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Updated: Sep 8, 2025

Validated Immunochemical Assay for Comprehensive Determination of the Human Epidermal Growth Factor Receptor 2 Released from and Bound to Cells
Published on: May 9, 2025
Improving HER2 Diagnostics with Digital Real-Time PCR for Ultrafast, Precise Prediction of Anti-HER2 Therapy Response
Hee-Joo Choi1,2,3, Soo Young Park4,5, Minsik Song6
1Department of Pathology, College of Medicine, Hanyang University, Seoul, Republic of Korea.
Abstract:
While human epidermal growth factor receptor (HER2) has emerged as a tumor-agnostic biomarker, standard HER2 testing for anti-HER2 therapies using immunohistochemistry (IHC) and in situ hybridization (ISH) assays remains subjective, time-consuming, and often inaccurate. To address these limitations, an ultrafast and precise HER2 testing method is developed using Lab-On-An-Array (LOAA) digital real-time PCR (drPCR), a fully automated digital PCR enabling real-time absolute quantification. A multicenter study involving four independent breast cancer cohorts cross-validates the high diagnostic accuracy of drPCR-based HER2 assessment. Comparative analyses with artificial intelligence algorithms, next-generation sequencing, and droplet digital PCR demonstrate that drPCR is faster, simpler, and more accurate than conventional assays for assessing HER2 status, while IHC/ISH frequently yields false positives. Importantly, in patients initially diagnosed as HER2-positive and treated with neoadjuvant anti-HER2 therapy, the HER2 drPCR(+)/IHC-ISH(+) group achieves high pathological complete response rates, while HER2 drPCR(-)/IHC-ISH(+) cases exhibit poor treatment responses, highlighting the superior predictive accuracy of drPCR for anti-HER2 therapy response. Additionally, drPCR identifies patients with chromosome 17 centromere abnormalities, HER2-zero/ERBB2 hemizygous deletion, and ERBB2 hyperamplification who respond favorably to anti-HER2 therapy. Collectively, these findings establish drPCR as a clinically feasible, standardized, and ultrafast HER2 testing method for improved prediction of anti-HER2 therapy response in patients with cancer.
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