Abstract Library

#3056 Multi-Omic Characterization and Evolution of Neuroendocrine Neoplasm Organoids

Introduction: Molecular characterizations of neuroendocrine neoplasm (NENs) have unveiled candidate alterations associated with aggressiveness and suggested that the molecular link between neuroendocrine tumors (NETs) and neuroendocrine carcinomas (NECs) might be subtler than initially thought. For example, we have recently unveiled a new entity of pulmonary carcinoids (supra-carcinoids) with carcinoid-like morphology yet the molecular and clinical features of large cell neuroendocrine carcinoma (LCNEC). Testing hypotheses to explain aggressiveness and the possibility of progression or transition from NET to NEC through the accumulation of genetic anomalies requires in vitro and in vivo experimental models.

Conference: 17th Annual ENETSConcerence (2020)

Presenting Author: Foll M

Authors: Alcala N, Dayton T, Mangiante L, Delhomme T, Tabone-Egling S,

Keywords: organoids, omics, evolution, lung, pancreas, bioinformatics,

#3028 Pancreatic Neuroendocrine Neoplasms: Dissecting the Molecular Heterogeneity

Introduction: Pancreatic neuroendocrine neoplasms (PNENs) are a group of rare but biologically and clinically heterogeneous neoplasms with variable patient outcomes. Little is known about the molecular differences between PNENs and the biologic significance of such divergence.

Conference: 17th Annual ENETSConcerence (2020)

Presenting Author:

Authors: Yang K, Kalloger S, Aird J, Lee M, Colborne S,

Keywords: Pancreatic neuroendocrine neoplasms, Exome, Transcriptome, Proteome,

#2992 The PanNENomics Project: A Call for an International Collaborative Effort Built on the Success of the LungNENomics Project

Introduction: Neuroendocrine tumors are rare understudied diseases at the molecular level, especially those occurring in sites outside the lung and the gastrointestinal track. This lack of knowledge has strong implications for the clinical management of these diseases (Rindi et al. Mad Pathol 2018).

Conference: 17th Annual ENETSConcerence (2020)

Presenting Author: Fernandez-Cuesta L

Authors: Fernandez-Cuesta L, Foll M, Walter T, Girard N, Lantuejoul S,

Keywords: Rare Cancers genomics, lungNENomics, panNENomics, supra-carcinoids, tumor maps,

#2988 Epigenetic Treatment with Histone Deacetylase Inhibitor Enhances Uptake of [111In]In-DOTA-TATE by Increased SST2 Expression on Neuroendocrine Tumor Cells

Introduction: The somatostatin-2 receptor (SST2) is a target for peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors (NETs). By using epigenetic drugs, which can regulate gene transcription, PRRT efficacy may be further improved due to enhanced SST2 expression.

Conference: 17th Annual ENETSConcerence (2020)

Presenting Author: Klomp I

Authors: Klomp I, Dalm S, van Koetsveld P, Dogan-Oruç F, de Jong M,

Keywords: neuroendocrine tumors, bon-1, epigenetic, histone, histone deacetylase inhibitor, HDACi, upregulation, reversibility, somatostatin receptor-2, somatostatin,

#2980 Metabolic Dysregulation and Circadian Clock in Cellular Models of Neuroendocrine Tumors

Introduction: The circadian clock genes encode transcription factors whose interaction with nuclear receptors allows the regulation of cellular metabolism.The invalidation of the genes of the clock core is associated with the development of many endocrine diseases including neuroendocrine cancer. Recently, the family of transcriptional coactivators PGC-1a has been identified as a key element in the integration of cellular metabolic state with the circadian clock. PRC, as a member of the PGC-1 family, was able to interact with several transcription factors, including the CLOCK factor. The specific induction of this PRC factor by the cell cycle, to modulate the energy function, the MAPkinase pathway and the expression of microRNAs, makes it a key factor in the metabolic adaptation of cancer cells.

Conference: 17th Annual ENETSConcerence (2020)

Presenting Author: Savagner F

Authors: Savagner F, Le Pennec S,

Keywords: Metabolism, Circadian clock, cell models,