Speakers
Andrew Davison
Warwick Dunn
Seamus Coyle
Parallel session
Chair: Andrew Davison
Mass spectrometry in the clinical laboratory - is metabolomics the next big thing?
9.30 - 10.00 - Discovery and validation of clinical metabolic biomarkers using metabolomic tools - Warwick Dunn
Metabolites are small biochemicals which can be assayed using many different scientific techniques. A range of metabolites are already applied in clinical biochemistry laboratories for disease diagnosis including glucose (for insulin resistance and diabetes) and amino acids/acyl carnitines for newborn screening for inborn errors in metabolism. Metabolomics is a discovery-based strategy applied to investigate 100-1000s of metabolites in human biofluids and tissues to enable the identification of multi-metabolite biomarker panels to be applied for disease diagnosis, risk stratification and response to treatment. In this presentation I will introduce (1) the role of metabolomics for discovery of new biomarker panels will be introduced with examples from the presenters group focused on blood cancers and exocrine function, (2) discuss the importance of validation and translation workflows and (3) discuss future applications and bottlenecks to overcome.
10.00 - 10.30 - Biomarkers of dying - how we die from cancer? Seamus Coyle
Predicting when a patient with advanced cancer is dying is a challenge and currently no prognostic test is available. Despite the fact that nearly 10 million people worldwide died from cancer in 2020 alone, little is known about the biochemical pathways that change as people die. We hypothesise there are specific metabolic changes associated with dying. This talk will present the results of recent metabolomic studies on the urine of patients with lung cancer. Metabolomics identifies new or changing metabolites from biological samples and can give an insight into changes in biochemical pathways. Data will be presented showing not only metabolite changes but also associated biochemical pathways. From these metabolites we developed a number of models predicting the dying process within the last weeks of life. The metabolites identified are potential biomarkers of dying in lung cancer and could be used as a tool to provide additional prognostic information to inform expert clinician judgement.
10.30 - 11.00 - Urine steroid metabolomics for the differential diagnosis of Adrenal Tumours - James Hawley
Adrenal tumours are detected in up to 7% of cross-sectional imaging studies, these have limited specificity for diagnosing adrenocortical carcinoma (ACC). Urine steroid metabolomics (USM) is a sensitive and specific tool for detecting ACC. USM was first established using multi-steroid profiling using gas chromatography-mass spectrometry combined with a machine learning (ML) based diagnostic algorithm. However, we have recently prospectively validated the use of liquid chromatography-tandem mass spectrometry (LC-MS/MS) for high-throughput USM for the detection of ACC. Here, I will discuss the journey so far as we look to translate LC-MS/MS USM combined with machine learning from a useful research test into routine NHS practice.
Chair: Andrew Davison
Andrew Davison is a Consultant Clinical Scientist in the department of Clinical Biochemistry at Liverpool Clinical Laboratories (LCL). He is clinical lead for research and development and mass spectrometry at LCL, and a senior clinical research fellow and honorary clinical lecturer at the University of Liverpool. He is also an honorary senior lecturer in Clinical Biochemistry at the University of Manchester, and a senior examiner for the Royal College of Pathologists. He is also a member of the European MSACL practical training committee and previously chaired the Clinical and Forensic Specialist Interest Group for the British Mass Spectrometry Society. He completed his NIHR funded PhD at the University of Liverpool studying the impact of nitisinone treatment on the metabolome and whether nitisinone induced hypertyrosinaemia alters neurotransmitter metabolism. He has over 65 peer reviewed publications (>22 first author). He is passionate about teaching and applying mass spectrometry/metabolomic based techniques to several areas of women’s health including endometrial cancer, and adrenal disease.
Warwick holds a PhD in mass spectrometry-based analytical chemistry and has applied chromatography-mass spectrometry platforms to study metabolism in mammals for more than twenty years. During the last 15 years he has focussed on studies to identify metabolic changes related to disease, ageing and food/exercise interventions including in precision medicine applications to stratify patients based on disease risk or treatment response. He has H-Index of 70 and > 24,500 citations. He is a Director of the Metabolomics Society and one of the founding members of the metabolomics quality assurance and quality control consortium (mQACC).
Dr Coyle is a Consultant in Palliative Medicine at The Clatterbridge Cancer Centre and an Honorary Senior Clinical Lecturer at the Liverpool Head and Neck Centre at the University of Liverpool. He moved to Liverpool to take up an Academic Clinical Fellowship in August 2012 and completed consultancy training in 2016. His main research area is the Biology of dying and the development of a urine test to predict dying (recently patented). He is the Clinical lead for Innovation at Clatterbridge since February 2022.
I am a Principal Clinical Scientist based at Manchester University NHS Foundation Trust and a current MRC Clinical Research Fellow.
I began my training at University Hospital Coventry and Warwickshire NHS Foundation Trust in 2009 and moved to Manchester in 2013 to take up a Senior Scientist position at Professor Brian Keevil’s laboratory. Since starting at Manchester I have completed full FRCPath and developed an interest in the clinical applications of LC-MS/MS. In particular, I have focussed on the accurate quantitation of steroid hormones and have developed and published several LC-MS/MS methods that are now in routine use in Manchester. I am currently undertaking a MRC funded fellowship with Professor Wiebke Arlt as we look to introduce steroid profiling combined with machine learning into the NHS.