Dataset Information

Peptidomic analysis of pancreatic neurodendocrine tumours (Glucagonoma)

ABSTRACT: A peptidomic analysis of plasma from patients with well characterised pancreatic neuroendocrine tumours (PNET) was performed. A nano LC-MS analysis identified a number of peptides from the glucagon gene, which were idenfiried in a previous case study using multiple immunoassays. Peptides to other proteins involved in peptide secretion were also identified. Plasma from a second glucagonoma patient was analysed using a high flow approach, and this identified similar peptides to the nano analysis. In order to demonstrate the potential clinical application of LC-MS to characterising neuroendocrine tumours, a large cohort of plasma samples were analysed to demonstrate the ability of this approach to identify glucagonoma patients, and differentiate from a single insulinoma patient

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Professor Fiona Gribble

PROVIDER: MSV000082880 | MassIVE | Fri Aug 31 15:39:00 BST 2018

SECONDARY ACCESSION(S): PXD008465

REPOSITORIES: MassIVE

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Peptidomic analysis of endogenous plasma peptides from patients with pancreatic neuroendocrine tumours.

Kay Richard G RG Challis Benjamin G BG Casey Ruth T RT Roberts Geoffrey P GP Meek Claire L CL Reimann Frank F Gribble Fiona M FM

Rapid communications in mass spectrometry : RCM 20180801 16

<h4>Rationale</h4>Diagnosis of pancreatic neuroendocrine tumours requires the study of patient plasma with multiple immunoassays, using multiple aliquots of plasma. The application of mass spectrometry based techniques could reduce the cost and amount of plasma required for diagnosis.<h4>Methods</h4>Plasma samples from two patients with pancreatic neuroendocrine tumours were extracted using an established acetonitrile-based plasma peptide enrichment strategy. The circulating peptidome was charac ...[more]

PMID: 29857350

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Project description:Background and Aims Small intestinal neuroendocrine tumours (SINETs) are the commonest malignancy of the small intestine; however underlying pathogenic mechanisms remain poorly characterised. Whole genome and exome sequencing has demonstrated that SINETs are mutationally quiet with the most frequent known mutation in the cyclin dependent kinase inhibitor 1B gene (CDKN1B) occurring in only ~8% of tumours, suggesting that alternative mechanisms may drive tumourigenesis. The aim of this study is to perform genome-wide molecular profiling of SINETs in order to identify pathogenic drivers based on molecular profiling. This study represents the largest unbiased integrated genomic, epigenomic, and transcriptomic analysis undertaken in this tumour type. Methods Here we present data from integrated molecular analysis of SINETs (n=97) including whole exome or targeted CDKN1B sequencing (n=29), HumanMethylation450 BeadChip (Illumina) array profiling (n=69), methylated DNA immunoprecipitation sequencing (n=16), copy number variance analysis (n=47) and Whole Genome-DASL (Illumina) expression array profiling (n=43). Results Based on molecular profiling SINETs can be classified in to three groups which demonstrate significantly different progression-free survival after resection of primary tumour (not reached at 10 years vs 56 months vs 21 months, p=0.04). Epimutations were found at a recurrence rate of up to 85% and 21 epigenetically dysregulated genes were identified, including CDX1 (86%), CELSR3 (84%), FBP1 (84%) and GIPR (74%). Conclusions This is the first comprehensive integrated molecular analysis of SINETs. We have demonstrated that these tumours are highly epigenetically dysregulated. Furthermore, we have identified novel molecular subtypes with significant impact on progression free survival. Background and Aims Small intestinal neuroendocrine tumours (SINETs) are the commonest malignancy of the small intestine; however underlying pathogenic mechanisms remain poorly characterised. Whole genome and exome sequencing has demonstrated that SINETs are mutationally quiet with the most frequent known mutation in the cyclin dependent kinase inhibitor 1B gene (CDKN1B) occurring in only ~8% of tumours, suggesting that alternative mechanisms may drive tumourigenesis. The aim of this study is to perform genome-wide molecular profiling of SINETs in order to identify pathogenic drivers based on molecular profiling. This study represents the largest unbiased integrated genomic, epigenomic, and transcriptomic analysis undertaken in this tumour type. Methods Here we present data from integrated molecular analysis of SINETs (n=97) including whole exome or targeted CDKN1B sequencing (n=29), HumanMethylation450 BeadChip (Illumina) array profiling (n=69), methylated DNA immunoprecipitation sequencing (n=16), copy number variance analysis (n=47) and Whole Genome-DASL (Illumina) expression array profiling (n=43). Results Based on molecular profiling SINETs can be classified in to three groups which demonstrate significantly different progression-free survival after resection of primary tumour (not reached at 10 years vs 56 months vs 21 months, p=0.04). Epimutations were found at a recurrence rate of up to 85% and 21 epigenetically dysregulated genes were identified, including CDX1 (86%), CELSR3 (84%), FBP1 (84%) and GIPR (74%). Conclusions This is the first comprehensive integrated molecular analysis of SINETs. We have demonstrated that these tumours are highly epigenetically dysregulated. Furthermore, we have identified novel molecular subtypes with significant impact on progression free survival. This study included 97 tumour samples from 85 individuals, this included both primary and metastatic tumour samples. 25 normal small intestinal samples were analysed.