Artificial intelligence-detected HER2 strong-positive tumor proportion predicts FISH positivity and treatment response in breast cancer

06 Jul 20264 min read0 viewsJournal Feed

GIST (Key Takeaways)

by Seung Geun Song, Soo Ick Cho, Taeyong Sim, Sangwon Shin, Wonkyung Jung, Jisoo Shin, Sukjun Kim, Heon Song, Sérgio Pereira, Donggeun Yoo, Sun Kyung Baek, Kiyong Na, Minsun Jung, So-Woon Kim Human epidermal growth factor receptor 2 (HER2)-targeted therapies have revolutionized breast cancer treatment, necessitating standardized HER2 testing. However, current immunochemistry-based HER2 assessment faces challenges due to subjectivity and variability among observers, prompting the guidance of artificial intelligence (AI).
We evaluated AI’s efficacy in HER2 status assessment and treatment response prediction, especially focusing on complete and intense circumferential HER2-positive (3+) tumor cells. An AI-powered HER2 analyzer (Lunit SCOPE HER2, Lunit Inc., Seoul, South Korea) and three pathologists independently assessed HER2 3 + tumor cell proportions from whole-slide images of 191 breast cancer cases from Kyung Hee University Hospital.
Logistic regression and receiver operating characteristic (ROC) curves determined predictive accuracy. AI-detected 3 + tumor cell proportions strongly correlated with fluorescent in situ hybridization (FISH) positivity (area under ROC curve [AUC]: 0.783) and pathological complete response (pCR) rates (odds ratio [OR]: 1.003–1.052), outperforming pathologists’ assessments.

Clinical Editorial

PLOS ONE (Medicine) published a clinical update in Research Highlights on 06 Jul 2026.

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