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Title: Molecular profiling of gastrointestinal neuroendocrine tumours
Author: Karpathakis, A.
ISNI:       0000 0004 5364 8708
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2015
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Small intestinal neuroendocrine tumours (SI NETs) are the most common malignancy of the small intestine, however they remain poorly characterised and the underlying pathogenic mechanisms driving disease development have yet to be elucidated. Whole genome and exome sequencing has suggested SI NETs to be mutationally quiet, with the most frequent mutation in Cyclin Dependent Kinase 1B occurring in only 8% of tumours, suggesting mechanisms other than genetic mutations may be responsible for driving SI NET tumourigenesis. Using integrated genomic and epigenomic analysis three distinct somatic copy number alteration (SCNA) profiles of SI NET were identified. The largest subgroup characterised by loss of heterozygosity at chromosome 18, negative CpG island methylator phenotype (CIMP) status, and the presence of CDKN1B mutations, is associated with improved clinical outcomes. A novel Multiple-SCNA signature has been described which defines a smaller subgroup of SI NETs and is characterized by significantly (p=0.04) reduced progression-free survival. A panel of 21 recurrently epigenetically dysregulated genes has been identified, and these represent putative novel pathogenic drivers for SI NET tumourigenesis and candidate novel biomarkers. Epigenetically dysregulated genes identified at a recurrence rate of 80-100% include gastric inhibitory polypeptide receptor (GIPR)(73.5%) – a target for novel imaging techniques in NETs, CDX1 (85.7%), CELSR3 (83.7%), FBP1 (83.7%), PCSK1 (67.3%) and TRIM15 (63.3%). The utility of methylated circulating tumour DNA analysis, and molecular profiling of circulating tumour cells as novel non-invasive biomarkers in SI NETs have been demonstrated. This is the first comprehensive integrated molecular analysis of SI NETs, providing evidence for epigenetic rather than mutational events in addition to SCNAs as drivers of SI NET development. These findings will facilitate improved patient management, treatment selection and prognostication.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available