Spatial Transcriptomics Reveals Local Subtype-Specific Identity and Signaling within Multifocal Small Intestinal Neuroendocrine Tumors

Akitada Yogo,; Naoki Akanuma; Grace E. Kim; Chrissie Thirlwell; Netta Makinen; Matthew Meyerson; Eric K. Nakakura

doi:10.1530/endoabs.116.B9

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Endocrine Abstracts (2025) 116 B9 | DOI: 10.1530/endoabs.116.B9

NANETS2025 18th Annual Multidisciplinary NET Medical Symposium NANETS 2025 Basic Science (10 abstracts)

Spatial Transcriptomics Reveals Local Subtype-Specific Identity and Signaling within Multifocal Small Intestinal Neuroendocrine Tumors

Akitada Yogo ^1,2 , Naoki Akanuma ³ , Grace E. Kim ^2,4 , Chrissie Thirlwell ⁵ , Netta Mäkinen ^6,7 , Matthew Meyerson ^6,7,8 & Eric K. Nakakura ^1,2

Author affiliations

¹Division of Surgical Oncology, Section of Hepatopancreaticobiliary Surgery, Department of Surgery, University of California, San Francisco, CA, USA; ²Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; ³Department of Pathology and Laboratory Medicine, University of California Davis, Sacramento, CA, USA; ⁴Department of Pathology, University of California, San Francisco, CA, USA; ⁵Bristol Medical School, University of Bristol, Bristol, UK; ⁶Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; ⁷Cancer Program, Broad Institute of Harvard and MIT, Cambridge, MA, USA; ⁸Departments of Genetics and Medicine, Harvard Medical School, Boston, MA, USA

Background: Small intestinal neuroendocrine tumors (SI-NETs) frequently present as multifocal lesions, but the spatial and molecular mechanisms underlying their development and heterogeneity remain unclear. This study aimed to characterize the phenotypic subtypes of tumor cells across anatomical sites in multifocal SI-NETs and identify local microenvironmental factors influencing tumor development.

Methods: Spatial transcriptomics was performed on 72 tissue microarray cores derived from four patients with multifocal SI-NETs, that included tumoral and non-tumoral tissues from various anatomical layers of the small intestine and regional metastatic sites. Unsupervised clustering, over-representation analysis (ORA), and ligand-receptor (L-R) pair analysis were used to define tumor subtypes and associated signaling networks. External datasets (GSE98894 and GTEx) were used for validation. Protein expression of selected genes was evaluated by immunohistochemistry.

Results: Unsupervised clustering revealed four major tumor subtypes: mucosal, mesenteric, lymphatic, and deep, based on anatomical location and transcriptomic profiles. Each subtype exhibited distinct gene expression patterns and L-R interactions. The mesenteric and lymphatic subtypes exhibited distinct L-R pairs, such as NRG1 - ERBB3 (HER3) and CXCL12 - CXCR4, respectively. 5HT - HTR1D was found in all subtypes except mucosal. Across the four subtypes, SST - SSTR1/2, PTN - NCL, MDK - NCL and GJD2 - GJD2 were consistently detected, suggesting fundamental roles in SI-NET biology.

Conclusions: While further validation is needed, our findings indicate that multifocal SI-NETs consist of spatially distinct tumor subtypes affected by local cellular interactions, providing insight into SI-NET intra-tumoral heterogeneity, possible microenvironmental-triggered tumorigenesis, and potential subtype-targeted therapeutic strategies.

Abstract ID #33417