Jia-You Lin1, Bao-Rong Juo2, Yu-Hsuan Yeh3, Shu-Hsuan Fu2, Yi-Ting Chen2,4, Chien-Lun Chen5,6, Kun-Pin Wu7. 1. Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, 11221, Taiwan. 2. Molecular Medicine Research Center, Chang Gung University, Taoyuan, 33302, Taiwan. 3. Department of Life Sciences and Institute of Genome Sciences, National Yang Ming Chiao Tung University, Taipei, 11221, Taiwan. 4. Department of Biomedical Sciences, Chang Gung University, Taoyuan, 33302, Taiwan. 5. Department of Urology, Chang Gung Memorial Hospital, Taoyuan, 33305, Taiwan. clc2679@cgmh.org.tw. 6. College of Medicine, Chang Gung University, Taoyuan, 33302, Taiwan. clc2679@cgmh.org.tw. 7. Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, 11221, Taiwan. kpwu@nycu.edu.tw.
Abstract
BACKGROUND: Early detection of bladder cancer remains challenging because patients with early-stage bladder cancer usually have no incentive to take cytology or cystoscopy tests if they are asymptomatic. Our goal is to find non-invasive marker candidates that may help us gain insight into the metabolism of early-stage bladder cancer and be examined in routine health checks. RESULTS: We acquired urine samples from 124 patients diagnosed with early-stage bladder cancer or hernia (63 cancer patients and 61 controls). In which 100 samples were included in our marker discovery cohort, and the remaining 24 samples were included in our independent test cohort. We obtained metabolic profiles of 922 compounds of the samples by gas chromatography-mass spectrometry. Based on the metabolic profiles of the marker discovery cohort, we selected marker candidates using Wilcoxon rank-sum test with Bonferroni correction and leave-one-out cross-validation; we further excluded compounds detected in less than 60% of the bladder cancer samples. We finally selected eight putative markers. The abundance of all the eight markers in bladder cancer samples was high but extremely low in hernia samples. Moreover, the up-regulation of these markers might be in association with sugars and polyols metabolism. CONCLUSIONS: In the present study, comparative urine metabolomics selected putative metabolite markers for the detection of early-stage bladder cancer. The suggested relations between early-stage bladder cancer and sugars and polyols metabolism may create opportunities for improving the detection of bladder cancer.
BACKGROUND: Early detection of bladder cancer remains challenging because patients with early-stage bladder cancer usually have no incentive to take cytology or cystoscopy tests if they are asymptomatic. Our goal is to find non-invasive marker candidates that may help us gain insight into the metabolism of early-stage bladder cancer and be examined in routine health checks. RESULTS: We acquired urine samples from 124 patients diagnosed with early-stage bladder cancer or hernia (63 cancerpatients and 61 controls). In which 100 samples were included in our marker discovery cohort, and the remaining 24 samples were included in our independent test cohort. We obtained metabolic profiles of 922 compounds of the samples by gas chromatography-mass spectrometry. Based on the metabolic profiles of the marker discovery cohort, we selected marker candidates using Wilcoxon rank-sum test with Bonferroni correction and leave-one-out cross-validation; we further excluded compounds detected in less than 60% of the bladder cancer samples. We finally selected eight putative markers. The abundance of all the eight markers in bladder cancer samples was high but extremely low in hernia samples. Moreover, the up-regulation of these markers might be in association with sugars and polyols metabolism. CONCLUSIONS: In the present study, comparative urine metabolomics selected putative metabolite markers for the detection of early-stage bladder cancer. The suggested relations between early-stage bladder cancer and sugars and polyols metabolism may create opportunities for improving the detection of bladder cancer.
Entities:
Keywords:
Bioinformatics; Biomarkers; Gas chromatography-mass spectrometry; Metabolomics; Omics data analysis
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