PURPOSE: Bladder cancer is one of the most common malignancies of the urinary system, and its screening relies heavily on invasive cystoscopy, which increases the risk of urethral injury and infection. This study aims to use non-targeted metabolomics methods to screen for metabolites that are significantly different between the urine of bladder cancer patients and cancer-free controls. METHODS: In this study, liquid chromatography-mass spectrometry was used to analyze the urine of bladder cancer patients (n = 57) and the cancer-free controls (n = 38) by non-targeted metabolomic analysis and metabolite identification. RESULTS: The results showed that there were significant differences in the expression of 27 metabolites between bladder cancer patients and the cancer-free controls. CONCLUSION: In the multivariate statistical analysis of this study, the urinary metabolic profile data of bladder cancer patients were analyzed, and the receiver operating characteristic curve analysis showed that it is possible to perform non-invasive clinical diagnoses of bladder cancer through these candidate biomarkers.
PURPOSE: Bladder cancer is one of the most common malignancies of the urinary system, and its screening relies heavily on invasive cystoscopy, which increases the risk of urethral injury and infection. This study aims to use non-targeted metabolomics methods to screen for metabolites that are significantly different between the urine of bladder cancer patients and cancer-free controls. METHODS: In this study, liquid chromatography-mass spectrometry was used to analyze the urine of bladder cancer patients (n = 57) and the cancer-free controls (n = 38) by non-targeted metabolomic analysis and metabolite identification. RESULTS: The results showed that there were significant differences in the expression of 27 metabolites between bladder cancer patients and the cancer-free controls. CONCLUSION: In the multivariate statistical analysis of this study, the urinary metabolic profile data of bladder cancer patients were analyzed, and the receiver operating characteristic curve analysis showed that it is possible to perform non-invasive clinical diagnoses of bladder cancer through these candidate biomarkers.
Authors: Roger Chou; John L Gore; David Buckley; Rongwei Fu; Katie Gustafson; Jessica C Griffin; Sara Grusing; Shelley Selph Journal: Ann Intern Med Date: 2015-12-15 Impact factor: 25.391
Authors: Zhiqiang Pang; Jasmine Chong; Guangyan Zhou; David Anderson de Lima Morais; Le Chang; Michel Barrette; Carol Gauthier; Pierre-Étienne Jacques; Shuzhao Li; Jianguo Xia Journal: Nucleic Acids Res Date: 2021-05-21 Impact factor: 16.971
Authors: Bryan M Wittmann; Steven M Stirdivant; Matthew W Mitchell; Jacob E Wulff; Jonathan E McDunn; Zhen Li; Aphrihl Dennis-Barrie; Bruce P Neri; Michael V Milburn; Yair Lotan; Robert L Wolfert Journal: PLoS One Date: 2014-12-26 Impact factor: 3.240
Authors: Joana Pinto; Ângela Carapito; Filipa Amaro; Ana Rita Lima; Carina Carvalho-Maia; Maria Conceição Martins; Carmen Jerónimo; Rui Henrique; Maria de Lourdes Bastos; Paula Guedes de Pinho Journal: Metabolites Date: 2021-03-26