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Updated: Jul 23, 2025
Establishment and Characterization of Small Bowel Neuroendocrine Tumor Spheroids
Published on: October 14, 2019
Transcriptome analysis of primary sporadic neuroendocrine tumours of the intestine identified three different
Paola Mattiolo1, Anastasios Gkountakos1, Giovanni Centonze2
1Department of Diagnostics and Public Health, Section of Pathology, University and Hospital Trust of Verona, Verona, Italy.
Background:
Intestinal neuroendocrine tumours (I-NETs) represent a non-negligible entity among intestinal neoplasms, with metastatic spreading usually present at the time of diagnosis. In this context, effective molecular actionable targets are still lacking. Through transcriptome analysis, we aim at refining the molecular taxonomy of I-NETs, also providing insights towards the identification of new therapeutic vulnerabilities.
Materials And Methods:
A retrospective series of 38 primary sporadic, surgically-resected I-NETs were assessed for transcriptome profiling of 20,815 genes.
Results:
Transcriptome analysis detected 643 highly expressed genes. Unsupervised hierarchical clustering, differential expression analysis and gene set enriched analysis identified three different tumour clusters (CL): CL-A, CL-B, CL-C. CL-A showed the overexpression of ARGFX, BIRC8, NANOS2, and SSTR4 genes. Its most characterizing signatures were those related to cell-junctions, and activation of mTOR and WNT pathway. CL-A was also enriched in T CD8 + lymphocytes. CL-B showed the overexpression of PCSK1, QPCT, ST18, and TPH1 genes. Its most characterizing signatures were those related to adipogenesis, neuroendocrine metabolism, and splice site machinery-related processes. CL-B was also enriched in T CD4 + lymphocytes. CL-C showed the overexpression of ALB, ANG, ARG1, and HP genes. Its most characterizing signatures were complement/coagulation and xenobiotic metabolism. CL-C was also enriched in M1/2 macrophages. These CL-based differences may have therapeutic implications in refining the management of I-NET patients. At last, we described a specific gene-set for differentiating I-NET from pancreatic NET.
Discussion:
Our data represent an additional step for refining the molecular taxonomy of I-NET, identifying novel transcriptome subgroups with different biology and therapeutic opportunities.
Insights
This study refines intestinal neuroendocrine tumor (I-NET) classification by identifying three distinct molecular subgroups (CL-A, CL-B, CL-C) through transcriptome analysis, revealing unique biological features and potential therapeutic targets for I-NETs.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Intestinal neuroendocrine tumors (I-NETs) are common neoplasms often diagnosed at metastatic stages.
- Effective molecular targets for I-NET treatment are currently limited.
- Understanding I-NET molecular heterogeneity is crucial for developing targeted therapies.
Purpose of the Study:
- To refine the molecular taxonomy of I-NETs using transcriptome analysis.
- To identify novel therapeutic vulnerabilities and subgroups within I-NETs.
- To provide insights for differentiating I-NETs from pancreatic neuroendocrine tumors (PNETs).
Main Methods:
- Retrospective analysis of 38 surgically-resected primary sporadic I-NETs.
- Comprehensive transcriptome profiling of 20,815 genes.
- Unsupervised hierarchical clustering, differential expression, and gene set enrichment analyses were performed.
Main Results:
- Three distinct tumor clusters (CL-A, CL-B, CL-C) were identified based on gene expression profiles.
- CL-A exhibited overexpression of ARGFX, BIRC8, NANOS2, SSTR4, and enrichment in T CD8+ lymphocytes, mTOR, and WNT pathways.
- CL-B showed overexpression of PCSK1, QPCT, ST18, TPH1, and enrichment in adipogenesis and neuroendocrine metabolism pathways, with T CD4+ lymphocytes.
- CL-C was characterized by overexpression of ALB, ANG, ARG1, HP, and enrichment in complement/coagulation and xenobiotic metabolism pathways, with M1/2 macrophages.
- A specific gene set for distinguishing I-NET from PNET was developed.
Conclusions:
- Transcriptome analysis revealed novel molecular subgroups within I-NETs.
- These subgroups possess distinct biological characteristics and potential therapeutic implications.
- The findings contribute to refining I-NET classification and identifying new treatment opportunities.
