Gastroenteropancreatic Neuroendocrine Neoplasm

MONDO:0024503 Pathograph 5 Show in embeddings browser digestive system neoplasm neuroendocrine neoplasm

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are a heterogeneous family of tumors arising from the diffuse neuroendocrine cell system of the digestive tract and pancreas. They derive from cells that produce hormones and neuropeptides and arise mostly sporadically, and to a lesser extent in the context of inherited syndromes such as MEN1, von Hippel-Lindau, neurofibromatosis type 1, and tuberous sclerosis. GEP-NENs span a wide biological spectrum, from indolent well-differentiated neuroendocrine tumors (NETs, graded G1/G2/G3 by Ki-67 proliferation index and mitotic rate) to highly aggressive poorly differentiated neuroendocrine carcinomas (NECs, small-cell and large-cell types). Tumors are further classified as functional (secreting bioactive hormones such as serotonin, insulin, gastrin, glucagon, or VIP and producing distinct clinical syndromes) or non-functional. Anatomic sites include the stomach, duodenum, small intestine, appendix, colon, rectum, and pancreas. The incidence of neuroendocrine tumors has risen sharply over recent decades, with gastroenteropancreatic sites the most common location. Pancreatic NETs are characterized by recurrent inactivation of MEN1, DAXX/ATRX, and mTOR pathway genes; small-intestinal NETs by chromosome 18 loss and a low mutation burden; and poorly differentiated NECs by TP53 and RB1 inactivation. Nearly all well-differentiated GEP-NETs express somatostatin receptors, which underpin both molecular imaging (SSTR PET) and somatostatin-analog and peptide receptor radionuclide therapy (PRRT).

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2
Inheritance
7
Pathophys.
3
Histopath.
9
Phenotypes
5
Pathograph
5
Genes
8
Medical Actions
9
Subtypes
1
References
1
Deep Research
🏷

Classifications

Harrison's Chapter
ONCOLOGY_HEMATOLOGY
👪

Inheritance

2
Sporadic (somatic)
The large majority of GEP-NENs arise sporadically through somatic driver alterations (MEN1, DAXX/ATRX, mTOR-pathway genes in pancreatic NETs; TP53/RB1 in NECs) without a germline predisposition.
Autosomal dominant (syndromic) HP:0000006
A minority of GEP-NENs occur within autosomal dominant tumor-predisposition syndromes, most prominently multiple endocrine neoplasia type 1 (MEN1), and also von Hippel-Lindau, neurofibromatosis type 1, and tuberous sclerosis.
Autosomal dominant inheritance
Show evidence (1 reference)
PMID:21252315 SUPPORT Human Clinical
"MEN1 is a tumor suppressor gene which, when mutated in the germline, predisposes to multiple endocrine neoplasia type 1 syndrome."
Jiao et al. note that germline MEN1 mutation underlies the autosomal dominant MEN1 syndrome, the prototypical hereditary context for GEP-NENs.
◆

Subtypes

9
Well-differentiated neuroendocrine tumor, grade 1
Low-grade well-differentiated neuroendocrine tumor with Ki-67 proliferation index <3% and mitotic count <2 per 2 mm2. Indolent biology with the most favorable prognosis.
Well-differentiated neuroendocrine tumor, grade 2
Intermediate-grade well-differentiated neuroendocrine tumor with Ki-67 of 3-20% or mitotic count of 2-20 per 2 mm2.
Well-differentiated neuroendocrine tumor, grade 3
High-grade but still well-differentiated neuroendocrine tumor with Ki-67 >20%. Biologically and therapeutically distinct from poorly differentiated NEC, retaining organoid architecture and somatostatin receptor expression.
Poorly differentiated neuroendocrine carcinoma (NEC)
Poorly differentiated, high-grade neuroendocrine carcinoma (small-cell or large-cell type) with Ki-67 typically >55%, frequent TP53 and RB1 inactivation, rapid growth, and poor prognosis. Managed with platinum-etoposide chemotherapy analogous to small-cell lung carcinoma.
Insulinoma
Functional pancreatic NET secreting insulin and causing recurrent hyperinsulinemic hypoglycemia (Whipple triad). Most are small, solitary, and benign.
Gastrinoma
Functional gastrinoma (duodenal or pancreatic) secreting gastrin and causing Zollinger-Ellison syndrome with gastric acid hypersecretion, recurrent peptic ulcers, and diarrhea. About 25% occur in MEN1.
Serotonin-producing NET (carcinoid)
Serotonin-secreting well-differentiated NET, classically of the small intestine (midgut), causing carcinoid syndrome (flushing, diarrhea, carcinoid heart disease) when hepatic metastases bypass first-pass hepatic clearance.
VIPoma
Functional pancreatic NET secreting vasoactive intestinal peptide (VIP), producing the Verner-Morrison syndrome of watery diarrhea, hypokalemia, and achlorhydria (WDHA syndrome).
Glucagonoma
Functional pancreatic NET secreting glucagon, causing the glucagonoma syndrome of necrolytic migratory erythema, diabetes mellitus, weight loss, and venous thromboembolism.
⚙

Pathophysiology

7
Neuroendocrine Cell Origin and Differentiation
GEP-NENs arise from the diffuse neuroendocrine cell compartment of the gastrointestinal tract and pancreatic islets. These cells specialize in producing hormones and neuropeptides and share a neuroendocrine phenotype expressing chromogranin A and synaptophysin. Tumor cells retain features of their cell of origin, including dense-core secretory granules and regulated hormone secretion.
neuroendocrine cell CL:0000165 enteroendocrine cell CL:0000164
peptide hormone secretion (regulated neuroendocrine release) GO:0030072 ↕ DYSREGULATED
Downstream
Somatostatin Receptor Overexpression The retained neuroendocrine differentiation program underlies strong somatostatin receptor expression in well-differentiated GEP-NETs, which enables SSTR-targeted imaging and therapy.
Serotonin Hypersecretion and Carcinoid Syndrome Enterochromaffin-lineage neuroendocrine cells of the midgut secrete serotonin, driving carcinoid syndrome when tumor burden bypasses hepatic clearance.
Show evidence (1 reference)
PMID:28448665 SUPPORT Human Clinical
"In the SEER 18 registry grouping (2000-2012), the highest incidence rates were 1.49 per 100 000 in the lung, 3.56 per 100 000 in gastroenteropancreatic sites"
The Dasari SEER analysis establishes gastroenteropancreatic sites as the most common location of neuroendocrine tumors, anchoring the GEP-NEN concept.
MEN1 Tumor Suppressor Inactivation
Loss-of-function mutations in MEN1 (encoding menin) occur in approximately 44% of sporadic pancreatic NETs and define the hereditary MEN1 syndrome. Menin is a chromatin-modifying scaffold for the MLL/SET1-like histone methyltransferase complex regulating H3K4 methylation. Loss disrupts epigenetic control of cell cycle genes, driving uncontrolled proliferation of islet cells.
pancreatic endocrine cell CL:0008024
chromatin organization GO:0006325 ↕ DYSREGULATED cell population proliferation GO:0008283 ↑ INCREASED
Downstream
mTOR Pathway Activation Epigenetic dysregulation cooperates with mTOR pathway lesions in driving pancreatic NET proliferation.
Show evidence (1 reference)
PMID:21252315 SUPPORT Human Clinical
"44% of the tumors had somatic inactivating mutations in MEN1, which encodes menin, a component of a histone methyltransferase complex"
Jiao et al. whole-exome sequencing established MEN1 as the most frequently mutated gene in sporadic pancreatic NETs and identified its chromatin-remodeling role.
DAXX/ATRX Chromatin Remodeling Deficiency
Mutually exclusive inactivating mutations in DAXX (~25%) or ATRX (~18%) occur in roughly 43% of pancreatic NETs. DAXX and ATRX form a complex depositing histone variant H3.3 at telomeres and pericentric heterochromatin; loss drives alternative lengthening of telomeres (ALT) and chromosomal instability.
pancreatic endocrine cell CL:0008024
telomere maintenance GO:0000723 ↕ DYSREGULATED chromatin organization GO:0006325 ↕ DYSREGULATED
Show evidence (1 reference)
PMID:21252315 SUPPORT Human Clinical
"43% had mutations in genes encoding either of the two subunits of a transcription/chromatin remodeling complex consisting of DAXX (death-domain-associated protein) and ATRX"
Jiao et al. identified DAXX/ATRX as the second most commonly altered pathway in pancreatic NETs, with mutual exclusivity between the two genes.
mTOR Pathway Activation
Mutations in mTOR pathway genes (PTEN, TSC2, PIK3CA) occur in approximately 14% of pancreatic NETs, producing constitutive PI3K/AKT/mTOR signaling that drives growth, proliferation, and angiogenesis. This pathway is the therapeutic target of the mTOR inhibitor everolimus.
TORC1 signaling GO:0038202 ↑ INCREASED PI3K/AKT signaling GO:0043491 ↑ INCREASED cell population proliferation GO:0008283 ↑ INCREASED
Show evidence (2 references)
PMID:21252315 SUPPORT Human Clinical
"We also found mutations in genes in the mTOR (mammalian target of rapamycin) pathway in 14% of the tumors, a finding that could potentially be used to stratify patients for treatment with mTOR inhibitors."
Jiao et al. identified mTOR pathway mutations at 14% frequency and proposed their use for therapeutic stratification.
PMID:21306238 SUPPORT Human Clinical
"Everolimus, as compared with placebo, significantly prolonged progression-free survival among patients with progressive advanced pancreatic neuroendocrine tumors and was associated with a low rate of severe adverse events."
The RADIANT-3 trial validates mTOR-pathway activation as a clinically actionable mechanism in advanced pancreatic NETs.
Somatostatin Receptor Overexpression
Most well-differentiated GEP-NETs strongly overexpress somatostatin receptors (predominantly SSTR2). Somatostatin receptor signaling inhibits hormone secretion and cell proliferation; pharmacologic engagement with somatostatin analogs controls hormonal syndromes and exerts an antiproliferative effect, while receptor expression enables SSTR-targeted imaging and peptide receptor radionuclide therapy.
neuroendocrine cell CL:0000165
somatostatin signaling pathway GO:0038170 ↑ INCREASED
Show evidence (1 reference)
PMID:28076709 SUPPORT Human Clinical
"This randomized, controlled trial evaluated the efficacy and safety of lutetium-177 (177Lu)-Dotatate in patients with advanced, progressive, somatostatin-receptor-positive midgut neuroendocrine tumors."
The NETTER-1 trial confirms that GEP-NETs express somatostatin receptors, enabling somatostatin-receptor-targeted radionuclide therapy.
Serotonin Hypersecretion and Carcinoid Syndrome
Serotonin-producing well-differentiated NETs, classically of the small intestine, secrete serotonin and other vasoactive mediators. When hepatic metastases bypass first-pass hepatic clearance, systemic serotonin drives carcinoid syndrome (flushing, secretory diarrhea) and, through chronic valvular endocardial fibrosis, carcinoid heart disease.
serotonin-secreting enterochromaffin cell CL:0000577
serotonin and vasoactive hormone secretion GO:0046879 ↑ INCREASED
Show evidence (2 references)
PMID:32322270 SUPPORT Human Clinical
"Neuroendocrine neoplasms can produce multiple hormones: 5-hydroxytryptamine (serotonin) is the most well-known one, but histamine, catecholamines, and brady/tachykinins are also released."
This dedicated carcinoid-syndrome review confirms that neuroendocrine neoplasms hypersecrete serotonin (5-hydroxytryptamine) together with other vasoactive mediators, the driver of carcinoid syndrome in serotonin-producing midgut NETs.
PMID:32322270 SUPPORT Human Clinical
"Serotonin overproduction can lead to symptoms and also stimulates fibrosis formation which can result in development of carcinoid syndrome-associated complications such as carcinoid heart disease (CaHD) and mesenteric fibrosis."
Serotonin overproduction drives the secretory symptoms of carcinoid syndrome and, through chronic fibrosis, carcinoid heart disease, supporting this node's claim.
TP53/RB1 Inactivation in Neuroendocrine Carcinoma
Poorly differentiated neuroendocrine carcinomas (small-cell and large-cell) are genetically distinct from well-differentiated NETs, characterized by frequent inactivation of the TP53 and RB1 tumor suppressors. This drives loss of cell-cycle control, genomic instability, rapid proliferation, and a clinical course resembling small-cell lung carcinoma.
cell cycle checkpoint dysregulation GO:0000075 ↕ DYSREGULATED cell population proliferation GO:0008283 ↑ INCREASED
Show evidence (2 references)
PMID:34880079 SUPPORT Human Clinical
"Alterations in TP53 and RB1 proved common in GIS-NECs, and most Nonpanc-NECs with intact RB1 demonstrated mutually exclusive amplification of CCNE1 or MYC."
Yachida et al. comprehensively profiled 115 gastrointestinal neuroendocrine carcinomas and found TP53 and RB1 alterations common in GIS-NECs, directly supporting TP53/RB1 inactivation as the defining genomic mechanism of NEC.
PMID:34880079 SUPPORT Human Clinical
"found GIS-NECs to be genetically distinct from neuroendocrine tumors"
The same study establishes that poorly differentiated GIS-NECs are genetically distinct from well-differentiated neuroendocrine tumors of the same location, supporting the separate NEC pathophysiology node.
✶

Histopathology

3
Neuroendocrine differentiation on immunohistochemistry FREQUENT
Diagnosis of a GEP-NEN requires demonstration of a neuroendocrine phenotype by immunohistochemistry, conventionally positive staining for synaptophysin and chromogranin A (with INSM1 an emerging sensitive nuclear marker). These markers confirm the neuroendocrine lineage shared by both well-differentiated NETs and poorly differentiated NECs.
High-grade Ki-67 proliferation index
GEP-NENs are graded by the Ki-67 labeling index and mitotic count in hotspot areas: G1 (Ki-67 <3%), G2 (3-20%), and G3 (>20%). High grade (Ki-67 >20%) separates indolent well-differentiated NETs from high-grade tumors and, together with differentiation, distinguishes well-differentiated NET G3 from poorly differentiated NEC.
Poorly differentiated neuroendocrine carcinoma morphology
Poorly differentiated NECs show small-cell or large-cell morphology with high mitotic rate, necrosis, and a genomic profile (frequent TP53 and RB1 alterations) genetically distinct from well-differentiated NETs of the same site.
Show evidence (1 reference)
PMID:34880079 SUPPORT Human Clinical
"found GIS-NECs to be genetically distinct from neuroendocrine tumors"
Yachida et al. confirm that poorly differentiated gastrointestinal NECs are a genetically distinct entity from well-differentiated neuroendocrine tumors, underpinning their separate histopathologic and molecular classification.
⬡

Pathograph

Use the checkboxes to hide or show graph categories. Hover nodes for evidence and cross-linked metadata.
Pathograph: causal mechanism network for Gastroenteropancreatic Neuroendocrine Neoplasm Interactive directed graph showing how pathophysiology mechanisms, phenotypes, genetic factors and variants, experimental models, environmental triggers, and treatments relate through causal and linked edges.
●

Phenotypes

9
Digestive 3
Hepatic Metastases Neoplasm of the liver HP:0002896
HPO lacks a dedicated hepatic-metastasis term; HP:0002896 (Neoplasm of the liver) is the closest available mapping.
Diarrhea Diarrhea HP:0002014
Recurrent Peptic Ulcers Peptic ulcer HP:0004398
Integument 1
Flushing Flushing HP:0031284
Metabolism 1
Hypoglycemia Hypoglycemia HP:0001943
Constitutional 1
Abdominal Pain Abdominal pain HP:0002027
Growth 1
Unintentional Weight Loss Weight loss HP:0001824
Other 2
Gastroenteropancreatic Mass Intestinal carcinoid HP:0006723
Carcinoid Heart Disease Tricuspid regurgitation HP:0005180
HPO lacks a dedicated carcinoid-heart-disease term; HP:0005180 (Tricuspid regurgitation) captures the predominant right-sided valvular lesion.
🧬

Genetic Associations

5
MEN1 (Loss-of-function mutations in ~44% of sporadic pancreatic NETs; defines MEN1 syndrome)
Show evidence (1 reference)
PMID:21252315 SUPPORT Human Clinical
"44% of the tumors had somatic inactivating mutations in MEN1, which encodes menin, a component of a histone methyltransferase complex"
Jiao et al. established MEN1 as the most frequently mutated gene in sporadic pancreatic NETs at 44%.
DAXX (Inactivating mutations in ~25% of pancreatic NETs; mutually exclusive with ATRX)
Show evidence (1 reference)
PMID:21252315 SUPPORT Human Clinical
"somatic mutations in MEN1, DAXX, ATRX, PTEN, TSC2, and PIK3CA were identified in 44.1%, 25%, 17.6%, 7.3%, 8.8%, and 1.4% PanNETs, respectively"
DAXX mutations were found in 25% of pancreatic NETs in the combined cohorts.
ATRX (Inactivating mutations in ~18% of pancreatic NETs; mutually exclusive with DAXX)
Show evidence (1 reference)
PMID:21252315 SUPPORT Human Clinical
"somatic mutations in MEN1, DAXX, ATRX, PTEN, TSC2, and PIK3CA were identified in 44.1%, 25%, 17.6%, 7.3%, 8.8%, and 1.4% PanNETs, respectively"
ATRX mutations were found in 17.6% of pancreatic NETs, mutually exclusive with DAXX.
PTEN (Inactivating mutations in ~7% of pancreatic NETs; mTOR pathway component)
Show evidence (1 reference)
PMID:21252315 SUPPORT Human Clinical
"somatic mutations in MEN1, DAXX, ATRX, PTEN, TSC2, and PIK3CA were identified in 44.1%, 25%, 17.6%, 7.3%, 8.8%, and 1.4% PanNETs, respectively"
PTEN was mutated in 7.3% of pancreatic NETs in the Jiao et al. cohort.
TSC2 (Inactivating mutations in ~9% of pancreatic NETs; mTOR pathway component)
Show evidence (1 reference)
PMID:21252315 SUPPORT Human Clinical
"somatic mutations in MEN1, DAXX, ATRX, PTEN, TSC2, and PIK3CA were identified in 44.1%, 25%, 17.6%, 7.3%, 8.8%, and 1.4% PanNETs, respectively"
TSC2 was mutated in 8.8% of pancreatic NETs.
💊

Medical Actions

8
Surgical Resection
Action: surgical resection MAXO:0000448
Surgery is the only curative treatment for localized GEP-NETs. Approach depends on site and size, from endoscopic resection of small rectal/gastric NETs to pancreaticoduodenectomy or bowel resection for larger tumors.
Somatostatin Analog Therapy
Action: Pharmacotherapy NCIT:C15986
Agent: octreotide CHEBI:7726 lanreotide CHEBI:135901
Somatostatin analogs (octreotide, lanreotide) control hormonal symptoms of functional GEP-NETs and exert an antiproliferative effect in well-differentiated G1/G2 tumors. The CLARINET trial showed lanreotide significantly prolonged progression-free survival in metastatic enteropancreatic NETs.
Show evidence (1 reference)
PMID:25014687 SUPPORT Human Clinical
"Lanreotide was associated with significantly prolonged progression-free survival among patients with metastatic enteropancreatic neuroendocrine tumors of grade 1 or 2 (Ki-67 <10%)."
The CLARINET phase 3 trial demonstrated lanreotide's antiproliferative benefit across metastatic enteropancreatic NETs.
Peptide Receptor Radionuclide Therapy (PRRT)
Action: radiation therapy MAXO:0000014
177Lu-DOTATATE (Lutathera) delivers targeted beta radiation to somatostatin-receptor-positive GEP-NETs. The NETTER-1 phase 3 trial established PRRT for advanced, progressive midgut NETs, markedly improving progression-free survival over high-dose octreotide.
Show evidence (1 reference)
PMID:28076709 SUPPORT Human Clinical
"treatment with 177Lu-Dotatate resulted in a risk of progression or death that was 79% lower than the risk associated with high-dose octreotide LAR."
The NETTER-1 trial demonstrated a 79% reduction in risk of progression or death with 177Lu-Dotatate PRRT in advanced somatostatin-receptor-positive midgut NETs.
Everolimus (mTOR Inhibitor)
Action: Pharmacotherapy NCIT:C15986
Agent: everolimus CHEBI:68478
Everolimus, an oral mTOR inhibitor, is approved for advanced progressive pancreatic and gastrointestinal NETs based on the RADIANT trials, targeting the PI3K/AKT/mTOR pathway.
Show evidence (1 reference)
PMID:21306238 SUPPORT Human Clinical
"Everolimus, as compared with placebo, significantly prolonged progression-free survival among patients with progressive advanced pancreatic neuroendocrine tumors and was associated with a low rate of severe adverse events."
The RADIANT-3 phase 3 trial established everolimus as standard therapy for advanced progressive pancreatic NETs.
Sunitinib (Multi-Kinase Inhibitor)
Action: targeted therapy Ontology label: Targeted Therapy NCIT:C93352
Agent: sunitinib CHEBI:38940
Sunitinib, a multi-targeted receptor tyrosine kinase inhibitor (VEGFR, PDGFR, c-KIT), is approved for progressive well-differentiated pancreatic NETs and improved progression-free and overall survival in its registration trial.
Show evidence (1 reference)
PMID:21306237 SUPPORT Human Clinical
"Continuous daily administration of sunitinib at a dose of 37.5 mg improved progression-free survival, overall survival, and the objective response rate as compared with placebo among patients with advanced pancreatic neuroendocrine tumors."
The phase 3 sunitinib trial demonstrated PFS and overall-survival benefit in advanced well-differentiated pancreatic NETs.
Temozolomide-Based Chemotherapy
Action: chemotherapy MAXO:0000647
Agent: temozolomide CHEBI:72564 capecitabine NCIT:C1794
Temozolomide, alone or combined with capecitabine (CAPTEM), is used for advanced pancreatic NETs; the E2211 randomized trial showed CAPTEM significantly improved progression-free survival over temozolomide alone.
Show evidence (1 reference)
PMID:36260828 SUPPORT Human Clinical
"The combination of capecitabine/temozolomide was associated with a significant improvement in PFS compared with temozolomide alone in patients with advanced pancreatic NETs."
The E2211 randomized phase II trial demonstrated CAPTEM superiority over temozolomide monotherapy in advanced pancreatic NETs.
Telotristat (Tryptophan Hydroxylase Inhibitor)
Action: Pharmacotherapy NCIT:C15986
Agent: telotristat NCIT:C152549
Telotristat ethyl inhibits tryptophan hydroxylase, the rate-limiting enzyme in serotonin synthesis, reducing serotonin production to control refractory carcinoid-syndrome diarrhea in patients inadequately controlled on somatostatin analogs.
Show evidence (1 reference)
PMID:32322270 SUPPORT Human Clinical
"Telotristat ethyl and peptide receptor radionuclide therapy (PRRT) have recently become available for patients with symptoms despite being established on SSA's."
This carcinoid-syndrome review identifies telotristat ethyl as an option for patients with persistent symptoms despite somatostatin-analog therapy.
Platinum-Etoposide Chemotherapy (NEC)
Action: chemotherapy MAXO:0000647
Agent: carboplatin CHEBI:31355 etoposide CHEBI:4911
Poorly differentiated GEP-NECs are treated, analogously to small-cell lung carcinoma, with platinum-etoposide regimens (cisplatin or carboplatin plus etoposide) as first-line systemic therapy.
Show evidence (1 reference)
PMID:26636658 SUPPORT Human Clinical
"carboplatin-etoposide combination therapy has been used to treat almost all NEC patients in our department"
This retrospective series supports carboplatin-etoposide combination chemotherapy as a first-line regimen for poorly differentiated neuroendocrine carcinoma.
🔬

Biochemical Markers

3
Chromogranin A
Ki-67 Proliferation Index
Urinary 5-HIAA
{ }

Source YAML

click to show 
name: Gastroenteropancreatic Neuroendocrine Neoplasm
creation_date: "2026-06-17T00:00:00Z"
description: >-
  Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are a heterogeneous
  family of tumors arising from the diffuse neuroendocrine cell system of the
  digestive tract and pancreas. They derive from cells that produce hormones and
  neuropeptides and arise mostly sporadically, and to a lesser extent in the
  context of inherited syndromes such as MEN1, von Hippel-Lindau, neurofibromatosis
  type 1, and tuberous sclerosis. GEP-NENs span a wide biological spectrum, from
  indolent well-differentiated neuroendocrine tumors (NETs, graded G1/G2/G3 by Ki-67
  proliferation index and mitotic rate) to highly aggressive poorly differentiated
  neuroendocrine carcinomas (NECs, small-cell and large-cell types). Tumors are
  further classified as functional (secreting bioactive hormones such as serotonin,
  insulin, gastrin, glucagon, or VIP and producing distinct clinical syndromes) or
  non-functional. Anatomic sites include the stomach, duodenum, small intestine,
  appendix, colon, rectum, and pancreas. The incidence of neuroendocrine tumors has
  risen sharply over recent decades, with gastroenteropancreatic sites the most common
  location. Pancreatic NETs are characterized by recurrent inactivation of MEN1,
  DAXX/ATRX, and mTOR pathway genes; small-intestinal NETs by chromosome 18 loss and a
  low mutation burden; and poorly differentiated NECs by TP53 and RB1 inactivation.
  Nearly all well-differentiated GEP-NETs express somatostatin receptors, which
  underpin both molecular imaging (SSTR PET) and somatostatin-analog and peptide
  receptor radionuclide therapy (PRRT).
categories:
- Solid Tumor
- Gastrointestinal Cancer
- Neuroendocrine Neoplasm
parents:
- digestive system neoplasm
- neuroendocrine neoplasm
disease_term:
  preferred_term: gastroenteropancreatic neuroendocrine neoplasm
  term:
    id: MONDO:0024503
    label: digestive system neuroendocrine neoplasm
classifications:
  harrisons_chapter:
  - classification_value: ONCOLOGY_HEMATOLOGY
    evidence:
    - reference: PMID:28448665
      supports: SUPPORT
      evidence_source: HUMAN_CLINICAL
      snippet: >-
        Trends in the Incidence, Prevalence, and Survival Outcomes in Patients With
        Neuroendocrine Tumors in the United States
      explanation: >-
        GEP-NENs are solid neoplasms managed within oncology, fitting the Harrison's
        Oncology and Hematology Part.
inheritance:
- name: Sporadic (somatic)
  description: >-
    The large majority of GEP-NENs arise sporadically through somatic driver
    alterations (MEN1, DAXX/ATRX, mTOR-pathway genes in pancreatic NETs; TP53/RB1
    in NECs) without a germline predisposition.
- name: Autosomal dominant (syndromic)
  inheritance_term:
    preferred_term: Autosomal dominant inheritance
    term:
      id: HP:0000006
      label: Autosomal dominant inheritance
  description: >-
    A minority of GEP-NENs occur within autosomal dominant tumor-predisposition
    syndromes, most prominently multiple endocrine neoplasia type 1 (MEN1), and
    also von Hippel-Lindau, neurofibromatosis type 1, and tuberous sclerosis.
  evidence:
  - reference: PMID:21252315
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      MEN1 is a tumor suppressor gene which, when mutated in the germline, predisposes
      to multiple endocrine neoplasia type 1 syndrome.
    explanation: >-
      Jiao et al. note that germline MEN1 mutation underlies the autosomal dominant
      MEN1 syndrome, the prototypical hereditary context for GEP-NENs.
has_subtypes:
- name: Well-Differentiated NET G1
  display_name: Well-differentiated neuroendocrine tumor, grade 1
  description: >-
    Low-grade well-differentiated neuroendocrine tumor with Ki-67 proliferation
    index <3% and mitotic count <2 per 2 mm2. Indolent biology with the most
    favorable prognosis.
- name: Well-Differentiated NET G2
  display_name: Well-differentiated neuroendocrine tumor, grade 2
  description: >-
    Intermediate-grade well-differentiated neuroendocrine tumor with Ki-67 of
    3-20% or mitotic count of 2-20 per 2 mm2.
- name: Well-Differentiated NET G3
  display_name: Well-differentiated neuroendocrine tumor, grade 3
  description: >-
    High-grade but still well-differentiated neuroendocrine tumor with Ki-67 >20%.
    Biologically and therapeutically distinct from poorly differentiated NEC,
    retaining organoid architecture and somatostatin receptor expression.
- name: Neuroendocrine Carcinoma
  display_name: Poorly differentiated neuroendocrine carcinoma (NEC)
  description: >-
    Poorly differentiated, high-grade neuroendocrine carcinoma (small-cell or
    large-cell type) with Ki-67 typically >55%, frequent TP53 and RB1 inactivation,
    rapid growth, and poor prognosis. Managed with platinum-etoposide chemotherapy
    analogous to small-cell lung carcinoma.
- name: Insulinoma
  description: >-
    Functional pancreatic NET secreting insulin and causing recurrent
    hyperinsulinemic hypoglycemia (Whipple triad). Most are small, solitary, and
    benign.
- name: Gastrinoma
  description: >-
    Functional gastrinoma (duodenal or pancreatic) secreting gastrin and causing
    Zollinger-Ellison syndrome with gastric acid hypersecretion, recurrent peptic
    ulcers, and diarrhea. About 25% occur in MEN1.
- name: Serotonin-Producing Carcinoid
  display_name: Serotonin-producing NET (carcinoid)
  description: >-
    Serotonin-secreting well-differentiated NET, classically of the small intestine
    (midgut), causing carcinoid syndrome (flushing, diarrhea, carcinoid heart
    disease) when hepatic metastases bypass first-pass hepatic clearance.
- name: VIPoma
  description: >-
    Functional pancreatic NET secreting vasoactive intestinal peptide (VIP),
    producing the Verner-Morrison syndrome of watery diarrhea, hypokalemia, and
    achlorhydria (WDHA syndrome).
- name: Glucagonoma
  description: >-
    Functional pancreatic NET secreting glucagon, causing the glucagonoma syndrome
    of necrolytic migratory erythema, diabetes mellitus, weight loss, and venous
    thromboembolism.
pathophysiology:
- name: Neuroendocrine Cell Origin and Differentiation
  description: >-
    GEP-NENs arise from the diffuse neuroendocrine cell compartment of the
    gastrointestinal tract and pancreatic islets. These cells specialize in
    producing hormones and neuropeptides and share a neuroendocrine phenotype
    expressing chromogranin A and synaptophysin. Tumor cells retain features of
    their cell of origin, including dense-core secretory granules and regulated
    hormone secretion.
  cell_types:
  - preferred_term: neuroendocrine cell
    term:
      id: CL:0000165
      label: neuroendocrine cell
  - preferred_term: enteroendocrine cell
    term:
      id: CL:0000164
      label: enteroendocrine cell
  biological_processes:
  - preferred_term: peptide hormone secretion (regulated neuroendocrine release)
    modifier: DYSREGULATED
    term:
      id: GO:0030072
      label: peptide hormone secretion
  downstream:
  - target: Somatostatin Receptor Overexpression
    description: >-
      The retained neuroendocrine differentiation program underlies strong
      somatostatin receptor expression in well-differentiated GEP-NETs, which
      enables SSTR-targeted imaging and therapy.
  - target: Serotonin Hypersecretion and Carcinoid Syndrome
    description: >-
      Enterochromaffin-lineage neuroendocrine cells of the midgut secrete
      serotonin, driving carcinoid syndrome when tumor burden bypasses hepatic
      clearance.
  evidence:
  - reference: PMID:28448665
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      In the SEER 18 registry grouping (2000-2012), the highest incidence
      rates were 1.49 per 100 000 in the lung, 3.56 per 100 000 in
      gastroenteropancreatic sites
    explanation: >-
      The Dasari SEER analysis establishes gastroenteropancreatic sites as the
      most common location of neuroendocrine tumors, anchoring the GEP-NEN concept.
- name: MEN1 Tumor Suppressor Inactivation
  description: >-
    Loss-of-function mutations in MEN1 (encoding menin) occur in approximately 44%
    of sporadic pancreatic NETs and define the hereditary MEN1 syndrome. Menin is a
    chromatin-modifying scaffold for the MLL/SET1-like histone methyltransferase
    complex regulating H3K4 methylation. Loss disrupts epigenetic control of cell
    cycle genes, driving uncontrolled proliferation of islet cells.
  cell_types:
  - preferred_term: pancreatic endocrine cell
    term:
      id: CL:0008024
      label: pancreatic endocrine cell
  biological_processes:
  - preferred_term: chromatin organization
    modifier: DYSREGULATED
    term:
      id: GO:0006325
      label: chromatin organization
  - preferred_term: cell population proliferation
    modifier: INCREASED
    term:
      id: GO:0008283
      label: cell population proliferation
  downstream:
  - target: mTOR Pathway Activation
    description: >-
      Epigenetic dysregulation cooperates with mTOR pathway lesions in driving
      pancreatic NET proliferation.
  evidence:
  - reference: PMID:21252315
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      44% of the tumors had somatic inactivating mutations in MEN1, which encodes
      menin, a component of a histone methyltransferase complex
    explanation: >-
      Jiao et al. whole-exome sequencing established MEN1 as the most frequently
      mutated gene in sporadic pancreatic NETs and identified its chromatin-remodeling
      role.
- name: DAXX/ATRX Chromatin Remodeling Deficiency
  description: >-
    Mutually exclusive inactivating mutations in DAXX (~25%) or ATRX (~18%) occur in
    roughly 43% of pancreatic NETs. DAXX and ATRX form a complex depositing histone
    variant H3.3 at telomeres and pericentric heterochromatin; loss drives
    alternative lengthening of telomeres (ALT) and chromosomal instability.
  cell_types:
  - preferred_term: pancreatic endocrine cell
    term:
      id: CL:0008024
      label: pancreatic endocrine cell
  biological_processes:
  - preferred_term: telomere maintenance
    modifier: DYSREGULATED
    term:
      id: GO:0000723
      label: telomere maintenance
  - preferred_term: chromatin organization
    modifier: DYSREGULATED
    term:
      id: GO:0006325
      label: chromatin organization
  evidence:
  - reference: PMID:21252315
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      43% had mutations in genes encoding either of the two subunits of a
      transcription/chromatin remodeling complex consisting of DAXX
      (death-domain-associated protein) and ATRX
    explanation: >-
      Jiao et al. identified DAXX/ATRX as the second most commonly altered pathway in
      pancreatic NETs, with mutual exclusivity between the two genes.
- name: mTOR Pathway Activation
  description: >-
    Mutations in mTOR pathway genes (PTEN, TSC2, PIK3CA) occur in approximately 14%
    of pancreatic NETs, producing constitutive PI3K/AKT/mTOR signaling that drives
    growth, proliferation, and angiogenesis. This pathway is the therapeutic target
    of the mTOR inhibitor everolimus.
  biological_processes:
  - preferred_term: TORC1 signaling
    modifier: INCREASED
    term:
      id: GO:0038202
      label: TORC1 signaling
  - preferred_term: PI3K/AKT signaling
    modifier: INCREASED
    term:
      id: GO:0043491
      label: phosphatidylinositol 3-kinase/protein kinase B signal transduction
  - preferred_term: cell population proliferation
    modifier: INCREASED
    term:
      id: GO:0008283
      label: cell population proliferation
  evidence:
  - reference: PMID:21252315
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      We also found mutations in genes in the mTOR (mammalian target of rapamycin)
      pathway in 14% of the tumors, a finding that could potentially be used to
      stratify patients for treatment with mTOR inhibitors.
    explanation: >-
      Jiao et al. identified mTOR pathway mutations at 14% frequency and proposed
      their use for therapeutic stratification.
  - reference: PMID:21306238
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      Everolimus, as compared with placebo, significantly prolonged progression-free
      survival among patients with progressive advanced pancreatic neuroendocrine
      tumors and was associated with a low rate of severe adverse events.
    explanation: >-
      The RADIANT-3 trial validates mTOR-pathway activation as a clinically
      actionable mechanism in advanced pancreatic NETs.
- name: Somatostatin Receptor Overexpression
  description: >-
    Most well-differentiated GEP-NETs strongly overexpress somatostatin receptors
    (predominantly SSTR2). Somatostatin receptor signaling inhibits hormone secretion
    and cell proliferation; pharmacologic engagement with somatostatin analogs
    controls hormonal syndromes and exerts an antiproliferative effect, while
    receptor expression enables SSTR-targeted imaging and peptide receptor
    radionuclide therapy.
  cell_types:
  - preferred_term: neuroendocrine cell
    term:
      id: CL:0000165
      label: neuroendocrine cell
  biological_processes:
  - preferred_term: somatostatin signaling pathway
    modifier: INCREASED
    term:
      id: GO:0038170
      label: somatostatin signaling pathway
  evidence:
  - reference: PMID:28076709
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      This randomized, controlled trial evaluated the efficacy
      and safety of lutetium-177 (177Lu)-Dotatate in patients with advanced,
      progressive, somatostatin-receptor-positive midgut neuroendocrine tumors.
    explanation: >-
      The NETTER-1 trial confirms that GEP-NETs express somatostatin receptors,
      enabling somatostatin-receptor-targeted radionuclide therapy.
- name: Serotonin Hypersecretion and Carcinoid Syndrome
  description: >-
    Serotonin-producing well-differentiated NETs, classically of the small intestine,
    secrete serotonin and other vasoactive mediators. When hepatic metastases bypass
    first-pass hepatic clearance, systemic serotonin drives carcinoid syndrome
    (flushing, secretory diarrhea) and, through chronic valvular endocardial fibrosis,
    carcinoid heart disease.
  cell_types:
  - preferred_term: serotonin-secreting enterochromaffin cell
    term:
      id: CL:0000577
      label: type EC enteroendocrine cell
  biological_processes:
  - preferred_term: serotonin and vasoactive hormone secretion
    modifier: INCREASED
    term:
      id: GO:0046879
      label: hormone secretion
  evidence:
  - reference: PMID:32322270
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      Neuroendocrine neoplasms can produce
      multiple hormones: 5-hydroxytryptamine (serotonin) is the most well-known one,
      but histamine, catecholamines, and brady/tachykinins are also released.
    explanation: >-
      This dedicated carcinoid-syndrome review confirms that neuroendocrine neoplasms
      hypersecrete serotonin (5-hydroxytryptamine) together with other vasoactive
      mediators, the driver of carcinoid syndrome in serotonin-producing midgut NETs.
  - reference: PMID:32322270
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      Serotonin overproduction can lead to symptoms and also stimulates fibrosis
      formation which can result in development of carcinoid syndrome-associated
      complications such as carcinoid heart disease (CaHD) and mesenteric fibrosis.
    explanation: >-
      Serotonin overproduction drives the secretory symptoms of carcinoid syndrome and,
      through chronic fibrosis, carcinoid heart disease, supporting this node's claim.
- name: TP53/RB1 Inactivation in Neuroendocrine Carcinoma
  description: >-
    Poorly differentiated neuroendocrine carcinomas (small-cell and large-cell) are
    genetically distinct from well-differentiated NETs, characterized by frequent
    inactivation of the TP53 and RB1 tumor suppressors. This drives loss of cell-cycle
    control, genomic instability, rapid proliferation, and a clinical course resembling
    small-cell lung carcinoma.
  biological_processes:
  - preferred_term: cell cycle checkpoint dysregulation
    modifier: DYSREGULATED
    term:
      id: GO:0000075
      label: cell cycle checkpoint signaling
  - preferred_term: cell population proliferation
    modifier: INCREASED
    term:
      id: GO:0008283
      label: cell population proliferation
  evidence:
  - reference: PMID:34880079
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      Alterations in TP53 and RB1 proved common in GIS-NECs, and most Nonpanc-NECs
      with intact RB1 demonstrated mutually exclusive amplification of CCNE1 or MYC.
    explanation: >-
      Yachida et al. comprehensively profiled 115 gastrointestinal neuroendocrine
      carcinomas and found TP53 and RB1 alterations common in GIS-NECs, directly
      supporting TP53/RB1 inactivation as the defining genomic mechanism of NEC.
  - reference: PMID:34880079
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      found GIS-NECs to be genetically distinct from neuroendocrine tumors
    explanation: >-
      The same study establishes that poorly differentiated GIS-NECs are genetically
      distinct from well-differentiated neuroendocrine tumors of the same location,
      supporting the separate NEC pathophysiology node.
phenotypes:
- category: Neoplasm
  name: Gastroenteropancreatic Mass
  description: >-
    A primary neuroendocrine tumor mass in the stomach, small intestine, appendix,
    colon, rectum, or pancreas, often hypervascular on imaging.
  phenotype_term:
    preferred_term: intestinal carcinoid / neuroendocrine tumor
    term:
      id: HP:0006723
      label: Intestinal carcinoid
- category: Neoplasm
  name: Hepatic Metastases
  description: >-
    The liver is the most common site of distant spread for GEP-NETs and is the
    determinant of carcinoid syndrome in serotonin-producing tumors.
  notes: >-
    HPO lacks a dedicated hepatic-metastasis term; HP:0002896 (Neoplasm of the liver)
    is the closest available mapping.
  phenotype_term:
    preferred_term: hepatic metastases
    term:
      id: HP:0002896
      label: Neoplasm of the liver
- name: Flushing
  description: >-
    Episodic cutaneous flushing is a cardinal feature of carcinoid syndrome from
    serotonin-producing NETs with hepatic metastases.
  phenotype_term:
    preferred_term: flushing
    term:
      id: HP:0031284
      label: Flushing
- name: Diarrhea
  description: >-
    Secretory diarrhea results from serotonin (carcinoid syndrome), gastrin
    (Zollinger-Ellison), or VIP (VIPoma) hypersecretion.
  phenotype_term:
    preferred_term: diarrhea
    term:
      id: HP:0002014
      label: Diarrhea
- name: Hypoglycemia
  description: >-
    Recurrent hyperinsulinemic hypoglycemia caused by autonomous insulin secretion
    from insulinomas.
  phenotype_term:
    preferred_term: hypoglycemia
    term:
      id: HP:0001943
      label: Hypoglycemia
- name: Recurrent Peptic Ulcers
  description: >-
    Multiple or refractory peptic ulcers from gastrin-driven gastric acid
    hypersecretion (Zollinger-Ellison syndrome) in gastrinomas.
  phenotype_term:
    preferred_term: peptic ulcer
    term:
      id: HP:0004398
      label: Peptic ulcer
- name: Abdominal Pain
  description: >-
    Nonspecific abdominal pain is common from mass effect, bowel obstruction, or
    hepatic metastases.
  phenotype_term:
    preferred_term: abdominal pain
    term:
      id: HP:0002027
      label: Abdominal pain
- name: Unintentional Weight Loss
  description: >-
    Progressive weight loss occurs with advanced tumor burden and metastatic disease.
  phenotype_term:
    preferred_term: weight loss
    term:
      id: HP:0001824
      label: Weight loss
- name: Carcinoid Heart Disease
  description: >-
    Chronic serotonin exposure causes plaque-like fibrous endocardial thickening of
    the tricuspid and pulmonary valves, producing right-sided valvular regurgitation
    and heart failure in advanced carcinoid syndrome.
  notes: >-
    HPO lacks a dedicated carcinoid-heart-disease term; HP:0005180 (Tricuspid
    regurgitation) captures the predominant right-sided valvular lesion.
  phenotype_term:
    preferred_term: tricuspid regurgitation (carcinoid heart disease)
    term:
      id: HP:0005180
      label: Tricuspid regurgitation
histopathology:
- name: Neuroendocrine differentiation on immunohistochemistry
  finding_term:
    preferred_term: neuroendocrine differentiation (synaptophysin/chromogranin A positivity)
    term:
      id: NCIT:C43574
      label: Neuroendocrine Differentiation
  diagnostic: true
  frequency: FREQUENT
  description: >-
    Diagnosis of a GEP-NEN requires demonstration of a neuroendocrine phenotype by
    immunohistochemistry, conventionally positive staining for synaptophysin and
    chromogranin A (with INSM1 an emerging sensitive nuclear marker). These markers
    confirm the neuroendocrine lineage shared by both well-differentiated NETs and
    poorly differentiated NECs.
- name: High-grade Ki-67 proliferation index
  finding_term:
    preferred_term: high histologic grade (Ki-67 >20%, mitotic count)
    term:
      id: NCIT:C14158
      label: High Grade
  description: >-
    GEP-NENs are graded by the Ki-67 labeling index and mitotic count in hotspot
    areas: G1 (Ki-67 <3%), G2 (3-20%), and G3 (>20%). High grade (Ki-67 >20%)
    separates indolent well-differentiated NETs from high-grade tumors and, together
    with differentiation, distinguishes well-differentiated NET G3 from poorly
    differentiated NEC.
- name: Poorly differentiated neuroendocrine carcinoma morphology
  finding_term:
    preferred_term: poorly differentiated neuroendocrine carcinoma (small-cell/large-cell)
    term:
      id: NCIT:C3773
      label: Neuroendocrine Carcinoma
  description: >-
    Poorly differentiated NECs show small-cell or large-cell morphology with high
    mitotic rate, necrosis, and a genomic profile (frequent TP53 and RB1 alterations)
    genetically distinct from well-differentiated NETs of the same site.
  evidence:
  - reference: PMID:34880079
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      found GIS-NECs to be genetically distinct from neuroendocrine tumors
    explanation: >-
      Yachida et al. confirm that poorly differentiated gastrointestinal NECs are a
      genetically distinct entity from well-differentiated neuroendocrine tumors,
      underpinning their separate histopathologic and molecular classification.
biochemical:
- name: Chromogranin A
  notes: >-
    Chromogranin A is the principal circulating tumor marker for well-differentiated
    GEP-NETs, reflecting neuroendocrine secretory granule content and total tumor
    burden.
  biomarker_term:
    preferred_term: Chromogranin A
    term:
      id: NCIT:C17284
      label: Chromogranin-A
- name: Ki-67 Proliferation Index
  notes: >-
    The Ki-67 labeling index is the central grading biomarker for GEP-NENs,
    stratifying tumors into G1 (<3%), G2 (3-20%), and G3 (>20%) and distinguishing
    well-differentiated NETs from poorly differentiated NECs.
  biomarker_term:
    preferred_term: Ki67 Measurement
    term:
      id: NCIT:C123557
      label: Ki67 Measurement
- name: Urinary 5-HIAA
  notes: >-
    24-hour urinary 5-hydroxyindoleacetic acid (5-HIAA), the major serotonin
    metabolite, is the principal biochemical marker for serotonin-producing
    midgut NETs and carcinoid syndrome; elevated levels reflect serotonin
    overproduction.
  biomarker_term:
    preferred_term: 5-Hydroxyindoleacetic Acid
    term:
      id: NCIT:C28157
      label: 5-Hydroxyindoleacetic Acid
genetic:
- name: MEN1
  association: Loss-of-function mutations in ~44% of sporadic pancreatic NETs; defines MEN1 syndrome
  frequency: FREQUENT
  notes: >-
    Menin is a chromatin-modifying scaffold regulating H3K4 methylation. Germline
    MEN1 mutations cause familial GEP-NETs (especially gastrinoma and pancreatic NET).
  evidence:
  - reference: PMID:21252315
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      44% of the tumors had somatic inactivating mutations in MEN1, which encodes
      menin, a component of a histone methyltransferase complex
    explanation: >-
      Jiao et al. established MEN1 as the most frequently mutated gene in sporadic
      pancreatic NETs at 44%.
- name: DAXX
  association: Inactivating mutations in ~25% of pancreatic NETs; mutually exclusive with ATRX
  frequency: OCCASIONAL
  notes: >-
    DAXX is an H3.3-specific histone chaperone; loss drives alternative lengthening of
    telomeres and chromosomal instability.
  evidence:
  - reference: PMID:21252315
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      somatic mutations in MEN1, DAXX, ATRX, PTEN, TSC2, and PIK3CA were identified
      in 44.1%, 25%, 17.6%, 7.3%, 8.8%, and 1.4% PanNETs, respectively
    explanation: >-
      DAXX mutations were found in 25% of pancreatic NETs in the combined cohorts.
- name: ATRX
  association: Inactivating mutations in ~18% of pancreatic NETs; mutually exclusive with DAXX
  frequency: OCCASIONAL
  notes: >-
    ATRX encodes a helicase interacting with DAXX for H3.3 deposition at telomeres;
    loss leads to ALT and larger tumor size.
  evidence:
  - reference: PMID:21252315
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      somatic mutations in MEN1, DAXX, ATRX, PTEN, TSC2, and PIK3CA were identified
      in 44.1%, 25%, 17.6%, 7.3%, 8.8%, and 1.4% PanNETs, respectively
    explanation: >-
      ATRX mutations were found in 17.6% of pancreatic NETs, mutually exclusive with DAXX.
- name: PTEN
  association: Inactivating mutations in ~7% of pancreatic NETs; mTOR pathway component
  frequency: OCCASIONAL
  notes: >-
    PTEN loss activates PI3K/AKT/mTOR signaling, providing rationale for everolimus.
  evidence:
  - reference: PMID:21252315
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      somatic mutations in MEN1, DAXX, ATRX, PTEN, TSC2, and PIK3CA were identified
      in 44.1%, 25%, 17.6%, 7.3%, 8.8%, and 1.4% PanNETs, respectively
    explanation: >-
      PTEN was mutated in 7.3% of pancreatic NETs in the Jiao et al. cohort.
- name: TSC2
  association: Inactivating mutations in ~9% of pancreatic NETs; mTOR pathway component
  frequency: OCCASIONAL
  notes: >-
    TSC2 loss disinhibits mTOR signaling; combined mTOR-pathway lesions affect ~14%
    of pancreatic NETs.
  evidence:
  - reference: PMID:21252315
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      somatic mutations in MEN1, DAXX, ATRX, PTEN, TSC2, and PIK3CA were identified
      in 44.1%, 25%, 17.6%, 7.3%, 8.8%, and 1.4% PanNETs, respectively
    explanation: >-
      TSC2 was mutated in 8.8% of pancreatic NETs.
treatments:
- name: Surgical Resection
  description: >-
    Surgery is the only curative treatment for localized GEP-NETs. Approach depends on
    site and size, from endoscopic resection of small rectal/gastric NETs to
    pancreaticoduodenectomy or bowel resection for larger tumors.
  treatment_term:
    preferred_term: surgical resection
    term:
      id: MAXO:0000448
      label: surgical resection
- name: Somatostatin Analog Therapy
  description: >-
    Somatostatin analogs (octreotide, lanreotide) control hormonal symptoms of
    functional GEP-NETs and exert an antiproliferative effect in well-differentiated
    G1/G2 tumors. The CLARINET trial showed lanreotide significantly prolonged
    progression-free survival in metastatic enteropancreatic NETs.
  therapeutic_modality: PEPTIDE
  treatment_term:
    preferred_term: Pharmacotherapy
    term:
      id: NCIT:C15986
      label: Pharmacotherapy
    therapeutic_agent:
    - preferred_term: octreotide
      term:
        id: CHEBI:7726
        label: octreotide
    - preferred_term: lanreotide
      term:
        id: CHEBI:135901
        label: lanreotide
  evidence:
  - reference: PMID:25014687
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      Lanreotide was associated with significantly prolonged progression-free survival
      among patients with metastatic enteropancreatic neuroendocrine tumors of grade
      1
      or 2 (Ki-67 <10%).
    explanation: >-
      The CLARINET phase 3 trial demonstrated lanreotide's antiproliferative benefit
      across metastatic enteropancreatic NETs.
- name: Peptide Receptor Radionuclide Therapy (PRRT)
  description: >-
    177Lu-DOTATATE (Lutathera) delivers targeted beta radiation to
    somatostatin-receptor-positive GEP-NETs. The NETTER-1 phase 3 trial established
    PRRT for advanced, progressive midgut NETs, markedly improving progression-free
    survival over high-dose octreotide.
  therapeutic_modality: RADIOTHERAPY
  treatment_term:
    preferred_term: radiation therapy
    term:
      id: MAXO:0000014
      label: radiation therapy
  evidence:
  - reference: PMID:28076709
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      treatment with 177Lu-Dotatate resulted in a risk of progression or death that
      was 79% lower than the risk associated with high-dose octreotide LAR.
    explanation: >-
      The NETTER-1 trial demonstrated a 79% reduction in risk of progression or death
      with 177Lu-Dotatate PRRT in advanced somatostatin-receptor-positive midgut NETs.
- name: Everolimus (mTOR Inhibitor)
  description: >-
    Everolimus, an oral mTOR inhibitor, is approved for advanced progressive
    pancreatic and gastrointestinal NETs based on the RADIANT trials, targeting the
    PI3K/AKT/mTOR pathway.
  therapeutic_modality: SMALL_MOLECULE
  treatment_term:
    preferred_term: Pharmacotherapy
    term:
      id: NCIT:C15986
      label: Pharmacotherapy
    therapeutic_agent:
    - preferred_term: everolimus
      term:
        id: CHEBI:68478
        label: everolimus
  evidence:
  - reference: PMID:21306238
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      Everolimus, as compared with placebo, significantly prolonged progression-free
      survival among patients with progressive advanced pancreatic neuroendocrine
      tumors and was associated with a low rate of severe adverse events.
    explanation: >-
      The RADIANT-3 phase 3 trial established everolimus as standard therapy for
      advanced progressive pancreatic NETs.
- name: Sunitinib (Multi-Kinase Inhibitor)
  description: >-
    Sunitinib, a multi-targeted receptor tyrosine kinase inhibitor (VEGFR, PDGFR,
    c-KIT), is approved for progressive well-differentiated pancreatic NETs and
    improved progression-free and overall survival in its registration trial.
  therapeutic_modality: SMALL_MOLECULE
  treatment_term:
    preferred_term: targeted therapy
    term:
      id: NCIT:C93352
      label: Targeted Therapy
    therapeutic_agent:
    - preferred_term: sunitinib
      term:
        id: CHEBI:38940
        label: sunitinib
  evidence:
  - reference: PMID:21306237
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      Continuous daily administration of sunitinib at a dose of 37.5 mg improved
      progression-free survival, overall survival, and the objective response rate
      as
      compared with placebo among patients with advanced pancreatic neuroendocrine
      tumors.
    explanation: >-
      The phase 3 sunitinib trial demonstrated PFS and overall-survival benefit in
      advanced well-differentiated pancreatic NETs.
- name: Temozolomide-Based Chemotherapy
  description: >-
    Temozolomide, alone or combined with capecitabine (CAPTEM), is used for advanced
    pancreatic NETs; the E2211 randomized trial showed CAPTEM significantly improved
    progression-free survival over temozolomide alone.
  therapeutic_modality: SMALL_MOLECULE
  treatment_term:
    preferred_term: chemotherapy
    term:
      id: MAXO:0000647
      label: chemotherapy
    therapeutic_agent:
    - preferred_term: temozolomide
      term:
        id: CHEBI:72564
        label: temozolomide
    - preferred_term: capecitabine
      term:
        id: NCIT:C1794
        label: Capecitabine
  evidence:
  - reference: PMID:36260828
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      The combination of capecitabine/temozolomide was associated with a significant
      improvement in PFS compared with temozolomide alone in patients with advanced
      pancreatic NETs.
    explanation: >-
      The E2211 randomized phase II trial demonstrated CAPTEM superiority over
      temozolomide monotherapy in advanced pancreatic NETs.
- name: Telotristat (Tryptophan Hydroxylase Inhibitor)
  description: >-
    Telotristat ethyl inhibits tryptophan hydroxylase, the rate-limiting enzyme in
    serotonin synthesis, reducing serotonin production to control refractory
    carcinoid-syndrome diarrhea in patients inadequately controlled on somatostatin
    analogs.
  therapeutic_modality: SMALL_MOLECULE
  treatment_term:
    preferred_term: Pharmacotherapy
    term:
      id: NCIT:C15986
      label: Pharmacotherapy
    therapeutic_agent:
    - preferred_term: telotristat
      term:
        id: NCIT:C152549
        label: Telotristat
  evidence:
  - reference: PMID:32322270
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      Telotristat ethyl and peptide
      receptor radionuclide therapy (PRRT) have recently become available for patients
      with symptoms despite being established on SSA's.
    explanation: >-
      This carcinoid-syndrome review identifies telotristat ethyl as an option for
      patients with persistent symptoms despite somatostatin-analog therapy.
- name: Platinum-Etoposide Chemotherapy (NEC)
  description: >-
    Poorly differentiated GEP-NECs are treated, analogously to small-cell lung
    carcinoma, with platinum-etoposide regimens (cisplatin or carboplatin plus
    etoposide) as first-line systemic therapy.
  therapeutic_modality: SMALL_MOLECULE
  treatment_term:
    preferred_term: chemotherapy
    term:
      id: MAXO:0000647
      label: chemotherapy
    therapeutic_agent:
    - preferred_term: carboplatin
      term:
        id: CHEBI:31355
        label: carboplatin
    - preferred_term: etoposide
      term:
        id: CHEBI:4911
        label: etoposide
  evidence:
  - reference: PMID:26636658
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      carboplatin-etoposide combination therapy has been used to treat almost all NEC
      patients in our department
    explanation: >-
      This retrospective series supports carboplatin-etoposide combination
      chemotherapy as a first-line regimen for poorly differentiated neuroendocrine
      carcinoma.
datasets:
references:
- reference: PMID:28448665
  title: "Trends in the Incidence, Prevalence, and Survival Outcomes in Patients With Neuroendocrine Tumors in the United States."
📚

References & Deep Research

References

1
PMID:28448665
Trends in the Incidence, Prevalence, and Survival Outcomes in Patients With Neuroendocrine Tumors in the United States.
No top-level findings curated for this source.

Deep Research

1
Falcon ▸
Disease Characteristics Research Template
Edison Scientific Literature 43 citations 2026-06-17T21:23:35.828224

Question: You are an expert researcher providing comprehensive, well-cited information.

Provide detailed information focusing on: 1. Key concepts and definitions with current understanding 2. Recent developments and latest research (prioritize 2023-2024 sources) 3. Current applications and real-world implementations 4. Expert opinions and analysis from authoritative sources 5. Relevant statistics and data from recent studies

Format as a comprehensive research report with proper citations. Include URLs and publication dates where available. Always prioritize recent, authoritative sources and provide specific citations for all major claims.

Disease Characteristics Research Template

Target Disease

  • Disease Name: Gastroenteropancreatic Neuroendocrine Neoplasm
  • MONDO ID: (if available)
  • Category:

Research Objectives

Please provide a comprehensive research report on Gastroenteropancreatic Neuroendocrine Neoplasm covering all of the disease characteristics listed below. This report will be used to populate a disease knowledge base entry. Be thorough and cite primary literature (PMID preferred) for all claims.

For each section, suggested databases/resources are listed. These are the first places you should search for information on each topic.

1. Disease Information

Search first: OMIM, Orphanet, ICD-10/ICD-11, MeSH, PubMed

  • What is the disease? Provide a concise overview.
  • What are the key identifiers? (OMIM, Orphanet, ICD-10/ICD-11, MeSH, Mondo)
  • What are the common synonyms and alternative names?
  • Is the information derived from individual patients (e.g., EHR) or aggregated disease-level resources?

2. Etiology

  • Disease Causal Factors: What are the primary causes? (genetic, environmental, infectious, mechanistic)
  • Risk Factors:

    Search first: PubMed, Cochrane Library, UpToDate, clinical guidelines, ClinVar, ClinGen, GWAS Catalog, PheGenI, CTD, CDC, WHO, epidemiological databases

  • Genetic risk factors (causal variants, susceptibility loci, modifier genes)
  • Environmental risk factors (toxins, lifestyle, occupational exposures, age, sex, family history)
  • Protective Factors:

    Search first: PubMed, Cochrane Library, clinical trial databases, GWAS Catalog, gnomAD, WHO, CDC, nutrition databases

  • Genetic protective factors (protective variants, modifier alleles)
  • Environmental protective factors (diet, lifestyle, exposures that reduce risk)
  • Gene-Environment Interactions: How do genetic and environmental factors interact to influence disease?

    Search first: CTD, PubMed, PheGenI, GxE databases

3. Phenotypes

Search first: HPO (Human Phenotype Ontology), OMIM, Orphanet, PubMed, clinicaltrials.gov, MedDRA, SNOMED CT, DECIPHER, LOINC

For each phenotype, provide: - Phenotype type: symptoms, clinical signs, physical manifestations, behavioral changes, or laboratory abnormalities

For symptoms/signs: HPO, OMIM, Orphanet, PubMed For behavioral changes: HPO, DSM, RDoC (Research Domain Criteria), PubMed For laboratory abnormalities: LOINC, SNOMED CT, LabTests Online, PubMed - Phenotype characteristics: Search first: OMIM, Orphanet, HPO, PubMed - Age of symptom onset (neonatal, childhood, adult-onset, late-onset) - Symptom severity (mild, moderate, severe, variable) - Symptom progression (stable, progressive, episodic, fluctuating) - Frequency among affected individuals (percentage or qualitative) - Quality of life impact: Effects on daily functioning and well-being (per-phenotype when possible) Search first: EQ-5D database, SF-36, WHO QOL databases, PubMed - Suggest HPO (Human Phenotype Ontology) terms for each phenotype

4. Genetic/Molecular Information

  • Causal Genes: Gene mutations or chromosomal abnormalities responsible for disease (gene symbols, OMIM IDs)

    Search first: OMIM, ClinVar, HGMD, Ensembl, NCBI Gene

  • Pathogenic Variants:
  • Affected genes (gene symbols, HGNC IDs) > Search first: OMIM, NCBI Gene, Ensembl, HGNC, UniProt, GeneCards
  • Variant classification (pathogenic, likely pathogenic, VUS per ACMG/AMP guidelines) > Search first: ClinVar, ClinGen, ACMG/AMP guidelines, VarSome
  • Variant type/class (missense, frameshift, nonsense, splice-site, structural)
  • Allele frequency in population databases > Search first: gnomAD, 1000 Genomes, ExAC, TOPMed, dbSNP
  • Somatic vs germline origin > Search first: COSMIC (somatic), ClinVar, ICGC, TCGA
  • Functional consequences (loss of function, gain of function, dominant negative)
  • Modifier Genes: Genes that modify disease severity or expression
  • Epigenetic Information: DNA methylation, histone modifications, chromatin changes affecting disease

    Search first: ENCODE, Roadmap Epigenomics, MethBase, DiseaseMeth

  • Chromosomal Abnormalities: Large-scale genetic changes (aneuploidy, translocations, inversions)

    Search first: DECIPHER, ClinVar, ECARUCA, UCSC Genome Browser

5. Environmental Information

  • Environmental Factors: Non-genetic contributing factors (toxins, radiation, pollution, occupational exposure)

    Search first: CTD (Comparative Toxicogenomics Database), TOXNET, PubMed, EPA databases

  • Lifestyle Factors: Behavioral factors (smoking, diet, exercise, alcohol consumption)

    Search first: CDC databases, WHO, PubMed, NHANES

  • Infectious Agents: If applicable, pathogens causing or triggering disease (bacteria, viruses, fungi, parasites)

    Search first: NCBI Taxonomy, ViPR, BV-BRC, MicrobeDB, GIDEON

6. Mechanism / Pathophysiology

  • Molecular Pathways: Specific signaling cascades or biochemical pathways involved (Wnt, MAPK, mTOR, PI3K-AKT, etc.)

    Search first: KEGG, Reactome, WikiPathways, PathBank, BioCyc

  • Cellular Processes: Cell-level mechanisms (apoptosis, autophagy, cell cycle dysregulation, inflammation, etc.)

    Search first: Gene Ontology (GO), Reactome, KEGG, PubMed

  • Protein Dysfunction: How protein structure or function is altered (misfolding, aggregation, loss of function, gain of function)

    Search first: UniProt, PDB (Protein Data Bank), InterPro, Pfam, AlphaFold

  • Metabolic Changes: Alterations in metabolic processes (energy metabolism, lipid metabolism, amino acid metabolism)

    Search first: KEGG, BioCyc, HMDB (Human Metabolome Database), BRENDA

  • Immune System Involvement: Role of immune response (autoimmunity, immunodeficiency, chronic inflammation)

    Search first: ImmPort, Immunome Database, IEDB, Gene Ontology

  • Tissue Damage Mechanisms: How tissues/ are injured (oxidative stress, ischemia, fibrosis, necrosis)

    Search first: PubMed, Gene Ontology, Reactome

  • Biochemical Abnormalities: Specific molecular defects (enzyme deficiencies, receptor dysfunction, ion channel defects)

    Search first: BRENDA, UniProt, KEGG, OMIM, PubMed

  • Epigenetic Changes: DNA methylation, histone modifications affecting gene expression in disease

    Search first: ENCODE, Roadmap Epigenomics, MethBase, DiseaseMeth

  • Molecular Profiling (if available):
  • Transcriptomics/gene expression changes > Search first: GEO (Gene Expression Omnibus), ArrayExpress, GTEx, Human Cell Atlas, SRA
  • Proteomics findings > Search first: PRIDE, ProteomeXchange, Human Protein Atlas, STRING, BioGRID
  • Metabolomics signatures > Search first: MetaboLights, Metabolomics Workbench, HMDB, METLIN
  • Lipidomics alterations > Search first: LIPID MAPS, SwissLipids, LipidHome, Metabolomics Workbench
  • Genomic structural features > Search first: UCSC Genome Browser, Ensembl, NCBI, dbVar, DGV
  • Advanced Technologies (if applicable):
  • Single-cell analysis findings (cell-type specific mechanisms, cellular heterogeneity) > Search first: Human Cell Atlas, Single Cell Portal, GEO, CELLxGENE
  • Spatial transcriptomics findings > Search first: GEO, Spatial Research, Vizgen, 10x Genomics data
  • Multi-omics integration results > Search first: TCGA, ICGC, cBioPortal, LinkedOmics, PubMed
  • Functional genomics screens (CRISPR, RNAi) > Search first: DepMap, GenomeRNAi, PubMed, BioGRID ORCS

For each mechanism, describe: - The causal chain from initial trigger to clinical manifestation - Which mechanisms are upstream vs downstream - What cell types and biological processes are involved - Suggest GO terms for biological processes and CL terms for cell types

7. Anatomical Structures Affected

  • Organ Level:
  • Primary organs directly affected
  • Secondary organ involvement (complications, secondary effects)
  • Body systems involved (cardiovascular, nervous, digestive, respiratory, endocrine, etc.)

    Search first: Uberon, FMA (Foundational Model of Anatomy), OMIM, HPO, ICD-11, MeSH, SNOMED CT

  • Tissue and Cell Level:
  • Specific tissue types affected (epithelial, connective, muscle, nervous)
  • Specific cell populations targeted (with Cell Ontology terms)

    Search first: Uberon, Human Protein Atlas, Cell Ontology, Human Cell Atlas, CellMarker, PanglaoDB

  • Subcellular Level:
  • Cellular compartments involved (mitochondria, nucleus, ER, lysosomes) (with GO Cellular Component terms)

    Search first: Gene Ontology (Cellular Component), UniProt, Human Protein Atlas

  • Localization:
  • Specific anatomical sites (with UBERON terms) > Search first: FMA, Uberon, NeuroNames (for brain), SNOMED CT
  • Lateralization (unilateral, bilateral, asymmetric) > Search first: HPO, clinical literature, imaging databases

8. Temporal Development

  • Onset:
  • Typical age of onset (congenital, pediatric, adult, geriatric)
  • Onset pattern (acute, subacute, chronic, insidious)

    Search first: OMIM, Orphanet, HPO, PubMed

  • Progression:
  • Disease stages (early, intermediate, advanced, end-stage) > Search first: Cancer Staging Manual (AJCC), WHO classifications, PubMed
  • Progression rate (rapid, slow, variable)
  • Disease course pattern (episodic, relapsing-remitting, progressive, stable)
  • Disease duration (self-limited, chronic lifelong)

    Search first: Disease registries, longitudinal cohort databases, natural history studies, PubMed, Orphanet, OMIM

  • Patterns:
  • Remission patterns (spontaneous, treatment-induced) > Search first: Clinical trial databases, disease registries, PubMed
  • Critical periods (time windows of vulnerability or opportunity for intervention) > Search first: PubMed, developmental biology databases, clinical guidelines

9. Inheritance and Population

  • Epidemiology:
  • Prevalence (cases per 100,000 at given time)
  • Incidence (new cases per 100,000 per year)

    Search first: Orphanet, CDC, WHO, GBD (Global Burden of Disease), national registries, SEER, disease registries

  • For Genetic Etiology:
  • Inheritance pattern (AD, AR, X-linked, mitochondrial, multifactorial, polygenic) > Search first: OMIM, Orphanet, ClinVar, GTR (Genetic Testing Registry)
  • Penetrance (complete, incomplete, age-dependent) > Search first: ClinVar, OMIM, PubMed, ClinGen
  • Expressivity (variable, consistent) > Search first: OMIM, ClinVar, PubMed
  • Genetic anticipation (increasing severity in successive generations) > Search first: OMIM, PubMed (especially for repeat expansion disorders)
  • Germline mosaicism > Search first: ClinVar, OMIM, genetic counseling literature, PubMed
  • Founder effects (population-specific mutations) > Search first: gnomAD, population genetics databases, PubMed
  • Consanguinity role > Search first: OMIM, population studies, genetic counseling resources
  • Carrier frequency > Search first: gnomAD, carrier screening databases, GeneReviews, GTR
  • Population Demographics:
  • Affected populations (ethnic or demographic groups with higher prevalence) > Search first: gnomAD, 1000 Genomes, PAGE Study, PubMed, population registries
  • Geographic distribution (endemic areas, regional variation) > Search first: WHO, CDC, GBD, Orphanet, geographic epidemiology databases
  • Geographic distribution of specific variants
  • Sex ratio (male:female) > Search first: Disease registries, OMIM, PubMed, epidemiological databases
  • Age distribution of affected individuals > Search first: CDC, disease registries, SEER, Orphanet

10. Diagnostics

  • Clinical Tests:
  • Laboratory tests (blood, urine, tissue chemistry, specific enzyme assays) > Search first: LOINC, LabTests Online, PubMed
  • Biomarkers (proteins, metabolites, genetic markers, circulating biomarkers) > Search first: FDA Biomarker List, BEST (Biomarkers, EndpointS, and other Tools), PubMed
  • Imaging studies (X-ray, CT, MRI, PET, ultrasound) > Search first: RadLex, DICOM, Radiopaedia, imaging databases
  • Functional tests (pulmonary function, cardiac stress tests) > Search first: LOINC, clinical guidelines, PubMed
  • Electrophysiology (EEG, EMG, ECG, nerve conduction studies) > Search first: LOINC, clinical neurophysiology databases, PubMed
  • Biopsy findings (histopathology, immunohistochemistry) > Search first: SNOMED CT, College of American Pathologists resources, PubMed
  • Pathology findings (microscopic examination) > Search first: SNOMED CT, Digital Pathology databases, PubMed
  • Genetic Testing:

    Search first: GTR (Genetic Testing Registry), GeneReviews, ClinGen

  • Overview of recommended genetic testing approach
  • Whole genome sequencing (WGS) utility > Search first: GTR, ClinVar, GEL (Genomics England), gnomAD
  • Whole exome sequencing (WES) utility > Search first: GTR, ClinVar, OMIM, GeneMatcher
  • Gene panels (which panels, which genes) > Search first: GTR, ClinVar, laboratory-specific databases
  • Single gene testing > Search first: GTR, ClinVar, OMIM, GeneReviews
  • Chromosomal microarray (CMA) > Search first: DECIPHER, ClinVar, dbVar, ECARUCA
  • Karyotyping > Search first: Chromosome Abnormality Database, ClinVar, cytogenetics resources
  • FISH > Search first: ClinVar, cytogenetics databases, PubMed
  • Mitochondrial DNA testing > Search first: MITOMAP, MSeqDR, ClinVar, GTR
  • Repeat expansion testing > Search first: GTR, ClinVar, repeat expansion databases, PubMed
  • Omics-Based Diagnostics (if applicable):
  • RNA sequencing / transcriptomics > Search first: GEO, ArrayExpress, GTEx, RNA-seq databases
  • Proteomics > Search first: PRIDE, ProteomeXchange, FDA Biomarker database
  • Metabolomics > Search first: MetaboLights, Metabolomics Workbench, HMDB
  • Epigenomics > Search first: GEO, ENCODE, Roadmap Epigenomics, MethBase
  • Liquid biopsy > Search first: COSMIC, ClinVar, liquid biopsy databases, PubMed
  • Clinical Criteria:
  • Standardized diagnostic criteria (DSM, ICD, society guidelines) > Search first: DSM-5, ICD-11, clinical society guidelines, UpToDate
  • Differential diagnosis (other conditions to rule out, with distinguishing features) > Search first: DynaMed, UpToDate, clinical decision support systems
  • Screening:
  • Screening methods for asymptomatic individuals (newborn screening, carrier screening, cascade screening) > Search first: ACMG recommendations, CDC newborn screening, GTR

11. Outcome/Prognosis

  • Survival and Mortality:
  • Survival rate (5-year, 10-year, overall) > Search first: SEER, cancer registries, disease-specific registries, PubMed
  • Life expectancy (with and without treatment if applicable) > Search first: Orphanet, disease registries, actuarial databases, PubMed
  • Mortality rate > Search first: CDC, WHO, GBD, national mortality databases
  • Disease-specific mortality (deaths directly attributable to disease) > Search first: Disease registries, CDC Wonder, GBD, PubMed
  • Morbidity and Function:
  • Morbidity (disease-related disability and health impacts) > Search first: GBD, WHO, disability databases, PubMed
  • Disability outcomes (long-term functional impairments) > Search first: ICF (International Classification of Functioning), disability registries
  • Quality of life measures (EQ-5D, SF-36, PROMIS, disease-specific tools) > Search first: EQ-5D database, SF-36, PROMIS, PubMed
  • Disease Course:
  • Complications (secondary problems: infections, organ failure, etc.) > Search first: ICD codes, disease registries, clinical databases, PubMed
  • Recovery potential (likelihood and extent of recovery, with vs without treatment) > Search first: Natural history studies, rehabilitation databases, PubMed
  • Prediction:
  • Prognostic factors (age, disease severity, biomarkers, treatment response) > Search first: Prognostic models databases, clinical calculators, PubMed
  • Prognostic biomarkers (molecular markers predicting disease course) > Search first: FDA Biomarker database, PubMed, cancer prognostic databases

12. Treatment

  • Pharmacotherapy:
  • Pharmacological treatments (drug names, drug classes, mechanisms of action) > Search first: DrugBank, RxNorm, ATC classification, DailyMed, FDA databases
  • Pharmacogenomics (how genetic variants affect drug metabolism, efficacy, toxicity) > Search first: PharmGKB, CPIC (Clinical Pharmacogenetics), FDA Table of PGx Biomarkers
  • Advanced Therapeutics:
  • Gene therapy (viral vectors, CRISPR, gene replacement, gene editing) > Search first: ClinicalTrials.gov, FDA gene therapy database, ASGCT resources
  • Cell therapy (stem cell transplant, CAR-T, cellular therapeutics) > Search first: ClinicalTrials.gov, FDA cell therapy database, FACT standards
  • RNA-based therapies (ASOs, siRNA, mRNA therapies) > Search first: ClinicalTrials.gov, FDA approvals, PubMed
  • Targeted therapies (treatments directed at specific molecular targets) > Search first: My Cancer Genome, OncoKB, ClinicalTrials.gov, FDA approvals
  • Immunotherapies (checkpoint inhibitors, monoclonal antibodies) > Search first: Cancer Immunotherapy Database, FDA approvals, ClinicalTrials.gov
  • Surgical and Interventional:
  • Surgical interventions (types of surgery, timing, outcomes) > Search first: CPT codes, surgical registries, clinical guidelines, PubMed
  • Supportive and Rehabilitative:
  • Supportive care (symptom management, pain control, nutrition) > Search first: Clinical guidelines, Cochrane Library, PubMed
  • Rehabilitation (physical therapy, occupational therapy, speech therapy) > Search first: Rehabilitation medicine databases, clinical guidelines, PubMed
  • Experimental:
  • Experimental treatments in clinical trials (with NCT identifiers if available) > Search first: ClinicalTrials.gov, EU Clinical Trials Register, WHO ICTRP
  • Treatment Outcomes:
  • Treatment response rates > Search first: Clinical trial databases, FDA reviews, systematic reviews, PubMed
  • Side effects and adverse events > Search first: FDA Adverse Event Reporting System (FAERS), MedWatch, PubMed
  • Treatment Strategy:
  • Treatment algorithms (clinical pathways, decision trees) > Search first: Clinical practice guidelines, NCCN Guidelines, UpToDate
  • Combination therapies > Search first: ClinicalTrials.gov, treatment guidelines, PubMed
  • Personalized medicine approaches (genotype-guided treatment) > Search first: My Cancer Genome, CIViC, PharmGKB, precision medicine databases

For each treatment, suggest MAXO (Medical Action Ontology) terms where applicable.

13. Prevention

  • Prevention Levels:
  • Primary prevention (preventing disease occurrence: vaccination, risk factor modification) > Search first: CDC, WHO, USPSTF recommendations, Cochrane Library
  • Secondary prevention (early detection and treatment: screening programs, early intervention) > Search first: USPSTF, CDC screening guidelines, WHO
  • Tertiary prevention (preventing complications in those with disease) > Search first: Clinical guidelines, disease management protocols, PubMed
  • Immunization: Vaccine strategies (if applicable)

    Search first: CDC vaccine schedules, WHO immunization, FDA vaccine database

  • Screening and Early Detection:
  • Screening programs (population-based: newborn screening, cancer screening) > Search first: CDC screening programs, USPSTF, cancer screening databases
  • Genetic screening (carrier screening, preimplantation genetic diagnosis, prenatal testing) > Search first: ACMG recommendations, ACOG guidelines, GTR
  • Risk stratification (identifying high-risk individuals for targeted prevention) > Search first: Risk prediction models, clinical calculators, PubMed
  • Behavioral Interventions: Lifestyle modifications to reduce risk

    Search first: CDC, WHO, behavioral intervention databases, Cochrane Library

  • Counseling: Genetic counseling (risk assessment, family planning guidance)

    Search first: NSGC resources, ACMG guidelines, GeneReviews

  • Public Health:
  • Public health interventions (sanitation, vector control, health education) > Search first: CDC, WHO, public health databases, PubMed
  • Environmental interventions (reducing environmental risk factors) > Search first: EPA databases, WHO environmental health, PubMed
  • Prophylaxis: Preventive medications or procedures

    Search first: Clinical guidelines, FDA approvals, PubMed

14. Other Species / Natural Disease

  • Taxonomy: Species affected (with NCBI Taxon identifiers)

    Search first: NCBI Taxonomy

  • Breed: Specific breeds affected (with VBO identifiers if applicable)

    Search first: VBO (Vertebrate Breed Ontology)

  • Gene: Orthologous genes in other species (with NCBI Gene IDs)

    Search first: NCBI Gene

  • Natural Disease:
  • Naturally occurring disease in other species (companion animals, wildlife) > Search first: OMIA (Online Mendelian Inheritance in Animals), VetCompass, PubMed
  • Veterinary relevance and importance in animal health > Search first: OMIA, veterinary databases, PubMed
  • Comparative Biology:
  • Comparative pathology (similarities and differences across species) > Search first: OMIA, comparative pathology databases, PubMed
  • Evolutionary conservation of disease mechanisms > Search first: HomoloGene, OrthoMCL, Alliance of Genome Resources
  • Transmission (if applicable):
  • Zoonotic potential > Search first: CDC zoonotic diseases, WHO zoonoses, GIDEON
  • Cross-species susceptibility > Search first: NCBI Taxonomy, veterinary databases, PubMed

15. Model Organisms

  • Model Types:
  • Model organism type (mammalian, invertebrate, cellular, in vitro) > Search first: Alliance of Genome Resources, model organism databases
  • Specific model systems (mouse, rat, zebrafish, Drosophila, C. elegans, yeast, cell lines, organoids, iPSCs) > Search first: MGI, RGD, ZFIN, FlyBase, WormBase, SGD, ATCC, Cellosaurus
  • Induced models (drug treatment, surgical intervention, environmental manipulation) > Search first: MGI, model organism databases, PubMed
  • Genetic Models:
  • Types available (knockout, knock-in, transgenic, conditional, humanized) > Search first: MGI, IMPC, KOMP, EuMMCR, IMSR
  • Model Characteristics:
  • Phenotype recapitulation (how well model reproduces human disease features) > Search first: Model organism databases, comparative studies, PubMed
  • Model limitations (aspects of human disease not captured) > Search first: Model organism databases, PubMed, review articles
  • Applications:
  • Research applications (what aspects of disease can be studied) > Search first: Model organism databases, PubMed
  • Resources:
  • Model databases > Search first: MGI, RGD, ZFIN, FlyBase, WormBase, IMSR, EMMA, MMRRC

Citation Requirements

  • Cite primary literature (PMID preferred) for all mechanistic and clinical claims
  • Prioritize recent reviews and landmark papers
  • Include direct quotes from abstracts where possible to support key statements
  • Distinguish evidence source types: human clinical, model organism, in vitro, computational

Output Format

Structure your response as a comprehensive narrative organized by the sections above. For each section, provide: - Factual content with specific details (numbers, percentages, gene names, variant nomenclature) - Ontology term suggestions (HPO, GO, CL, UBERON, CHEBI, MAXO, MONDO) where applicable - Evidence citations with PMIDs - Direct quotes from abstracts to support key claims - Clear indication when information is not available or not applicable for this disease

This report will be used to populate a disease knowledge base entry with: - Pathophysiology descriptions with causal chains - Gene/protein annotations (HGNC, GO terms) - Phenotype associations (HP terms) with frequencies - Cell type involvement (CL terms) - Anatomical locations (UBERON terms) - Chemical entities (CHEBI terms) - Treatment annotations (MAXO terms) - Evidence items with PMIDs and exact abstract quotes - Epidemiology, prognosis, diagnostic, and prevention information - Animal model descriptions with phenotype recapitulation details

Comprehensive Research Report: Gastroenteropancreatic Neuroendocrine Neoplasm (GEP‑NEN)

Target disease

  • Disease name: Gastroenteropancreatic neuroendocrine neoplasm (GEP‑NEN)
  • Category: Neoplasm/cancer of the gastroenteropancreatic (digestive) neuroendocrine system.
  • MONDO: A closely aligned ontology entry supported in OpenTargets is “digestive system neuroendocrine neoplasm” (MONDO_0024503) (OpenTargets Search: gastroenteropancreatic neuroendocrine neoplasm,pancreatic neuroendocrine tumor,neuroendocrine carcinoma). (A GEP‑NEN‑specific MONDO identifier was not retrieved in the available tool context.)

1) Disease information (definitions, identifiers, synonyms)

1.1 What is the disease?

GEP‑NENs are heterogeneous neoplasms arising from the diffuse neuroendocrine system within the gastrointestinal tract and pancreas, spanning indolent well‑differentiated neuroendocrine tumors (NETs) to aggressive poorly differentiated neuroendocrine carcinomas (NECs) (pellegrino2023diagnosticmanagementof pages 1-2, castillon2023seomgetneclinicalguidelines pages 1-2).

1.2 Classification (current understanding)

Across major contemporary sources, digestive NENs are organized by differentiation and proliferation, using mitotic rate and Ki‑67 proliferation index to grade tumors. WHO‑aligned frameworks distinguish: - Well‑differentiated NETs graded G1–G3 by Ki‑67/mitoses, and - Poorly differentiated NECs (high‑grade, typically G3) (castillon2023seomgetneclinicalguidelines pages 1-2, qasim2026neuroendocrineneoplasmsof pages 2-3, qasim2026neuroendocrineneoplasmsof pages 7-8).

Quantitative Ki‑67 grading thresholds cited in recent reviews include G1 <3%, G2 3–20%, G3 >20% (qasim2026neuroendocrineneoplasmsof pages 7-8, tan2024gastroenteropancreaticneuroendocrineneoplasms pages 1-2).

1.3 Synonyms / alternative names

Commonly used equivalents in the retrieved literature include: - “GEP‑NEN”, “gastro‑entero‑pancreatic neuroendocrine neoplasm” (pellegrino2023diagnosticmanagementof pages 1-2, castillon2023seomgetneclinicalguidelines pages 1-2) - “GEP‑NET” (often used when focusing on well‑differentiated tumors) (peshin2025currentclinicaltrial pages 4-6, peshin2025currentclinicaltrial pages 1-3) - “Digestive high‑grade NEN”, “NET G3”, “NEC” in high‑grade contexts (sorbye2025characteristicsandtreatment pages 1-2, elvebakken2024treatmentoutcomeaccording pages 1-2).

1.4 Evidence source type

Most information in this report is derived from aggregated disease‑level resources (clinical guidelines, registry studies, systematic reviews) plus selected human clinical cohorts and prospective imaging trials (castillon2023seomgetneclinicalguidelines pages 1-2, uhlig2024epidemiologytreatmentand pages 1-2, taherifard2024efficacyandsafety pages 1-3, boeckxstaens2023prospectivecomparisonof pages 1-2).

2) Etiology (causal factors, risk factors, protective factors)

2.1 Primary causal factors (genetic/mechanistic)

Most GEP‑NENs are described as sporadic, with a minority occurring in hereditary cancer predisposition syndromes (castillon2023seomgetneclinicalguidelines pages 1-2, andersen2024welldifferentiatedg1and pages 1-2).

2.2 Genetic risk factors / hereditary syndromes

Guideline‑level estimates indicate ~5% of NETs are associated with hereditary syndromes such as MEN1 (castillon2023seomgetneclinicalguidelines pages 1-2). A 2024 epidemiology review reports hereditary syndromes accounting for ~10% of NENs, listing MEN1, von Hippel–Lindau (VHL), and neurofibromatosis type 1 (NF1) (tan2024gastroenteropancreaticneuroendocrineneoplasms pages 1-2). In a 2024 systematic review/meta‑analysis of well‑differentiated G1/G2 pancreatic NETs, 13.3% (30/225) were categorized as hereditary tumors (andersen2024welldifferentiatedg1and pages 1-2).

Somatic molecular etiologic drivers differ by differentiation/grade and site: - Pancreatic well‑differentiated NETs commonly harbor MEN1, DAXX, ATRX and mTOR‑pathway alterations (uhlig2024epidemiologytreatmentand pages 1-2, andersen2024welldifferentiatedg1and pages 1-2). - Pancreatic NECs more often show TP53 and RB1 pathway alterations (uhlig2024epidemiologytreatmentand pages 1-2, qasim2026neuroendocrineneoplasmsof pages 7-8, castillon2023seomgetneclinicalguidelines pages 1-2).

2.3 Environmental risk factors, protective factors, and GxE

No robust environmental or protective factors (nor gene‑environment interactions) were retrieved in the current tool evidence. This is an evidence gap relative to the requested template.

3) Phenotypes (clinical presentation, HPO terms, QoL)

3.1 Functional vs nonfunctional disease

GEP‑NENs are often divided clinically into: - Nonfunctioning tumors, and - Functioning tumors that secrete bioactive hormones producing distinct clinical syndromes.

A radiology review states most (60–80%) are nonfunctioning, while 20–30% are hormone‑secreting, citing examples such as insulinomas, gastrinomas, glucagonomas, VIPomas, and somatostatinomas (pellegrino2023diagnosticmanagementof pages 1-2). A separate epidemiology review reports 30–40% of pancreatic NETs are functioning (tan2024gastroenteropancreaticneuroendocrineneoplasms pages 1-2).

3.2 Key symptoms / manifestations

From the imaging review: functioning syndromes include hypoglycemia (insulinoma), watery diarrhea (VIPoma), and carcinoid syndrome manifestations such as watery diarrhea, flushing, bronchospasm, and right‑sided heart disease (pellegrino2023diagnosticmanagementof pages 1-2).

3.3 Suggested HPO terms (examples)

(HPO IDs were not retrieved directly via tools; suggested terms reflect standard HPO naming.) - Flushing → HP:0031284 (Flushing) (suggested) - Diarrhea (including watery diarrhea) → HP:0002014 (Diarrhea) (suggested) - Hypoglycemia → HP:0001943 (Hypoglycemia) (suggested) - Bronchospasm/wheezing → HP:0002094 (Wheezing) (suggested) - Carcinoid heart disease/right heart involvement → HP:0001708 (Right ventricular hypertrophy) (suggested)

3.4 Quality of life (QoL)

QoL endpoints were not directly retrieved in the tool evidence. Symptom burden and need for multidisciplinary care are emphasized in guideline/review contexts (pellegrino2023diagnosticmanagementof pages 1-2, castillon2023seomgetneclinicalguidelines pages 1-2).

4) Genetic / molecular information

4.1 Key genes and molecular features

Well‑differentiated pancreatic NET (PanNET) mutation frequencies (G1/G2; meta‑analysis): - MEN1 altered in 42% (95/225) - DAXX altered in 16% (37/225) - ATRX altered in 12% (27/225) DAXX mutations were more frequent in tumors with MEN1 mutations (p<0.05) (andersen2024welldifferentiatedg1and pages 1-2).

High‑grade GEP‑NEN genomic landscape (NET G3 vs NEC; cohort study): High‑grade gastro‑entero‑pancreatic neoplasms had frequent alterations in TP53 (26%), APC (20%), KRAS (11%), and MEN1 (11%), with NET G3 enriched in MEN1 and NEC enriched in TP53/APC/KRAS; histologic type and Rb1 loss were independent prognostic factors (elvebakken2024treatmentoutcomeaccording pages 1-2).

4.2 Somatic vs germline

The 2024 PanNET meta‑analysis explicitly partitions tumors into sporadic vs hereditary groups and provides hereditary syndrome gene examples (e.g., MEN1, VHL, PTEN, CDKN1B, BRCA2) (andersen2024welldifferentiatedg1and pages 1-2).

4.3 Epigenetic / transcriptomic / ctDNA (emerging)

A 2024 systematic review emphasizes growing interest in liquid biopsy modalities—CTCs, ctDNA, miRNA, and mRNA signatures (NETest)—for diagnosis, prognostication, monitoring, and recurrence detection, while highlighting lack of standardization and need for prospective validation (almeida2024theroleof pages 1-2).

Suggested GO biological process terms (examples) (not tool‑retrieved; ontology suggestions): - Neuroendocrine cell differentiation → GO:0048666 (neuron development) (suggested proxy) - Cell proliferation → GO:0008283 (cell population proliferation) (suggested) - mTOR signaling → GO:0031929 (TOR signaling) (suggested)

5) Environmental information

No specific toxins, lifestyle factors, or infectious causes were retrieved in the current evidence set. (Evidence gap.)

6) Mechanism / pathophysiology

6.1 Differentiation‑linked biology and clinical behavior

A central mechanistic concept is that differentiation and proliferative index (Ki‑67) correlate strongly with behavior and prognosis, with well‑differentiated G1/G2 generally more indolent than high‑grade G3 and NEC (pellegrino2023diagnosticmanagementof pages 1-2, castillon2023seomgetneclinicalguidelines pages 1-2, sorbye2025characteristicsandtreatment pages 1-2).

6.2 High‑grade disease mechanisms (TP53/RB1 axis)

High‑grade digestive NENs show clinically and molecularly distinct categories (NET G3 vs NEC), with outcomes and treatment responses differing by subtype and biomarkers such as Ki‑67 and tumor suppressor alterations (sorbye2025characteristicsandtreatment pages 1-2, elvebakken2024treatmentoutcomeaccording pages 1-2).

7) Anatomical structures affected

7.1 Primary sites and metastasis

GEP‑NENs arise in gastrointestinal tract and pancreas; a 2024 review notes that at diagnosis >50% have lymph node metastases, and the liver is the predominant metastatic site (82%) (tan2024gastroenteropancreaticneuroendocrineneoplasms pages 1-2).

Suggested UBERON terms (examples) (suggested; not tool‑retrieved): - Pancreas → UBERON:0001264 (suggested) - Small intestine → UBERON:0002108 (suggested) - Liver (metastasis) → UBERON:0002107 (suggested)

8) Temporal development (onset and progression)

Median age at diagnosis is approximately ~60 years in guideline summaries (castillon2023seomgetneclinicalguidelines pages 1-2). High‑grade digestive NENs can show rapid progression with poor survival in advanced disease compared with NET G3 (sorbye2025characteristicsandtreatment pages 1-2).

9) Inheritance and population

9.1 Epidemiology (incidence/prevalence)

  • Guideline incidence estimate for GEP‑NEN: 3.56 per 100,000; prevalence increased from 0.006% (1993) to 0.048% (2012) (castillon2023seomgetneclinicalguidelines pages 1-2).
  • U.S. NCDB analysis: 86,324 GEP‑NEN patients; annual cases increased from 4,010 (2004) to 9,379 (2016), driven largely by low‑stage/low‑grade disease (uhlig2024epidemiologytreatmentand pages 1-2).
  • A 2024 review cites a 6.4‑fold rise in U.S. NEN incidence from 1973–2012 (tan2024gastroenteropancreaticneuroendocrineneoplasms pages 1-2).

9.2 Heritability

Hereditary syndromes contribute a minority of cases (see §2), with pooled hereditary classification 13.3% in one PanNET sequencing meta‑analysis dataset (andersen2024welldifferentiatedg1and pages 1-2).

10) Diagnostics

10.1 Pathology and immunohistochemistry (IHC)

Minimum recommended confirmation of neuroendocrine phenotype includes synaptophysin and chromogranin A immunostaining (castillon2023seomgetneclinicalguidelines pages 1-2). INSM1 is highlighted as a promising sensitive/specific nuclear marker (castillon2023seomgetneclinicalguidelines pages 1-2).

Ki‑67 grading: reviews cite G1 <3%, G2 3–20%, G3 >20% and note technical requirements such as counting 500–2,000 tumor cells in “hot spot” areas (qasim2026neuroendocrineneoplasmsof pages 7-8, tan2024gastroenteropancreaticneuroendocrineneoplasms pages 1-2).

10.2 Imaging (real‑world implementation)

A 2023 imaging review describes a combined approach using: - Morphologic imaging: contrast‑enhanced CT (ENETS‑aligned) and contrast‑enhanced MRI with DWI for liver/pancreas/bone assessment (pellegrino2023diagnosticmanagementof pages 1-2). - Functional imaging: FDG PET‑CT for more aggressive/nonfunctioning lesions and somatostatin receptor (SSTR) PET for receptor‑expressing disease; identifying heterogeneity in SSTR expression is clinically important for therapy planning (pellegrino2023diagnosticmanagementof pages 1-2).

10.3 Recent development (2023–2024): next‑generation SSTR PET tracer

A prospective comparison study reported improved lesion detection using [^18F]AlF‑NOTA‑octreotide (18F‑AlF‑OC) versus [^68Ga]Ga‑DOTATATE. Key abstract‑level metrics include: - “195 unique lesions were detected: 167 with [^68Ga]Ga‑DOTATATE and 193 with [^18F]AlF‑OC.” - “The DR for [^18F]AlF‑OC was 99.1% versus 91.4% for [^68Ga]Ga‑DOTATATE…” - “…of 33 incremental lesions… 91% were confirmed by MRI…” Trial registration: ClinicalTrials.gov NCT04552847 (registered 17 Sep 2020) (boeckxstaens2023prospectivecomparisonof pages 1-2). Tables with DR comparisons are visible in the extracted images (boeckxstaens2023prospectivecomparisonof media b98f7885, boeckxstaens2023prospectivecomparisonof media be4d67f8, boeckxstaens2023prospectivecomparisonof media 4b687989).

11) Outcomes / prognosis

11.1 Stage‑based survival

Guideline‑level 5‑year overall survival (OS) estimates vary strongly by stage: - Localized: 83–97% - Regional: 67–84% - Metastatic: 28–50% For NEC, 5‑year OS is substantially worse (e.g., metastatic around 10%) (castillon2023seomgetneclinicalguidelines pages 1-2).

11.2 Prognosis in advanced high‑grade disease (recent registry)

The prospective NORDIC NEC 2 cohort reported for advanced digestive high‑grade NENs: - Immediate progression: 41% (NEC) vs 24% (NET G3) - Median PFS: 3.4 months (NEC) vs 7.4 months (NET G3) - Median OS: 7.4 months (NEC) vs 21.8 months (NET G3) and identified adverse prognostic factors including Ki‑67 >55% and performance status (sorbye2025characteristicsandtreatment pages 1-2).

12) Treatment (standard of care + recent developments)

12.1 Core treatment modalities in current practice

An NCDB analysis found most patients received surgery: 72.9% surgery alone and 4.9% surgery plus systemic therapy; surgical resection was associated with the longest OS in that dataset (uhlig2024epidemiologytreatmentand pages 1-2).

Systemic and locoregional modalities referenced across guideline/review evidence include: surgery, liver‑directed therapy, somatostatin analogues (SSAs), PRRT, cytotoxic chemotherapy, and targeted therapies (castillon2023seomgetneclinicalguidelines pages 1-2).

12.2 Somatostatin analogues (SSAs)

SSAs are used as antiproliferative therapy in well‑differentiated, SSTR‑expressing disease; PROMID and CLARINET trial metrics are summarized in recent evidence syntheses (peshin2025currentclinicaltrial pages 4-6, hernandezfelix2025emergingdiagnosticsand pages 5-6).

12.3 PRRT (177Lu‑DOTATATE) and theranostics

PRRT is a key real‑world implementation for SSTR‑positive GEP‑NETs, supported by trials summarized in recent critical reviews (hernandezfelix2025emergingdiagnosticsand pages 5-6). The same body of evidence emphasizes that modern SSTR‑PET imaging has become central for selecting candidates for PRRT and other SSTR‑targeted approaches (pellegrino2023diagnosticmanagementof pages 1-2, hernandezfelix2025emergingdiagnosticsand pages 5-6).

12.4 Targeted therapies (everolimus, sunitinib) and sequencing

Recent evidence syntheses summarize PFS benefit from mTOR inhibition and TKIs in NET populations, and emphasize that therapy sequencing is increasingly individualized (hernandezfelix2025emergingdiagnosticsand pages 5-6, peshin2025currentclinicaltrial pages 4-6).

12.5 Alkylator chemotherapy (temozolomide; CAPTEM)

A 2024 systematic review/meta‑analysis of temozolomide‑based regimens in advanced pancreatic NETs pooled 14 studies (441 patients) and reported: - ORR 41.2% (95% CI 32.4–50.6) - DCR 85.3% (95% CI 74.9–91.9) - ≥50% chromogranin A decrease 44.9% - Serious adverse events 23.7% (registered PROSPERO CRD42023409280) (taherifard2024efficacyandsafety pages 1-3).

12.6 High‑grade NEC chemotherapy and biomarkers

For digestive high‑grade NEN treated with platinum/etoposide, a 2024 BJC study found TP53 mutation predicted inferior response rate in multivariate analysis (p=0.009), and observed additional subtype‑specific associations (e.g., RB1 deletions in small‑cell NEC) (elvebakken2024treatmentoutcomeaccording pages 1-2).

12.7 Recent development: Cabozantinib phase III (CABINET)

A major recent development is the CABINET phase 3 trial of cabozantinib in previously treated progressive NETs: - Extra‑pancreatic NET: median PFS 8.4 vs 3.9 months (HR 0.38; p<0.001) - Pancreatic NET: median PFS 13.8 vs 4.4 months (HR 0.23; p<0.001) - Confirmed ORR: 5% (epNET) and 19% (pNET) vs 0% with placebo - Grade ≥3 adverse events: 62–65% with cabozantinib vs 23–27% with placebo (published Feb 2025; URL in citation) (chan2025phase3trial pages 1-3).

Suggested MAXO terms (examples; suggested) - Surgical resection → MAXO:0000004 (surgery) (suggested) - Somatostatin analogue therapy → MAXO:0000037 (pharmacotherapy) (suggested) - PRRT → MAXO:0000533 (radiotherapy) (suggested) - Tyrosine kinase inhibitor therapy → MAXO:0000037 (pharmacotherapy) (suggested) - Chemotherapy (CAPTEM; platinum‑etoposide) → MAXO:0000037 (pharmacotherapy) (suggested)

13) Prevention

No primary prevention strategies or population screening programs were retrieved in the available evidence. Secondary prevention in practice mainly reflects improved detection via modern imaging/endoscopy (uhlig2024epidemiologytreatmentand pages 1-2, pellegrino2023diagnosticmanagementof pages 1-2).

14) Other species / natural disease

Not retrieved in current evidence.

15) Model organisms

Not sufficiently retrieved in current evidence. (Although preclinical model work exists, including genetically engineered mouse models of PanNET, it was not gathered into citeable context in this run.)

Expert opinion and analysis (synthesis from authoritative sources)

Recent guideline and high‑impact trial evidence supports several converging expert‑level themes: 1) Classification matters clinically: NET G3 and NEC differ in molecular profile and prognosis, requiring nuanced pathology with Ki‑67, morphology, and marker patterns (castillon2023seomgetneclinicalguidelines pages 1-2, sorbye2025characteristicsandtreatment pages 1-2, elvebakken2024treatmentoutcomeaccording pages 1-2). 2) Theranostics is central to real‑world implementation: SSTR expression assessment with modern PET is pivotal for treatment planning (SSA/PRRT), and newer tracers such as 18F‑AlF‑OC may improve lesion detection and logistics over 68Ga agents (pellegrino2023diagnosticmanagementof pages 1-2, boeckxstaens2023prospectivecomparisonof pages 1-2, boeckxstaens2023prospectivecomparisonof media b98f7885). 3) Therapy options are expanding in 2023–2025: systematic review evidence supports CAPTEM/temozolomide efficacy in pNET, and CABINET provides phase III evidence for cabozantinib in progressive NETs (taherifard2024efficacyandsafety pages 1-3, chan2025phase3trial pages 1-3). 4) Liquid biopsy is promising but not standardized: ctDNA and transcriptomic assays (e.g., NETest) show potential for diagnosis/monitoring, especially in higher grade disease, but require prospective validation and harmonization before routine adoption (almeida2024theroleof pages 1-2).

Structured summary table

Domain Key knowledge-base facts
Definition / classification Digestive-system NENs are classified into well-differentiated NET and poorly differentiated NEC; WHO/consensus grading uses Ki-67 and mitotic count. NET grades: G1 <3%, G2 3–20%, G3 >20%; NECs are biologically high-grade and typically G3. WHO 2022/current framework also recognizes MiNEN and separates NET G3 from NEC (qasim2026neuroendocrineneoplasmsof pages 2-3, qasim2026neuroendocrineneoplasmsof pages 7-8, castillon2023seomgetneclinicalguidelines pages 1-2, tan2024gastroenteropancreaticneuroendocrineneoplasms pages 1-2)
Epidemiology GEP-NEN incidence reported at 3.56/100,000; prevalence increased from 0.006% (1993) to 0.048% (2012). In NCDB, annual GEP-NEN cases increased from 4,010 to 9,379 (2004–2016); 86,324 patients represented 6.33% of all GEP malignancies. U.S. SEER data cited a 6.4-fold rise in NEN incidence from 1973–2012 (castillon2023seomgetneclinicalguidelines pages 1-2, uhlig2024epidemiologytreatmentand pages 1-2, tan2024gastroenteropancreaticneuroendocrineneoplasms pages 1-2)
Hereditary syndromes / risk About ~5% of NETs are associated with hereditary syndromes in guideline summaries; broader reviews estimate hereditary syndromes in ~5–10% of PanNETs / ~10% of NENs overall. Key syndromes: MEN1, VHL, NF1; pooled sequencing of G1/G2 PanNETs found 13.3% hereditary tumors (30/225) (castillon2023seomgetneclinicalguidelines pages 1-2, tan2024gastroenteropancreaticneuroendocrineneoplasms pages 1-2, andersen2024welldifferentiatedg1and pages 1-2)
Key molecular alterations In pooled G1/G2 PanNET sequencing, MEN1 42% (95/225), DAXX 16% (37/225), ATRX 12% (27/225); nonfunctioning PanNETs showed recurrent PI3K/Wnt/NOTCH/RTK-Ras pathway alterations. High-grade GEP-NENs: TP53 26%, APC 20%, KRAS 11%, MEN1 11%; NET G3 enriched for MEN1, NEC enriched for TP53/APC/KRAS; Rb1 loss independently prognostic. Pancreatic WDNETs commonly harbor DAXX/ATRX, MEN1, mTOR-pathway alterations, whereas pancreatic NECs show RB1, TP53, CDKN2A changes (andersen2024welldifferentiatedg1and pages 1-2, uhlig2024epidemiologytreatmentand pages 1-2, qasim2026neuroendocrineneoplasmsof pages 7-8, elvebakken2024treatmentoutcomeaccording pages 1-2)
Core diagnostics Histopathology should demonstrate neuroendocrine phenotype with at minimum synaptophysin and chromogranin A; INSM1 is highlighted as a sensitive/specific nuclear marker. Site-of-origin IHC may include CDX2 (intestinal), Islet-1/PAX6 (pancreas), TTF-1 (lung). Ki-67 grading cutoffs: <3%, 3–20%, >20%; WHO 2022 guidance recommends counting 500–2,000 cells in hotspot areas (castillon2023seomgetneclinicalguidelines pages 1-2, qasim2026neuroendocrineneoplasmsof pages 7-8, tan2024gastroenteropancreaticneuroendocrineneoplasms pages 1-2)
Imaging Morphologic workup: contrast-enhanced CT recommended; contrast-enhanced MRI with DWI used for liver/pancreas/brain/bone. Functional imaging: SSTR PET for receptor-positive disease and FDG PET-CT for more aggressive/nonfunctioning lesions; heterogeneity of SSTR expression helps treatment selection. In prospective comparison of 18F-AlF-NOTA-octreotide vs 68Ga-DOTATATE, unique lesions 193 vs 167, detection ratio 99.1% vs 91.4%, and 33 incremental 18F lesions with 91% MRI confirmation; trial NCT04552847 (pellegrino2023diagnosticmanagementof pages 1-2, boeckxstaens2023prospectivecomparisonof pages 1-2, boeckxstaens2023prospectivecomparisonof pages 8-9)
Prognosis Five-year OS by stage for GEP-NENs: localized 83–97%, regional 67–84%, metastatic 28–50%; for NECs, localized 25–60%, regional 9.2–28.5%, metastatic about 10%. In NORDIC NEC 2 high-grade digestive NENs, first-line palliative therapy showed immediate progression 41% NEC vs 24% NET G3, median PFS 3.4 vs 7.4 mo, OS 7.4 vs 21.8 mo; adverse prognostic factors included Ki-67 >55%, PS, ALP, age (castillon2023seomgetneclinicalguidelines pages 1-2, sorbye2025characteristicsandtreatment pages 1-2)
Treatments Surgery remains main curative option; most NCDB patients underwent surgery (72.9% alone). SSAs: PROMID TTP 14.3 vs 6 mo; CLARINET median PFS NR/32.8 vs 18 mo. PRRT: NETTER-1 median PFS NR vs 8.4 mo, ORR 18% vs 3%; NETTER-2 PFS 22.8 vs 8.5 mo. Everolimus: RADIANT-3 PFS 11.0 vs 4.6 mo; sunitinib: 11.4 vs 5.5 mo. Temozolomide-based therapy meta-analysis: ORR 41.2%, DCR 85.3%. Platinum-etoposide remains first-line backbone for NEC, but immediate progression can be ~30–41%. CABINET phase 3: cabozantinib improved PFS in epNET 8.4 vs 3.9 mo (HR 0.38) and pNET 13.8 vs 4.4 mo (HR 0.23); ORR 5% epNET / 19% pNET (uhlig2024epidemiologytreatmentand pages 1-2, hernandezfelix2025emergingdiagnosticsand pages 5-6, taherifard2024efficacyandsafety pages 1-3, elvebakken2024treatmentoutcomeaccording pages 1-2, chan2025phase3trial pages 1-3)
Liquid biopsy Liquid biopsy review analyzed 65 articles. ctDNA appears more informative in high-grade tumors; CTCs are limited by low shedding. NETest/other mRNA-miRNA assays are described as having high sensitivity/specificity and may outperform chromogranin A; one review cites about ~91% diagnostic accuracy for NETest, but standardization and prospective validation remain limiting (almeida2024theroleof pages 1-2, peshin2025currentclinicaltrial pages 4-6)

Table: This table condenses high-yield disease characteristics, diagnostics, molecular features, prognosis, and treatment outcomes for gastroenteropancreatic neuroendocrine neoplasms. It is designed for rapid knowledge-base population using evidence-backed quantitative facts and context citations.

Key sources (URLs and publication dates as retrieved)

  • SEOM‑GETNE guideline for diagnosis/treatment of GEP and bronchial NENs. May 2023. https://doi.org/10.1007/s12094-023-03205-6 (castillon2023seomgetneclinicalguidelines pages 1-2)
  • Diagnostic imaging review for GEP‑NENs. Jan 2023. https://doi.org/10.3390/tomography9010018 (pellegrino2023diagnosticmanagementof pages 1-2)
  • NCDB epidemiology/treatment/outcomes of GEP‑NENs. Dec 2024. https://doi.org/10.1038/s41598-024-81518-4 (uhlig2024epidemiologytreatmentand pages 1-2)
  • PanNET sequencing meta‑analysis (G1/G2). May 2024. https://doi.org/10.3389/fendo.2024.1351624 (andersen2024welldifferentiatedg1and pages 1-2)
  • Liquid biopsy systematic review in GEP‑NENs. Sep 2024. https://doi.org/10.3390/cancers16193349 (almeida2024theroleof pages 1-2)
  • Prospective SSTR PET comparison (18F‑AlF‑OC vs 68Ga‑DOTATATE). Jun 2023. https://doi.org/10.1186/s13550-023-01003-3; NCT04552847 (boeckxstaens2023prospectivecomparisonof pages 1-2)
  • Temozolomide‑based regimens meta‑analysis (advanced pNET). Feb 2024. https://doi.org/10.1186/s12885-024-11926-2; PROSPERO CRD42023409280 (taherifard2024efficacyandsafety pages 1-3)
  • High‑grade digestive NEN chemo outcomes and genetics. Jun 2024. https://doi.org/10.1038/s41416-024-02773-w (elvebakken2024treatmentoutcomeaccording pages 1-2)
  • NORDIC NEC 2 prospective cohort (advanced high‑grade digestive NENs). May 2025. https://doi.org/10.1038/s41416-025-03054-w (sorbye2025characteristicsandtreatment pages 1-2)
  • CABINET phase III cabozantinib. Feb 2025. https://doi.org/10.1056/NEJMoa2403991 (chan2025phase3trial pages 1-3)

Limitations of this extraction

  • ICD‑10/ICD‑11, MeSH, Orphanet, OMIM identifiers were not retrieved in the current tool context; thus, only MONDO support from OpenTargets is provided (OpenTargets Search: gastroenteropancreatic neuroendocrine neoplasm,pancreatic neuroendocrine tumor,neuroendocrine carcinoma).
  • Many sources in this run provide DOIs but do not expose PMIDs in the extracted text; therefore, PMID‑level citations could not be consistently supplied.
  • Environmental risk/protective factors, QoL instruments, prevention, non‑human disease, and model organism details were not sufficiently captured in the retrieved evidence.

References

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  7. (peshin2025currentclinicaltrial pages 4-6): Supriya Peshin, Shivani Modi, Rodrick Babakhanlou, and Junaid Arshad. Current clinical trial landscape of gastroenteropancreatic neuroendocrine tumors: a new era of landmark trials. Journal of Clinical Medicine, 14:6522, Sep 2025. URL: https://doi.org/10.3390/jcm14186522, doi:10.3390/jcm14186522. This article has 3 citations.

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  9. (sorbye2025characteristicsandtreatment pages 1-2): Halfdan Sorbye, Geir Olav Hjortland, Lene Weber Vestermark, Morten Ladekarl, Johanna Svensson, Anna Sundlöv, Eva Tiensuu Janson, Herish Garresori, Eva Hofsli, Christian Kersten, Hege Elvebakken, Per Pfeiffer, Siren Morken, Jorg Assmus, Inger Marie Bowitz Lothe, Elizaveta Tabaksblat, Ulrich Knigge, Anne Couvelard, Aurel Perren, and Seppo W. Langer. Characteristics and treatment outcome in a prospective cohort of 639 advanced high-grade digestive neuroendocrine neoplasms (net g3 and nec). the nordic nec 2 study. British Journal of Cancer, 133:316-324, May 2025. URL: https://doi.org/10.1038/s41416-025-03054-w, doi:10.1038/s41416-025-03054-w. This article has 34 citations and is from a domain leading peer-reviewed journal.

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  13. (boeckxstaens2023prospectivecomparisonof pages 1-2): Lennert Boeckxstaens, Elin Pauwels, Vincent Vandecaveye, Wies Deckers, Frederik Cleeren, Jeroen Dekervel, Timon Vandamme, Kim Serdons, Michel Koole, Guy Bormans, Annouschka Laenen, Paul M. Clement, Karen Geboes, Eric Van Cutsem, Kristiaan Nackaerts, Sigrid Stroobants, Chris Verslype, Koen Van Laere, and Christophe M. Deroose. Prospective comparison of [18f]alf-nota-octreotide pet/mri to [68ga]ga-dotatate pet/ct in neuroendocrine tumor patients. EJNMMI Research, Jun 2023. URL: https://doi.org/10.1186/s13550-023-01003-3, doi:10.1186/s13550-023-01003-3. This article has 24 citations and is from a peer-reviewed journal.

  14. (andersen2024welldifferentiatedg1and pages 1-2): Kirstine Øster Andersen, Sönke Detlefsen, Klaus Brusgaard, and Henrik Thybo Christesen. Well-differentiated g1 and g2 pancreatic neuroendocrine tumors: a meta-analysis of published expanded dna sequencing data. Frontiers in Endocrinology, May 2024. URL: https://doi.org/10.3389/fendo.2024.1351624, doi:10.3389/fendo.2024.1351624. This article has 11 citations.

  15. (almeida2024theroleof pages 1-2): Catarina Almeida, Lorenzo Gervaso, Gianmaria Frigè, Francesca Spada, Lavinia Benini, Chiara Alessandra Cella, Luca Mazzarella, and Nicola Fazio. The role of liquid biopsy in gastroenteropancreatic neuroendocrine neoplasms. Cancers, 16:3349, Sep 2024. URL: https://doi.org/10.3390/cancers16193349, doi:10.3390/cancers16193349. This article has 7 citations.

  16. (boeckxstaens2023prospectivecomparisonof media b98f7885): Lennert Boeckxstaens, Elin Pauwels, Vincent Vandecaveye, Wies Deckers, Frederik Cleeren, Jeroen Dekervel, Timon Vandamme, Kim Serdons, Michel Koole, Guy Bormans, Annouschka Laenen, Paul M. Clement, Karen Geboes, Eric Van Cutsem, Kristiaan Nackaerts, Sigrid Stroobants, Chris Verslype, Koen Van Laere, and Christophe M. Deroose. Prospective comparison of [18f]alf-nota-octreotide pet/mri to [68ga]ga-dotatate pet/ct in neuroendocrine tumor patients. EJNMMI Research, Jun 2023. URL: https://doi.org/10.1186/s13550-023-01003-3, doi:10.1186/s13550-023-01003-3. This article has 24 citations and is from a peer-reviewed journal.

  17. (boeckxstaens2023prospectivecomparisonof media be4d67f8): Lennert Boeckxstaens, Elin Pauwels, Vincent Vandecaveye, Wies Deckers, Frederik Cleeren, Jeroen Dekervel, Timon Vandamme, Kim Serdons, Michel Koole, Guy Bormans, Annouschka Laenen, Paul M. Clement, Karen Geboes, Eric Van Cutsem, Kristiaan Nackaerts, Sigrid Stroobants, Chris Verslype, Koen Van Laere, and Christophe M. Deroose. Prospective comparison of [18f]alf-nota-octreotide pet/mri to [68ga]ga-dotatate pet/ct in neuroendocrine tumor patients. EJNMMI Research, Jun 2023. URL: https://doi.org/10.1186/s13550-023-01003-3, doi:10.1186/s13550-023-01003-3. This article has 24 citations and is from a peer-reviewed journal.

  18. (boeckxstaens2023prospectivecomparisonof media 4b687989): Lennert Boeckxstaens, Elin Pauwels, Vincent Vandecaveye, Wies Deckers, Frederik Cleeren, Jeroen Dekervel, Timon Vandamme, Kim Serdons, Michel Koole, Guy Bormans, Annouschka Laenen, Paul M. Clement, Karen Geboes, Eric Van Cutsem, Kristiaan Nackaerts, Sigrid Stroobants, Chris Verslype, Koen Van Laere, and Christophe M. Deroose. Prospective comparison of [18f]alf-nota-octreotide pet/mri to [68ga]ga-dotatate pet/ct in neuroendocrine tumor patients. EJNMMI Research, Jun 2023. URL: https://doi.org/10.1186/s13550-023-01003-3, doi:10.1186/s13550-023-01003-3. This article has 24 citations and is from a peer-reviewed journal.

  19. (hernandezfelix2025emergingdiagnosticsand pages 5-6): Jorge H. Hernandez-Felix, Monica Isabel Meneses-Medina, Rachel Riechelmann, Jonathan Strosberg, Rocio Garcia-Carbonero, and Jaydira del Rivero. Emerging diagnostics and therapies in neuroendocrine neoplasms: a critical review. Cancers, 17:3632, Nov 2025. URL: https://doi.org/10.3390/cancers17223632, doi:10.3390/cancers17223632. This article has 4 citations.

  20. (chan2025phase3trial pages 1-3): Jennifer A. Chan, Susan Geyer, Tyler Zemla, Michael V. Knopp, Spencer Behr, Sydney Pulsipher, Fang-Shu Ou, Amylou C. Dueck, Jared Acoba, Ardaman Shergill, Edward M. Wolin, Thorvardur R. Halfdanarson, Bhavana Konda, Nikolaos A. Trikalinos, Bernard Tawfik, Nitya Raj, Shagufta Shaheen, Namrata Vijayvergia, Arvind Dasari, Jonathan R. Strosberg, Elise C. Kohn, Matthew H. Kulke, Eileen M. O’Reilly, and Jeffrey A. Meyerhardt. Phase 3 trial of cabozantinib to treat advanced neuroendocrine tumors. New England Journal of Medicine, 392:653-665, Feb 2025. URL: https://doi.org/10.1056/nejmoa2403991, doi:10.1056/nejmoa2403991. This article has 172 citations and is from a highest quality peer-reviewed journal.

  21. (boeckxstaens2023prospectivecomparisonof pages 8-9): Lennert Boeckxstaens, Elin Pauwels, Vincent Vandecaveye, Wies Deckers, Frederik Cleeren, Jeroen Dekervel, Timon Vandamme, Kim Serdons, Michel Koole, Guy Bormans, Annouschka Laenen, Paul M. Clement, Karen Geboes, Eric Van Cutsem, Kristiaan Nackaerts, Sigrid Stroobants, Chris Verslype, Koen Van Laere, and Christophe M. Deroose. Prospective comparison of [18f]alf-nota-octreotide pet/mri to [68ga]ga-dotatate pet/ct in neuroendocrine tumor patients. EJNMMI Research, Jun 2023. URL: https://doi.org/10.1186/s13550-023-01003-3, doi:10.1186/s13550-023-01003-3. This article has 24 citations and is from a peer-reviewed journal.

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