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ASCO 2025 | AI for gastric cancer treatment prediction and guidance
Hyung-Don Kim, MD, PhD, Asan Medical Center, Seoul, South Korea, discusses using an artificial intelligence (AI) model to predict claudin 18.2 expression and immune phenotype and refine patient selection for targeted therapies like zolbetuximab in gastric cancer. The model accurately identified claudin 18.2 positivity and stratified patients by likely treatment response. In settings with limited tissue or testing resources, AI-driven prediction can help prioritize biomarker testing and guide first-line therapy, supporting more accessible and personalized use of targeted treatments. This interview took place during the 2025 American Society of Clinical Oncology (ASCO) Meeting in Chicago, IL.
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Transcript
The standard approach for zolbetuximab-based chemotherapy would be the positivity for Claudin 18.2 IHC. However, for some instances, it may not be feasible to do all of the IHC biomarkers because of the limited tissue availability. And in some areas, the resources for the evaluation of the biomarker may not be sufficient. So in that regard, this AI-based approach may provide an effective way of directing biomarker testing and guiding the first-line treatment...
The standard approach for zolbetuximab-based chemotherapy would be the positivity for Claudin 18.2 IHC. However, for some instances, it may not be feasible to do all of the IHC biomarkers because of the limited tissue availability. And in some areas, the resources for the evaluation of the biomarker may not be sufficient. So in that regard, this AI-based approach may provide an effective way of directing biomarker testing and guiding the first-line treatment.
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