMI &lt;25, 25-29, &gt;30-kg/m2 (ptrend =0.0001), respectively, and 1.31, 1.34 and 1.65 for a 1 SD increase in DV (ptrend =0.01), respectively. Associations between NDV and breast cancer risk did not differ by BMI category for premenopausal (ptrend =0.52) or postmenopausal (ptrend =0.07) women.

Conclusions: The effect of VPD on breast cancer risk is strongest in overweight/obese women. As volumetric breast density and BMI are commonly used in clinical risk stratification, these differences in risk have high clinical relevance for informing prevention decisions.

Citation Format: Natalie J. Engmann, Christopher G. Scott, Matthew R. Jensen, Stacey J. Winham, Lin Ma, Kathleen R. Brandt, Amir Mahmoudzadeh, Serghei Malkov, Dana Whaley, Carrie Hruska, Fang Fang Wu, Diana L. Miglioretti, Aaron D. Norman, John Heine, John Shepherd, Vernon S. Pankratz, Celine M. Vachon, Karla Kerlikowske. Overweight and obese women with high volumetric breast density at high breast cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3226.

Automated and Clinical Breast Imaging Reporting and Data System Density Measures Predict Risk for Screen-Detected and Interval Cancers: A Case-Control Study

BACKGROUND

In 30 states, women who have had screening mammography are informed of their breast density on the basis of Breast Imaging Reporting and Data System (BI-RADS) density categories estimated subjectively by radiologists. Variation in these clinical categories across and within radiologists has led to discussion about whether automated BI-RADS density should be reported instead.

OBJECTIVE

To determine whether breast cancer risk and detection are similar for automated and clinical BI-RADS density measures.

DESIGN

Case-control.

SETTING

San Francisco Mammography Registry and Mayo Clinic.

PARTICIPANTS

1609 women with screen-detected cancer, 351 women with interval invasive cancer, and 4409 matched control participants.

MEASUREMENTS

Automated and clinical BI-RADS density assessed on digital mammography at 2 time points from September 2006 to October 2014, interval and screen-detected breast cancer risk, and mammography sensitivity.

RESULTS

Of women whose breast density was categorized by automated BI-RADS more than 6 months to 5 years before diagnosis, those with extremely dense breasts had a 5.65-fold higher interval cancer risk (95% CI, 3.33 to 9.60) and a 1.43-fold higher screen-detected risk (CI, 1.14 to 1.79) than those with scattered fibroglandular densities. Associations of interval and screen-detected cancer with clinical BI-RADS density were similar to those with automated BI-RADS density, regardless of whether density was measured more than 6 months to less than 2 years or 2 to 5 years before diagnosis. Automated and clinical BI-RADS density measures had similar discriminatory accuracy, which was higher for interval than screen-detected cancer (c-statistics: 0.70 vs. 0.62 [P < 0.001] and 0.72 vs. 0.62 [P < 0.001], respectively). Mammography sensitivity was similar for automated and clinical BI-RADS categories: fatty, 93% versus 92%; scattered fibroglandular densities, 90% versus 90%; heterogeneously dense, 82% versus 78%; and extremely dense, 63% versus 64%, respectively.

LIMITATION

Neither automated nor clinical BI-RADS density was assessed on tomosynthesis, an emerging breast screening method.

CONCLUSION

Automated and clinical BI-RADS density similarly predict interval and screen-detected cancer risk, suggesting that either measure may be used to inform women of their breast density.

PRIMARY FUNDING SOURCE

National Cancer Institute.

Does mammographic density mediate risk factor associations with breast cancer? An analysis by tumor characteristics

BACKGROUND

Though mammographic density (MD) has been proposed as an intermediate marker of breast cancer risk, few studies have examined whether the associations between breast cancer risk factors and risk are mediated by MD, particularly by tumor characteristics.

METHODS

Our study population included 3392 cases (1105 premenopausal) and 8882 (3192 premenopausal) controls from four case-control studies. For established risk factors, we estimated the percent of the total risk factor association with breast cancer that was mediated by percent MD (secondarily, by dense area and non-dense area) for invasive breast cancer as well as for subtypes defined by the estrogen receptor (ER+/ER-), progesterone receptor (PR+/PR-), and HER2 (HER2+/HER2-). Analyses were conducted separately in pre- and postmenopausal women.

RESULTS

Positive associations between prior breast biopsy and risk of invasive breast cancer as well as all subtypes were partially mediated by percent MD in pre- and postmenopausal women (percent mediated = 11-27%, p ≤ 0.02). In postmenopausal women, nulliparity and hormone therapy use were positively associated with invasive, ER+ , PR+ , and HER2- breast cancer; percent MD partially mediated these associations (percent mediated ≥ 31%, p ≤ 0.02). Further, among postmenopausal women, percent MD partially mediated the positive association between later age at first birth and invasive as well as ER+ breast cancer (percent mediated = 16%, p ≤ 0.05).

CONCLUSION

Percent MD partially mediated the associations between breast biopsy, nulliparity, age at first birth, and hormone therapy with risk of breast cancer, particularly among postmenopausal women, suggesting that these risk factors at least partially influence breast cancer risk through changes in breast tissue composition.

The role of OleA His285 in orchestration of long-chain acyl-coenzyme A substrates

Renewable production of hydrocarbons is being pursued as a petroleum-independent source of commodity chemicals and replacement for biofuels. The bacterial biosynthesis of long-chain olefins represents one such platform. The process is initiated by OleA catalyzing the condensation of two fatty acyl-coenzyme A substrates to form a β-keto acid. Here, the mechanistic role of the conserved His285 is investigated through mutagenesis, activity assays, and X-ray crystallography. Our data demonstrate that His285 is required for product formation, influences the thiolase nucleophile Cys143 and the acyl-enzyme intermediate before and after transesterification, and orchestrates substrate coordination as a defining component of an oxyanion hole. As a consequence, His285 plays a key role in enabling a mechanistic strategy in OleA that is distinct from other thiolases.

A vicious circle in chronic lymphoedema pathophysiology? An adipocentric view

Chronic lymphoedema is a disease caused by a congenital or acquired damage to the lymphatic system and characterized by complex chains of pathophysiologic events such as lymphatic fluid stasis, chronic inflammation, lymphatic vessels impairment, adipose tissue deposition and fibrosis. These events seem to maintain and reinforce themselves through a positive feedback loop: regardless of the initial cause of lymphatic stasis, the dysfunctional adipose tissue and its secretion products can worsen lymphatic vessels' function, aggravating lymph leakage and stagnation, which can promote further adipose tissue deposition and fibrosis, similar to what may happen in obesity. In addition to the current knowledge about the tight and ancestral interrelation between immunity system and metabolism, there is evidence for similarities between obesity-related and lymphatic damage-induced lymphoedema. Together, these observations indicate strong reciprocal relationship between lymphatics and adipose tissue and suggest a possible key role of the adipocyte in the pathophysiology of chronic lymphoedema's vicious circle.

Interaction of mammographic breast density with menopausal status and postmenopausal hormone use in relation to the risk of aggressive breast cancer subtypes

PURPOSE

We examined the associations of mammographic breast density with breast cancer risk by tumor aggressiveness and by menopausal status and current postmenopausal hormone therapy.

METHODS

This study included 2596 invasive breast cancer cases and 4059 controls selected from participants of four nested case-control studies within four established cohorts: the Mayo Mammography Health Study, the Nurses' Health Study, Nurses' Health Study II, and San Francisco Mammography Registry. Percent breast density (PD), absolute dense (DA), and non-dense areas (NDA) were assessed from digitized film-screen mammograms using a computer-assisted threshold technique and standardized across studies. We used polytomous logistic regression to quantify the associations of breast density with breast cancer risk by tumor aggressiveness (defined as presence of at least two of the following tumor characteristics: size ≥2 cm, grade 2/3, ER-negative status, or positive nodes), stratified by menopausal status and current hormone therapy.

RESULTS

Overall, the positive association of PD and borderline inverse association of NDA with breast cancer risk was stronger in aggressive vs. non-aggressive tumors (≥51 vs. 11-25% OR 2.50, 95% CI 1.94-3.22 vs. OR 2.03, 95% CI 1.70-2.43, p-heterogeneity = 0.03; NDA 4th vs. 2nd quartile OR 0.54, 95% CI 0.41-0.70 vs. OR 0.71, 95% CI 0.59-0.85, p-heterogeneity = 0.07). However, there were no differences in the association of DA with breast cancer by aggressive status. In the stratified analysis, there was also evidence of a stronger association of PD and NDA with aggressive tumors among postmenopausal women and, in particular, current estrogen+progesterone users (≥51 vs. 11-25% OR 3.24, 95% CI 1.75-6.00 vs. OR 1.93, 95% CI 1.25-2.98, p-heterogeneity = 0.01; NDA 4th vs. 2nd quartile OR 0.43, 95% CI 0.21-0.85 vs. OR 0.56, 95% CI 0.35-0.89, p-heterogeneity = 0.01), even though the interaction was not significant.

CONCLUSION

Our findings suggest that associations of mammographic density with breast cancer risk differ by tumor aggressiveness. While there was no strong evidence that these associations differed by menopausal status or hormone therapy, they did appear more prominent among current estrogen+progesterone users.

Tissue-based associations of mammographic breast density with breast stem cell markers

Background

Mammographic breast density is a well-established, strong breast cancer risk factor but the biology underlying this association remains unclear. Breast density may reflect underlying alterations in the size and activity of the breast stem cell pool. We examined, for the first time, associations of CD44, CD24, and aldehyde dehydrogenase family 1 member A1 (ALDH1A1) breast stem cell markers with breast density.

Methods

We included in this study 64 asymptomatic healthy women who previously volunteered for a unique biopsy study of normal breast tissue at the Mayo Clinic (2006-2008). Mammographically identified dense and non-dense areas were confirmed/localized by ultrasound and biopsied. Immunohistochemical analysis of the markers was performed according to a standard protocol and the staining was assessed by a single blinded pathologist. In core biopsy samples retrieved from areas of high vs. low density within the same woman, we compared staining extent and an expression score (the product of staining intensity and extent), using the signed rank test. All tests of statistical significance were two-sided.

Results

A total of 64, 28, and 10 women were available for CD44, CD24, and ALDH1A1 staining, respectively. For all three markers, we found higher levels of staining extent in dense as compared to non-dense tissue, though for CD24 and ALDH1A1 the difference did not reach statistical significance (CD44, 6.3% vs. 2.0%, p < 0.001; CD24, 8.0% vs. 5.6%, p = 0.10; and ALDH1A1, 0.5% vs. 0.3%, p = 0.12). The expression score for CD44 was significantly greater in dense as compared to non-dense tissue (9.8 vs.3.0, p < 0.001).

Conclusions

Our findings suggest an increased presence and/or activity of stem cells in dense as compared to non-dense breast tissue.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-017-0889-3) contains supplementary material, which is available to authorized users.

Combining quantitative and qualitative breast density measures to assess breast cancer risk

BACKGROUND

Accurately identifying women with dense breasts (Breast Imaging Reporting and Data System [BI-RADS] heterogeneously or extremely dense) who are at high breast cancer risk will facilitate discussions of supplemental imaging and primary prevention. We examined the independent contribution of dense breast volume and BI-RADS breast density to predict invasive breast cancer and whether dense breast volume combined with Breast Cancer Surveillance Consortium (BCSC) risk model factors (age, race/ethnicity, family history of breast cancer, history of breast biopsy, and BI-RADS breast density) improves identifying women with dense breasts at high breast cancer risk.

METHODS

We conducted a case-control study of 1720 women with invasive cancer and 3686 control subjects. We calculated ORs and 95% CIs for the effect of BI-RADS breast density and Volpara™ automated dense breast volume on invasive cancer risk, adjusting for other BCSC risk model factors plus body mass index (BMI), and we compared C-statistics between models. We calculated BCSC 5-year breast cancer risk, incorporating the adjusted ORs associated with dense breast volume.

RESULTS

Compared with women with BI-RADS scattered fibroglandular densities and second-quartile dense breast volume, women with BI-RADS extremely dense breasts and third- or fourth-quartile dense breast volume (75% of women with extremely dense breasts) had high breast cancer risk (OR 2.87, 95% CI 1.84-4.47, and OR 2.56, 95% CI 1.87-3.52, respectively), whereas women with extremely dense breasts and first- or second-quartile dense breast volume were not at significantly increased breast cancer risk (OR 1.53, 95% CI 0.75-3.09, and OR 1.50, 95% CI 0.82-2.73, respectively). Adding continuous dense breast volume to a model with BCSC risk model factors and BMI increased discriminatory accuracy compared with a model with only BCSC risk model factors (C-statistic 0.639, 95% CI 0.623-0.654, vs. C-statistic 0.614, 95% CI 0.598-0.630, respectively; P < 0.001). Women with dense breasts and fourth-quartile dense breast volume had a BCSC 5-year risk of 2.5%, whereas women with dense breasts and first-quartile dense breast volume had a 5-year risk ≤ 1.8%.

CONCLUSIONS

Risk models with automated dense breast volume combined with BI-RADS breast density may better identify women with dense breasts at high breast cancer risk than risk models with either measure alone.

Abstract B27: Interaction of mammographic breast density with menopausal status and postmenopausal hormone use in relation to the risk of aggressive breast cancer subtypes

Purpose: The evidence on associations of mammographic breast density with breast cancer risk by combination of tumor aggressiveness features is limited. We examined associations of breast density phenotypes with risk of aggressive breast tumor features by menopausal status, and current postmenopausal hormone therapy.

Methods: This study included 2,635 invasive breast cancer cases and 4,059 controls from participants of four nested case-control studies within four established cohorts: the Mayo Mammography Health Study, the Nurses Health Study, Nurses Health Study II, and San Francisco Mammography Registry. Percent breast density, absolute dense and non-dense areas were assessed from digitized film-screen mammograms using a computer-assisted threshold technique and standardized across studies. We used polytomous logistic regression to quantify the associations of breast density measures with risk of breast tumor aggressiveness (defined as presence of 2 or more of the following tumor characteristics: size ≥2cm, grade 2 or 3, or positive nodes), stratified by menopausal status and current hormone therapy (i.e., premenopausal, postmenopausal/estrogen therapy, postmenopausal/combined therapy, and postmenopausal/no hormones). We also evaluated differences in the strength of associations across categories. In a secondary analysis, we examined these associations while excluding cases with mammogram date within 2 years of diagnosis.

Results: Positive associations of percent density and dense area and inverse associations of non-dense area with breast cancer risk were stronger in aggressive vs. non-aggressive tumors (OR=2.62, 95%CI 2.08-3.31 vs. OR=1.94, 95%CI 1.62-2.33 for percent density≥51% vs. 11-25%, p-heterogeneity=0.001; OR=1.89, 95%CI 1.54-2.31 vs. OR=1.65, 95%CI 1.41-1.93 for dense area 4th vs. 2nd quartile, p-heterogeneity=0.015; OR=0.56, 95%CI 0.44-0.72 vs. OR=0.71, 95%CI 0.59-0.86 for non-dense area 4th vs 2nd quartile, p-heterogeneity=0.007, respectively). These patterns were similar across all menopausal and hormone therapy groups (P-interactions=0.62, 0.76, and 0.23, for percent density, dense area and non-dense area, respectively). Excluding cases diagnosed within 2 years of mammography resulted in similar findings.

Conclusion: Mammographic density phenotypes were more strongly associated with aggressive cancer (having two or more of the following: size ≥2cm, grade 2 or 3, or positive nodes) vs. non-aggressive types of breast cancer across categories of menopause and hormone therapy types.

Citation Format: Lusine Yaghjyan, Rulla Tamimi, Kimberly Bertrand, Christopher G. Scott, Matthew R. Jensen, Shane Pankratz, Kathleen Brandt, Daniel Visscher, Aaron Norman, Fergus Cough, John Shepherd, Bo Fan, Yunn-Yi Chen, Lin Ma, Andrew H. Beck, Steven R. Cummings, Karla Kerlikowske, Celine Vachon. Interaction of mammographic breast density with menopausal status and postmenopausal hormone use in relation to the risk of aggressive breast cancer subtypes. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B27.

Longitudinal Changes in Volumetric Breast Density with Tamoxifen and Aromatase Inhibitors

Background: Reductions in breast density with tamoxifen and aromatase inhibitors may be an intermediate marker of treatment response. We compare changes in volumetric breast density among breast cancer cases using tamoxifen or aromatase inhibitors (AI) to untreated women without breast cancer.Methods: Breast cancer cases with a digital mammogram prior to diagnosis and after initiation of tamoxifen (n = 366) or AI (n = 403) and a sample of controls (n = 2170) were identified from the Mayo Clinic Mammography Practice and San Francisco Mammography Registry. Volumetric percent density (VPD) and dense breast volume (DV) were measured using Volpara (Matakina Technology) and Quantra (Hologic) software. Linear regression estimated the effect of treatment on annualized changes in density.Results: Premenopausal women using tamoxifen experienced annualized declines in VPD of 1.17% to 1.70% compared with 0.30% to 0.56% for controls and declines in DV of 7.43 to 15.13 cm³ compared with 0.28 to 0.63 cm³ in controls, for Volpara and Quantra, respectively. The greatest reductions were observed among women with ≥10% baseline density. Postmenopausal AI users had greater declines in VPD than controls (Volpara P = 0.02; Quantra P = 0.03), and reductions were greatest among women with ≥10% baseline density. Declines in VPD among postmenopausal women using tamoxifen were only statistically greater than controls when measured with Quantra.Conclusions: Automated software can detect volumetric breast density changes among women on tamoxifen and AI.Impact: If declines in volumetric density predict breast cancer outcomes, these measures may be used as interim prognostic indicators. Cancer Epidemiol Biomarkers Prev; 26(6); 930-7. ©2017 AACR.

Mammographic breast density and risk of breast cancer in women with atypical hyperplasia: an observational cohort study from the Mayo Clinic Benign Breast Disease (BBD) cohort

Background

Atypical hyperplasia (AH) and mammographic breast density (MBD) are established risk factors for breast cancer (BC), but their joint contributions are not well understood. We examine associations of MBD and BC by histologic impression, including AH, in a subcohort of women from the Mayo Clinic Benign Breast Disease Cohort.

Methods

Women with a diagnosis of BBD and mammogram between 1985 and 2001 were eligible. Histologic impression was assessed via pathology review and coded as non-proliferative disease (NP), proliferative disease without atypia (PDWA) and AH. MBD was assessed clinically using parenchymal pattern (PP) or BI-RADS criteria and categorized as low, moderate or high. Percent density (PD) was also available for a subset of women. BC and clinical information were obtained by questionnaires, medical records and the Mayo Clinic Tumor Registry. Women were followed from date of benign biopsy to BC, death or last contact. Standardized incidence ratios (SIRs) compared the observed number of BCs to expected counts. Cox regression estimated multivariate-adjusted MBD hazard ratios.

Results

Of the 6271 women included in the study, 1132 (18.0%) had low MBD, 2921 (46.6%) had moderate MBD, and 2218 (35.4%) had high MBD. A total of 3532 women (56.3%) had NP, 2269 (36.2%) had PDWA and 470 (7.5%) had AH. Over a median follow-up of 14.3 years, 528 BCs were observed. The association of MBD and BC risk differed by histologic impression (p-interaction = 0.03), such that there was a strong MBD and BC association among NP (p < 0.001) but non-significant associations for PDWA (p = 0.27) and AH (p = 0.96). MBD and BC associations for AH women were not significant within subsets defined by type of MBD measure (PP vs. BI-RADS), age at biopsy, number of foci of AH, type of AH (lobular vs. ductal) and body mass index, and after adjustment for potential confounding variables. Women with atypia who also had high PD (>50%) demonstrated marginal evidence of increased BC risk (SIR 4.98), but results were not statistically significant.

Conclusion

We found no evidence of an association between MBD and subsequent BC risk in women with AH.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-017-3082-2) contains supplementary material, which is available to authorized users.

β-Lactone Synthetase Found in the Olefin Biosynthesis Pathway

The first β-lactone synthetase enzyme is reported, creating an unexpected link between the biosynthesis of olefinic hydrocarbons and highly functionalized natural products. The enzyme OleC, involved in the microbial biosynthesis of long-chain olefinic hydrocarbons, reacts with syn- and anti-β-hydroxy acid substrates to yield cis- and trans-β-lactones, respectively. Protein sequence comparisons reveal that enzymes homologous to OleC are encoded in natural product gene clusters that generate β-lactone rings, suggesting a common mechanism of biosynthesis.

Mammographic texture and risk of breast cancer by tumor type and estrogen receptor status

Background

Several studies have shown that mammographic texture features are associated with breast cancer risk independent of the contribution of breast density. Thus, texture features may provide novel information for risk stratification. We examined the association of a set of established texture features with breast cancer risk by tumor type and estrogen receptor (ER) status, accounting for breast density.

Methods

This study combines five case–control studies including 1171 breast cancer cases and 1659 controls matched for age, date of mammogram, and study. Mammographic breast density and 46 breast texture features, including first- and second-order features, Fourier transform, and fractal dimension analysis, were evaluated from digitized film-screen mammograms. Logistic regression models evaluated each normalized feature with breast cancer after adjustment for age, body mass index, first-degree family history, percent density, and study.

Results

Of the mammographic features analyzed, fractal dimension and second-order statistics features were significantly associated (p < 0.05) with breast cancer. Fractal dimensions for the thresholds equal to 10% and 15% (FD_TH10 and FD_TH15) were associated with an increased risk of breast cancer while thresholds from 60% to 85% (FD_TH60 to FD_TH85) were associated with a decreased risk. Increasing the FD_TH75 and Energy feature values were associated with a decreased risk of breast cancer while increasing Entropy was associated with a decreased risk of breast cancer. For example, 1 standard deviation increase of FD_TH75 was associated with a 13% reduced risk of breast cancer (odds ratio = 0.87, 95% confidence interval 0.79–0.95). Overall, the direction of associations between features and ductal carcinoma in situ (DCIS) and invasive cancer, and estrogen receptor positive and negative cancer were similar.

Conclusion

Mammographic features derived from film-screen mammograms are associated with breast cancer risk independent of percent mammographic density. Some texture features also demonstrated associations for specific tumor types. For future work, we plan to assess risk prediction combining mammographic density and features assessed on digital images.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-016-0778-1) contains supplementary material, which is available to authorized users.

Substrate Trapping in Crystals of the Thiolase OleA Identifies Three Channels That Enable Long Chain Olefin Biosynthesis

Phylogenetically diverse microbes that produce long chain, olefinic hydrocarbons have received much attention as possible sources of renewable energy biocatalysts. One enzyme that is critical for this process is OleA, a thiolase superfamily enzyme that condenses two fatty acyl-CoA substrates to produce a β-ketoacid product and initiates the biosynthesis of long chain olefins in bacteria. Thiolases typically utilize a ping-pong mechanism centered on an active site cysteine residue. Reaction with the first substrate produces a covalent cysteine-thioester tethered acyl group that is transferred to the second substrate through formation of a carbon-carbon bond. Although the basics of thiolase chemistry are precedented, the mechanism by which OleA accommodates two substrates with extended carbon chains and a coenzyme moiety-unusual for a thiolase-are unknown. Gaining insights into this process could enable manipulation of the system for large scale olefin production with hydrocarbon chains lengths equivalent to those of fossil fuels. In this study, mutagenesis of the active site cysteine in Xanthomonas campestris OleA (Cys¹⁴³) enabled trapping of two catalytically relevant species in crystals. In the resulting structures, long chain alkyl groups (C₁₂ and C₁₄) and phosphopantetheinate define three substrate channels in a T-shaped configuration, explaining how OleA coordinates its two substrates and product. The C143A OleA co-crystal structure possesses a single bound acyl-CoA representing the Michaelis complex with the first substrate, whereas the C143S co-crystal structure contains both acyl-CoA and fatty acid, defining how a second substrate binds to the acyl-enzyme intermediate. An active site glutamate (Gluβ¹¹⁷) is positioned to deprotonate bound acyl-CoA and initiate carbon-carbon bond formation.

Abstract 2593: Association of mammographic density measures and breast cancer ‘intrinsic’ molecular subtypes

Percent mammographic density (PMD) is a risk factor for estrogen receptor (ER)-positive and ER-negative invasive breast cancer (BC). Gene expression profiling has identified molecular signatures that classify invasive BC into distinct subtypes that vary in their clinical behavior, response to treatment and likely, etiology. Immunohistochemical (IHC) staining of tumor sections using antibody panels can be used to classify these ‘intrinsic’ molecular subtypes. We evaluated whether density measures [PMD, absolute dense area (DA) and non-dense area (NDA)], are associated equally with all ‘intrinsic’ molecular subtypes.

Pooled analysis of six cohort or case-control studies included 3492 women with invasive BC and 10,148 without, who underwent screening mammography a median 4 years prior to diagnosis (for cases). PMD, DA, and NDA were assessed from digitized film-screen mammograms using a computer-assisted thresholding technique, and categorized as 0-10%, 11-25%, 26-50% and 51%+ (PMD) or into quartiles (DA and NDA). Receptor status was abstracted from pathology records and supplemented by IHC staining. We classified tumors as Luminal A (ER+ and/or PR+ and HER2- and grade 1 or 2), Luminal B (ER+ and/or PR+ and HER2+ or Luminal A and grade 3), HER2 expressing (HER2+/ER-/PR-) and triple negative (TN) (ER-/PR-/HER2-). For TN, we also differentiated basal-like tumors (positive for EGFR and/or CK 5/6) from unclassified (negative on both markers). We used polytomous logistic regression to calculate the odds ratio (OR) of each ‘intrinsic’ subtype of BC by categories of PMD, DA or NDA, adjusting for age, body mass index and study. We tested for statistical heterogeneity of associations by subtype.

Of 3492 invasive BC cases, 2217 (63%) were classified as Luminal A, 747 (21%) as Luminal B, 159 (5%) as HER2 expressing, and 369 (11%) as TN. Of TN, 203 were evaluated for CK 5/6 and EGFR, with 167 (82%) classified as basal-like and 36 (18%) unclassified. PMD was associated with BC risk across all subtypes. For Luminal A, compared to women with 11-25% PMD (reference), women with 0-10% had a reduced risk of BC (OR = 0.63 [95% confidence interval: 0.55, 0.74]) while women with 26-50% had an OR = 1.5 [1.3, 1.7] and women with 51%+ had the highest risk, OR = 2.3 [2.0, 2.7]. Similar BC associations were seen across PMD categories when comparing the five subtypes (P-heterogeneity = 0.63). Similar trends were seen for DA and BC across the five subtypes (P-het = 0.25). NDA was inversely associated with BC across subtypes, and there was suggestion of a stronger inverse trend among HER2-expressing BC compared to other subtypes (P-het = 0.09).

Our results suggest mammographic density measures are associated with all ‘intrinsic’ molecular subtypes. However, NDA may be more strongly inversely associated with HER2-expressing than other subtypes. Understanding the importance of density measures for BC subtypes has significance for subtype-specific risk models.

Citation Format: Aaron D. Norman, Rulla M. Tamimi, Christopher G. Scott, Kimberly A. Bertrand, Matthew R. Jensen, Daniel W. Visscher, Fergus J. Couch, John Shepherd, Bo Fan, Yunn-Yi Chen, Lin Ma, Andrew Beck, Vernon S. Pankratz, Karla Kerlikowske, Celine M. Vachon. Association of mammographic density measures and breast cancer ‘intrinsic’ molecular subtypes. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2593.

Abstract 3424: Longitudinal changes in volumetric breast density with adjuvant endocrine therapy among women with breast cancer

Breast density represents the stromal and epithelial tissue in the breast and is a strong risk factor for breast cancer. Reductions in breast density attributable to tamoxifen (TAM) and aromatase inhibitors (AI) may be associated with reduced risk of first primary and subsequent breast cancer. Studies assessing breast density changes have principally used two-dimensional measures. We assess changes in breast density following initiation of TAM and AI using two automated volumetric density measures that have shown strong associations to breast cancer risk.

Breast cancer cases with a full field digital mammogram (FFDM) prior to diagnosis (index mammogram) and after initiation of TAM (n = 379) or AI (n = 425) were identified from the Mayo Clinic Mammography Practice and the San Francisco Mammography Registry. Volumetric percent density (VPD) and dense volume (DV) were measured on 4-view FFDM using VolparaTM (Matakina Technology) and QuantraTM (Hologic) automated software. We used linear regression to assess the effect of treatment on mean annualized change in VPD and DV (change from index to last mammogram divided by time interval) for each software type, adjusting for age, body mass index (BMI) and density at index mammogram.

The median time between index mammogram and cancer diagnosis was 0.6 months (IQR: 0.2, 2.2) and median time between index and last mammogram was 3 years (IQR: 2.0, 3.9). Women on TAM were younger, had lower BMI and higher baseline VPD and DV relative to women on AI (Table). An annual decrease in VPD and DV was observed with both TAM and AI. Both Volpara and Quantra estimated a similar magnitude of change in VPD in women on TAM and AI, and a greater change in DV with TAM.

Our findings suggest that both Volpara and Quantra can assess volumetric changes in breast density among women on hormone therapy. If declines in volumetric density correlate with a reduction in breast cancer risk, these automated measures could be used in clinical practice to assess response to therapy. Annualized changes in volumetric breast density estimated by linear regression.Tamoxifen (n = 379)Aromatase Inhibitors (n = 425)Baseline Median (IQR)Annualized Change (95% CI)*Baseline Median (IQR)Annualized Change (95% CI)*Age at Diagnosis50.0 (45.0, 60.0)–63.0 (58.0, 71.0)–Body Mass Index (BMI)23.6 (21.5, 26.8)–25.7 (22.7, 29.9)–Time Interval¥3.0 (2.1, 3.9)–3.0 (2.1, 3.9)–VolparaPercent Density (VPD,%)11.6 (6.8, 18.8)-0.17 (-0.27, -0.10)7.2 (5.0, 11.0)-0.19 (-0.29, -0.12)Dense Volume (DV, cm3)64.7 (45.4, 90.9)-0.90 (-1.45, -0.48)51.9 (38.9, 69.9)-0.52 (-0.93, -0.23)QuantraPercent Density (VPD,%)14.5 (9.2, 20.2)-0.42 (-0.59, -0.28)9.9 (7.1, 14.5)-0.38 (-0.54, -0.25)Dense Volume (DV, cm3)94.0 (58.0, 144.0)-2.20 (-3.52, -1.19)80.0 (49.0, 128.0)-0.95 (-1.85, -0.35)IQR = Interquartile range ¥ Median number of years between index mammogram and last mammogram post-initiation of therapy. *Annualized change estimated as change from index to last mammogram divided by time interval and adjusted for study site, age at diagnosis, BMI and density at index mammogram.

Citation Format: Natalie J. Engmann, Celine M. Vachon, Christopher G. Scott, Matthew R. Jensen, Lin Ma, Kathleen R. Brandt, Amir P. Mahmoudzadeh, Serghei Malkov, Dana H. Whaley, Carrie B. Hruska, Fang F. Wu, Stacey J. Winham, Diana L. Miglioretti, Aaron D. Norman, John J. Heine, John Shepherd, V Shane Pankratz, Karla Kerlikowske. Longitudinal changes in volumetric breast density with adjuvant endocrine therapy among women with breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3424.

Comparison of Clinical and Automated Breast Density Measurements: Implications for Risk Prediction and Supplemental Screening

Purpose To compare the classification of breast density with two automated methods, Volpara (version 1.5.0; Matakina Technology, Wellington, New Zealand) and Quantra (version 2.0; Hologic, Bedford, Mass), with clinical Breast Imaging Reporting and Data System (BI-RADS) density classifications and to examine associations of these measures with breast cancer risk. Materials and Methods In this study, 1911 patients with breast cancer and 4170 control subjects matched for age, race, examination date, and mammography machine were evaluated. Participants underwent mammography at Mayo Clinic or one of four sites within the San Francisco Mammography Registry between 2006 and 2012 and provided informed consent or a waiver for research, in compliance with HIPAA regulations and institutional review board approval. Digital mammograms were retrieved a mean of 2.1 years (range, 6 months to 6 years) before cancer diagnosis, with the corresponding clinical BI-RADS density classifications, and Volpara and Quantra density estimates were generated. Agreement was assessed with weighted κ statistics among control subjects. Breast cancer associations were evaluated with conditional logistic regression, adjusted for age and body mass index. Odds ratios, C statistics, and 95% confidence intervals (CIs) were estimated. Results Agreement between clinical BI-RADS density classifications and Volpara and Quantra BI-RADS estimates was moderate, with κ values of 0.57 (95% CI: 0.55, 0.59) and 0.46 (95% CI: 0.44, 0.47), respectively. Differences of up to 14% in dense tissue classification were found, with Volpara classifying 51% of women as having dense breasts, Quantra classifying 37%, and clinical BI-RADS assessment used to classify 43%. Clinical and automated measures showed similar breast cancer associations; odds ratios for extremely dense breasts versus scattered fibroglandular densities were 1.8 (95% CI: 1.5, 2.2), 1.9 (95% CI: 1.5, 2.5), and 2.3 (95% CI: 1.9, 2.8) for Volpara, Quantra, and BI-RADS classifications, respectively. Clinical BI-RADS assessment showed better discrimination of case status (C = 0.60; 95% CI: 0.58, 0.61) than did Volpara (C = 0.58; 95% CI: 0.56, 0.59) and Quantra (C = 0.56; 95% CI: 0.54, 0.58) BI-RADS classifications. Conclusion Automated and clinical assessments of breast density are similarly associated with breast cancer risk but differ up to 14% in the classification of women with dense breasts. This could have substantial effects on clinical practice patterns. (©) RSNA, 2015 Online supplemental material is available for this article.

The contributions of breast density and common genetic variation to breast cancer risk

We evaluated whether a 76-locus polygenic risk score (PRS) and Breast Imaging Reporting and Data System (BI-RADS) breast density were independent risk factors within three studies (1643 case patients, 2397 control patients) using logistic regression models. We incorporated the PRS odds ratio (OR) into the Breast Cancer Surveillance Consortium (BCSC) risk-prediction model while accounting for its attributable risk and compared five-year absolute risk predictions between models using area under the curve (AUC) statistics. All statistical tests were two-sided. BI-RADS density and PRS were independent risk factors across all three studies (P interaction = .23). Relative to those with scattered fibroglandular densities and average PRS (2(nd) quartile), women with extreme density and highest quartile PRS had 2.7-fold (95% confidence interval [CI] = 1.74 to 4.12) increased risk, while those with low density and PRS had reduced risk (OR = 0.30, 95% CI = 0.18 to 0.51). PRS added independent information (P < .001) to the BCSC model and improved discriminatory accuracy from AUC = 0.66 to AUC = 0.69. Although the BCSC-PRS model was well calibrated in case-control data, independent cohort data are needed to test calibration in the general population.

Dense and nondense mammographic area and risk of breast cancer by age and tumor characteristics

BACKGROUND

Mammographic density (MD) is a strong breast cancer risk factor. We previously reported associations of percent mammographic density (PMD) with larger and node-positive tumors across all ages, and estrogen receptor (ER)-negative status among women ages <55 years. To provide insight into these associations, we examined the components of PMD [dense area (DA) and nondense area (NDA)] with breast cancer subtypes.

METHODS

Data were pooled from six studies including 4,095 breast cancers and 8,558 controls. DA and NDA were assessed from digitized film-screen mammograms and standardized across studies. Breast cancer odds by density phenotypes and age according to histopathologic characteristics and receptor status were calculated using polytomous logistic regression.

RESULTS

DA was associated with increased breast cancer risk [OR for quartiles: 0.65, 1.00 (Ref), 1.22, 1.55; P(trend) <0.001] and NDA was associated with decreased risk [ORs for quartiles: 1.39, 1.00 (Ref), 0.88, 0.72; P(trend) <0.001] across all ages and invasive tumor characteristics. There were significant trends in the magnitude of associations of both DA and NDA with breast cancer by increasing tumor size (P(trend) < 0.001) but no differences by nodal status. Among women <55 years, DA was more strongly associated with increased risk of ER(+) versus ER(-) tumors (P(het) = 0.02), while NDA was more strongly associated with decreased risk of ER(-) versus ER(+) tumors (P(het) = 0.03).

CONCLUSIONS

DA and NDA have differential associations with ER(+) versus ER(-) tumors that vary by age.

IMPACT

DA and NDA are important to consider when developing age- and subtype-specific risk models.

Abstract 3279: Dense and non-dense mammographic area and risk of breast cancer by age and tumor characteristics

Introduction: We recently reported the percentage of mammographic density (MD) to be a breast cancer risk factor across tumor characteristics and age groups. Yet, we noted stronger associations for tumors of large size and positive lymph nodes across all ages, and ER-negative status among women ages &lt;55 years, suggesting high MD may play an important role in tumor aggressiveness, especially in younger women. We extend this initial study to investigate whether these associations with aggressive disease are due to the underlying associations of absolute dense or non-dense area, or both, with breast cancer risk.

Methods: Data were pooled from six studies including 3517 women with invasive breast cancer and 8558 without. Dense area and non-dense area were assessed from digitized film-screen mammograms using a computer-assisted threshold technique. We standardized dense and non-dense area measurements made within each study and categorized into quartiles based on the control distribution for pooled analyses. We used polytomous logistic regression to calculate breast cancer odds according to tumor type, histopathological characteristics, and receptor (ER, PR) status by age (&lt;55, 55-64, and ≥65 years), adjusting for continuous age, body mass index, and study site.

Results: Absolute dense area was associated with increased breast cancer risk [odds ratios (ORs) Q1 vs Q2: 0.67, Q3 vs Q2: 1.25, Q4 vs Q2: 1.62] and non-dense area was associated with decreased breast cancer risk (ORs: Q1 vs Q2: 1.44, Q3 vs Q2: 0.89, Q4 vs Q2: 0.71) overall and across all age groups. Positive associations for absolute dense area were observed across all invasive tumor characteristics. Stronger associations were noted for larger tumors across all ages (p-trend &lt;0.01). Among women &lt;55 years, stronger associations were observed for ER+ vs ER- [p-heterogeneity (het) = 0.02] and PR+ vs PR- tumors (p-het = 0.02). Non-dense area was inversely associated with all tumor characteristics evaluated except for tumors &lt;1.1 cm, for which no association was present. The inverse association was stronger for larger tumors, particularly for women &lt;55 years (p-trend &lt;0.01). Also among women &lt;55 years, a stronger inverse association with non-dense area was observed for ER- vs. ER+ tumors (p-het = 0.02).

Conclusion: These results suggest the strong association we previously observed of high percent MD and ER-negative disease in women &lt;55 years could be explained by the low amount of non-dense area in these women. Further research is warranted to clarify the possible differential associations of absolute dense and non-dense area on breast cancer risk according to tumor characteristics.

Citation Format: Kimberly A. Bertrand, Christopher G. Scott, Rulla M. Tamimi, Matthew R. Jensen, V. Shane Pankratz, Aaron Norman, John Shepherd, Yunn-Yi Chen, Karla Kerlikowske, Celine M. Vachon. Dense and non-dense mammographic area and risk of breast cancer by age and tumor characteristics. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3279. doi:10.1158/1538-7445.AM2014-3279

Mammographic density and risk of breast cancer by age and tumor characteristics

Introduction

Understanding whether mammographic density (MD) is associated with all breast tumor subtypes and whether the strength of association varies by age is important for utilizing MD in risk models.

Methods

Data were pooled from six studies including 3414 women with breast cancer and 7199 without who underwent screening mammography. Percent MD was assessed from digitized film-screen mammograms using a computer-assisted threshold technique. We used polytomous logistic regression to calculate breast cancer odds according to tumor type, histopathological characteristics, and receptor (estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor (HER2)) status by age (<55, 55–64, and ≥65 years).

Results

MD was positively associated with risk of invasive tumors across all ages, with a two-fold increased risk for high (>51%) versus average density (11-25%). Women ages <55 years with high MD had stronger increased risk of ductal carcinoma in situ (DCIS) compared to women ages 55–64 and ≥65 years (P_{age-interaction} = 0.02). Among all ages, MD had a stronger association with large (>2.1 cm) versus small tumors and positive versus negative lymph node status (P’s < 0.01). For women ages <55 years, there was a stronger association of MD with ER-negative breast cancer than ER-positive tumors compared to women ages 55–64 and ≥65 years (P_{age-interaction} = 0.04). MD was positively associated with both HER2-negative and HER2-positive tumors within each age group.

Conclusion

MD is strongly associated with all breast cancer subtypes, but particularly tumors of large size and positive lymph nodes across all ages, and ER-negative status among women ages <55 years, suggesting high MD may play an important role in tumor aggressiveness, especially in younger women.

The influence of mammogram acquisition on the mammographic density and breast cancer association in the Mayo Mammography Health Study cohort

Introduction

Mammographic density is a strong risk factor for breast cancer. Image acquisition technique varies across mammograms to limit radiation and produce a clinically useful image. We examined whether acquisition technique parameters at the time of mammography were associated with mammographic density and whether the acquisition parameters confounded the density and breast cancer association.

Methods

We examined this question within the Mayo Mammography Health Study (MMHS) cohort, comprised of 19,924 women (51.2% of eligible) seen in the Mayo Clinic mammography screening practice from 2003 to 2006. A case-cohort design, comprising 318 incident breast cancers diagnosed through December 2009 and a random subcohort of 2,259, was used to examine potential confounding of mammogram acquisition technique parameters (x-ray tube voltage peak (kVp), milliampere-seconds (mAs), thickness and compression force) on the density and breast cancer association. The Breast Imaging Reporting and Data System four-category tissue composition measure (BI-RADS) and percent density (PD) (Cumulus program) were estimated from screen-film mammograms at time of enrollment. Spearman correlation coefficients (r) and means (standard deviations) were used to examine the relationship of density measures with acquisition parameters. Hazard ratios (HR) and C-statistics were estimated using Cox proportional hazards regression, adjusting for age, menopausal status, body mass index and postmenopausal hormones. A change in the HR of at least 15% indicated confounding.

Results

Adjusted PD and BI-RADS density were associated with breast cancer (p-trends < 0.001), with a 3 to 4-fold increased risk in the extremely dense vs. fatty BI-RADS categories (HR: 3.0, 95% CI, 1.7 - 5.1) and the ≥ 25% vs. ≤ 5% PD categories (HR: 3.8, 95% CI, 2.5 - 5.9). Of the acquisition parameters, kVp was not correlated with PD (r = 0.04, p = 0.07). Although thickness (r = -0.27, p < 0.001), compression force (r = -0.16, p < 0.001), and mAs (r = -0.06, p = 0.008) were inversely correlated with PD, they did not confound the PD or BI-RADS associations with breast cancer and their inclusion did not improve discriminatory accuracy. Results were similar for associations of dense and non-dense area with breast cancer.

Conclusions

We confirmed a strong association between mammographic density and breast cancer risk that was not confounded by mammogram acquisition technique.

Cardiac and thromboembolic complications and mortality in patients undergoing total hip and total knee arthroplasty

OBJECTIVE

To study 90-day complications following total hip arthroplasty (THA) or total knee arthroplasty (TKA).

METHOD

In a population-based cohort of all Olmsted County residents who underwent a THA or TKA (1994-2008), we assessed 90-day occurrence and predictors of cardiac complications (myocardial infarction, cardiac arrhythmia or congestive heart failure), thromboembolic complications (deep venous thrombosis or pulmonary embolism) and mortality.

RESULTS

90-day complication rates after THA and TKA were: cardiac, 6.9% and 6.7%; thromboembolic, 4.0% and 4.9%; and mortality, 0.7% and 0.4%, respectively. In multivariable-adjusted logistic regression analyses, ASA class III-IV (OR 6.1, 95% CI:1.6-22.8) and higher Deyo-Charlson comorbidity score (OR 1.2, 95% CI:1.0-1.4) were significantly associated with odds of 90-day cardiac event post-THA in patients with no known previous cardiac event. In those with known previous cardiac disease, ASA class III-IV (OR 4.4, 95% CI:2.0-9.9), male gender (OR 0.5, 95% CI:0.3-0.9) and history of thromboembolic disease (OR 3.2; 95% CI:1.4-7.0) were significantly associated with odds of cardiac complication 90 days post-THA. No significant predictors of thromboembolism were found in THA patients. In TKA patients with no previous cardiac history, age >65 years (OR 4.1, 95% CI:1.2-14.0) and in TKA patients with known cardiac disease, ASA class III-IV (OR 3.2, 95% CI:1.8-5.7) was significantly associated with odds of 90-day cardiac events. In TKA patients with no previous thromboembolic disease, male gender (OR 0.5, 95% CI:0.2-0.9) and higher Charlson index (OR 1.2, 95% CI:1.1-1.3) and in patients with known thromboembolic disease, higher Charlson index score (OR 1.2, 95% CI:1.1-1.4) was associated with odds of 90-day thromboembolic events.

CONCLUSION

Older age, higher comorbidity, higher ASA class and previous history of cardiac/thromboembolic disease were associated with an increased risk.

Increased long-term survival of posterior cruciate-retaining versus posterior cruciate-stabilizing total knee replacements

BACKGROUND

Considerable debate remains regarding the use of posterior cruciate-retaining or posterior cruciate-stabilizing designs for total knee arthroplasty. Multiple studies have investigated kinematic, radiographic, and clinical outcomes of both. Nevertheless, long-term survivorship analyses directly comparing the two designs have not been performed, to our knowledge. Our goal was to analyze the fifteen-year survival of posterior cruciate-retaining and posterior cruciate-stabilizing total knee replacements at our institution.

METHODS

A retrospective review identified 8117 total knee arthroplasties (5389 posterior cruciate-retaining and 2728 posterior cruciate-stabilizing) that had been performed from 1988 to 1998. This range was chosen because both designs were used in high volumes at our institution during this period. Patients were followed via our total joint registry at one, two, and five years after the arthroplasty and every five years thereafter. Aseptic revision surgery was the primary end point of our analysis. Implant survival was estimated with Kaplan-Meier curves.

RESULTS

Survival at fifteen years was 90% for posterior cruciate-retaining total knee replacements, compared with 77% for posterior cruciate-stabilizing total knee replacements (p < 0.001). In knees with preoperative deformity, the fifteen-year survival was 90% for posterior cruciate-retaining total knee replacements, compared with 75% for posterior cruciate-stabilizing total knee replacements (p < 0.04). Likewise, in knees without preoperative deformity, the fifteen-year survival was 88% for posterior cruciate-retaining total knee replacements, compared with 78% for posterior cruciate-stabilizing total knee replacements (p < 0.001). After adjustment for age, sex, preoperative diagnosis, and preoperative deformity, the risk of revision was significantly lower in knees with a posterior cruciate-retaining total knee replacement (p < 0.001; hazard ratio = 0.5; 95% confidence interval, 0.4 to 0.6).

CONCLUSIONS

In evaluating the implants used at our institution for total knee arthroplasty during the study period, posterior cruciate-retaining prostheses had significantly improved survival in comparison with posterior cruciate-stabilizing prostheses at fifteen years. Furthermore, this significant difference remained when accounting for age, sex, diagnosis, and deformity.

Abstract 3716: The Mayo Mammography Health Study (MMHS): A prospective cohort study on mammographic breast density and breast cancer

INTRODUCTION: Mammographic breast density is a strong risk factor for breast cancer (BC). We established the Mayo Mammography Health Study (MMHS) cohort study at the Mayo Clinic in Rochester, Minnesota (MN) to examine the association of breast density with BC. We evaluated the influence of the image acquisition technique on the density and BC association.

METHODS: From October 2003 to September 2006, all women scheduled for screening mammography at the Mayo Clinic were invited to participate. Eligible women were residents of MN, Iowa (IA) or Wisconsin (WI); age 35+; and had no personal history of BC. A risk factor questionnaire, consent form and permission to link to tumor registries were obtained. Incident BC was identified through 2009 by linkage to the Mayo and state cancer registries. A case-cohort of all incident BCs and 2300 randomly selected women (the subcohort) were used to examine the association of breast density and BC using digitized film mammograms at the time of enrollment while controlling for the influence of the acquisition parameters (peak kilovoltage, milliampere-second, and compressed breast thickness). Two density measures were considered: a quantitative percent density (PD) measure estimated using the computer-assisted thresholding program, Cumulus (University of Toronto), and the 4-category clinical BI-RADS measure. Proportional hazards regression was used to calculate hazards ratios (HR) and 95% confidence intervals (CI) for BC associated with quartiles of PD (0-6.2%,6.3-14.9%, 15.0-25.7% and 25.8%+) and BI-RADS categories 1-4 (almost entirely fatty to extremely dense). All models included age, postmenopausal hormone use (PMH), BMI, and menopausal status. The influence of acquisition parameters was evaluated by examining models with and without their inclusion.

RESULTS: A total of 20,982 (50%) women participated in MMHS; 1058 (5%) with a prior history of BC were excluded, for a total cohort of 19,924. Compared to nonresponders, responders were younger (57.5 vs. 58.4 yrs), more likely to have ever used PMH (45% vs. 33%), and more likely to have a BC family history (19% vs 16%). The case-cohort consisted of 317 incident cases and 2300 women in the subcohort. Women were excluded from the current analysis if PD could not be estimated or if acquisition parameters were not available, leaving 249 cases and 1937 in the subcohort. As expected, PD was associated with BC [HR (95% CI): 1.0 (REF), 2.1 (1.4-3.1), 3.0 (2.0-4.5), and 4.6 (3.0-7.0) for quartiles; p-trend&lt;0.001]. Controlling for acquisition parameters attenuated the association [HR (95% CI): 1.0 (REF), 2.3 (1.5-3.4), 2.4 (1.6-3.7), and 3.0 (1.8-5.0) for quartiles; p-trend&lt;0.001]. Results for BI-RADS density were similar to those for PD.

CONCLUSION: This study confirms that breast density is a significant risk factor for BC and demonstrates that the acquisition technique confounds the density and BC risk association.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3716. doi:10.1158/1538-7445.AM2011-3716

Abstract 4828: Longitudinal breast density and risk of breast cancer

Introduction: Mammographic breast density is one of the strongest risk factors for breast cancer and appears to be modifiable. However, whether longitudinal changes in density are associated with breast cancer risk is unknown. We hypothesize that decreases in breast density are associated with reduced breast cancer risk.

Methods: The Mayo Mammography Health Study cohort enrolled 19,924 women having a screening mammogram (mgm) at the Mayo Clinic, Rochester, between 2003 and 2006. Participants were 35 years and older, had no prior breast cancer and lived in the tri-state area (MN, IA and WI). Risk factor data were collected through self-administered questionnaire and clinic databases. Incident breast cancers were identified through tumor registries (Mayo Clinic, MN, IA, WI). The BI-RADS, 4-category clinical density measure (fatty, scattered density, heterogeneous density and extreme density) was available on all mgms performed after 1996. A case-cohort design consisting of incident cases (n=241) and a random selection of the cohort (n=2300, 28 developed cancer) was used to examine the association between change in BI-RADS density and breast cancer. BI-RADS densities measured from the earliest available, and enrollment mgms (average 6 years apart) were used to assess density change. Proportional hazards regression was performed to estimate the hazard ratio (HR) associated with a change in one or more BI-RADS density categories over time, relative to staying within the same category. Age was used as the time scale, and the subcohort was weighted by the inverse of the sampling proportion. Analyses were adjusted for age, years between mgms, BI-RADS density at earliest mgm, and changes in BMI, postmenopausal hormone use, and menopausal status.

Results: Longitudinal analyses were conducted on the 219 cases and 1900 non-cases in the subcohort with at least one mgm available prior to enrollment mgm. Compared to the subcohort, cases were older (56.8 vs. 52.9 years), more likely postmenopausal (73.4% vs. 61.6%), had higher BMI (29.0 vs 28.1) and were more frequently screened (8.0 vs. 6.9 pre-enrollment mgms). As expected, cases were more likely to have extreme density (BI-RADS=4) at earliest mgm than non-cases (16.2% vs 14.3%). Cases were less likely than non-cases to experience a reduction of one density category or more (37.0% vs 38.6%) following earliest mgm. Adjusting for potential confounders, women who decreased one BI-RADS category or more over an average 6 years were at reduced risk of breast cancer (HR=0.72, 95%CI: 0.50-0.99) compared to those whose density was unchanged. However, women who increased one or more BI-RADS categories had suggestion of increased risk (HR=1.52, 95%CI: 0.97-2.4).

Conclusion: Women with a decrease in BI-RADS density category over 6 years may have decreased breast cancer risk relative to women whose breast density category remains stable. Two measures of breast density may inform women's risk beyond a measure at one point in time.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4828.

Next generation adoptive immunotherapy--human T cells as carriers of therapeutic nanoparticles

An important step in adoptive immunotherapy in general and specifically with respect to cancer treatment is the initiation of an inflammatory T cell response at the tumor site. Here we suggest a new concept for a controlled inflammatory response in which the intrinsic cytotoxic properties of T cells are upgraded with the properties of nanoparticles transfected into the T cells during the ex vivo expansion process. We report in vitro upgrading of human T cells using PEGylated boron carbide nanoparticles functionalised with a translocation peptide aimed at Boron Neutron Capture Therapy (BNCT). A key finding is that the metabolism of such upgraded human T cells were not affected by a payload of 0.13 pg boron per cell and that the nanoparticles were retained in the cell population after several cell divisions. This is vital for transporting nanoparticles by T cells to the tumor site.

Preparation and characterization of Boron carbide nanoparticles for use as a novel agent in T cell-guided boron neutron capture therapy

Boron carbide nanoparticles are proposed as a system for T cell-guided boron neutron capture therapy. Nanoparticles were produced by ball milling in various atmospheres of commercially available boron carbide. The physical and chemical properties of the particles were investigated using transmission electron microscopy, photon correlation spectroscopy, X-ray photoelectron spectroscopy, X-ray diffraction, vibrational spectroscopy, gel electrophoresis and chemical assays and reveal profound changes in surface chemistry and structural characteristics. In vitro thermal neutron irradiation of B16 melanoma cells incubated with sub-100 nm nanoparticles (381.5 microg/g (10)B) induces complete cell death. The nanoparticles alone induce no toxicity.

Functionalization and Cellular Uptake of Boron Carbide Nanoparticles. The First Step toward T Cell-Guided Boron Neutron Capture Therapy

In this paper we present surface modification strategies of boron carbide nanoparticles, which allow for bioconjugation of the transacting transcriptional activator (TAT) peptide and fluorescent dyes. Coated nanoparticles can be translocated into murine EL4 thymoma cells and B16 F10 malignant melanoma cells in amounts as high as 0.3 wt. % and 1 wt. %, respectively. Neutron irradiation of a test system consisting of untreated B16 cells mixed with B16 cells loaded with boron carbide nanoparticles were found to inhibit the proliferative capacity of untreated cells, showing that cells loaded with boron-containing nanoparticles can hinder the growth of neighboring cells upon neutron irradiation. This could provide the first step toward a T cell-guided boron neutron capture therapy.