Abstract Library

#4583 Improved assessment of gene rearrangements by targeting non-coding DNA regions in patients diagnosed with pancreatic neuroendocrine neoplasms

Introduction: Whole-genome sequencing projects documented the heterogeneity of pancreatic neuroendocrine neoplasms (PanNEN), while showing that few core pathways are consistently affected in their tumorigenesis. Comprehensive genomic profiling (CGP) of real-world cases is expected to recapitulate such heterogeneity for patient stratification and to inform precision therapy. While coding DNA is the focus of current CGP panels, the potential of targeting non-coding DNA (ncDNA) to improve structural variants detection has not been widely explored in this context.

Conference:

Presenting Author: Agnoletto C

Authors: Agnoletto C, Trevisani E, Borghesani M, Landoni L, Luchini C,

Keywords: neuroendocrine, non-coding DNAs, structural variants, clinical relevance, CGP panel,

#4557 miR-1290 and miR-320c regulate cell proliferation and predict patient prognosis in neuroendocrine carcinomas

Introduction: The biology of neuroendocrine carcinomas (NECs) remains largely unknown, limiting the use of biomarkers for patient stratification and therapy response prediction in clinical practice.

Conference:

Presenting Author: Liverani C

Authors: Liverani C, Sgolacchia F, Bongiovanni A, Calabrese C, Vanni S,

Keywords: biomarker, miRNAs, neuroendocrine carcinoma,

#3976 Radiologic tumor border status can further stratify patients with pancreatic neuroendocrine tumor

Introduction: Recently, pattern-based classifications of the tumor border of pancreatic neuroendocrine tumor (PanNET) have been attempted by independent groups for patient stratification, which are only available in the post-operative setting.

Conference:

Presenting Author: Ahn B

Authors: Ahn B, Park H, Kim H, Hong S,

Keywords: pancreas, neuroendocrine tumor, pathologic tumor border, radiologic tumor border, survival, prognosis,

#3183 Clinical stratification of pancreatic neuroendocrine tumors by systematically integrating multimodal and clinical data

Introduction: Non-functional pancreatic neuroendocrine tumors (PanNETs) are heterogeneous with at least two transcriptome subtypes with differential biology, immune mechanisms and prognosis. However, it is challenging to understand how multimodal data interact with clinical variables and contribute to the disease heterogeneity and phenotypes.

Conference: 18th Annual ENETS Concerence (2021)

Presenting Author: Sadanandam A

Authors: Sadanandam A, Lawlor R, Mafficini A, Luchini C, Nyamundanda G,

Keywords: pancreatic neuroendocrine tumor, multimodal data integration, multiomics, clinical data integration, machine learning, artificial intelligence, subtypes, pancreatic cancer, phenotypes, PhenMap, mutations, gene expression, microRNA,

#2215 Development of Multiplex Biomarker Assay to Subtype Pancreatic Neuroendocrine Tumors (PanNETs) with Distinct Prognosis and Mutations

Introduction: Overall 5-year survival for PanNETs ranges from 25-100%. The treatment paradigm for PanNETs largely based upon grades, which is significantly heterogeneous. We previously defined three molecular subtypes (distributed grades) of PanNETs using PanNETassigner signature. There is an unmet clinical need for prognostic and predictive biomarkers and clinically-relevant assays to complement grade and improve patient stratification.

Conference: 15th Annual ENETSConcerence (2018)

Presenting Author: Sadanandam A

Authors: Sadanandam A, Young K, Nyamundanda G, Ragulan C, Lawlor R,

Keywords: molecular subtypes, biomarker assay, clinical assay, patient prognosis, subtype-specific mutations, NanoString Technologies, low-cost assay, pancreatic neuroendocrine tumors, grades, PanNETassigner subtype, patient stratification, pnet,