The discovery and evaluation of metabolic and epigenetic biomarkers in the diagnosis of epithelial ovarian cancer
File(s)
Author(s)
Davis, Kayleigh Rebecca
Type
Thesis
Abstract
Background: Epithelial ovarian cancer (EOC) is often diagnosed late in the advanced stages of the disease with an associated poor prognosis. A large scale multicentre randomised control screening trial, the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), failed to show a significant reduction in mortality in the screening groups using trans-vaginal ultrasound and cancer antigen 125 (CA 125) compared to the no screening group. More sensitive biomarkers for diagnosis of ovarian cancer are a clinical priority. Molecular profiling of ‘liquid biopsies’ has the potential to detect changes associated with the tumour in non-invasively collected blood samples. This study focusses on the use of epigenomics, specifically DNA methylation and metabonomics to identify tumour-specific changes and their performance as diagnostic and prognostic biomarkers in non-invasively collected biofluid.
Methods: Differential methylation analysis using the Illumina Infinium® Methylation BeadChip was interrogated to identify candidate methylation biomarkers specific to EOC tumour DNA compared to peripheral blood mononuclear cells (PBMCs). Bisulphite pyrosequencing was used to characterise these biomarkers in tumour and blood.
Metabolic profiling techniques including nuclear magnetic resonance (NMR) and mass spectrometry (MS) of blood and urine were used to identify metabolic changes associated with EOC diagnosis and survival.
Results: Nine loci differentially methylated between tumour and PBMC DNA, were identified. Methylation of 5/9 candidate loci were shown to be significantly different in prospectively collected plasma samples from patients with high grade serous ovarian cancer (HGSOC) compared to benign/healthy controls with one marker achieving an area under the curve (AUC) of 0.901.
Metabonomic analysis of plasma samples identified alterations in amino acid, ketone body and lipid metabolism associated with EOC. Several of these metabolites including tryptophan and beta-hydroxybutyrate were also shown to be significantly associated with overall survival (OS) with hazard ratios of 0.39 (95% CI 0.18-0.83) and 2.76 (95% CI 1.28-5.97) respectively.
Conclusions: EOC tumour-specific DNA methylation can be detected in tumour and plasma of EOC cancer patients, providing insight into the biology of the disease and potential as novel diagnostic biomarkers. Metabolic profiling has uncovered a number of candidate EOC biomarkers associated with prognosis. Prospective validation of these biomarkers could help EOC treatment stratification in the future.
Methods: Differential methylation analysis using the Illumina Infinium® Methylation BeadChip was interrogated to identify candidate methylation biomarkers specific to EOC tumour DNA compared to peripheral blood mononuclear cells (PBMCs). Bisulphite pyrosequencing was used to characterise these biomarkers in tumour and blood.
Metabolic profiling techniques including nuclear magnetic resonance (NMR) and mass spectrometry (MS) of blood and urine were used to identify metabolic changes associated with EOC diagnosis and survival.
Results: Nine loci differentially methylated between tumour and PBMC DNA, were identified. Methylation of 5/9 candidate loci were shown to be significantly different in prospectively collected plasma samples from patients with high grade serous ovarian cancer (HGSOC) compared to benign/healthy controls with one marker achieving an area under the curve (AUC) of 0.901.
Metabonomic analysis of plasma samples identified alterations in amino acid, ketone body and lipid metabolism associated with EOC. Several of these metabolites including tryptophan and beta-hydroxybutyrate were also shown to be significantly associated with overall survival (OS) with hazard ratios of 0.39 (95% CI 0.18-0.83) and 2.76 (95% CI 1.28-5.97) respectively.
Conclusions: EOC tumour-specific DNA methylation can be detected in tumour and plasma of EOC cancer patients, providing insight into the biology of the disease and potential as novel diagnostic biomarkers. Metabolic profiling has uncovered a number of candidate EOC biomarkers associated with prognosis. Prospective validation of these biomarkers could help EOC treatment stratification in the future.
Version
Open Access
Date Issued
2017-09
Date Awarded
2018-03
Copyright Statement
Attribution NoDerivatives 4.0 International Licence (CC BY-ND)
Advisor
Brown, Robert
Nicholson, Jeremy
Sponsor
Imperial College London
Publisher Department
Department of Surgery & Cancer
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)