6/9/2017 Disclosures Involution and Breast Density • I do not have conflicts of interest to disclose. Mark Sherman (Presenter) & Gretchen Gierach • I will not discuss off-label use of Health Sciences Research, Mayo Clinic Division of Cancer Epidemiology and Genetics medications. National Cancer Institute Molecular Histology of the Breast Agenda Mammographic Density • What are terminal duct lobular units (TDLUs)? • Why study TDLUs? Increasing Risk • How are TDLU content and mammographic density related? Increasing Risk • Future aspirations and directions Terminal Duct Lobular Unit (TDLU) Radisky BCRT 2016; Figueroa JNCI 2014 1
6/9/2017 TDLU Morphology / Microenvironment TDLU Morphology / Microenvironment TDLU Morphometry • Number TDLU / unit area (“Density”) • TDLU span • Acini / TDLU Lobule Type: 1-4 • Types 1-3 reflect acini content Reproducibility of TDLU Metrics Is TDLU Status an Intermediate Endpoint? Carcinogenesis??? Invasion Involution Correlation of TDLU Metrics Comparison Correlation (Spearman) # TDLUs Acini / TDLU 0.36 • Physiology – Lactation Breast Cancer Types • Other Changes - BBD # TDLUs Span/ TDLU 0.25 • Luminal (A or B) • Carcinogenesis • Basal Acini / TDLU Span/ TDLU 0.77 • Process with • HER2 uncertain outcomes • Claudin Low Results similar for mean, median or maximum values 2
6/9/2017 Agenda Colony Forming Cells • What are terminal duct lobular units (TDLUs)? • Why study TDLUs? • How are TDLU content and mammographic density related? • Future aspirations and directions Most proliferating cells are ER-, suggesting paracrine signaling Kannan et al Stem Cell Reports 2013 Why Study TDLUs? Age Related TDLU Involution • Hypothesized that TDLU involution is related to breast • Predict breast cancer risk (benign biopsy) density and cancer risk (Henson & Tarone Cancer 1993) • Predict local recurrence (e.g. DCIS) • Lack of involution is a risk factor for breast cancer • Prevent cancer by inducing involution Biopsy BBD • Understand link: breast density and cancer risk Cancer Vs. TDLU Involution No Cancer • Study mechanisms of carcinogenesis • Independent risk factor after benign biopsy • Intermediate endpoint in prevention trials • Mayo Benign Breast Disease (BBD) Cohort • Nurses’ Cohort • Association is robust; shown with different methods Milanese JNCI 2006, McKian JCO 2009, Ghosh JCO 2010, Baer Cancer 2008 3
6/9/2017 TDLU Involution Modifies Risks Associated TDLU Involution in Repeat Biopsies with Other Factors 100 Involution TDLUs N= None ↑ 80 P=Partial ↔ Biopsy 2 >75% C=Complete ↓ 60 51-75% 26-50% 40 0-25% 20 0 0-25% 26-50% 51-75% >75% Biopsy 1 Non-progressive TDLU involution is related to increased breast cancer risk HR Adj = 1.63 (95% CI: 1.03-2.57) Milanese JNCI 2006 Radisky BCRT 2016 Involution, Mammographic Density and Breast Density Modifies Risk in BBD Breast Cancer Risk 3.5 Standard Incidence Ratio Involution Density HR Adj (95% CI) 3 Complete Low 1.00 2.5 Density Complete High 1.66 (0.75-3.70) Low 2 ∗ Partial Low 1.57 (0.73-3.36) Medium 1.5 Partial High 2.70 (1.32-5.53) High 1 None Low 3.24 (1.05-9.98) None High 4.08 (1.72-9.68) 0.5 0 TDLU involution and mammographic density are NP PDWA AH independent breast cancer risk factors (p Int =0.60) Assessed via parenchymal pattern or BIRADS; independently confirmed with automated quantitative measurement Vierkant BMC Cancer 2017 Ghosh JNCI 2010 4
6/9/2017 TDLU Involution in Benign Biopsies Predicts LN+ TDLU Involution Metrics Vs. Age Correlations (Spearman ) Counts vs. Span r=0.16 TDLU Counts Involution Cancers + LN SIR (95% CI) Counts vs. Acini r=0.18 # (Column %) # ( Row %) Span vs. Acini r=0.71 None 242 (21.2) 87 (36) 2.05 (1.80-2.33) TDLU counts per section vs. TDLU #/mm 2 highly Partial 690 (60.5) 193 (28) 1.70 (1.57-1.83) correlated – standardized TDLU Span samples Complete 208 (18.2) 41 (20) 1.09 (0.95-1.25) Total 1140 321 • 321 (28%) of 1140 were LN+ Acini / TDLU • Percentage with LN+ by involution : None>Partial>Complete (Categorical) • Number with LN+ by TDLU involution: Partial>None>Complete; partial involution contributes 60% of LN+ • Data are independent of age Visscher Cancer 2016 Published by Oxford University Press 2014. Figueroa J D et al. JNCI J Natl Cancer Inst 2014;106:dju286 TDLU Counts by Age And Parity Status Breast Density Vs. Age Nulliparous women had fewer TDLUs than uniparous women: Premenopausal RR=0.79 (0.73-0.85) Postmenopausal RR=0.67 (0.56-0.79) Increasing births related to higher TDLU counts: Premenopausal p trend = 0.01; Postmenopausal p trend = 0.007 TDLU Counts: Uniparous Women P interaction = <=0.001 Yrs Since Birth RR (85% CI) <5 1.00 5-9 0.59 (0.29-1.21) 10+ 0.43 (0.20-0.93) P trend = 0.03 Age at last birth is not recorded in studies Ginsburg BJC 2008 (Also summarizing data from Maskarinec CEBP 2006, Vachon CEBP 2007) Figueroa J Natl Cancer Inst 2014 5
6/9/2017 Tissue Composition Vs. Age & Density TDLU Involution Vs. Mammographic Density High Density Less Involution Low Density High Involution Ginsburg BJC 2008, Li CEBP 2005, Caman BMC Public Health 2013, Sun CEBP 2014 Ghosh JCO 2010 Average TDLU Count and Average TDLU Count by Age Average Percent Breast Density by Age Serum Hormones Vs. TDLU Counts Serum Levels Premenopausal Postmenopausal OR (95% CI) OR (95CI) TDLU Count / 100 mm 2 % Dense Area Window of Susceptibility Estradiol 0.88 (.80-0.97) 1.61 (1.32-1.97) Testosterone 0.89 (0.88-1.08) 1.32 (1.09-1.59) Radiation, smoking, age of Progesterone 0.80 (0.72-0.89) immigration low to high risk area Prolactin 1.29 (1.04-1.59) 1.18 (1.07-1.31) SHBG 1.04 (0.93-1.16) 1.14 (0.89-1.45) Age TDLU Count % Dense Area Adjusted for covariates. Results significant after correction for multiple comparisons bolded More at-risk epithelium may partially explain risk associated with higher BD Khodr CEBP 2014 (Komen Tissue bank) Gierach GL Cancer Prev Res 2016 6
6/9/2017 Breast Radiology Evaluation And Study Premenopausal Women of Tissues (BREAST) Stamp Project Gierach Cancer Prev Res 2016 TDLU Involution vs. Mammographic Density TDLU Counts TDLU Span 50 • 465 women ages 40-65 years undergoing % Mammographic Density 45 biopsy for radiologic finding at the University of Bars = Quintiles 40 Vermont (2007-10) 35 • Questionnaires and blood collected 30 25 • Area and volumetric density measured globally 20 and peri-lesionally (around biopsy target) 15 • 348 women with benign biopsies evaluable 10 5 0 % Dense-A % Dense-V %Dense-A %Dense-V Shepherd CEBP 2011, Gierach Cancer Prev Res 2016 P trend 0.09 0.11 0.01 0.003 Breast Radiology Evaluation And Study of Premenopausal Women Tissues (BREAST) Stamp Project Non-Dense Area/Volume (cm 2 / cm 3 ) Gierach Cancer Prev Res 2016 Premenopausal women: TDLU Counts TDLU Span • TDLU counts and span are directly related to 450 global and perilesional area/volume % density 400 – Associations for global absolute density weaker; 350 associations found for absolute peri-lesional density 300 • TDLU metrics are inversely related to global 250 absolute non-dense area and volume 200 – Associations for perilesional non-dense content weak 150 Postmenopausal women: Associations weak/null 100 Acini/TDLU weak/null associations with density 50 0 Non-Dense-A Non-Dense-V Non-Dense-A Non-Dense-V P trend 0.004 <0.02 0.01 0.009 7
6/9/2017 Relationship of IGFs to Mammographic Density Relationship of IGFs, Breast Density and TDLU and TDLU Involution Involution • In rodents, IGFs affect breast development, including • 228 women (155 pre- and 73 post- events at puberty, pregnancy, post-weaning involution menopausal) with blood, TDLU assessment • IGFs are involved in stromal-epithelial interactions (corrected for area), not using hormones • Mammographic density is a risk factor related to • Serum analysis: IGF-1; IGFBP-3 and ratio fibroglandular content and tissue organization • IGFs have inconsistent relationship with density, but • Relate IGFs to TDLU involution, stratified by more consistent relationship with breast cancer risk menopausal status, adjusted for confounders • IGF levels inversely related to level of TDLU involution; • Mammographic density assessed as effect increased IGF1-R associated with increased breast cancer risk (Rice Breast Cancer Res 2012) modifier Circulating Insulin-like Growth Factors (IGFs) TDLU Involution & Mammographic Density and TDLU Count by Tertiles of Breast Density Elevated IGF1 or High TDLU Counts IGF1:IGFBP3 ratio Higher Breast Cancer Risk Premenopausal P -int Postmenopausal P -int High Breast Density??? <0.001 0.006 IGF-1:IGFBP-3 Higher Breast Cancer Risk Density Tertile 1 High Breast Cancer Risk Density Tertile 2 Density Tertile 3 Key Pathways High TDLU High MD IGFs? 0.5 1.0 1.5 2.0 2.5 3.0 0.5 1.0 1.5 2.0 2.5 3.0 Counts Cancer Risk Hormones? RR (95% CI) Inflammation? CancerRisk Jak-Stat Signaling Is this local or Systemic? Horne H,…Gierach GL. Breast Cancer Res 2016. 8
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