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Sherman ME, Vierkant RA, Winham SJ, Vachon CM, Carter JM, Pacheco-Spann L, Jensen MR, McCauley BM, Hoskin TL, Seymour L, Gehling D, Fischer J, Ghosh K, Radisky DC, Degnim AC. Benign Breast Disease and Breast Cancer Risk in the Percutaneous Biopsy Era. JAMA Surg 2024; 159:193-201. [PMID: 38091020 PMCID: PMC10719829 DOI: 10.1001/jamasurg.2023.6382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 09/08/2023] [Indexed: 12/17/2023]
Abstract
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.
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Affiliation(s)
- Mark E. Sherman
- Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida
| | | | | | | | - Jodi M. Carter
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | | | | | | | - Tanya L. Hoskin
- Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Lisa Seymour
- Department of Surgery, Mayo Clinic, Rochester, Minnesota
| | - Denice Gehling
- Department of Surgery, Mayo Clinic, Rochester, Minnesota
| | | | - Karthik Ghosh
- Department of General Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | | | - Amy C. Degnim
- Department of Surgery, Mayo Clinic, Rochester, Minnesota
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Abubakar M, Klein A, Fan S, Lawrence S, Mutreja K, Henry JE, Pfeiffer RM, Duggan MA, Gierach GL. Host, reproductive, and lifestyle factors in relation to quantitative histologic metrics of the normal breast. Breast Cancer Res 2023; 25:97. [PMID: 37582731 PMCID: PMC10426057 DOI: 10.1186/s13058-023-01692-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 07/29/2023] [Indexed: 08/17/2023] Open
Abstract
BACKGROUND Emerging data indicate that variations in quantitative epithelial and stromal tissue composition and their relative abundance in benign breast biopsies independently impact risk of future invasive breast cancer. To gain further insights into breast cancer etiopathogenesis, we investigated associations between epidemiological factors and quantitative tissue composition metrics of the normal breast. METHODS The study participants were 4108 healthy women ages 18-75 years who voluntarily donated breast tissue to the US-based Susan G. Komen Tissue Bank (KTB; 2008-2019). Using high-accuracy machine learning algorithms, we quantified the percentage of epithelial, stromal, adipose, and fibroglandular tissue, as well as the proportion of fibroglandular tissue that is epithelium relative to stroma (i.e., epithelium-to-stroma proportion, ESP) on digitized hematoxylin and eosin (H&E)-stained normal breast biopsy specimens. Data on epidemiological factors were obtained from participants using a detailed questionnaire administered at the time of tissue donation. Associations between epidemiological factors and square root transformed tissue metrics were investigated using multivariable linear regression models. RESULTS With increasing age, the amount of stromal, epithelial, and fibroglandular tissue declined and adipose tissue increased, while that of ESP demonstrated a bimodal pattern. Several epidemiological factors were associated with individual tissue composition metrics, impacting ESP as a result. Compared with premenopausal women, postmenopausal women had lower ESP [β (95% Confidence Interval (CI)) = -0.28 (- 0.43, - 0.13); P < 0.001] with ESP peaks at 30-40 years and 60-70 years among pre- and postmenopausal women, respectively. Pregnancy [β (95%CI) vs nulligravid = 0.19 (0.08, 0.30); P < 0.001] and increasing number of live births (P-trend < 0.001) were positively associated with ESP, while breastfeeding was inversely associated with ESP [β (95%CI) vs no breastfeeding = -0.15 (- 0.29, - 0.01); P = 0.036]. A positive family history of breast cancer (FHBC) [β (95%CI) vs no FHBC = 0.14 (0.02-0.26); P = 0.02], being overweight or obese [β (95%CI) vs normal weight = 0.18 (0.06-0.30); P = 0.004 and 0.32 (0.21-0.44); P < 0.001, respectively], and Black race [β (95%CI) vs White = 0.12 (- 0.005, 0.25); P = 0.06] were positively associated with ESP. CONCLUSION Our findings revealed that cumulative exposure to etiological factors over the lifespan impacts normal breast tissue composition metrics, individually or jointly, to alter their dynamic equilibrium, with potential implications for breast cancer susceptibility and tumor etiologic heterogeneity.
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Affiliation(s)
- Mustapha Abubakar
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Shady Grove, Bethesda, MD, 20850, USA.
| | - Alyssa Klein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Shady Grove, Bethesda, MD, 20850, USA
| | - Shaoqi Fan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Shady Grove, Bethesda, MD, 20850, USA
| | - Scott Lawrence
- Molecular and Digital Pathology Laboratory, Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD, 21702, USA
| | - Karun Mutreja
- Molecular and Digital Pathology Laboratory, Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD, 21702, USA
| | - Jill E Henry
- Biospecimen Collection and Banking Core, Susan G. Komen Tissue Bank at the IU Simon Comprehensive Cancer Center, Indianapolis, IN, USA
| | - Ruth M Pfeiffer
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Shady Grove, Bethesda, MD, 20850, USA
| | - Maire A Duggan
- Department of Pathology and Laboratory Medicine, University of Calgary, Calgary, AB, T2N2Y9, Canada
| | - Gretchen L Gierach
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Shady Grove, Bethesda, MD, 20850, USA
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3
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Davis Lynn BC, Lord BD, Cora R, Pfeiffer RM, Lawrence S, Zirpoli G, Bethea TN, Palmer JR, Gierach GL. Associations between quantitative measures of TDLU involution and breast tumor molecular subtypes among breast cancer cases in the Black Women's Health Study: a case-case analysis. Breast Cancer Res 2022; 24:86. [PMID: 36471360 PMCID: PMC9720909 DOI: 10.1186/s13058-022-01577-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 11/07/2022] [Indexed: 12/07/2022] Open
Abstract
BACKGROUND Terminal duct lobular units (TDLUs) are the structures in the breast that give rise to most breast cancers. Previous work has shown that TDLU involution is inversely associated with TDLU metrics, such as TDLU count/100mm2, TDLU span (µm), and number of acini/TDLU, and that these metrics may be elevated in the normal breast tissue of women diagnosed with triple-negative (TN) compared with luminal A breast tumors. It is unknown whether this relationship exists in Black women, who have the highest incidence of TN breast cancer and the highest overall breast cancer mortality rate. We examined relationships between TDLU metrics and breast cancer molecular subtype among breast cancer cases in the Black Women's Health Study (BWHS). METHODS We assessed quantitative TDLU metrics (TDLU count/100mm2, TDLU span (µm), and number of acini/TDLU) in digitized 247 hematoxylin and eosin-stained adjacent normal tissue sections from 223 BWHS breast cancer cases, including 65 triple negative (TN) cancers (estrogen receptor (ER) negative, progesterone receptor (PR) negative, human epidermal growth factor-2 (HER2) negative) and 158 luminal A cancers (ER positive, HER2 negative). We evaluated associations of least square mean TDLU metrics adjusted for age and body mass index (BMI) with patient and clinical characteristics. In logistic regression models, we evaluated associations between TDLU metrics and breast cancer subtype, adjusting for age, BMI, and tumor size. RESULTS Older age and higher BMI were associated with lower TDLU metrics and larger tumor size and lymph node invasion with higher TDLU metrics. The odds of TN compared with luminal A breast cancer increased with increasing tertiles of TDLU metrics, with odds ratios (95% confidence intervals) for tertile 3 versus tertile 1 of 2.18 (0.99, 4.79), 2.77 (1.07, 7.16), and 1.77 (0.79, 3.98) for TDLU count, TDLU span, and acini count/TDLU, respectively. CONCLUSION Associations of TDLU metrics with breast cancer subtypes in the BWHS are consistent with previous studies of White and Asian women, demonstrating reduced TDLU involution in TN compared with luminal A breast cancers. Further investigation is needed to understand the factors that influence TDLU involution and the mechanisms that mediate TDLU involution and breast cancer subtype.
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Affiliation(s)
- Brittny C Davis Lynn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD, USA
| | - Brittany D Lord
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD, USA
| | | | - Ruth M Pfeiffer
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD, USA
| | - Scott Lawrence
- Molecular and Digital Pathology Laboratory, Leidos Biomedical Research, Inc., 9615 Medical Center Drive, Rockville, MD, USA
| | - Gary Zirpoli
- Slone Epidemiology Center, Boston University, 72 East Concord Street L-7, Boston, MA, USA
| | - Traci N Bethea
- Office of Minority Health and Health Disparities Research, Georgetown Lombardi Comprehensive Cancer Center, 1000 New Jersey Ave SE, Washington, DC, USA
| | - Julie R Palmer
- Slone Epidemiology Center, Boston University, 72 East Concord Street L-7, Boston, MA, USA
| | - Gretchen L Gierach
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD, USA.
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Sung H, Koka H, Marino N, Pfeiffer RM, Cora R, Figueroa JD, Sherman ME, Gierach GL, Yang XR. Associations of Genetic Ancestry with Terminal Duct Lobular Unit Involution among Healthy Women. J Natl Cancer Inst 2022; 114:1420-1424. [PMID: 35333343 DOI: 10.1093/jnci/djac063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 01/31/2022] [Accepted: 03/16/2022] [Indexed: 11/13/2022] Open
Abstract
Reduced age-related terminal duct lobular unit (TDLU) involution has been linked to increased breast cancer risk and triple-negative breast cancer (TNBC). Associations of TDLU involution levels with race and ethnicity remain incompletely explored. Herein, we examined associations between genetic ancestry and TDLU involution in normal breast tissue donated by 2,014 healthy women in the US. Women of African ancestry were more likely than European women to have increased TDLU counts (odds ratio [OR]trend=1.36; 95% CI = 1.07-1.74), acini counts/TDLU (OR = 1.47; 95% CI = 1.06-2.03), and median TDLU span (ORtrend=1.44; 95% CI = 1.08-1.91), indicating lower involution; whereas East Asian descendants were associated with decreased TDLU counts (ORtrend=0.52; 95% CI = 0.35-0.78) after controlling for potential confounders. These associations are consistent with the racial variations in incidence rates of TNBC in the US and suggest opportunities for future work examining whether TDLU involution may mediate the racial differences in subtype-specific breast cancer risk.
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Affiliation(s)
- Hyuna Sung
- Surveillance and Health Equity Science,American Cancer Society, Atlanta, Georgia, USA
| | - Hela Koka
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Natascia Marino
- Susan G. Komen Tissue Bank at the IU Simon Comprehensive Cancer Center, Indianapolis, IN, USA.,Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ruth M Pfeiffer
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Renata Cora
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Jonine D Figueroa
- Usher institute, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Mark E Sherman
- Quantitative Health Sciences,Mayo Clinic, Jacksonville, Florida, USA
| | - Gretchen L Gierach
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Xiaohong R Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
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5
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Brandão M, Guisseve A, Damasceno A, Bata G, Silva-Matos C, Alberto M, Ferro J, Garcia C, Zaqueu C, Lorenzoni C, Leitão D, Soares O, Gudo-Morais A, Schmitt F, Morais S, Tulsidás S, Carrilho C, Lunet N. Risk Factors for Breast Cancer, Overall and by Tumor Subtype, among Women from Mozambique, Sub-Saharan Africa. Cancer Epidemiol Biomarkers Prev 2021; 30:1250-1259. [PMID: 33849971 DOI: 10.1158/1055-9965.epi-20-1730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 03/01/2021] [Accepted: 04/07/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Breast cancer incidence is rising in Africa, but there are scare data regarding risk factors in this region. We assessed the relation between risk factors and the occurrence of breast cancer, overall and by tumor subtype in women from Mozambique. METHODS The associations between education, number of births, height, weight, body mass index (BMI), and breast cancer risk among 138 cases (participants from the Moza-BC cohort) and 638 controls from the general population (from a World Health Organization stepwise approach to surveillance survey), recruited during 2014 to 2017, were investigated. Adjusted ORs (aOR) and 95% confidence intervals (CI) were estimated using multivariable logistic regression. RESULTS Multiparity (≥6 vs. 0-1 live births) was a protective factor for the development of hormone receptor (HR)-positive (aOR = 0.22; 95% CI, 0.08-0.64) and HR-positive/HER2-negative tumors (aOR = 0.20; 95% CI, 0.06-0.68), whereas a higher educational level (≥8 vs. 0 schooling years) increased breast cancer risk across all subtypes (overall aOR = 1.98; 95% CI, 1.04-3.80). Higher weight and BMI were associated with a higher breast cancer risk among postmenopausal women (per 1-kg increase: aOR = 1.05; 95% CI, 1.02-1.08; per 1-kg/m2 increase: aOR = 1.11; 95% CI, 1.04-1.18, respectively), but were protective in premenopausal women (aOR = 0.98; 95% CI, 0.96-0.99; aOR = 0.95; 95% CI, 0.91-0.99, respectively), regardless of subtype. Higher height increased the risk of HR-negative tumors in postmenopause (per 10-cm increase: aOR = 2.81; 95% CI, 1.41-6.03). CONCLUSION These results demonstrate the etiological heterogeneity of breast cancer among native African women, namely regarding the differential effect of multiparity, education, and body parameters in breast cancer risk. IMPACT As the prevalence of obesity grows, these findings are important to inform public health policies on cancer prevention, by highlighting obesity as a modifiable risk factor for breast cancer among African women.
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Affiliation(s)
- Mariana Brandão
- EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, Porto, Portugal.,Departamento de Ciências da Saúde Pública e Forenses e Educação Médica, Faculdade de Medicina da Universidade do Porto, Alameda Prof. Hernâni Monteiro, Porto, Portugal.,Institut Jules Bordet, Université Libre de Bruxelles, Boulevard de Waterloo, Brussels, Belgium
| | - Assucena Guisseve
- Department of Pathology, Faculty of Medicine, University Eduardo Mondlane, Avenida Salvador Allende, Maputo, Mozambique.,Department of Pathology, Maputo Central Hospital, Avenida Eduardo Mondlane, Maputo, Mozambique
| | - Albertino Damasceno
- Cardiology Department, Maputo Central Hospital, Avenida Eduardo Mondlane, Maputo, Mozambique
| | - Genoveva Bata
- Oncology Department, Maputo Central Hospital, Avenida Eduardo Mondlane, Maputo, Mozambique
| | - Carla Silva-Matos
- Unidade de Gestão do Fundo Global - Direcção de Planificação e Cooperação, Ministério da Saúde, Avenida Eduardo Mondlane, Maputo, Mozambique
| | - Matos Alberto
- Department of Pathology, Maputo Central Hospital, Avenida Eduardo Mondlane, Maputo, Mozambique
| | - Josefo Ferro
- Department of Pathology, Beira Central Hospital, Avenida Mártires da Revolução, Beira, Mozambique
| | - Carlos Garcia
- Department of Pathology, Beira Central Hospital, Avenida Mártires da Revolução, Beira, Mozambique
| | - Clésio Zaqueu
- Department of Pathology, Nampula Central Hospital, Avenida Samora Machel, Nampula, Mozambique
| | - Cesaltina Lorenzoni
- Department of Pathology, Faculty of Medicine, University Eduardo Mondlane, Avenida Salvador Allende, Maputo, Mozambique.,Department of Pathology, Maputo Central Hospital, Avenida Eduardo Mondlane, Maputo, Mozambique
| | - Dina Leitão
- Pathology Department, Centro Hospitalar Universitário de São João, Alameda Prof. Hernâni Monteiro, Porto, Portugal.,Departmento de Patologia e Oncologia, Faculdade de Medicina da Universidade do Porto, Alameda Prof. Hernâni Monteiro, Porto, Portugal.,Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), Rua Júlio Amaral de Carvalho, Porto, Portugal
| | - Otília Soares
- Oncology Department, Maputo Central Hospital, Avenida Eduardo Mondlane, Maputo, Mozambique
| | - Alberto Gudo-Morais
- Oncology Department, Maputo Central Hospital, Avenida Eduardo Mondlane, Maputo, Mozambique.,Radiotherapy Unit, Maputo Central Hospital, Avenida Eduardo Mondlane, Maputo, Mozambique
| | - Fernando Schmitt
- Departmento de Patologia e Oncologia, Faculdade de Medicina da Universidade do Porto, Alameda Prof. Hernâni Monteiro, Porto, Portugal.,Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), Rua Júlio Amaral de Carvalho, Porto, Portugal
| | - Samantha Morais
- EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, Porto, Portugal.,Departamento de Ciências da Saúde Pública e Forenses e Educação Médica, Faculdade de Medicina da Universidade do Porto, Alameda Prof. Hernâni Monteiro, Porto, Portugal
| | - Satish Tulsidás
- EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, Porto, Portugal.,Departamento de Ciências da Saúde Pública e Forenses e Educação Médica, Faculdade de Medicina da Universidade do Porto, Alameda Prof. Hernâni Monteiro, Porto, Portugal.,Oncology Department, Maputo Central Hospital, Avenida Eduardo Mondlane, Maputo, Mozambique
| | - Carla Carrilho
- EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, Porto, Portugal. .,Department of Pathology, Faculty of Medicine, University Eduardo Mondlane, Avenida Salvador Allende, Maputo, Mozambique.,Department of Pathology, Maputo Central Hospital, Avenida Eduardo Mondlane, Maputo, Mozambique
| | - Nuno Lunet
- EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, Porto, Portugal.,Departamento de Ciências da Saúde Pública e Forenses e Educação Médica, Faculdade de Medicina da Universidade do Porto, Alameda Prof. Hernâni Monteiro, Porto, Portugal
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Vellal AD, Sirinukunwattan K, Kensler KH, Baker GM, Stancu AL, Pyle ME, Collins LC, Schnitt SJ, Connolly JL, Veta M, Eliassen AH, Tamimi RM, Heng YJ. Deep Learning Image Analysis of Benign Breast Disease to Identify Subsequent Risk of Breast Cancer. JNCI Cancer Spectr 2021; 5:pkaa119. [PMID: 33644680 PMCID: PMC7898083 DOI: 10.1093/jncics/pkaa119] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 11/04/2020] [Accepted: 12/18/2020] [Indexed: 12/16/2022] Open
Abstract
Background New biomarkers of risk may improve breast cancer (BC) risk prediction. We developed a computational pathology method to segment benign breast disease (BBD) whole slide images into epithelium, fibrous stroma, and fat. We applied our method to the BBD BC nested case-control study within the Nurses' Health Studies to assess whether computer-derived tissue composition or a morphometric signature was associated with subsequent risk of BC. Methods Tissue segmentation and nuclei detection deep-learning networks were established and applied to 3795 whole slide images from 293 cases who developed BC and 1132 controls who did not. Percentages of each tissue region were calculated, and 615 morphometric features were extracted. Elastic net regression was used to create a BC morphometric signature. Associations between BC risk factors and age-adjusted tissue composition among controls were assessed using analysis of covariance. Unconditional logistic regression, adjusting for the matching factors, BBD histological subtypes, parity, menopausal status, and body mass index evaluated the relationship between tissue composition and BC risk. All statistical tests were 2-sided. Results Among controls, direction of associations between BBD subtypes, parity, and number of births with breast composition varied by tissue region; select regions were associated with childhood body size, body mass index, age of menarche, and menopausal status (all P < .05). A higher proportion of epithelial tissue was associated with increased BC risk (odds ratio = 1.39, 95% confidence interval = 0.91 to 2.14, for highest vs lowest quartiles, P trend = .047). No morphometric signature was associated with BC. Conclusions The amount of epithelial tissue may be incorporated into risk assessment models to improve BC risk prediction.
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Affiliation(s)
- Adithya D Vellal
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Korsuk Sirinukunwattan
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Engineering Science, Institute of Biomedical Engineering (IBME), University of Oxford, Oxford, UK
- Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford University NHS Foundation Trust, Oxford, UK
| | - Kevin H Kensler
- Division of Population Sciences, Dana Farber Cancer Institute, Boston, MA, USA
| | - Gabrielle M Baker
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Andreea L Stancu
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Michael E Pyle
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Laura C Collins
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Stuart J Schnitt
- Dana-Farber/Brigham and Women's Cancer Center, Harvard Medical School, Dana-Farber Cancer Institute-Brigham and Women's Hospital, Boston, MA, USA
| | - James L Connolly
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Mitko Veta
- Medical Image Analysis Group, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - A Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Rulla M Tamimi
- Channing Division of Network Medicine, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
| | - Yujing J Heng
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
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7
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Breast Cancer and Microcalcifications: An Osteoimmunological Disorder? Int J Mol Sci 2020; 21:ijms21228613. [PMID: 33203195 PMCID: PMC7696282 DOI: 10.3390/ijms21228613] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 11/02/2020] [Accepted: 11/09/2020] [Indexed: 12/11/2022] Open
Abstract
The presence of microcalcifications in the breast microenvironment, combined with the growing evidences of the possible presence of osteoblast-like or osteoclast-like cells in the breast, suggest the existence of active processes of calcification in the breast tissue during a woman’s life. Furthermore, much evidence that osteoimmunological disorders, such as osteoarthritis, rheumatoid arthritis, or periodontitis influence the risk of developing breast cancer in women exists and vice versa. Antiresorptive drugs benefits on breast cancer incidence and progression have been reported in the past decades. More recently, biological agents targeting pro-inflammatory cytokines used against rheumatoid arthritis also demonstrated benefits against breast cancer cell lines proliferation, viability, and migratory abilities, both in vitro and in vivo in xenografted mice. Hence, it is tempting to hypothesize that breast carcinogenesis should be considered as a potential osteoimmunological disorder. In this review, we compare microenvironments and molecular characteristics in the most frequent osteoimmunological disorders with major events occurring in a woman’s breast during her lifetime. We also highlight what the use of bone anabolic drugs, antiresorptive, and biological agents targeting pro-inflammatory cytokines against breast cancer can teach us.
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Kensler KH, Liu EZF, Wetstein SC, Onken AM, Luffman CI, Baker GM, Collins LC, Schnitt SJ, Bret-Mounet VC, Veta M, Pluim JPW, Liu Y, Colditz GA, Eliassen AH, Hankinson SE, Tamimi RM, Heng YJ. Automated Quantitative Measures of Terminal Duct Lobular Unit Involution and Breast Cancer Risk. Cancer Epidemiol Biomarkers Prev 2020; 29:2358-2368. [PMID: 32917665 DOI: 10.1158/1055-9965.epi-20-0723] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 07/02/2020] [Accepted: 09/04/2020] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Manual qualitative and quantitative measures of terminal duct lobular unit (TDLU) involution were previously reported to be inversely associated with breast cancer risk. We developed and applied a deep learning method to yield quantitative measures of TDLU involution in normal breast tissue. We assessed the associations of these automated measures with breast cancer risk factors and risk. METHODS We obtained eight quantitative measures from whole slide images from a benign breast disease (BBD) nested case-control study within the Nurses' Health Studies (287 breast cancer cases and 1,083 controls). Qualitative assessments of TDLU involution were available for 177 cases and 857 controls. The associations between risk factors and quantitative measures among controls were assessed using analysis of covariance adjusting for age. The relationship between each measure and risk was evaluated using unconditional logistic regression, adjusting for the matching factors, BBD subtypes, parity, and menopausal status. Qualitative measures and breast cancer risk were evaluated accounting for matching factors and BBD subtypes. RESULTS Menopausal status and parity were significantly associated with all eight measures; select TDLU measures were associated with BBD histologic subtype, body mass index, and birth index (P < 0.05). No measure was correlated with body size at ages 5-10 years, age at menarche, age at first birth, or breastfeeding history (P > 0.05). Neither quantitative nor qualitative measures were associated with breast cancer risk. CONCLUSIONS Among Nurses' Health Studies women diagnosed with BBD, TDLU involution is not a biomarker of subsequent breast cancer. IMPACT TDLU involution may not impact breast cancer risk as previously thought.
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Affiliation(s)
- Kevin H Kensler
- Division of Population Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Emily Z F Liu
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Suzanne C Wetstein
- Medical Image Analysis Group, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Allison M Onken
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Christina I Luffman
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Gabrielle M Baker
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Laura C Collins
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Stuart J Schnitt
- Department of Pathology, Harvard Medical School and Brigham and Women's Hospital; Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Vanessa C Bret-Mounet
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Mitko Veta
- Medical Image Analysis Group, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Josien P W Pluim
- Medical Image Analysis Group, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Ying Liu
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine and Alvin J. Siteman Cancer Center, St Louis, Missouri
| | - Graham A Colditz
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine and Alvin J. Siteman Cancer Center, St Louis, Missouri
| | - A Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Susan E Hankinson
- Channing Division of Network Medicine, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, Massachusetts
| | - Rulla M Tamimi
- Channing Division of Network Medicine, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York
| | - Yujing J Heng
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
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9
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Bodelon C, Oh H, Derkach A, Sampson JN, Sprague BL, Vacek P, Weaver DL, Fan S, Palakal M, Papathomas D, Xiang J, Patel DA, Linville L, Clare SE, Visscher DW, Mies C, Hewitt SM, Brinton LA, Storniolo AMV, He C, Chanock SJ, Garcia-Closas M, Gierach GL, Figueroa JD. Polygenic risk score for the prediction of breast cancer is related to lesser terminal duct lobular unit involution of the breast. NPJ Breast Cancer 2020; 6:41. [PMID: 32964115 PMCID: PMC7477555 DOI: 10.1038/s41523-020-00184-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 08/06/2020] [Indexed: 12/26/2022] Open
Abstract
Terminal duct lobular units (TDLUs) are the predominant anatomical structures where breast cancers originate. Having lesser degrees of age-related TDLU involution, measured as higher TDLUs counts or more epithelial TDLU substructures (acini), is related to increased breast cancer risk among women with benign breast disease (BBD). We evaluated whether a recently developed polygenic risk score (PRS) based on 313-common variants for breast cancer prediction is related to TDLU involution in the background, normal breast tissue, as this could provide mechanistic clues on the genetic predisposition to breast cancer. Among 1398 women without breast cancer, higher values of the PRS were significantly associated with higher TDLU counts (P = 0.004), but not with acini counts (P = 0.808), in histologically normal tissue samples from donors and diagnostic BBD biopsies. Mediation analysis indicated that TDLU counts may explain a modest proportion (≤10%) of the association of the 313-variant PRS with breast cancer risk. These findings suggest that TDLU involution might be an intermediate step in the association between common genetic variation and breast cancer risk.
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Affiliation(s)
- Clara Bodelon
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Hannah Oh
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
- Division of Health Policy and Management, College of Health Sciences, Korea University, Seoul, Korea
| | - Andriy Derkach
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Joshua N. Sampson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Brian L. Sprague
- University of Vermont College of Medicine and Vermont Cancer Center, Burlington, VT USA
| | - Pamela Vacek
- University of Vermont College of Medicine and Vermont Cancer Center, Burlington, VT USA
| | - Donald L. Weaver
- University of Vermont College of Medicine and Vermont Cancer Center, Burlington, VT USA
| | - Shaoqi Fan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Maya Palakal
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Daphne Papathomas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Jackie Xiang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Deesha A. Patel
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Laura Linville
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Susan E. Clare
- Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL USA
| | - Daniel W. Visscher
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN USA
| | - Carolyn Mies
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Stephen M. Hewitt
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, MD USA
| | - Louise A. Brinton
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Anna Maria V. Storniolo
- Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN USA
| | - Chunyan He
- Department Internal Medicine, Division of Medical Oncology, College of Medicine, University of Kentucky, Lexington, KY USA
- Markey Cancer Center, University of Kentucky, Lexington, KY USA
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | | | - Gretchen L. Gierach
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Jonine D. Figueroa
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
- Usher Institute of Population Health Sciences and Informatics and Cancer Research UK Edinburgh Centre, University of Edinburgh, Edinburgh, UK
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10
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Wetstein SC, Onken AM, Luffman C, Baker GM, Pyle ME, Kensler KH, Liu Y, Bakker B, Vlutters R, van Leeuwen MB, Collins LC, Schnitt SJ, Pluim JPW, Tamimi RM, Heng YJ, Veta M. Deep learning assessment of breast terminal duct lobular unit involution: Towards automated prediction of breast cancer risk. PLoS One 2020; 15:e0231653. [PMID: 32294107 PMCID: PMC7159218 DOI: 10.1371/journal.pone.0231653] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 03/27/2020] [Indexed: 02/07/2023] Open
Abstract
Terminal duct lobular unit (TDLU) involution is the regression of milk-producing structures in the breast. Women with less TDLU involution are more likely to develop breast cancer. A major bottleneck in studying TDLU involution in large cohort studies is the need for labor-intensive manual assessment of TDLUs. We developed a computational pathology solution to automatically capture TDLU involution measures. Whole slide images (WSIs) of benign breast biopsies were obtained from the Nurses' Health Study. A set of 92 WSIs was annotated for acini, TDLUs and adipose tissue to train deep convolutional neural network (CNN) models for detection of acini, and segmentation of TDLUs and adipose tissue. These networks were integrated into a single computational method to capture TDLU involution measures including number of TDLUs per tissue area, median TDLU span and median number of acini per TDLU. We validated our method on 40 additional WSIs by comparing with manually acquired measures. Our CNN models detected acini with an F1 score of 0.73±0.07, and segmented TDLUs and adipose tissue with Dice scores of 0.84±0.13 and 0.87±0.04, respectively. The inter-observer ICC scores for manual assessments on 40 WSIs of number of TDLUs per tissue area, median TDLU span, and median acini count per TDLU were 0.71, 0.81 and 0.73, respectively. Intra-observer reliability was evaluated on 10/40 WSIs with ICC scores of >0.8. Inter-observer ICC scores between automated results and the mean of the two observers were: 0.80 for number of TDLUs per tissue area, 0.57 for median TDLU span, and 0.80 for median acini count per TDLU. TDLU involution measures evaluated by manual and automated assessment were inversely associated with age and menopausal status. We developed a computational pathology method to measure TDLU involution. This technology eliminates the labor-intensiveness and subjectivity of manual TDLU assessment, and can be applied to future breast cancer risk studies.
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Affiliation(s)
- Suzanne C. Wetstein
- Medical Image Analysis Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Allison M. Onken
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Christina Luffman
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Gabrielle M. Baker
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Michael E. Pyle
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Kevin H. Kensler
- Division of Population Sciences, Dana Farber Cancer Institute, Boston, Massachusetts, United States of America
| | - Ying Liu
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine and Alvin J. Siteman Cancer Center, St Louis, Missouri, United States of America
| | - Bart Bakker
- Philips Research Europe, High Tech Campus, Eindhoven, The Netherlands
| | - Ruud Vlutters
- Philips Research Europe, High Tech Campus, Eindhoven, The Netherlands
| | | | - Laura C. Collins
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Stuart J. Schnitt
- Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Dana-Farber Cancer Institute-Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Josien P. W. Pluim
- Medical Image Analysis Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Rulla M. Tamimi
- Channing Division of Network Medicine, Department of Medicine, Harvard Medical School, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Yujing J. Heng
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Mitko Veta
- Medical Image Analysis Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
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11
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Relationship of Serum Progesterone and Progesterone Metabolites with Mammographic Breast Density and Terminal Ductal Lobular Unit Involution among Women Undergoing Diagnostic Breast Biopsy. J Clin Med 2020; 9:jcm9010245. [PMID: 31963437 PMCID: PMC7019918 DOI: 10.3390/jcm9010245] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 01/06/2020] [Accepted: 01/09/2020] [Indexed: 12/21/2022] Open
Abstract
The association of progesterone/progesterone metabolites with elevated mammographic breast density (MBD) and delayed age-related terminal duct lobular unit (TDLU) involution, strong breast cancer risk factors, has received limited attention. Using a reliable liquid chromatography-tandem mass-spectrometry assay, we quantified serum progesterone/progesterone metabolites and explored cross-sectional relationships with MBD and TDLU involution among women, ages 40–65, undergoing diagnostic breast biopsy. Quantitative MBD measures were estimated in pre-biopsy digital mammograms. TDLU involution was quantified in diagnostic biopsies. Adjusted partial correlations and trends across MBD/TDLU categories were calculated. Pregnenolone was positively associated with percent MBD-area (MBD-A, rho: 0.30; p-trend = 0.01) among premenopausal luteal phase women. Progesterone tended to be positively associated with percent MBD-A among luteal phase (rho: 0.26; p-trend = 0.07) and postmenopausal (rho: 0.17; p-trend = 0.04) women. Consistent with experimental data, implicating an elevated 5α-pregnanes/3α-dihydroprogesterone (5αP/3αHP) metabolite ratio in breast cancer, higher 5αP/3αHP was associated with elevated percent MBD-A among luteal phase (rho: 0.29; p-trend = 0.08), but not postmenopausal women. This exploratory analysis provided some evidence that endogenous progesterone and progesterone metabolites might be correlated with MBD, a strong breast cancer risk factor, in both pre- and postmenopausal women undergoing breast biopsy. Additional studies are needed to understand the role of progesterone/progesterone metabolites in breast tissue composition and breast cancer risk.
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12
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Involution of Breast Lobules, Mammographic Breast Density and Prognosis Among Tamoxifen-Treated Estrogen Receptor-Positive Breast Cancer Patients. J Clin Med 2019; 8:jcm8111868. [PMID: 31689948 PMCID: PMC6912285 DOI: 10.3390/jcm8111868] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 10/17/2019] [Accepted: 10/22/2019] [Indexed: 11/23/2022] Open
Abstract
Mammographic breast density (MD) reflects breast fibroglandular content. Its decline following adjuvant tamoxifen treated, estrogen receptor (ER)-positive breast cancer has been associated with improved outcomes. Breast cancers arise from structures termed lobules, and lower MD is associated with increased age-related lobule involution. We assessed whether pre-treatment involution influenced associations between MD decline and risk of breast cancer-specific death. ER-positive tamoxifen treated patients diagnosed at Kaiser Permanente Northwest (1990-2008) were defined as cases who died of breast cancer (n = 54) and matched controls (remained alive over similar follow-up; n = 180). Lobule involution was assessed by examining terminal duct lobular units (TDLUs) in benign tissues surrounding cancers as TDLU count/mm2, median span and acini count/TDLU. MD (%) was measured in the unaffected breast at baseline (median 6-months before) and follow-up (median 12-months after tamoxifen initiation). TDLU measures and baseline MD were positively associated among controls (p < 0.05). In multivariable regression models, MD decline (≥10%) was associated with reduced risk of breast cancer-specific death before (odds ratio (OR): 0.41, 95% CI: 0.18-0.92) and after (OR: 0.41, 95% CI: 0.18-0.94) adjustment for TDLU count/mm2, TDLU span (OR: 0.34, 95% CI: 0.14-0.84), and acini count/TDLU (OR: 0.33, 95% CI: 0.13-0.81). MD decline following adjuvant tamoxifen is associated with reduced risk of breast cancer-specific death, irrespective of pre-treatment lobule involution.
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13
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Association between mammographic density and tumor marker-defined breast cancer subtypes: a case-control study. Eur J Cancer Prev 2019; 27:239-247. [PMID: 28957821 DOI: 10.1097/cej.0000000000000353] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
High mammographic density (MD) is the most important risk factor for breast cancer. This study aimed to clarify the relationship between MD and breast cancer subtypes defined by tumor markers. We enrolled 642 women with breast cancer (69% premenopausal) and 1241 controls matched for age and menopausal status. Absolute mammographic dense area (ADA), percent mammographic dense area (PDA), and nondense area were assessed using a computer-assisted thresholding technique. We classified breast cancer cases into four subtypes using information on tumor marker expression such as estrogen receptor (ER), progesterone receptor (PR), and Cerb2 receptor (HER2); luminal A (ER+ and/or PR+, HER2-), luminal B (ER+ and/or PR+, HER2+), HER2-overexpressing (ER-, PR-, and HER2+), and triple-negative (ER-, PR-, and HER2-). Analysis was carried out using a conditional logistic regression model with adjustment for covariates. ADA and PDA were associated positively with the risk of breast cancer overall. Both ADA and PDA tended to have a positive association with breast cancer with any ER, any PR, or HER2-, but not for HER2+. The risk of luminal A breast cancer increased significantly 1.11 times (95% confidence interval: 1.01-1.23) for ADA and 1.12 times (95% confidence interval: 1.01-1.24) for PDA, estimated per 1 SD of the age and BMI-adjusted MD. However, the risk of breast cancer with luminal B, HER2-overexpressing, and triple-negative subtypes did not differ (P>0.10). Differential associations between MD measures and breast cancer by tumor marker status or tumor marker-defined subtypes were not detected. These findings suggested that the association between MD and breast cancer subtype may be because of other causal pathways.
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14
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Clinical subtypes and prognosis in breast cancer according to parity: a nationwide study in Korean Breast Cancer Society. Breast Cancer Res Treat 2018; 173:679-691. [DOI: 10.1007/s10549-018-5032-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 10/27/2018] [Indexed: 12/20/2022]
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15
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Chollet-Hinton L, Puvanesarajah S, Sandhu R, Kirk EL, Midkiff BR, Ghosh K, Brandt KR, Scott CG, Gierach GL, Sherman ME, Vachon CM, Troester MA. Stroma modifies relationships between risk factor exposure and age-related epithelial involution in benign breast. Mod Pathol 2018; 31:1085-1096. [PMID: 29463881 PMCID: PMC6076344 DOI: 10.1038/s41379-018-0033-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Revised: 01/03/2018] [Accepted: 01/03/2018] [Indexed: 12/01/2022]
Abstract
Delayed age-related lobular involution has been previously associated with elevated breast cancer risk. However, intraindividual variability in epithelial involution status within a woman is undefined. We developed a novel measure of age-related epithelial involution, density of epithelial nuclei in epithelial areas using digital image analysis in combination with stromal characteristics (percentage of section area comprising stroma). Approximately 1800 hematoxylin and eosin stained sections of benign breast tissue were evaluated from 416 participants having breast surgery for cancer or benign conditions. Two to sixteen slides per woman from different regions of the breast were studied. Epithelial involution status varied within a woman and as a function of stromal area. Percentage stromal area varied between samples from the same woman (median difference between highest and lowest stromal area within a woman was 7.5%, but ranged from 0.01 to 86.7%). Restricting to women with at least 10% stromal area (N = 317), epithelial nuclear density decreased with age (-637.1 cells/mm2 per decade of life after age 40, p < 0.0001), increased with mammographic density (457.8 cells/mm2 per increasing BI-RADs density category p = 0.002), and increased non-significantly with recent parity, later age at first pregnancy, and longer and more recent oral contraceptive use. These associations were attenuated in women with mostly fat samples (<10% stroma (N = 99)). Thirty-one percent of women evaluated had both adequate stroma (≥10%) and mostly fat (<10% stroma) regions of breast tissue, with the probability of having both types increasing with the number breast tissue samplings. Several breast cancer risk factors are associated with elevated age-related epithelial content, but associations depend upon stromal context. Stromal characteristics appear to modify relationships between risk factor exposures and breast epithelial involution.
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Affiliation(s)
| | | | - Rupninder Sandhu
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC
| | - Erin L. Kirk
- Department of Epidemiology, University of North Carolina at Chapel Hill, NC
| | - Bentley R. Midkiff
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC
| | - Karthik Ghosh
- Department of Internal Medicine, Mayo Clinic College of Medicine, Rochester, MN
| | | | - Christopher G. Scott
- Division of Biostatistics, Department of Health Sciences, Mayo Clinic College of Medicine, Rochester, MN
| | - Gretchen L. Gierach
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Mark E. Sherman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Celine M. Vachon
- Division of Epidemiology, Department of Health Sciences, Mayo Clinic College of Medicine, Rochester, MN
| | - Melissa A. Troester
- Department of Epidemiology, University of North Carolina at Chapel Hill, NC,Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC,Department of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, NC
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16
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Quantification of Estrogen Receptor Expression in Normal Breast Tissue in Postmenopausal Women With Breast Cancer and Association With Tumor Subtypes. Appl Immunohistochem Mol Morphol 2017; 25:548-552. [DOI: 10.1097/pai.0000000000000337] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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17
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Guo C, Sung H, Zheng S, Guida J, Li E, Li J, Hu N, Deng J, Figueroa JD, Sherman ME, Gierach GL, Lu N, Yang XR. Age-related terminal duct lobular unit involution in benign tissues from Chinese breast cancer patients with luminal and triple-negative tumors. Breast Cancer Res 2017; 19:61. [PMID: 28545469 PMCID: PMC5445352 DOI: 10.1186/s13058-017-0850-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Accepted: 05/02/2017] [Indexed: 01/20/2023] Open
Abstract
Background Terminal duct lobular unit (TDLU) involution is a physiological process of breast tissue aging characterized by a reduction in the epithelial component. In studies of women with benign breast disease, researchers have found that age-matched women with lower levels of TDLU involution are at increased risk of developing breast cancer. We previously showed that breast cancer cases with core basal phenotype (CBP; estrogen receptor negative [ER−], progesterone receptor-negative [PR−], human epidermal growth factor receptor 2-negative [HER2−], cytokeratins (CK 5 or CK5/6)-positive [CK5/6+] and/or epidermal growth factor receptor-positive [EGFR+]) tumors had significantly reduced TDLU involution compared with cases with luminal A (ER+ and/or PR+, HER2−, CK5/6−, EGFR−) tumors from a population-based case-control study in Poland. We evaluated the association of TDLU involution with tumor subtypes in an independent population of women in China, where the breast cancer incidence rate, prevalence of known risk factors, and mammographic breast density are thought to be markedly different from those of Polish women. Methods We performed morphometric assessment of TDLUs by using three reproducible semiquantitative measures that inversely correlate with TDLU involution (TDLU count/100 mm2, TDLU span in micrometer, and acini count/TDLU) by examining benign tissue blocks from 254 age-matched luminal A and 250 triple-negative (TN; ER−, PR−, HER2−, including 125 CBP) breast cancer cases treated in a tertiary hospital in Beijing, China. Results Overall, we found that TN and particularly CBP cases tended to have greater TDLU measures (less involution) than luminal A cases in logistic regression models accounting for age, body mass index, parity, and tumor grade. The strongest association was observed for tertiles of acini count among younger women (aged <50 years) (CBP vs. luminal A; ORtrend 2.11, 95% CI 1.22–3.67, P = 0.008). Conclusions These data extend previous findings that TN/CBP breast cancers are associated with reduced TDLU involution in surrounding breast parenchyma compared with luminal A cases among Chinese women, providing further support for differences in the pathogenesis of these tumor subtypes. Electronic supplementary material The online version of this article (doi:10.1186/s13058-017-0850-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Changyuan Guo
- National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hyuna Sung
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Shan Zheng
- National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jennifer Guida
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Erni Li
- National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jing Li
- National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Nan Hu
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Joseph Deng
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jonine D Figueroa
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.,Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK
| | - Mark E Sherman
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.,Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA
| | - Gretchen L Gierach
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ning Lu
- National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaohong R Yang
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
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Ma H, Ursin G, Xu X, Lee E, Togawa K, Duan L, Lu Y, Malone KE, Marchbanks PA, McDonald JA, Simon MS, Folger SG, Sullivan-Halley J, Deapen DM, Press MF, Bernstein L. Reproductive factors and the risk of triple-negative breast cancer in white women and African-American women: a pooled analysis. Breast Cancer Res 2017; 19:6. [PMID: 28086982 PMCID: PMC5237290 DOI: 10.1186/s13058-016-0799-9] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2016] [Accepted: 12/22/2016] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Early age at menarche, nulliparity, late age at first completed pregnancy, and never having breastfed, are established breast cancer risk factors. However, among breast cancer subtypes, it remains unclear whether all of these are risk factors for triple-negative breast cancer (TNBC). METHODS We evaluated the associations of these reproductive factors with TNBC, in 2658 patients with breast cancer (including 554 with TNBC) and 2448 controls aged 20-64 years, who participated in one of the three population-based case-control studies: the Women's Contraceptive and Reproductive Experiences Study, the Women's Breast Carcinoma in situ Study, or the Women's Learning the Influence of Family and Environment Study. We used multivariable polychotomous unconditional logistic regression methods to conduct case-control comparisons among breast cancer subtypes defined by estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2 expression status. RESULTS TNBC risk decreased with increasing duration of breastfeeding (P trend = 0.006), but age at menarche, age at first completed pregnancy, and nulliparity were not associated with risk of TNBC. Parous women who breastfed for at least one year had a 31% lower risk of TNBC than parous women who had never breastfed (odds ratio, OR = 0.69; 95% confidence interval, CI = 0.50-0.96). The association between breastfeeding and risk of TNBC was modified by age and race. Parous African-American women aged 20-44 years who breastfed for 6 months or longer had an 82% lower risk of TNBC than their counterparts who had never breastfed (OR = 0.18, 95% CI = 0.07-0.46). CONCLUSIONS Our data indicate that breastfeeding decreases the risk of TNBC, especially for younger African-American women.
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Affiliation(s)
- Huiyan Ma
- Department of Population Sciences, Beckman Research Institute, 1500 East Duarte Rd. Duarte, City of Hope, CA 91010 USA
| | - Giske Ursin
- Cancer Registry of Norway, Oslo, Norway
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Xinxin Xu
- Department of Population Sciences, Beckman Research Institute, 1500 East Duarte Rd. Duarte, City of Hope, CA 91010 USA
| | - Eunjung Lee
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033 USA
| | - Kayo Togawa
- Department of Population Sciences, Beckman Research Institute, 1500 East Duarte Rd. Duarte, City of Hope, CA 91010 USA
- Section of Environment and Radiation, International Agency for Research on Cancer, Lyon, France
| | - Lei Duan
- Department of Population Sciences, Beckman Research Institute, 1500 East Duarte Rd. Duarte, City of Hope, CA 91010 USA
- School of Social Work, University of Southern California, Los Angeles, CA 90033 USA
| | - Yani Lu
- Department of Population Sciences, Beckman Research Institute, 1500 East Duarte Rd. Duarte, City of Hope, CA 91010 USA
| | - Kathleen E. Malone
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109 USA
| | - Polly A. Marchbanks
- Division of Reproductive Health, Centers for Disease Control and Prevention, Atlanta, GA 30333 USA
| | - Jill A. McDonald
- College of Health and Social Services, New Mexico State University, Las Cruces, NM 88003 USA
| | - Michael S. Simon
- Karmanos Cancer Institute, Department of Oncology, Wayne State University, Detroit, MI 48201 USA
| | - Suzanne G. Folger
- Division of Reproductive Health, Centers for Disease Control and Prevention, Atlanta, GA 30333 USA
| | - Jane Sullivan-Halley
- Department of Population Sciences, Beckman Research Institute, 1500 East Duarte Rd. Duarte, City of Hope, CA 91010 USA
| | - Dennis M. Deapen
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033 USA
| | - Michael F. Press
- Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033 USA
| | - Leslie Bernstein
- Department of Population Sciences, Beckman Research Institute, 1500 East Duarte Rd. Duarte, City of Hope, CA 91010 USA
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Relationship of Predicted Risk of Developing Invasive Breast Cancer, as Assessed with Three Models, and Breast Cancer Mortality among Breast Cancer Patients. PLoS One 2016; 11:e0160966. [PMID: 27560501 PMCID: PMC4999085 DOI: 10.1371/journal.pone.0160966] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2016] [Accepted: 07/27/2016] [Indexed: 11/19/2022] Open
Abstract
PURPOSE Breast cancer risk prediction models are used to plan clinical trials and counsel women; however, relationships of predicted risks of breast cancer incidence and prognosis after breast cancer diagnosis are unknown. METHODS Using largely pre-diagnostic information from the Breast Cancer Surveillance Consortium (BCSC) for 37,939 invasive breast cancers (1996-2007), we estimated 5-year breast cancer risk (<1%; 1-1.66%; ≥1.67%) with three models: BCSC 1-year risk model (BCSC-1; adapted to 5-year predictions); Breast Cancer Risk Assessment Tool (BCRAT); and BCSC 5-year risk model (BCSC-5). Breast cancer-specific mortality post-diagnosis (range: 1-13 years; median: 5.4-5.6 years) was related to predicted risk of developing breast cancer using unadjusted Cox proportional hazards models, and in age-stratified (35-44; 45-54; 55-69; 70-89 years) models adjusted for continuous age, BCSC registry, calendar period, income, mode of presentation, stage and treatment. Mean age at diagnosis was 60 years. RESULTS Of 6,021 deaths, 2,993 (49.7%) were ascribed to breast cancer. In unadjusted case-only analyses, predicted breast cancer risk ≥1.67% versus <1.0% was associated with lower risk of breast cancer death; BCSC-1: hazard ratio (HR) = 0.82 (95% CI = 0.75-0.90); BCRAT: HR = 0.72 (95% CI = 0.65-0.81) and BCSC-5: HR = 0.84 (95% CI = 0.75-0.94). Age-stratified, adjusted models showed similar, although mostly non-significant HRs. Among women ages 55-69 years, HRs approximated 1.0. Generally, higher predicted risk was inversely related to percentages of cancers with unfavorable prognostic characteristics, especially among women 35-44 years. CONCLUSIONS Among cases assessed with three models, higher predicted risk of developing breast cancer was not associated with greater risk of breast cancer death; thus, these models would have limited utility in planning studies to evaluate breast cancer mortality reduction strategies. Further, when offering women counseling, it may be useful to note that high predicted risk of developing breast cancer does not imply that if cancer develops it will behave aggressively.
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Figueroa JD, Pfeiffer RM, Brinton LA, Palakal MM, Degnim AC, Radisky D, Hartmann LC, Frost MH, Stallings Mann ML, Papathomas D, Gierach GL, Hewitt SM, Duggan MA, Visscher D, Sherman ME. Standardized measures of lobular involution and subsequent breast cancer risk among women with benign breast disease: a nested case-control study. Breast Cancer Res Treat 2016; 159:163-72. [PMID: 27488681 DOI: 10.1007/s10549-016-3908-7] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2015] [Accepted: 07/11/2016] [Indexed: 01/21/2023]
Abstract
Lesser degrees of terminal duct-lobular unit (TDLU) involution predict higher breast cancer risk; however, standardized measures to quantitate levels of TDLU involution have only recently been developed. We assessed whether three standardized measures of TDLU involution, with high intra/inter pathologist reproducibility in normal breast tissue, predict subsequent breast cancer risk among women in the Mayo benign breast disease (BBD) cohort. We performed a masked evaluation of biopsies from 99 women with BBD who subsequently developed breast cancer (cases) after a median of 16.9 years and 145 age-matched controls. We assessed three metrics inversely related to TDLU involution: TDLU count/mm(2), median TDLU span (microns, which approximates acini content), and median category of acini counts/TDLU (0-10; 11-20; 21-30; 31-50; >50). Associations with subsequent breast cancer risk for quartiles (or categories of acini counts) of each of these measures were assessed with multivariable conditional logistic regression to estimate odds ratios (ORs) and 95 % confidence intervals (CI). In multivariable models, women in the highest quartile compared to the lowest quartiles of TDLU counts and TDLU span measures were significantly associated with subsequent breast cancer diagnoses; TDLU counts quartile4 versus quartile1, OR = 2.44, 95 %CI 0.96-6.19, p-trend = 0.02; and TDLU spans, quartile4 versus quartile1, OR = 2.83, 95 %CI = 1.13-7.06, p-trend = 0.03. Significant associations with categorical measures of acini counts/TDLU were also observed: compared to women with median category of <10 acini/TDLU, women with >25 acini counts/TDLU were at significantly higher risk, OR = 3.40, 95 %CI 1.03-11.17, p-trend = 0.032. Women with TDLU spans and TDLU count measures above the median were at further increased risk, OR = 3.75 (95 %CI 1.40-10.00, p-trend = 0.008), compared with women below the median for both of these metrics. Similar results were observed for combinatorial metrics of TDLU acini counts/TDLU, and TDLU count. Standardized quantitative measures of TDLU counts and acini counts approximated by TDLU span measures or visually assessed in categories are independently associated with breast cancer risk. Visual assessment of TDLU numbers and acini content, which are highly reproducible between pathologists, could help identify women at high risk for subsequent breast cancer among the million women diagnosed annually with BBD in the US.
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Affiliation(s)
- Jonine D Figueroa
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA. .,Medical School, The Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK.
| | - Ruth M Pfeiffer
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Louise A Brinton
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Maya M Palakal
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | | | | | | | | | | | - Daphne Papathomas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Gretchen L Gierach
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Stephen M Hewitt
- Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Maire A Duggan
- Department of Pathology and Laboratory Medicine, University of Calgary, Calgary, AB, Canada
| | | | - Mark E Sherman
- Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA
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Reproductive behaviors and risk of developing breast cancer according to tumor subtype: A systematic review and meta-analysis of epidemiological studies. Cancer Treat Rev 2016; 49:65-76. [PMID: 27529149 DOI: 10.1016/j.ctrv.2016.07.006] [Citation(s) in RCA: 147] [Impact Index Per Article: 18.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2016] [Revised: 07/19/2016] [Accepted: 07/21/2016] [Indexed: 11/20/2022]
Abstract
BACKGROUND Breast cancer is composed of distinct subtypes defined mainly based on the expression of hormone receptors (HR) and HER2. For years, reproductive factors were shown to impact breast cancer risk but it is unclear whether this differs according to tumor subtype. In this meta-analysis we evaluated the association between parity, age at first birth, breastfeeding and the risk of developing breast cancer according to tumor subtype. METHODS PubMed and Embase were searched to identify epidemiological studies that evaluated the impact of parity and/or age at first birth and/or breastfeeding on breast cancer risk with available information on HR and HER2. Tumor subtypes were defined as: luminal (HR-positive, HER2-negative or HER2-positive), HER2 (HR-negative, HER2-positive) and triple-negative (HR-negative, HER2-negative). Summary risk estimates (pooled OR [pOR]) and 95% confidence intervals (CI) were calculated using random effects models. The MOOSE guidelines were applied. RESULTS This meta-analysis evaluated 15 studies, including 21,941 breast cancer patients and 864,177 controls. Parity was associated with a 25% reduced risk of developing luminal subtype (pOR 0.75; 95% CI, 0.70-0.81; p<0.0001). Advanced age at first birth was associated with an increased risk of developing luminal subtype (pOR 1.15; 95% CI, 1.00-1.32; p=0.05). Ever breastfeeding was associated with a reduced risk of developing both luminal (pOR 0.77; 95% CI, 0.66-0.88; p=0.003) and triple-negative (pOR 0.79, 95% CI, 0.66-0.94; p=0.01) subtypes. CONCLUSIONS The reproductive behaviors impact the risk of developing breast cancer but this varies according to subtype.
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Relation of Serum Estrogen Metabolites with Terminal Duct Lobular Unit Involution Among Women Undergoing Diagnostic Image-Guided Breast Biopsy. Discov Oncol 2016; 7:305-315. [PMID: 27138982 DOI: 10.1007/s12672-016-0265-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2016] [Accepted: 04/19/2016] [Indexed: 12/11/2022] Open
Abstract
Higher levels of circulating estrogens and estrogen metabolites (EMs) have been associated with higher breast cancer risk. In breast tissues, reduced levels of terminal duct lobular unit (TDLU) involution, as reflected by higher numbers of TDLUs and acini per TDLU, have also been linked to elevated breast cancer risk. However, it is unknown whether reduced TDLU involution mediates the risk associated with circulating EMs. In a cross-sectional analysis of 94 premenopausal and 92 postmenopausal women referred for clinical breast biopsy at an academic facility in Vermont, we examined the associations of 15 EMs, quantified using liquid chromatography-tandem mass spectrometry, with the number of TDLUs and acini count/TDLU using zero-inflated Poisson regression with a robust variance estimator and ordinal logistic regression models, respectively. All analyses were stratified by menopausal status and adjusted for potential confounders. Among premenopausal women, comparing the highest vs. the lowest tertiles, levels of unconjugated estradiol (risk ratio (RR) = 1.74, 95 % confidence interval (CI) = 1.06-2.87, p trend = 0.03), 2-hydroxyestrone (RR = 1.74, 95 % CI = 1.01-3.01, p trend = 0.04), and 4-hydroxyestrone (RR = 1.74, 95 % CI = 0.99-3.06, p trend = 0.04) were associated with significantly higher TDLU count. Among postmenopausal women, higher levels of estradiol (RR = 2.09, 95 % CI = 1.01-4.30, p trend = 0.04) and 16α-hydroxyestrone (RR = 2.27, 95 % CI = 1.29-3.99, p trend = 0.02) were significantly associated with higher TDLU count. Among postmenopausal women, higher levels of EMs, specifically conjugated estrone and 2- and 4-pathway catechols, were also associated with higher acini count/TDLU. Our data suggest that higher levels of serum EMs are generally associated with lower levels of TDLU involution.
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23
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Physical activity, mammographic density, and age-related lobular involution among premenopausal and postmenopausal women. Menopause 2016; 22:964-75. [PMID: 25710783 DOI: 10.1097/gme.0000000000000433] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
OBJECTIVE Physical activity may protect against breast cancer by modulating breast tissue composition. We evaluated the association of physical activity with two visual assessments of breast tissue composition-percentage of mammographic density (a radiologic observation) and age-related lobular involution (a histologic assessment). METHODS Among 164 premenopausal and postmenopausal women with breast cancer, physical activity (household, occupational, and recreational) performed during the year preceding the diagnosis was evaluated using a validated questionnaire. Percentage of mammographic density was assessed in the contralateral breast by a computer-assisted method. Age-related lobular involution was assessed in normal breast tissue on H&E-stained slides. Multivariate generalized linear models were used to assess associations by quartiles of physical activity. RESULTS Overall, we observed no significant association between total physical activity and percentage of mammographic density or degree of lobular involution. However, occupational physical activity was significantly positively associated with the predominant type I/no type III lobules among premenopausal women (last quartile: prevalence ratio [PR], 5.92; P(trend )= 0.04). Although total physical activity was positively associated with the predominant type I/no type III lobules among premenopausal women (last quartile: PR, 2.61; P(trend) = 0.08), an inverse association was observed among postmenopausal women (last quartile: PR, 0.44; P(trend) = 0.01). Higher levels of household physical activity were significantly associated with higher prevalence of lower mammographic density and complete involution among postmenopausal women (last quartile: PR, 1.21; P(trend) = 0.01). CONCLUSIONS Physical activity may be associated with less dense and more involuted breasts. Physical activity's effect on mammographic density or age-related lobular involution may mediate, in part, its protective effect against breast cancer.
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Gierach GL, Patel DA, Pfeiffer RM, Figueroa JD, Linville L, Papathomas D, Johnson JM, Chicoine RE, Herschorn SD, Shepherd JA, Wang J, Malkov S, Vacek PM, Weaver DL, Fan B, Mahmoudzadeh AP, Palakal M, Xiang J, Oh H, Horne HN, Sprague BL, Hewitt SM, Brinton LA, Sherman ME. Relationship of Terminal Duct Lobular Unit Involution of the Breast with Area and Volume Mammographic Densities. Cancer Prev Res (Phila) 2015; 9:149-58. [PMID: 26645278 DOI: 10.1158/1940-6207.capr-15-0282] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2015] [Accepted: 11/17/2015] [Indexed: 01/05/2023]
Abstract
Elevated mammographic density (MD) is an established breast cancer risk factor. Reduced involution of terminal duct lobular units (TDLU), the histologic source of most breast cancers, has been associated with higher MD and breast cancer risk. We investigated relationships of TDLU involution with area and volumetric MD, measured throughout the breast and surrounding biopsy targets (perilesional). Three measures inversely related to TDLU involution (TDLU count/mm(2), median TDLU span, median acini count/TDLU) assessed in benign diagnostic biopsies from 348 women, ages 40-65, were related to MD area (quantified with thresholding software) and volume (assessed with a density phantom) by analysis of covariance, stratified by menopausal status and adjusted for confounders. Among premenopausal women, TDLU count was directly associated with percent perilesional MD (P trend = 0.03), but not with absolute dense area/volume. Greater TDLU span was associated with elevated percent dense area/volume (P trend<0.05) and absolute perilesional MD (P = 0.003). Acini count was directly associated with absolute perilesional MD (P = 0.02). Greater TDLU involution (all metrics) was associated with increased nondense area/volume (P trend ≤ 0.04). Among postmenopausal women, TDLU measures were not significantly associated with MD. Among premenopausal women, reduced TDLU involution was associated with higher area and volumetric MD, particularly in perilesional parenchyma. Data indicating that TDLU involution and MD are correlated markers of breast cancer risk suggest that associations of MD with breast cancer may partly reflect amounts of at-risk epithelium. If confirmed, these results could suggest a prevention paradigm based on enhancing TDLU involution and monitoring efficacy by assessing MD reduction.
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Affiliation(s)
- Gretchen L Gierach
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
| | - Deesha A Patel
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Ruth M Pfeiffer
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Jonine D Figueroa
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Laura Linville
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Daphne Papathomas
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Jason M Johnson
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | - John A Shepherd
- University of California, San Francisco, San Francisco, California
| | - Jeff Wang
- University of California, San Francisco, San Francisco, California
| | - Serghei Malkov
- University of California, San Francisco, San Francisco, California
| | | | | | - Bo Fan
- University of California, San Francisco, San Francisco, California
| | | | - Maya Palakal
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Jackie Xiang
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Hannah Oh
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Hisani N Horne
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | | | - Stephen M Hewitt
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Louise A Brinton
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Mark E Sherman
- Breast and Gynecologic Cancer Research Group, Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
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Sandhu R, Chollet-Hinton L, Kirk EL, Midkiff B, Troester MA. Digital histologic analysis reveals morphometric patterns of age-related involution in breast epithelium and stroma. Hum Pathol 2015; 48:60-8. [PMID: 26772400 DOI: 10.1016/j.humpath.2015.09.031] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2015] [Revised: 09/11/2015] [Accepted: 09/23/2015] [Indexed: 12/29/2022]
Abstract
Complete age-related regression of mammary epithelium, often termed postmenopausal involution, is associated with decreased breast cancer risk. However, most studies have qualitatively assessed involution. We quantitatively analyzed epithelium, stroma, and adipose tissue from histologically normal breast tissue of 454 patients in the Normal Breast Study. High-resolution digital images of normal breast hematoxylin and eosin-stained slides were partitioned into epithelium, adipose tissue, and nonfatty stroma. Percentage area and nuclei per unit area (nuclear density) were calculated for each component. Quantitative data were evaluated in association with age using linear regression and cubic spline models. Stromal area decreased (P = 0.0002), and adipose tissue area increased (P < 0.0001), with an approximate 0.7% change in area for each component, until age 55 years when these area measures reached a steady state. Although epithelial area did not show linear changes with age, epithelial nuclear density decreased linearly beginning in the third decade of life. No significant age-related trends were observed for stromal or adipose nuclear density. Digital image analysis offers a high-throughput method for quantitatively measuring tissue morphometry and for objectively assessing age-related changes in adipose tissue, stroma, and epithelium. Epithelial nuclear density is a quantitative measure of age-related breast involution that begins to decline in the early premenopausal period.
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Affiliation(s)
- Rupninder Sandhu
- UNC Lineberger Comprehensive Cancer Center, Chapel Hill, NC, 27599
| | - Lynn Chollet-Hinton
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599
| | - Erin L Kirk
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599
| | - Bentley Midkiff
- Department of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, NC, 27599
| | - Melissa A Troester
- UNC Lineberger Comprehensive Cancer Center, Chapel Hill, NC, 27599; Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599; Department of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, NC, 27599.
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Casbas-Hernandez P, Sun X, Roman-Perez E, D'Arcy M, Sandhu R, Hishida A, McNaughton KK, Yang XR, Makowski L, Sherman ME, Figueroa JD, Troester MA. Tumor intrinsic subtype is reflected in cancer-adjacent tissue. Cancer Epidemiol Biomarkers Prev 2014; 24:406-14. [PMID: 25465802 DOI: 10.1158/1055-9965.epi-14-0934] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
INTRODUCTION Overall survival of early-stage breast cancer patients is similar for those who undergo breast-conserving therapy (BCT) and mastectomy; however, 10% to 15% of women undergoing BCT suffer ipsilateral breast tumor recurrence. The risk of recurrence may vary with breast cancer subtype. Understanding the gene expression of the cancer-adjacent tissue and the stromal response to specific tumor subtypes is important for developing clinical strategies to reduce recurrence risk. METHODS We utilized two independent datasets to study gene expression data in cancer-adjacent tissue from invasive breast cancer patients. Complementary in vitro cocultures were used to study cell-cell communication between fibroblasts and specific breast cancer subtypes. RESULTS Our results suggest that intrinsic tumor subtypes are reflected in histologically normal cancer-adjacent tissue. Gene expression of cancer-adjacent tissues shows that triple-negative (Claudin-low or basal-like) tumors exhibit increased expression of genes involved in inflammation and immune response. Although such changes could reflect distinct immune populations present in the microenvironment, altered immune response gene expression was also observed in cocultures in the absence of immune cell infiltrates, emphasizing that these inflammatory mediators are secreted by breast-specific cells. In addition, although triple-negative breast cancers are associated with upregulated immune response genes, luminal breast cancers are more commonly associated with estrogen-response pathways in adjacent tissues. CONCLUSIONS Specific characteristics of breast cancers are reflected in the surrounding histologically normal tissue. This commonality between tumor and cancer-adjacent tissue may underlie second primaries and local recurrences. IMPACT Biomarkers derived from cancer-adjacent tissue may be helpful in defining personalized surgical strategies or in predicting recurrence risk.
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Affiliation(s)
- Patricia Casbas-Hernandez
- Department of Pathology and Laboratory Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Xuezheng Sun
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Erick Roman-Perez
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Monica D'Arcy
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Rupninder Sandhu
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Asahi Hishida
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Kirk K McNaughton
- Department of Physiology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Xiaohong R Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville, Maryland
| | - Liza Makowski
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Mark E Sherman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville, Maryland
| | - Jonine D Figueroa
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville, Maryland
| | - Melissa A Troester
- Department of Pathology and Laboratory Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
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Figueroa JD, Pfeiffer RM, Patel DA, Linville L, Brinton LA, Gierach GL, Yang XR, Papathomas D, Visscher D, Mies C, Degnim AC, Anderson WF, Hewitt S, Khodr ZG, Clare SE, Storniolo AM, Sherman ME. Terminal duct lobular unit involution of the normal breast: implications for breast cancer etiology. J Natl Cancer Inst 2014; 106:dju286. [PMID: 25274491 DOI: 10.1093/jnci/dju286] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Greater degrees of terminal duct lobular unit (TDLU) involution have been linked to lower breast cancer risk; however, factors that influence this process are poorly characterized. METHODS To study this question, we developed three reproducible measures that are inversely associated with TDLU involution: TDLU counts, median TDLU span, and median acini counts/TDLU. We determined factors associated with TDLU involution using normal breast tissues from 1938 participants (1369 premenopausal and 569 postmenopausal) ages 18 to 75 years in the Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center. Multivariable zero-inflated Poisson models were used to estimate relative risks (RRs) and 95% confidence intervals (95% CIs) for factors associated with TDLU counts, and multivariable ordinal logistic regression models were used to estimate odds ratios (ORs) and 95% CIs for factors associated with categories of median TDLU span and acini counts/TDLU. RESULTS All TDLU measures started declining in the third age decade (all measures, two-sided P trend ≤ .001); and all metrics were statistically significantly lower among postmenopausal women. Nulliparous women demonstrated lower TDLU counts compared with uniparous women (among premenopausal women, RR = 0.79, 95% CI = 0.73 to 0.85; among postmenopausal, RR = 0.67, 95% CI = 0.56 to 0.79); however, rates of age-related TDLU decline were faster among parous women. Other factors were related to specific measures of TDLU involution. CONCLUSION Morphometric analysis of TDLU involution warrants further evaluation to understand the pathogenesis of breast cancer and assessing its role as a progression marker for women with benign biopsies or as an intermediate endpoint in prevention studies.
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Affiliation(s)
- Jonine D Figueroa
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS).
| | - Ruth M Pfeiffer
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Deesha A Patel
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Laura Linville
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Louise A Brinton
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Gretchen L Gierach
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Xiaohong R Yang
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Daphne Papathomas
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Daniel Visscher
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Carolyn Mies
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Amy C Degnim
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - William F Anderson
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Stephen Hewitt
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Zeina G Khodr
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Susan E Clare
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Anna Maria Storniolo
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
| | - Mark E Sherman
- Division of Cancer Epidemiology and Genetics (JDF, RMP, DAP, LL, LAB, GLG, XRY, DP, WFA, ZGK, MES), Laboratory of Pathology (SH), and Division of Cancer Prevention (MES), National Cancer Institute, Bethesda, MD; Mayo Clinic Cancer Center, Rochester, MN (DV, ACD); Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA (CM); Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL (SEC); Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN (AMS)
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Sun X, Sandhu R, Figueroa JD, Gierach GL, Sherman ME, Troester MA. Benign breast tissue composition in breast cancer patients: association with risk factors, clinical variables, and gene expression. Cancer Epidemiol Biomarkers Prev 2014; 23:2810-8. [PMID: 25249325 DOI: 10.1158/1055-9965.epi-14-0507] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Breast tissue composition (epithelium, non-fatty stroma, and adipose) changes qualitatively and quantitatively throughout the lifespan, and may mediate relationships between risk factors and breast cancer initiation. We sought to identify relationships between tissue composition, risk factors, tumor characteristics, and gene expression. METHODS Participants were 146 patients from the Polish Breast Cancer Study, with data on risk factor and clinicopathological characteristics. Benign breast tissue composition was evaluated using digital image analysis of histologic sections. Whole-genome microarrays were performed on the same tissue blocks. RESULTS Mean epithelial, non-fatty stromal, and adipose proportions were 8.4% (SD = 4.9%), 27.7% (SD = 24.0%), and 64.0% (SD = 24.0%), respectively. Among women <50 years old, stroma proportion decreased and adipose proportion increased with age, with approximately 2% difference per year (P < 0.01). The variation in epithelial proportion with age was modest (0.1% per year). Higher epithelial proportion was associated with obesity (7.6% in nonobese vs. 10.1% in obese; P = 0.02) and with poorly differentiated tumors (7.8% in well/moderate vs. 9.9% in poor; P = 0.05). Gene expression signatures associated with epithelial and stromal proportion were identified and validated. Stroma-associated genes were in metabolism and stem cell maintenance pathways, whereas epithelial genes were enriched for cytokine and immune response pathways. CONCLUSIONS Breast tissue composition was associated with age, body mass index, and tumor grade, with consequences for breast gene expression. IMPACT Breast tissue morphologic factors may influence breast cancer etiology. Composition and gene expression may act as biomarkers of breast cancer risk and progression.
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Affiliation(s)
| | - Rupninder Sandhu
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Jonine D Figueroa
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, and
| | - Gretchen L Gierach
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, and
| | - Mark E Sherman
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, and Breast and Gynecologic Cancer Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland
| | - Melissa A Troester
- Department of Epidemiology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
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Razzaghi H, Troester MA, Gierach GL, Olshan AF, Yankaskas BC, Millikan RC. Association between mammographic density and basal-like and luminal A breast cancer subtypes. Breast Cancer Res 2014; 15:R76. [PMID: 24008056 PMCID: PMC3978452 DOI: 10.1186/bcr3470] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2013] [Accepted: 07/18/2013] [Indexed: 12/19/2022] Open
Abstract
Introduction Mammographic density is a strong risk factor for breast cancer overall, but few studies have examined the association between mammographic density and specific subtypes of breast cancer, especially aggressive basal-like breast cancers. Because basal-like breast cancers are less frequently screen-detected, it is important to understand how mammographic density relates to risk of basal-like breast cancer. Methods We estimated associations between mammographic density and breast cancer risk according to breast cancer subtype. Cases and controls were participants in the Carolina Breast Cancer Study (CBCS) who also had mammograms recorded in the Carolina Mammography Registry (CMR). A total of 491 cases had mammograms within five years prior to and one year after diagnosis and 528 controls had screening or diagnostic mammograms close to the dates of selection into CBCS. Mammographic density was reported to the CMR using Breast Imaging Reporting and Data System categories. The expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 1 and 2 (HER1 and HER2), and cytokeratin 5/6 (CK5/6) were assessed by immunohistochemistry and dichotomized as positive or negative, with ER+ and/or PR+, and HER2- tumors classified as luminal A and ER-, PR-, HER2-, HER1+ and/or CK5/6+ tumors classified as basal-like breast cancer. Triple negative tumors were defined as negative for ER, PR and HER2. Of the 491 cases 175 were missing information on subtypes; the remaining cases included 181 luminal A, 17 luminal B, 48 basal-like, 29 ER-/PR-/HER2+, and 41 unclassified subtypes. Odds ratios comparing each subtype to all controls and case-case odds ratios comparing mammographic density distributions in basal-like to luminal A breast cancers were estimated using logistic regression. Results Mammographic density was associated with increased risk of both luminal A and basal-like breast cancers, although estimates were imprecise. The magnitude of the odds ratio associated with mammographic density was not substantially different between basal-like and luminal A cancers in case–control analyses and case-case analyses (case-case OR = 1.08 (95% confidence interval: 0.30, 3.84)). Conclusions These results suggest that risk estimates associated with mammographic density are not distinct for separate breast cancer subtypes (basal-like/triple negative vs. luminal A breast cancers). Studies with a larger number of basal-like breast cancers are needed to confirm our findings.
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Jindal S, Gao D, Bell P, Albrektsen G, Edgerton SM, Ambrosone CB, Thor AD, Borges VF, Schedin P. Postpartum breast involution reveals regression of secretory lobules mediated by tissue-remodeling. Breast Cancer Res 2014; 16:R31. [PMID: 24678808 PMCID: PMC4053254 DOI: 10.1186/bcr3633] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2013] [Accepted: 03/06/2014] [Indexed: 01/05/2023] Open
Abstract
Introduction A postpartum diagnosis of breast cancer is an independent predictor of metastases, however the reason is unknown. In rodents, the window of postpartum mammary gland involution promotes tumor progression, suggesting a role for breast involution in the poor prognosis of human postpartum breast cancers. Rodent mammary gland involution is characterized by the programmed elimination of the secretory lobules laid down in preparation for lactation. This tissue involution process involves massive epithelial cell death, stromal remodeling, and immune cell infiltration with similarities to microenvironments present during wound healing and tumor progression. Here, we characterize breast tissue from premenopausal women with known reproductive histories to determine the extent, duration and cellular mechanisms of postpartum lobular involution in women. Methods Adjacent normal breast tissues from premenopausal women (n = 183) aged 20 to 45 years, grouped by reproductive categories of nulliparous, pregnant and lactating, and by time since last delivery were evaluated histologically and by special stain for lobular area, lobular type composition, apoptosis and immune cell infiltration using computer assisted quantitative methods. Results Human nulliparous glands were composed dominantly of small (approximately 10 acini per lobule) and medium (approximately 35 acini per lobule) sized lobules. With pregnancy and lactation, a >10 fold increase in breast epithelial area was observed compared to nulliparous cases, and lactating glands were dominated by mature lobules (>100 acini per lobule) with secretory morphology. Significant losses in mammary epithelial area and mature lobule phenotypes were observed within 12 months postpartum. By 18 months postpartum, lobular area content and lobule composition were indistinguishable from nulliparous cases, data consistent with postpartum involution facilitating regression of the secretory lobules developed in preparation for lactation. Analyses of apoptosis and immune cell infiltrate confirmed that human postpartum breast involution is characterized by wound healing-like tissue remodeling programs that occur within a narrowed time frame. Conclusions Human postpartum breast involution is a dominant tissue-remodeling process that returns the total lobular area of the gland to a level essentially indistinguishable from the nulliparous gland. Further research is warranted to determine whether the normal physiologic process of postpartum involution contributes to the poor prognosis of postpartum breast cancer.
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Rosebrock A, Caban JJ, Figueroa J, Gierach G, Linville L, Hewitt S, Sherman M. Quantitative Analysis of TDLUs using Adaptive Morphological Shape Techniques. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2013; 8676. [PMID: 25722829 DOI: 10.1117/12.2006619] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Within the complex branching system of the breast, terminal duct lobular units (TDLUs) are the anatomical location where most cancer originates. With aging, TDLUs undergo physiological involution, reflected in a loss of structural components (acini) and a reduction in total number. Data suggest that women undergoing benign breast biopsies that do not show age appropriate involution are at increased risk of developing breast cancer. To date, TDLU assessments have generally been made by qualitative visual assessment, rather than by objective quantitative analysis. This paper introduces a technique to automatically estimate a set of quantitative measurements and use those variables to more objectively describe and classify TDLUs. To validate the accuracy of our system, we compared the computer-based morphological properties of 51 TDLUs in breast tissues donated for research by volunteers in the Susan G. Komen Tissue Bank and compared results to those of a pathologist, demonstrating 70% agreement. Secondly, in order to show that our method is applicable to a wider range of datasets, we analyzed 52 TDLUs from biopsies performed for clinical indications in the National Cancer Institute's Breast Radiology Evaluation and Study of Tissues (BREAST) Stamp Project and obtained 82% correlation with visual assessment. Lastly, we demonstrate the ability to uncover novel measures when researching the structural properties of the acini by applying machine learning and clustering techniques. Through our study we found that while the number of acini per TDLU increases exponentially with the TDLU diameter, the average elongation and roundness remain constant.
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Affiliation(s)
| | - Jesus J Caban
- National Intrepid Center of Excellence, Naval Medical Center
| | - Jonine Figueroa
- Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute (NCI), National Institutes of Health (NIH)
| | - Gretchen Gierach
- Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute (NCI), National Institutes of Health (NIH)
| | - Laura Linville
- Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute (NCI), National Institutes of Health (NIH)
| | | | - Mark Sherman
- Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute (NCI), National Institutes of Health (NIH) ; Applied Molecular Pathology Lab (AMPL), NCI, NIH
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Current World Literature. Curr Opin Obstet Gynecol 2013; 25:81-9. [DOI: 10.1097/gco.0b013e32835cc6b6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Gierach GL, Yang XR, Figueroa JD, Sherman ME. Emerging Concepts in Breast Cancer Risk Prediction. CURRENT OBSTETRICS AND GYNECOLOGY REPORTS 2012; 2:43-52. [DOI: 10.1007/s13669-012-0034-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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Estrogen receptor and progesterone receptor expression in normal terminal duct lobular units surrounding invasive breast cancer. Breast Cancer Res Treat 2012; 137:837-47. [PMID: 23271326 DOI: 10.1007/s10549-012-2380-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2012] [Accepted: 12/06/2012] [Indexed: 12/14/2022]
Abstract
Molecular and morphological alterations related to carcinogenesis have been found in terminal duct lobular units (TDLUs), the microscopic structures from which most breast cancer precursors and cancers develop, and therefore, analysis of these structures may reveal early changes in breast carcinogenesis and etiologic heterogeneity. Accordingly, we evaluated relationships of breast cancer risk factors and tumor pathology to estrogen receptor (ER) and progesterone receptor (PR) expression in TDLUs surrounding breast cancers. We analyzed 270 breast cancer cases included in a population-based breast cancer case-control study conducted in Poland. TDLUs were mapped in relation to breast cancer: within the same block as the tumor (TDLU-T), proximal to tumor (TDLU-PT), or distant from (TDLU-DT). ER/PR was quantitated using image analysis of immunohistochemically stained TDLUs prepared as tissue microarrays. In surgical specimens containing ER-positive breast cancers, ER and PR levels were significantly higher in breast cancer cells than in normal TDLUs, and higher in TDLU-T than in TDLU-DT or TDLU-PT, which showed similar results. Analyses combining DT-/PT TDLUs within subjects demonstrated that ER levels were significantly lower in premenopausal women versus postmenopausal women (odds ratio [OR] = 0.38, 95 % confidence interval [CI] = 0.19, 0.76, P = 0.0064) and among recent or current menopausal hormone therapy users compared with never users (OR = 0.14, 95 % CI = 0.046-0.43, P (trend) = 0.0006). Compared with premenopausal women, TDLUs of postmenopausal women showed lower levels of PR (OR = 0.90, 95 % CI = 0.83-0.97, P (trend) = 0.007). ER and PR expression in TDLUs was associated with epidermal growth factor receptor (EGFR) expression in invasive tumors (P = 0.019 for ER and P = 0.03 for PR), but not with other tumor features. Our data suggest that TDLUs near breast cancers reflect field effects, whereas those at a distance demonstrate influences of breast cancer risk factors on at-risk breast tissue. Analyses of mapped TDLUs may provide information about the sequence of molecular changes occurring in breast carcinogenesis.
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Faupel-Badger JM, Arcaro KF, Balkam JJ, Eliassen AH, Hassiotou F, Lebrilla CB, Michels KB, Palmer JR, Schedin P, Stuebe AM, Watson CJ, Sherman ME. Postpartum remodeling, lactation, and breast cancer risk: summary of a National Cancer Institute-sponsored workshop. J Natl Cancer Inst 2012; 105:166-74. [PMID: 23264680 DOI: 10.1093/jnci/djs505] [Citation(s) in RCA: 74] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
The pregnancy-lactation cycle (PLC) is a period in which the breast is transformed from a less-developed, nonfunctional organ into a mature, milk-producing gland that has evolved to meet the nutritional, developmental, and immune protection needs of the newborn. Cessation of lactation initiates a process whereby the breast reverts to a resting state until the next pregnancy. Changes during this period permanently alter the morphology and molecular characteristics of the breast (molecular histology) and produce important, yet poorly understood, effects on breast cancer risk. To provide a state-of-the-science summary of this topic, the National Cancer Institute invited a multidisciplinary group of experts to participate in a workshop in Rockville, Maryland, on March 2, 2012. Topics discussed included: 1) the epidemiology of the PLC in relation to breast cancer risk, 2) breast milk as a biospecimen for molecular epidemiological and translational research, and 3) use of animal models to gain mechanistic insights into the effects of the PLC on breast carcinogenesis. This report summarizes conclusions of the workshop, proposes avenues for future research on the PLC and its relationship with breast cancer risk, and identifies opportunities to translate this knowledge to improve breast cancer outcomes.
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Affiliation(s)
- Jessica M Faupel-Badger
- Cancer Prevention Fellowship Program and Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
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