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Subtyping of pancreatic neuroendocrine tumors by transcription factors, hormones, histology, and patient outcome

  • 0Department of Pathology, TUM School of Medicine and Health, Munich, Trogerstr. 18, 81675, Munich, Germany. elisa.moser@tum.de.
Pathologie (heidelberg, Germany) +

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October 8, 2024

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October 8, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Pancreatic neuroendocrine tumors (PanNETs) can be classified into five subtypes based on transcription factor (TF) signatures. These subtypes correlate with tumor histology, hormone production, and patient prognosis, aiding in personalized treatment strategies.

Area Of Science

  • Endocrinology
  • Oncology
  • Molecular Biology

Background

  • Pancreatic neuroendocrine tumors (PanNETs) exhibit significant heterogeneity in hormone and transcription factor (TF) expression.
  • Specific TFs like ARX and PDX1 are linked to alpha- and beta-cell features and patient outcomes, but comprehensive correlation studies are limited.

Purpose Of The Study

  • To identify distinct PanNET subtypes based on TF expression.
  • To associate these subtypes with histological, hormonal, and prognostic characteristics.

Main Methods

  • Cluster analysis of 185 resected PanNETs based on four TFs (ARX, PDX1, ISL1, CDX2) to define five subtypes (A1, A2, B, C, D).
  • Correlation of subtypes with hormone expression, DAXX/ATRX status, Alternative Lengthening of Telomeres (ALT) activation, histology, and progression-free survival.

Main Results

  • Five subtypes (A1, A2, B, C, D) were identified, with A1 being the most frequent (46%).
  • Subtypes A1 and A2 associated with trabecular patterns and glucagon/PP expression; subtype B with insulinomas; subtype C with solid morphology and serotonin/calcitonin/ACTH expression.
  • Subtype D exhibited solid morphology, specific hormone expression, and the shortest disease-free survival. ALT positivity correlated with poorer outcomes in subtypes A1 and A2.

Conclusions

  • PanNETs can be classified into five distinct subgroups using TF signatures.
  • These TF-based subgroups show strong associations with tumor histology, hormone production, functionality, and patient prognosis.

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