# Concept of neuroendocrine neoplasms of all organs with a focus on grading, subtyping

**Authors:** Atsuko Kasajima, Aurel Perren, Günter Klöppel

PMC · DOI: 10.1007/s00428-025-04296-y · Virchows Archiv · 2026-01-02

## TL;DR

This paper discusses neuroendocrine neoplasms, focusing on how they are classified, graded, and subtyped based on their biology and clinical features.

## Contribution

The paper highlights recent advances in molecular subtyping and grading systems for neuroendocrine neoplasms, emphasizing their clinical and prognostic implications.

## Key findings

- NETs and NECs differ in histology, clinical behavior, and molecular profiles, with NETs often linked to hereditary syndromes.
- TP53 mutations and RB1 inactivation are key in NECs, while NETs show mutations in genes like MEN1 and ATRX.
- Integrated histological, molecular, and clinical approaches improve classification and management of NEN subtypes.

## Abstract

Neuroendocrine neoplasms (NENs) are a heterogeneous group of neoplasms encompassing both well differentiate neuroendocrine tumors (NETs), and poorly differentiated neuroendocrine carcinomas (NECs). This classification is supported by distinct histological, clinical, and molecular profiles. NETs are typically slow-growing and hormone-producing, with organoid architecture and frequent associations with hereditary syndromes such as multiple endocrine neoplasia type 1 (MEN1) and von Hippel-Lindau (VHL) disease. In contrast, NECs are highly malignant, rapidly proliferating tumors characterized by mutations in adenocarcinoma-driver genes and in addition to TP53 mutations and RB1 inactivation, without hereditary links to endocrine tumor syndomes. Recent WHO classifications introduced site-specific grading systems, including NET G3 in the digestive, urogenital, gynecological and head and neck organs. There is growing evidence of progression from NET G1 to G3 with occasionally NEC-like features via acquired TP53 mutations. Advances in transcription factor profiling related to hormonal expression, molecular alterations resulted in further subtyping especially in pancreatic, pulmonary, and pituitary NETs. These tools support more precise treatment strategies. Genomic studies focusing on pancreatic NETs highlighted mutations in MEN1, DAXX, ATRX, and targets in mTOR pathway. NECs display higher tumor mutation burdens and harbor various actionable alterations. Approximately 5–10% of NETs are associated with hereditary syndromes, though recent findings suggest germline pathogenic variants, which were present in additional 5% of apparently sporadic NETs and NECs, requiring further study. An integrated histological, molecular, and clinical approach is essential to improve the classification, prognostication, and management of NENs, while recognizing the distinct biology of individual subtypes.

## Linked entities

- **Genes:** MEN1 (menin 1) [NCBI Gene 4221], VHL (von Hippel-Lindau tumor suppressor) [NCBI Gene 7428], TP53 (tumor protein p53) [NCBI Gene 7157], RB1 (RB transcriptional corepressor 1) [NCBI Gene 5925], DAXX (death domain associated protein) [NCBI Gene 1616], ATRX (ATRX chromatin remodeler) [NCBI Gene 546]
- **Diseases:** multiple endocrine neoplasia type 1 (MONDO:0007540), von Hippel-Lindau disease (MONDO:0008667)

## Full-text entities

- **Genes:** RB1 (RB transcriptional corepressor 1) [NCBI Gene 5925] {aka OSRC, PPP1R130, RB, p105-Rb, p110-RB1, pRb}, ATRX (ATRX chromatin remodeler) [NCBI Gene 546] {aka JMS, MRX52, RAD54, RAD54L, XH2, XNP}, DAXX (death domain associated protein) [NCBI Gene 1616] {aka BING2, DAP6, EAP1}, MTOR (mechanistic target of rapamycin kinase) [NCBI Gene 2475] {aka FRAP, FRAP1, FRAP2, RAFT1, RAPT1, SKS}, TP53 (tumor protein p53) [NCBI Gene 7157] {aka BCC7, BMFS5, LFS1, P53, TRP53}
- **Diseases:** NETs (MESH:D018358), MEN1 (MESH:D018761), Neuroendocrine neoplasms (MESH:D009369), von Hippel-Lindau (VHL) disease (MESH:D006623), NECs (MESH:D018278), adenocarcinoma (MESH:D000230), hereditary syndromes (MESH:D009386), endocrine tumor (MESH:D004701)

## Full text

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## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12876108/full.md

## References

15 references — full list in the complete paper: https://tomesphere.com/paper/PMC12876108/full.md

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Source: https://tomesphere.com/paper/PMC12876108