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Cancer Epidemiology, Biomarkers & Prevention
Cancer Epidemiology, Biomarkers & Prevention
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Research Article

Automated Quantitative Measures of Terminal Duct Lobular Unit Involution and Breast Cancer Risk

Kevin H. Kensler, Emily Z.F. Liu, Suzanne C. Wetstein, Allison M. Onken, Christina I. Luffman, Gabrielle M. Baker, Laura C. Collins, Stuart J. Schnitt, Vanessa C. Bret-Mounet, Mitko Veta, Josien P.W. Pluim, Ying Liu, Graham A. Colditz, A. Heather Eliassen, Susan E. Hankinson, Rulla M. Tamimi and Yujing J. Heng
Kevin H. Kensler
1Division of Population Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts.
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  • ORCID record for Kevin H. Kensler
Emily Z.F. Liu
2Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
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Suzanne C. Wetstein
3Medical Image Analysis Group, Eindhoven University of Technology, Eindhoven, the Netherlands.
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Allison M. Onken
2Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
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Christina I. Luffman
2Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
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Gabrielle M. Baker
2Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
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Laura C. Collins
2Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
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Stuart J. Schnitt
4Department of Pathology, Harvard Medical School and Brigham and Women's Hospital; Dana-Farber Cancer Institute, Boston, Massachusetts.
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Vanessa C. Bret-Mounet
2Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
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Mitko Veta
3Medical Image Analysis Group, Eindhoven University of Technology, Eindhoven, the Netherlands.
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Josien P.W. Pluim
3Medical Image Analysis Group, Eindhoven University of Technology, Eindhoven, the Netherlands.
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Ying Liu
5Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine and Alvin J. Siteman Cancer Center, St Louis, Missouri.
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Graham A. Colditz
5Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine and Alvin J. Siteman Cancer Center, St Louis, Missouri.
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A. Heather Eliassen
6Channing Division of Network Medicine, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts.
7Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
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Susan E. Hankinson
6Channing Division of Network Medicine, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts.
8Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, Massachusetts.
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Rulla M. Tamimi
6Channing Division of Network Medicine, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts.
7Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
9Department of Population Health Sciences, Weill Cornell Medicine, New York, New York.
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Yujing J. Heng
2Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
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  • For correspondence: yheng@bidmc.harvard.edu
DOI: 10.1158/1055-9965.EPI-20-0723
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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.

Footnotes

  • Note: Supplementary data for this article are available at Cancer Epidemiology, Biomarkers & Prevention Online (http://cebp.aacrjournals.org/).

  • Cancer Epidemiol Biomarkers Prev 2020;XX:XX–XX

  • Received May 12, 2020.
  • Revision received July 2, 2020.
  • Accepted September 4, 2020.
  • Published first September 11, 2020.
  • ©2020 American Association for Cancer Research.

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This OnlineFirst version was published on September 30, 2020
doi: 10.1158/1055-9965.EPI-20-0723

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Automated Quantitative Measures of Terminal Duct Lobular Unit Involution and Breast Cancer Risk
Kevin H. Kensler, Emily Z.F. Liu, Suzanne C. Wetstein, Allison M. Onken, Christina I. Luffman, Gabrielle M. Baker, Laura C. Collins, Stuart J. Schnitt, Vanessa C. Bret-Mounet, Mitko Veta, Josien P.W. Pluim, Ying Liu, Graham A. Colditz, A. Heather Eliassen, Susan E. Hankinson, Rulla M. Tamimi and Yujing J. Heng
Cancer Epidemiol Biomarkers Prev September 30 2020 DOI: 10.1158/1055-9965.EPI-20-0723

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Automated Quantitative Measures of Terminal Duct Lobular Unit Involution and Breast Cancer Risk
Kevin H. Kensler, Emily Z.F. Liu, Suzanne C. Wetstein, Allison M. Onken, Christina I. Luffman, Gabrielle M. Baker, Laura C. Collins, Stuart J. Schnitt, Vanessa C. Bret-Mounet, Mitko Veta, Josien P.W. Pluim, Ying Liu, Graham A. Colditz, A. Heather Eliassen, Susan E. Hankinson, Rulla M. Tamimi and Yujing J. Heng
Cancer Epidemiol Biomarkers Prev September 30 2020 DOI: 10.1158/1055-9965.EPI-20-0723
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