Facilitating Selection with Artificial Intelligence-Based Glypican-3 Expression Quantification in Patients with Solid Tumors
Background: Glypican-3 (GPC3), a cell surface glycoprotein, regulates cell growth and exhibits increased expression in hepatocellular carcinoma (HCC) and squamous non-small cell lung cancer (SQ-NSCLC). This study developed an artificial intelligence (AI) algorithm for predicting GPC3 expression to accelerate clinical trial enrollment, comparing it with manual immunohistochemistry (IHC) scoring.
Authors
- Qi Tang (ORCID: https://orcid.org/0000-0002-5273-9769)
- Serena Masciari
- Ying Tong (ORCID: https://orcid.org/0000-0003-1623-7814)
- Robin Meng
- Wan‐Teck Lim (ORCID: https://orcid.org/0000-0002-4655-0206)
- Elham Attieh
- Lei Tang (ORCID: https://orcid.org/0000-0001-8171-6470)
- Jens Samol (ORCID: https://orcid.org/0000-0001-6109-3528)
- Cécile Combeau
- Maxime Chénard-Poirier (ORCID: https://orcid.org/0000-0001-5800-0124)
- Giovanni Abbadessa (ORCID: https://orcid.org/0009-0007-2823-1870)
- Asma Kefsi
- Yuchen Li (ORCID: https://orcid.org/0009-0009-9141-9627)
- Hong Wang (ORCID: https://orcid.org/0000-0003-0212-5379)
- Rui Wang (ORCID: https://orcid.org/0000-0003-1130-8214)
- Ellen Shuhan Meng
- Paola Fiorentini
- Benoit Pasquier (ORCID: https://orcid.org/0000-0002-3838-5976)
Institutions
- Nanyang Technological University (SG)
- WuXi AppTec (China) (CN)
- Tan Tock Seng Hospital (SG)
- National Cancer Centre Singapore (SG)
- Johns Hopkins Hospital (US)
Publication Details
- Journal
- AI in Precision Oncology
- Published
- 2025-04-30
- DOI
- https://doi.org/10.1089/aipo.2024.0057
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00