Malkov, Serghei

Abstract Delayed terminal duct lobular unit (TDLU) involution is associated with elevated mammographic breast density (MD). Both are independent breast cancer risk factors among women with benign breast disease (BBD). Prior digital analyses of normal breast tissues revealed that epithelial nuclear density (END) and TDLU involution are inversely correlated. Accordingly, we examined associations of END, TDLU involution, and MD in BBD clinical biopsies. This study included digitized images of 262 representative image-guided hematoxylin and eosin–stained biopsies from 224 women diagnosed with BBD, enrolled within the cross-sectional BREAST-Stamp project that were visually assessed for TDLU involution (TDLU count/100 mm2, median TDLU span and median acini count per TDLU). A digital algorithm estimated nuclei count per unit epithelial area, or END. Single X-ray absorptiometry of prebiopsy ipsilateral craniocaudal digital mammograms measured global and localized MD surrounding the biopsy region. Adjusted ordinal logistic regression models assessed relationships between tertiles of TDLU and END measures. Analysis of covariance examined mean differences in MD across END tertiles. TDLU measures were positively associated with increasing END tertiles [TDLU count/100 mm2, ORT3vsT1: 3.42, 95% confidence interval (CI), 1.87–6.28; acini count/TDLUT3vsT1, OR: 2.40, 95% CI, 1.39–4.15]. END was significantly associated with localized, but not, global MD. Relationships were most apparent among patients with nonproliferative BBD. These findings suggest that quantitative END reflects different but complementary information to the histologic information captured by visual TDLU and radiologic MD measures and merits continued evaluation in assessing cellularity of breast parenchyma to understand the etiology of BBD.

Abstract Background: Mammographic breast density (MBD) is a strong breast cancer (BC) risk factor, but its biologic underpinnings are poorly understood. Use of estrogen plus progestin menopausal hormone therapy is linked to increased MBD and BC risk. Experimental data suggest that ratios of tumor promoting (5α-dihydroprogesterone [5αP]) and anti-tumorigenic (3α-dihydroprogesterone [3αP]) progesterone metabolite levels may be related to BC risk. However, relationships of endogenous progesterone and its metabolites with MBD and BC risk have not been established. Accordingly, we assessed levels of circulating progesterone and its metabolites with MBD. Methods: In this cross-sectional study, serum progesterone and its metabolites were quantified using a novel liquid chromatography-tandem mass spectrometry assay in 103 postmenopausal and 52 premenopausal (luteal menstrual cycle phase) women, ages 40-65, undergoing diagnostic image-guided ipsilateral breast biopsy. MBD was measured as percent fibroglandular volume (MBD-V) on pre-biopsy digital mammograms using single X-ray absorptiometry. Square-root transformed MBD-V was examined across tertile categories of progesterone/progesterone metabolites using age and body mass index (BMI)-adjusted linear regression models. Results: Concentrations of the hormones were as follows among postmenopausal women: progesterone [mean: 12.6 pmol/L (range: 5.2-45.8)], 3αP [5.6 pmol/L (1.4-18.8)], 5αP [100 pmol/L (16.7-388)], and 5αP/3αP ratio [26.1 (2.1-150)]; and among luteal phase premenopausal women: progesterone [2063 pmol/L (13.6-7098), 3αP [12.7 pmol/L (2.4-64.4)], 5αP [243 pmol/L (25.3-774)], 5αP/3αP ratio [25.9 (2.3-73.7)]. Among postmenopausal women, progesterone was positively associated with MBD-V (Tertile 3 vs. 1: β=0.68, p-trend=0.02). A similar borderline positive association was observed among premenopausal women (β=0.74, p-trend=0.10). Additional adjustment for circulating estradiol did not substantively alter observed associations. Levels of 3αP, 5αP and the 5αP/3αP ratio were not associated with MBD-V among pre- or postmenopausal women. Conclusions: Concentrations of progesterone and it metabolites show substantial inter-woman variation. We observed a positive association between endogenous progesterone and MBD-V among both postmenopausal and premenopausal luteal phase women. We did not observe an association with the ratio of 5αP to 3αP levels and MBD-V. These findings suggest the need for additional studies to understand the biological basis of the role of progesterone and its metabolites in MBD and BC risk. Citation Format: Manila Hada, Hannah Oh, Sharon Fan, Roni T. Falk, Berta Geller, Pamela Vacek, Donald Weaver, John Shepherd, Jeff Wang, Bo Fan, Amir P. Mahmoudzadeh, Serghei Malkov, Sally Herschorn, Louise A. Brinton, Xia Xu, Mark E. Sherman, Britton Trabert, Gretchen L. Gierach. Relationship of serum progesterone and progesterone metabolites with mammographic density [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 588.

Abstract 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 [<25 (underweight), 25-30 (normal weight) and >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<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 <25, 25-30 and >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 <25, 25-29, >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.

Abstract 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.

Abstract 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.