Location of Gastrointestinal Stromal Tumor (GIST) in the Stomach Predicts Tumor Mutation Profile and Drug Sensitivity
Autor: | Jill P. Mesirov, Beiqun Zhao, Thomas L. Sutton, Jeremy L. Davis, Hester van Boven, Hitendra Patel, Andrew M. Blakely, Vi Nguyen, Paul T. Fanta, Petur Snaebjornsson, Santiago Horgan, Chih Min Tang, Hyunho Yoon, Jason K. Sicklick, Ashwyn K. Sharma, Winan J. van Houdt, Nikki S. IJzerman, Christopher L. Corless, Alexa de la Fuente, Michael Heinrich, Adam M. Burgoyne, Tahsin M. Khan, Maha Alkhuziem, Jorge I. de la Torre, Skye C. Mayo, Christina Cui, Neeltje Steeghs, Sudeep Banerjee, Annemarie Bruining, Shumei Kato |
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Přispěvatelé: | Medical Oncology |
Rok vydání: | 2021 |
Předmět: |
Oncology
Cancer Research medicine.medical_specialty Stromal cell Receptor Platelet-Derived Growth Factor alpha Gastrointestinal Stromal Tumors Oncology and Carcinogenesis PDGFRA Article Rare Diseases SDG 3 - Good Health and Well-being Clinical Research Internal medicine Operative report medicine Genetics Humans Oncology & Carcinogenesis Stromal tumor Cancer GiST business.industry Stomach Platelet-Derived Growth Factor alpha medicine.disease Prognosis digestive system diseases Proto-Oncogene Proteins c-kit medicine.anatomical_structure Mutation Personalized medicine business Digestive Diseases Receptor |
Zdroj: | Clin Cancer Res Clinical cancer research : an official journal of the American Association for Cancer Research, vol 27, iss 19 Clinical Cancer Research, 27(19), 5334-5342. American Association for Cancer Research Inc. |
ISSN: | 1557-3265 1078-0432 |
Popis: | Purpose: Gastrointestinal stromal tumors (GIST) commonly arise in different regions of the stomach and are driven by various mutations (most often in KIT, PDGFRA, and SDHx). We hypothesized that the anatomic location of gastric GIST is associated with unique genomic profiles and distinct driver mutations. Experimental Design: We compared KIT versus non-KIT status with tumor location within the National Cancer Database (NCDB) for 2,418 patients with primary gastric GIST. Additionally, we compiled an international cohort (TransAtlantic GIST Collaborative, TAGC) of 236 patients and reviewed sequencing results, cross-sectional imaging, and operative reports. Subgroup analyses were performed for tumors located proximally versus distally. Risk factors for KIT versus non-KIT tumors were identified using multivariate regression analysis. A random forest machine learning model was then developed to determine feature importance. Results: Within the NCDB cohort, non-KIT mutants dominated distal tumor locations (P < 0.03). Proximal GIST were almost exclusively KIT mutant (96%) in the TAGC cohort, whereas 100% of PDGFRA and SDH-mutant GIST occurred in the distal stomach. On multivariate regression analysis, tumor location was associated with KIT versus non-KIT mutations. Using random forest machine learning analysis, stomach location was the most important feature for predicting mutation status. Conclusions: We provide the first evidence that the mutational landscape of gastric GIST is related to tumor location. Proximal gastric GIST are overwhelmingly KIT mutant, irrespective of morphology or age, whereas distal tumors display non-KIT genomic diversity. Anatomic location of gastric GIST may therefore provide immediate guidance for clinical treatment decisions and selective confirmatory genomic testing when resources are limited. |
Databáze: | OpenAIRE |
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