Molecular diversity in neuroendocrine tumors: A house divided.

Abstract

e15170 Background: Despite significant morphological overlap between sub-groups, significant clinical heterogeneity is the hallmark of NENs. We sought to examine the molecular profiles of NENs to demonstrate the molecular heterogeneity that underpins differences in tumor biology. Methods: Tissue samples from 76 patients with NENs were analyzed, encompassing six WHO categories and various anatomic sites of origin (ASO). Molecular profiling was conducted using a semiconductor-based NGS platform at Datar Cancer Genetics. Mutation frequencies and pathway alterations were evaluated across WHO categories. Results: The cohort was distributed across WHO categories: NET grade 1 (N = 1), NET grade 2 (N = 9), NET grade 3 (N = 8), small cell NEC (N = 25), large cell NEC (N = 18), and mixed neuroendocrine-non-neuroendocrine neoplasms (MiNENs) (N = 5). An additional 10 tumors were classified as poorly differentiated NEC. Lung was the most common ASO (37%), followed by the pancreas (16%), gastrointestinal tract accounted (15%), female genitourinary tract (8%) and other rare sites contributed the rest. PD-L1 22C3 analysis (N = 42) showed negative status in 90% of cases, and 10% of cases showed positivity, with positive cases being limited to NECs. MSI status was stable in all cases (N = 40). High TMB (>10 muts/mb) was observed in 27% of samples (N = 13/48).High TMB was restricted to NECs, except for two cases of pancreatic NETs showing high TMB. Molecular profiling of the entire cohort together showed TP53 muattions as most frequent alterations (49%), followed by RB1 mutations (17%), CTNND2 amplifications (16%), RICTOR (11%), and MYC (10%) amplifications, along with NF1 mutations (9%). The PI3K/AKT/mTOR pathway was altered in 25% of tumors, and MAPK/ERK alterations in 16% of cases. PIK3CA , KRAS , and RB1 alterations were restricted to NECs and absent in NETs. Except for TP53 acting as a sole driver in 5% of cases, no two tumors shared an identical molecular profile, highlighting the pronounced molecular heterogeneity even within the same grade and organ of origin. Conclusions: We highlight the significant molecular heterogeneity among NENs, even within the same grade and ASO. These findings emphasize the necessity of integrating molecular profiling into the clinical management of NENs to enable personalized therapeutic strategies. Further studies in larger cohorts may shed added light into further characterisation of NENs. Incidence of genomic alterations across neuroendocrine tumor grades/subtypes. Gene NETGrade 1/2 NETGrade 3 Small cell NEC Large cell NEC MiNEN SNVs /InDels TP53 10.0% 37.5% 56.0% 55.6% 60.0% RB1 -- -- 36.0% 11.1% -- NF1 -- 12.5% 4.0% 16.7% -- KRAS -- -- -- 16.7% 20.0% PIK3CA -- -- -- 11.1% 20.0% CDKN2A 10.0% 12.5% 4.0% -- -- RET 10.0% 12.5% -- -- -- BRAF -- -- -- -- 20.0% Amplifications MYC -- -- 4.0% 16.7% -- CTNND2 -- -- 16.0% 11.1% 20.0% RICTOR -- -- 12.0% 11.1% 20.0% PIK3CA -- -- 20.0% -- 20.0% FGFR1 -- -- -- 11.1% -- PDGFRA -- -- -- 5.6% 20.0% ERBB2 -- -- -- 5.6% --