Genomic Landscape of Gastroenteropancreatic Neuroendocrine Neoplasms Using Panel Sequencing

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.

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.

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).

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.