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

Aidt, F.; Arbel, E.; Remer, I.; Ben-David, O.; Ben-Dor, A.; Rabkin, D.; Hoff, K.; Salomon, K.; Aviel-Ronen, S.; Nielsen, G.; Mollerup, J.; Jacobsen, L.; Tsalenko, A.

doi:10.1101/2025.01.22.634230

bioRxiv · 10.1101/2025.01.22.634230

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

Aidt, F.·Arbel, E.·Remer, I.·Ben-David, O.·Ben-Dor, A.·Rabkin, D.·Hoff, K.·Salomon, K.·Aviel-Ronen, S.·Nielsen, G.·Mollerup, J.·Jacobsen, L.·Tsalenko, A.

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Abstract

Recent results of clinical trials in antibody drug conjugate 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 remain 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 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 formalin-fixed paraffin-embedded 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 128x128{micro}m2 area within tumor regions. We observed statistically significant differences in HER2 expression between IHC 0, 0<IHC<1+, and IHC 1+ groups, and high degree 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 R2 of 0.87. 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.

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Aidt, F., Arbel, E., Remer, I., Ben-David, O., Ben-Dor, A., Rabkin, D., Hoff, K., Salomon, K., Aviel-Ronen, S., Nielsen, G., Mollerup, J., Jacobsen, L., Tsalenko, A.. 2025-01-25. Quantification of HER2-low and ultra-low expression in breast cancer specimens by quantitative IHC and artificial intelligence. https://doi.org/10.1101/2025.01.22.634230

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