Location of gastrointestinal stromal tumor (GIST) in the stomach predicts tumor mutation profile and drug sensitivity

Ashwyn K. Sharma, Jorge de la Torre, Nikki S. IJzerman, Thomas L. Sutton, Beiqun Zhao, Tahsin M. Khan, Sudeep Banerjee, Christina Cui, Vi Nguyen, Maha Alkhuziem, Petur Snaebjornsson, Hester van Boven, Annemarie Bruining, Chih Min Tang, Hyunho Yoon, Alexa de la Fuente, Shumei Kato, Hitendra Patel, Michael C. Heinrich, Christopher L. CorlessSantiago Horgan, Adam M. Burgoyne, Paul Fanta, Jill P. Mesirov, Andrew M. Blakely, Jeremy L. Davis, Skye C. Mayo, Winan J. van Houdt, Neeltje Steeghs, Jason K. Sicklick

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)5334-5342
Number of pages9
JournalClinical Cancer Research
Issue number19
StatePublished - Oct 1 2021

ASJC Scopus subject areas

  • General Medicine


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