Mark E Sherman1, Thomas de Bel2,3, Michael G Heckman4, Launia J White4, Joshua Ogony4, Melody Stallings-Mann5, Tracy Hilton4, Amy C Degnim6, Robert A Vierkant7, Tanya Hoskin7, Matthew R Jensen7, Laura Pacheco-Spann4, Jill E Henry8, Anna Maria Storniolo8, Jodi M Carter9, Stacey J Winham7, Derek C Radisky5, Jeroen van der Laak2,3,10. 1. Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, 32224, USA. Sherman.Mark@Mayo.edu. 2. Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands. 3. Radboud Institute of Health Sciences, Nijmegen, The Netherlands. 4. Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, 32224, USA. 5. Department of Cancer Biology, Mayo Clinic, Jacksonville, FL, 32224, USA. 6. Department of Surgery, Mayo Clinic, Rochester, MN, USA. 7. Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA. 8. Susan G. Komen Tissue Bank at the IU Simon Cancer Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA. 9. Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA. 10. Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden.
Abstract
PURPOSE: Breast terminal duct lobular units (TDLUs) are the main source of breast cancer (BC) precursors. Higher serum concentrations of hormones and growth factors have been linked to increased TDLU numbers and to elevated BC risk, with variable effects by menopausal status. We assessed associations of circulating factors with breast histology among premenopausal women using artificial intelligence (AI) and preliminarily tested whether parity modifies associations. METHODS: Pathology AI analysis was performed on 316 digital images of H&E-stained sections of normal breast tissues from Komen Tissue Bank donors ages ≤ 45 years to assess 11 quantitative metrics. Associations of circulating factors with AI metrics were assessed using regression analyses, with inclusion of interaction terms to assess effect modification. RESULTS: Higher prolactin levels were related to larger TDLU area (p < 0.001) and increased presence of adipose tissue proximate to TDLUs (p < 0.001), with less significant positive associations for acini counts (p = 0.012), dilated acini (p = 0.043), capillary area (p = 0.014), epithelial area (p = 0.007), and mononuclear cell counts (p = 0.017). Testosterone levels were associated with increased TDLU counts (p < 0.001), irrespective of parity, but associations differed by adipose tissue content. AI data for TDLU counts generally agreed with prior visual assessments. CONCLUSION: Among premenopausal women, serum hormone levels linked to BC risk were also associated with quantitative features of normal breast tissue. These relationships were suggestively modified by parity status and tissue composition. We conclude that the microanatomic features of normal breast tissue may represent a marker of BC risk.
PURPOSE: Breast terminal duct lobular units (TDLUs) are the main source of breast cancer (BC) precursors. Higher serum concentrations of hormones and growth factors have been linked to increased TDLU numbers and to elevated BC risk, with variable effects by menopausal status. We assessed associations of circulating factors with breast histology among premenopausal women using artificial intelligence (AI) and preliminarily tested whether parity modifies associations. METHODS: Pathology AI analysis was performed on 316 digital images of H&E-stained sections of normal breast tissues from Komen Tissue Bank donors ages ≤ 45 years to assess 11 quantitative metrics. Associations of circulating factors with AI metrics were assessed using regression analyses, with inclusion of interaction terms to assess effect modification. RESULTS: Higher prolactin levels were related to larger TDLU area (p < 0.001) and increased presence of adipose tissue proximate to TDLUs (p < 0.001), with less significant positive associations for acini counts (p = 0.012), dilated acini (p = 0.043), capillary area (p = 0.014), epithelial area (p = 0.007), and mononuclear cell counts (p = 0.017). Testosterone levels were associated with increased TDLU counts (p < 0.001), irrespective of parity, but associations differed by adipose tissue content. AI data for TDLU counts generally agreed with prior visual assessments. CONCLUSION: Among premenopausal women, serum hormone levels linked to BC risk were also associated with quantitative features of normal breast tissue. These relationships were suggestively modified by parity status and tissue composition. We conclude that the microanatomic features of normal breast tissue may represent a marker of BC risk.
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