Development of a deep-learning model tailored for HER2 detection in breast cancer to aid pathologists in interpreting HER2-low cases.

Journal: Histopathology
PMID: 39004603

Abstract

AIMS: Over 50% of breast cancer cases are "Human epidermal growth factor receptor 2 (HER2) low breast cancer (BC)", characterized by HER2 immunohistochemistry (IHC) scores of 1+ or 2+ alongside no amplification on fluorescence in situ hybridization (FISH) testing. The development of new anti-HER2 antibody-drug conjugates (ADCs) for treating HER2-low breast cancers illustrates the importance of accurately assessing HER2 status, particularly HER2-low breast cancer. In this study we evaluated the performance of a deep-learning (DL) model for the assessment of HER2, including an assessment of the causes of discordances of HER2-Null between a pathologist and the DL model. We specifically focussed on aligning the DL model rules with the ASCO/CAP guidelines, including stained cells' staining intensity and completeness of membrane staining.

Authors

  • Pierre-Antoine Bannier
    Owkin France, Paris, France.
  • Glenn Broeckx
    Department of Pathology, ZAS Hospitals, Antwerp, Belgium.
  • Loïc Herpin
    Owkin France, Paris, France.
  • Remy Dubois
    Owkin Lab, Owkin, Inc, New York, NY, USA.
  • Lydwine Van Praet
    Owkin France, Paris, France.
  • Charles Maussion
    OWKIN Paris, France.
  • Frederik Deman
    Department of Pathology, ZAS Hospitals, Antwerp, Belgium.
  • Ellen Amonoo
    Cancer & Pharmaceutical Sciences, King's College London, London, UK.
  • Anca Mera
    Cancer & Pharmaceutical Sciences, King's College London, London, UK.
  • Jasmine Timbres
    Cancer & Pharmaceutical Sciences, King's College London, London, UK.
  • Cheryl Gillett
    King's Health Partners Cancer Biobank, King's College London, London, UK.
  • Elinor Sawyer
    Cancer & Pharmaceutical Sciences, King's College London, London, UK.
  • Patrycja Gazinska
    Breast Cancer Now Unit, School of Cancer and Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.
  • Piotr Ziolkowski
    Department of Clinical and Experimental Pathology, Wroclaw Medical University, Wroclaw, Poland.
  • Magali Lacroix-Triki
    Institut Claudius Regaud, Biology and Pathology Department; INSERM UMR1037, Toulouse, France. Lacroix.Magali@claudiusregaud.fr.
  • Roberto Salgado
    Breast Cancer Translational Research Laboratory, Université Libre de Bruxelles, Brussels, Belgium; Department of Pathology, GZA Hospitals Antwerp, Belgium.
  • Sheeba Irshad
    Cancer & Pharmaceutical Sciences, King's College London, London, UK.

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