Nat Commun
August 2024
Eur J Endocrinol
January 2024
Objective: Metabolic profiling is a valuable tool to characterize tumor biology but remains largely unexplored in neuroendocrine tumors (NETs). Our aim was to comprehensively assess the metabolomic profile of NETs and identify novel prognostic biomarkers and dysregulated molecular pathways.
Design And Methods: Multiplatform untargeted metabolomic profiling (GC-MS, CE-MS, and LC-MS) was performed in plasma from 77 patients with G1-2 extra-pancreatic NETs enrolled in the AXINET trial (NCT01744249) (study cohort) and from 68 non-cancer individuals (control).
Poorly differentiated gastroenteropancreatic neuroendocrine carcinomas are aggressive neoplasms of challenging clinical management. A small proportion of patients with early-stage disease may achieve long-term survival, but the majority of patients present with rapidly lethal metastatic disease. Current standard of care still follows the treatment paradigm of small cell lung cancer, a far more common G3 neuroendocrine neoplasm, although emerging molecular and clinical data increasingly question this approach.
View Article and Find Full Text PDFNeuroendocrine neoplasms (NENs) are mutationally quiet (low number of mutations/Mb), and epigenetic mechanisms drive their development and progression. We aimed at comprehensively characterising the microRNA (miRNA) profile of NENs, and exploring downstream targets and their epigenetic modulation. In total, 84 cancer-related miRNAs were analysed in 85 NEN samples from lung and gastroenteropancreatic (GEP) origin, and their prognostic value was evaluated by univariate and multivariate models.
View Article and Find Full Text PDFPurpose: High-throughput "-omic" technologies have enabled the detailed analysis of metabolic networks in several cancers, but NETs have not been explored to date. We aim to assess the metabolomic profile of NET patients to understand metabolic deregulation in these tumors and identify novel biomarkers with clinical potential.
Methods: Plasma samples from 77 NETs and 68 controls were profiled by GC-MS, CE-MS and LC-MS untargeted metabolomics.