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Peer-reviewedCC BY-NC-ND 4.0JCO Precision Oncology

Genomic Landscape of Gastroenteropancreatic Neuroendocrine Neoplasms Using Panel Sequencing

  • Ali Zaidi1
  • Emma Titmuss1
  • Renata D'Alpino Peixoto1
  • Sharlene Gill1
  • Sharon Gorski2
  • David Schaeffer3
  • Joao Paulo Solar Vasconcelos1
  • Jonathan M. Loree1
  • Gordon Taylor Moffat4,5
5 affiliations
  1. 1Department of Medical Oncology, BC Cancer Vancouver Centre, Vancouver, BC, Canada
  2. 2Department of Basic and Translational Research, BC Cancer Research Centre, Vancouver, BC, Canada
  3. 3Division of Anatomic Pathology, Vancouver General Hospital, Vancouver, BC, Canada
  4. 4Department of Oncology, Queen's University, Kingston, ON, Canada
  5. 5Cancer Centre of Southeastern Ontario, Kingston, ON, Canada
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Abstract

Purpose: The clinical utility of genomic profiling in gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) remains incompletely defined, particularly for clinically relevant annotated alterations and prognostic stratification. We performed a multi-institutional analysis to characterize genomic alterations across GEP-NEN subtypes, generate prevalence estimates to inform precision oncology efforts, and evaluate associations with clinical actionability and survival.

Methods: We performed a retrospective analysis of 1,691 GEP-NENs from the American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange database. Tumors were classified into neuroendocrine tumors (NETs) or neuroendocrine carcinomas (NECs) and stratified by primary site. Genomic alterations, including single-nucleotide variants, insertions/deletions, copy number alterations, and structural variants, were analyzed using a panel-adjusted approach. Alterations were annotated for clinical relevance using multiple knowledge bases. Overall survival was evaluated in a subset (n = 502) with available data.

Results: Genomic alterations were identified in 86.5% of patients. NETs were enriched for alterations in chromatin-remodeling genes (MEN1, DAXX) and mTOR pathway regulator TSC2, whereas NECs were characterized by canonical drivers (TP53, RB1, KRAS, APC, and BRAF). Annotated alterations were identified in 34.1% of all patients, with higher rates in NECs compared with NETs (74.4% v 28.5%, P < .001). Notable annotated targets included BRAF V600E (2.2%; 14.8% of all colorectal NECs), KRAS-activating mutations (6.8%; 0.35% G12C), and NTRK fusions (0.2%). Annotation rates varied by primary site with the highest rates observed in colorectal, gastric, and esophageal NECs. In NETs, the presence of NEC-associated driver alterations was associated with worse overall survival (hazard ratio, 3.67 [95% CI, 2.49 to 5.42], P < .001).

Conclusion: Genomic profiling reveals meaningful differences in biomarker prevalence and prognosis across GEP-NEN subtypes. These findings support integrating genomic profiling with histologic classification to refine risk stratification and inform biomarker-driven clinical trials.

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Cite

BibTeXRIS
BibTeX
@article{zaidi2026genomic,
  title = {{Genomic Landscape of Gastroenteropancreatic Neuroendocrine Neoplasms Using Panel Sequencing}},
  author = {Ali Zaidi and Emma Titmuss and Renata D'Alpino Peixoto and Sharlene Gill and Sharon Gorski and David Schaeffer and Joao Paulo Solar Vasconcelos and Jonathan M. Loree and Gordon Taylor Moffat},
  journal = {JCO Precision Oncology},
  year = {2026},
  month = oct,
  doi = {10.1200/po-26-00601},
  url = {https://doi.org/10.1200/po-26-00601},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Genomic Landscape of Gastroenteropancreatic Neuroendocrine Neoplasms Using Panel Sequencing
AU  - Ali Zaidi
AU  - Emma Titmuss
AU  - Renata D'Alpino Peixoto
AU  - Sharlene Gill
AU  - Sharon Gorski
AU  - David Schaeffer
AU  - Joao Paulo Solar Vasconcelos
AU  - Jonathan M. Loree
AU  - Gordon Taylor Moffat
PY  - 2026
DA  - 2026/10/27
JO  - JCO Precision Oncology
DO  - 10.1200/po-26-00601
UR  - https://doi.org/10.1200/po-26-00601
AB  - Purpose: The clinical utility of genomic profiling in gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) remains incompletely defined, particularly for clinically relevant annotated alterations and prognostic stratification. We performed a multi-institutional analysis to characterize genomic alterations across GEP-NEN subtypes, generate prevalence estimates to inform precision oncology efforts, and evaluate associations with clinical actionability and survival.  Methods: We performed a retrospective analysis of 1,691 GEP-NENs from the American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange database. Tumors were classified into neuroendocrine tumors (NETs) or neuroendocrine carcinomas (NECs) and stratified by primary site. Genomic alterations, including single-nucleotide variants, insertions/deletions, copy number alterations, and structural variants, were analyzed using a panel-adjusted approach. Alterations were annotated for clinical relevance using multiple knowledge bases. Overall survival was evaluated in a subset (n = 502) with available data.  Results: Genomic alterations were identified in 86.5% of patients. NETs were enriched for alterations in chromatin-remodeling genes (MEN1, DAXX) and mTOR pathway regulator TSC2, whereas NECs were characterized by canonical drivers (TP53, RB1, KRAS, APC, and BRAF). Annotated alterations were identified in 34.1% of all patients, with higher rates in NECs compared with NETs (74.4% v 28.5%, P < .001). Notable annotated targets included BRAF V600E (2.2%; 14.8% of all colorectal NECs), KRAS-activating mutations (6.8%; 0.35% G12C), and NTRK fusions (0.2%). Annotation rates varied by primary site with the highest rates observed in colorectal, gastric, and esophageal NECs. In NETs, the presence of NEC-associated driver alterations was associated with worse overall survival (hazard ratio, 3.67 [95% CI, 2.49 to 5.42], P < .001).  Conclusion: Genomic profiling reveals meaningful differences in biomarker prevalence and prognosis across GEP-NEN subtypes. These findings support integrating genomic profiling with histologic classification to refine risk stratification and inform biomarker-driven clinical trials.
SN  - 2473-4284
ER  -