Automated Quantitative Measures of Terminal Duct Lobular Unit Involution and Breast Cancer Risk. Academic Article uri icon

Overview

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.

authors

  • Kensler, Kevin
  • Liu, Emily Z F
  • Wetstein, Suzanne C
  • Onken, Allison M
  • Luffman, Christina I
  • Baker, Gabrielle M
  • Collins, Laura C
  • Schnitt, Stuart J
  • Bret-Mounet, Vanessa C
  • Veta, Mitko
  • Pluim, Josien P W
  • Liu, Ying
  • Colditz, Graham A
  • Eliassen, A Heather
  • Hankinson, Susan E
  • Tamimi, Rulla
  • Heng, Yujing J

publication date

  • September 11, 2020

Research

keywords

  • Breast Neoplasms

Identity

PubMed Central ID

  • PMC7642012

Scopus Document Identifier

  • 85103146483

Digital Object Identifier (DOI)

  • 10.1158/1055-9965.EPI-20-0723

PubMed ID

  • 32917665

Additional Document Info

volume

  • 29

issue

  • 11