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Conserved Neuronal-like and Secretory Programs Define the Spatial Architecture of Gastroenteropancreatic Neuroendocrine Tumors

Karam, J.; Hoffman, S. E.; Garza, A.; Gui, D.; Hoffman, H. I.; Titchen, B. M.; Tanaka, Y.; Pimenta, E.; Pappa, T.; Valderrbano, L.; Bi, K.; Gillani, R.; Brais, L.; Shannon, E.; Hornick, J. L.; Park, J.; Chan, J.; Van Allen, E.

2025-12-29 cancer biology
10.64898/2025.12.28.696762 bioRxiv
Show 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 (pNET) 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 (si-cNMF1/p-cNMF1), and a secretory neuroendocrine program (si-cNMF2/p-cNMF2). 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 pNETs, indicating organ-specific epigenetic control. Spatial transcriptomic analyses revealed that si/p-cNMF1-high regions localized to high cell density, immune-rich tumor areas, whereas si/p-cNMF2-high regions occupied stromal and vascularized niches and co-occured with fibroblast and endothelial compartments enriched for TGFB1-ITGB1, VEGFA-FLT1, and LAMA2-ITGA1 signaling. Across both tumor types, the cNMF2 program was enriched in metastatic lesions and was enrichedfor 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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