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Novel mutational mechanisms and drivers in Pancreatic Neuroendocrine Tumours

Pancreatic neuroendocrine tumours (PanNETs) are increasing in prevalence due to earlier detection, consequently creating challenges in clinical care, as current classification permits unsatisfactory therapeutic stratification. We performed whole genome sequencing of 102 primary PanNETs and defined the genomic events underlying their pathogenesis. We describe the mutational signatures they harbour, including a novel G:C>T:A Base-Excision-Repair-deficiency signature due to MUTYH inactivation. We uncover a larger than expected proportion of germline mutations in clinically sporadic PanNETs. These include previously unreported mutations in DNA repair genes MUTYH, CHEK2, BRCA2, and PALB2, which together with MEN1 and VHL occur in 16% of patients. Somatic mutations (point mutations and structural rearrangements) commonly occurred in genes involved in 4 main pathways: chromatin remodelling, DNA damage repair, activation of mTOR signalling (including novel EWSR1 gene fusions) and telomere maintenance. Aberrations in these mechanisms are associated with subtypes of PanNET with potential clinical application for prognostic and therapeutic stratification.

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID Description Technology Samples
EGAD00001002684 196
EGAD00001003336 29
EGAD00001006063 41
Publications Citations
Whole-genome sequencing reveals distinct genetic bases for insulinomas and non-functional pancreatic neuroendocrine tumours: leading to a new classification system.
Gut 69: 2020 877-887
51
DNA methylation patterns identify subgroups of pancreatic neuroendocrine tumors with clinical association.
Commun Biol 4: 2021 155
15
Longitudinal Copy-Number Alteration Analysis in Plasma Cell-Free DNA of Neuroendocrine Neoplasms is a Novel Specific Biomarker for Diagnosis, Prognosis, and Follow-up.
Clin Cancer Res 28: 2022 338-349
14
Cdk5 drives formation of heterogeneous pancreatic neuroendocrine tumors.
Oncogenesis 10: 2021 83
10
Transcriptomic Deconvolution of Neuroendocrine Neoplasms Predicts Clinically Relevant Characteristics.
Cancers (Basel) 15: 2023 936
0
Generalising uncertainty improves accuracy and safety of deep learning analytics applied to oncology.
Sci Rep 13: 2023 7395
0