Single-cell transcriptional landscape of gastric submucosal tumors (GISTs and GLMs) reveals antagonistic fibroblast–macrophage niches

While targeted therapy with imatinib is standard, acquired resistance remains a major clinical challenge driven by incompletely defined microenvironmental mechanisms. To characterize the cellular landscape and identify microenvironmental determinants of therapy response, we performed single-cell RNA sequencing (scRNA-seq) on five prospectively collected, treatment-naïve gastric submucosal tumors, including three gastrointestinal stromal tumors (GISTs) and two gastric leiomyomas (GLMs) as benign mesenchymal controls.

Tissues were processed using the Singleron GEXSCOPE platform. Analysis of this dataset revealed that five transcriptionally distinct GIST tumor-cell states with distinct functional programs. Among these states, the S100A6-associated state (C2_S100A6) and the IGF2-associated state (C4_IGF2) showed opposing associations with imatinib response and distinct relationships with TAM programs.This dataset provides a high-resolution transcriptomic atlas of GIST and GLM, highlighting immunometabolic signatures relevant for risk stratification and therapeutic strategy.