Quantitative IHC and AI based evaluation of HER2 low and ultra-low expression in breast cancer specimens.

e13603 Background: Recent advancements in antibody drug conjugate therapies have significantly broadened treatment options for a substantial subgroup of 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. Advanced computational approaches can improve the interpretation of such IHC assays and could be of high benefit for identifying the best treatment options for current and future HER2 targeted therapies. More importantly, it may provide a basis for objectively assessing the lower level of HER2 protein expression that maximizes therapeutic benefits, while minimizing drug exposure risks for patients. Methods: 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 a quantitative IHC (qIHC) assay (Jensen et al, Mod Path 2017) that enables precise and tunable HER2 detection across different expression levels as demonstrated in formalin-fixed paraffin-embedded (FFPE) cell lines . Additionally, we developed an AI-based interpretation of HercepTest™ mAb pharmDx (Dako Omnis) (HercepTest™ mAb) using qIHC measurements as the ground truth. Both methodologies allowed spatial resolution and visualization of low and ultra-low levels of HER2 expression across entire tissue sections to demonstrate and enable quantification of heterogeneity of HER2 expression. Serial sections of 82 FFPE patient tissue blocks of invasive breast carcinoma with HER2 IHC scores 0 or 1+ were stained with H&E, HercepTest™ mAb, qIHC and p63, then scanned and digitally aligned. Tumor areas were manually selected and reviewed by expert pathologists. HER2 expression was quantitatively evaluated based on the qIHC assay in each 128x128µm 2 area within tumor regions. Results: We observed statistically significant differences in HER2 expression between IHC 0, 0 < IHC < 1+, and IHC 1+ groups, and a high level of spatial heterogeneity of the HER2 expression levels within the same tissue, up to five-fold in some cases. We demonstrated high slide-level tumor region agreement of estimates of HER2 expression between the AI-based interpretation of HercepTest™ mAb and the qIHC ground truth with a Pearson correlation of 0.94, and R 2 of 0.87. Conclusions: The developed methodologies can be used to stratify HER2 low-expression patient groups, potentially improving the interpretation of IHC assays and maximizing therapeutic benefits. This method can be implemented in histology labs without requiring a specialized workflow. Disclaimer: This study is for proof of concept only. This study does not imply any clinical functionality, nor off-label use for any products mentioned.