Abstract Library

#4609 External validation of Rachel score: A prognostic tool for lung neuroendocrine tumours

Introduction: Lung NETs are a heterogeneous group of tumours with variegated clinical presentation and course. The histological subtype (TC vs AC) and TNM stage are established prognostic factors. In a previous work by our group, we developed a prognostic model named Rachel score, with a satisfactory ability to predict OS and PFS in this population.

Conference:

Presenting Author: La Salvia A

Authors: La Salvia A, Marcozzi B, Lamberti G, Manai C, Mazzilli R,

Keywords: lung neuroendocrine tumour, prognostic tool, Rachel score, external cohort, validation,

#4600 Artificial intelligence in predicting neuroendocrine tumour (NET) outcomes: A model-based prognostic approach

Introduction: Neuroendocrine tumours (NETs) vary widely in clinical behaviour, complicating prognosis. Traditional models often struggle with accuracy due to the complexity of NETs. Artificial intelligence (AI) offers tools for enhanced prognostic precision by analysing complex datasets. This study explores an AI-driven approach to predict outcomes in NET patients at Cantonment General Hospital, Pakistan.

Conference:

Presenting Author: Fatima A

Authors: Fatima A,

Keywords: artificial intelligence, machine learning, Precision medicine, Personalised treatment,

#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,

#4516 A methylation-based classifier for neuroendocrine tumour detection using smMIP technology

Introduction: DNA methylation plays an important role in NET pathogenesis. Distinct methylation profiles can differentiate between tumour subtypes, predict malignancy potential, and provide insights into tumour progression.

Conference:

Presenting Author:

Authors: Ibrahim J, Mariën L, Vanpoucke T, Neefs I, Vandenhoeck J,

Keywords: neuroendocrine tumour, DNA methylation, biomarker selection, IMPRESS technology, classifier model,

#4423 Exploring decorin in plasma-derived small extracellular vesicles (sEVs) as a potential diagnostic biomarker for pancreatic neuroendocrine tumours

Introduction: Pancreatic Neuroendocrine tumours (PanNETs), the most common site for GEP‑NENs in Asian countries, particularly India, have shown increasing incidence. Due to a lack of specific biomarkers, often detected at advanced stages. So, this study utilised PanNET tissue proteomics for cancer biomarker discovery and explored the impact of small extracellular cellular vesicles (sEVs) in PanNET growth and metastasis, as they reflect the molecular profile of their tissue of origin.

Conference:

Presenting Author:

Authors: Gorai P, As S, Naik M, Kumar S, Pal S,

Keywords: Decorin, small extracellular vesicles, Pancreatic Neuroendocrine Tumour, Proteomics, circulating biomarker,