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Navigating HER2-Low Testing in Invasive Breast Cancer: Update Recommendations for Pathologists.

Leticia Bornstein-QuevedoJazmín de Anda-GonzálezCesar Octavio Lara-TorresJuan Pablo Flores-GutiérrezRita Dorantes-HerediaVerónica Bautista-PiñaPerla Zaragoza-VargasAldo Alcaraz-WongAna Karen Soto-SañudoSaulo Mendoza-RamírezMoisés Salamanca-GarcíaGeorgina Loyola-RodríguezGabriela Sofia Gómez-MacíasMario Murguia-PerezMarcela De Luna-SánchezRicardo Villalobos-ValenciaEnrique TalamantesClaudia Arce-Salinas
Published in: Journal of personalized medicine (2024)
The article discusses the importance of accurately distinguishing HER2-low from HER2-negative breast cancer, as novel ADCs have demonstrated activity in a large population of patients with HER2-low-expressing BC. While current guidelines recommend a dichotomous classification of HER2 as either positive or negative, the emergence of the HER2-low concept calls for standardization of HER2 testing in breast cancer, using currently available assays to better discriminate HER2 levels. This review covers the evolution and latest updates of the ASCO/CAP guidelines relevant to this important biomarker in breast cancer, including still-evolving concepts such as HER2 low, HER2 heterogeneity, and HER2 evolution. Our group presents the latest Mexican recommendations for HER2 status evaluation in breast cancer, considering the ASCO/CAP guidelines and introducing the HER2-low concept. In the era of personalized medicine, accurate HER2 status assessment remains one of the most important biomarkers in breast cancer, and the commitment of Mexican pathologists to theragnostic biomarker quality is crucial for providing the most efficient care in oncology.
Keyphrases
  • clinical practice
  • healthcare
  • palliative care
  • machine learning
  • deep learning
  • quality improvement
  • young adults
  • chronic pain
  • affordable care act