Quantification of HER2-low and ultra-low expression in breast cancer specimens by quantitative IHC and artificial intelligence.

ABSTRACT: Recent results of clinical trials in antibody drug conjugate (ADC) therapies have significantly broadened treatment options for the HER2 low and ultra-low breast cancer patients. However, sensitive, accurate and quantitative evaluation of HER2 expression based on current immunohistochemistry (IHC) assays remains challenging, especially in low and ultra-low HER2 expression ranges. We developed a novel methodology for quantifying HER2 protein expression, targeting breast cancer cases in the HER2 IHC 0 and 1+ categories. We measured HER2 expression using quantitative IHC (qIHC) that enables precise and tunable HER2 detection across different expression levels as demonstrated in formalin-fixed paraffin-embedded cell lines. Additionally, we developed an AI-based interpretation of HercepTest™ mA

SUBMITTER: Aidt F 

PROVIDER: S-EPMC12495233 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature