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Application of Holistic Liquid Chromatography-High Resolution Mass Spectrometry Based Urinary Metabolomics for Prostate Cancer Detection and Biomarker Discovery
Authors:Tong Zhang  David G Watson  Lijie Wang  Muhammad Abbas  Laura Murdoch  Lisa Bashford  Imran Ahmad  Nga-Yee Lam  Anthony C F Ng  Hing Y Leung
Institution:1. Strathclyde Institute of Pharmacy and Biomedical Sciences, Glasgow, Scotland, United Kingdom.; 2. Department of Urology, Gartnavel General Hospital, Glasgow, Scotland, United Kingdom.; 3. The Beatson Institute for Cancer Research, Glasgow, Scotland, United Kingdom.; 4. Glasgow Clinical Research Facility, Glasgow, Scotland, United Kingdom.; 5. Department of Urology, Chinese University of Hong Kong, Hong Kong.; Florida International University, United States of America,
Abstract:Human exhibit wide variations in their metabolic profiles because of differences in genetic factors, diet and lifestyle. Therefore in order to detect metabolic differences between individuals robust analytical methods are required. A protocol was produced based on the use of Liquid Chromatography- High Resolution Mass Spectrometry (LC-HRMS) in combination with orthogonal Hydrophilic Interaction (HILIC) and Reversed Phase (RP) liquid chromatography methods for the analysis of the urinary metabolome, which was then evaluated as a diagnostic tool for prostate cancer (a common but highly heterogeneous condition). The LC-HRMS method was found to be robust and exhibited excellent repeatability for retention times (<±1%), and mass accuracy (<±1 ppm). Based on normalised data (against creatinine levels, osmolality or MS total useful signals/MSTUS) coupled with supervised multivariate analysis using Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA), we were able to discriminate urine samples from men with or without prostate cancer with R2Y(cum) >0.9. In addition, using the receiver operator characteristics (ROC) test, the area under curve (AUC) for the combination of the four best characterised biomarker compounds was 0.896. The four biomarker compounds were also found to differ significantly (P<0.05) between an independent patient cohort and controls. This is the first time such a rigorous test has been applied to this type of model. If validated, the established protocol provides a robust approach with a potentially wide application to metabolite profiling of human biofluids in health and disease.
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