Article
Deep Learning Predicts Mutations and Outcomes in Gastrointestinal Stromal Tumors.
Cancer research - 14 Aug 2026
Bonetti Arianna, Le Van-Linh, Carrero Zunamys I, Wolf Fabian, Gustav Marco, Lam Suk Wai, Vanhersecke Lucile, Sobczuk Pawel, Le Loarer François, Lenarcik Małgorzata, Rutkowski Piotr, van Sabben Joris M, Steeghs Neeltje, Van Boven Hester H, Machado Isidro, Bagué Silvia, Navarro Samuel, Medina-Ceballos Emilio, Agra-Pujol Carolina, Giner Francisco, Tapia Gustavo, Hernández-Gallego Alba, Civantos-Jubera Gema, Cuatrecasas Miriam, Lopez-Prades Sandra, Perret Raul, Soubeyran Isabelle, Khalifa Emmanuel, Blouin Laura, Wardelmann Eva, Meurgey Alexandra, Collini Paola, Voloshin Artem, Yatabe Yasushi, Hirano Hidekazu, Gronchi Alessandro, Nishida Toshirou, Bouche Olivier, Emile Jean-Francois, Ngo Carine, Hohenberger Peter, Cotarelo Cristina, Jakob Jens, Bovee Judith V M G, Gelderblom Hans, Szumera-Ciećkiewicz Anna, Jean-Denis Myriam, Bollard Julien, Lassau Nathalie, Le Cesne Axel, Blay Jean-Yves, Italiano Antoine, Crombe Amandine, Coindre Jean-Michel, Kather Jakob Nikolas
Abstract excerpt
Gastrointestinal stromal tumor (GIST) is the most common gastrointestinal mesenchymal tumor, driven by tyrosine-protein kinase (KIT) and platelet-derived growth factor receptor A (PDGFRA) mutations. Specific variants, such as KIT exon 11 deletions, carry prognostic and therapeutic implications, whereas wild-type variants derive limited benefit from tyrosine kinase inhibitors. Given the limited reproducibility of...
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