Journal of Clinical InvestigationCancer BiologyPeer-reviewed journal article
Conserved Neuronal-like and Secretory Programs Define the Spatial Architecture of Gastroenteropancreatic Neuroendocrine Tumors
Julie Karam, Samantha E. HoffmaniD, Amanda GarzaiD, Dan Y. GuiiD, Hannah I. HoffmaniD, Breanna M. TitcheniD, Yutaro TanakaiD, Erica Maria PimentaiD, Θεοδώρα ΠαππάiD, Laura Valderrábano, Kevin BiiD, Riaz GillaniiD, Lauren K. BraisiD, Erin E. ShannoniD, Jason L. HornickiD, Jihye ParkiD, Jennifer Chan, Eliezer M. Van AlleniD
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.
- organism: human
- assay: snRNA-seq
- assay: spatial transcriptomics
- assay: ATAC-seq
- research focus: cell type annotation
- research focus: clustering
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: deep learning
- approach: statistical model
- Citations
- 2
- FWCI
- 9.22
- Field percentile
- top 4%
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