[Not Available].

Journal: Bulletin du cancer
Published Date:

Abstract

HER2 is an important prognostic and predictive biomarker in breast cancer. Its detection makes it possible to define which patients will benefit from a targeted treatment. While assessment of HER2 status by immunohistochemistry in positive vs negative categories is well implemented and reproducible, the introduction of a new "HER2-low" category could raise some concerns about its scoring and reproducibility. We herein described the current HER2 testing methods and the application of innovative machine learning techniques to improve these determinations, as well as the main challenges and opportunities related to the implementation of digital pathology in the up-and-coming AI era.

Authors

  • Ingrid Garberis
    Inserm UMR 981, Gustave Roussy Cancer Campus, Villejuif, France; Université Paris-Saclay, 94270 Le Kremlin-Bicêtre, France. Electronic address: ingrid-judith.garberis@gustaveroussy.fr.
  • Fabrice Andre
    Université Paris-Saclay, Institut Gustave Roussy, Inserm U981 Predictive Biomarkers and New Therapeutic Strategies in Oncology, 114 Rue Edouard Vaillant, Villejuif 94800, France; Université Paris-Saclay, Institut Gustave Roussy, Prism Precision Medicine Center, 114 Rue Edouard Vaillant, Villejuif 94800, France.
  • Magali Lacroix-Triki
    Institut Claudius Regaud, Biology and Pathology Department; INSERM UMR1037, Toulouse, France. Lacroix.Magali@claudiusregaud.fr.