ArticleThe Journal of clinical investigation2026
Conserved neuronal-like and secretory programs define the spatial architecture of gastroenteropancreatic neuroendocrine tumors.
Article in The Journal of clinical investigation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
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Abstract
Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are clinically heterogeneous malignancies whose biology and microenvironmental organization remain poorly understood. Here, we integrated single-nucleus multiomic (snRNA-seq and snATAC-seq) and spatial transcriptomic profiling across 38 well-differentiated pancreatic (PanNET) and small-intestinal (siNET) tumors to define conserved malignant programs, their regulatory circuits, and spatial niches. We observed two conserved malignant cell programs spanning a continuous transcriptional spectrum: a neuronal-like program, and a secretory neuroendocrine program. Matched chromatin accessibility profiles uncovered distinct, tissue-specific regulatory networks, including MAX::MYC and MITF transcription factor binding motifs in siNETs versus ISL1 and TFAP4 in PanNETs, indicating organ-specific epigenetic control. Spatial transcriptomic analyses revealed that neuronal-like-high regions localized to densely cellular tumor areas with relative depletion of stromal infiltration, whereas secretory neuroendocrine-high regions occupied fibrovascular and stromal niches enriched for endothelial, fibroblast, and myeloid populations, and associated with TGFB1-ITGB1, VEGFA-FLT1, and LAMA2-ITGA1 signaling. Across both tumor types, the cNMF2 program was enriched in metastatic lesions and was enriched for pro-fibrotic and pro-angiogenic gene signatures. Thus, GEP-NETs are organized along a conserved neuronal-to-secretory axis defined by distinct epigenetic programs and spatially coupled to specific microenvironmental niches. This framework unifies NET heterogeneity across organ sites and identifies pathway-specific, microenvironment-linked vulnerabilities for therapeutic targeting.
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