Trial reportJCO precision oncology2025
Artificial Intelligence-Powered Human Epidermal Growth Factor Receptor 2 Quantification and Clinical Outcomes in Human Epidermal Growth Factor Receptor 2-Positive Biliary Tract Cancer Treated With Trastuzumab Plus Folinic Acid, Fluorouracil, and Oxaliplatin.
Trial report in JCO precision oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Trastuzumab plus nivolumab with gemcitabine and cisplatin as first-line therapy for HER2-positive unresectable biliary tract cancer: a phase 1b/2 trial.Nature medicine · 2026Article
- Artificial Intelligence for Molecular Biomarker Identification in Gastrointestinal and Hepatobiliary Cancers.International journal of molecular sciences · 2026Review
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeDespite recent advances in anti-human epidermal growth factor receptor 2 (HER2) treatments for HER2-positive biliary tract cancer (BTC), current guidelines lack clear thresholds for defining HER2 positivity in BTC. This study investigated the use of artificial intelligence (AI) to analyze HER2 expression and immune phenotypes (IP) in patients with HER2-positive BTC treated with anti-HER2 therapy. MATERIALS AND
methodsWe conducted a post hoc analysis of a phase II trial (KCSG HB19-14) of trastuzumab plus folinic acid, fluorouracil, and oxaliplatin (FOLFOX) for HER2-positive BTC. AI-powered HER2 quantification and IP analyses were performed on whole-slide images of pretreatment samples. Clinical outcomes were analyzed on the basis of HER2 positivity using a continuous AI-based HER2 immunohistochemistry scoring system. Additionally, we evaluated the spatial distribution of tumor-infiltrating lymphocytes using AI-based IP analysis.
resultsAmong 29 patients, the overall concordance rate between pathologists and the HER2-AI analyzer was 79.1%. AI-defined HER2-positivity status, characterized by a ≥30% H3 tumor cell proportion threshold, significantly predicted improved outcomes with trastuzumab plus FOLFOX (progression-free survival: 6.7
conclusionAI-powered HER2 quantification provides a refined biomarker for predicting the response to HER2-targeted therapies in BTC, proposing a ≥30% HER2 3+ tumor cell proportion threshold. Our findings highlight the potential of combining anti-HER2 therapy with immune checkpoint inhibitors on the basis of IP profiles.
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