Investigation For Influence Of The Urinary Metabolic Variations And The Application In Bladder Cancer Biomarker Discovery

Clinical outcomes of bladder cancer(BC)is tightly associated with the stage and grade of initial diagnosed BC so that early detection is clearly important for patients with BC.Although several non-invasive methods such as urinary cytology,imageology method and several urine-based tests have been applied for detection of BC,diagnostic capability of the detective methods is insufficient,especially for early stage of BC called non-muscle invasive(NMI)BC.Urine metabolomics has become a useful strategy to identify biomarkers for cancers.However,individual variations among humans could contribute to the metabolic composition of urine.Perturbations in effect factors must be considered during the design of experimentsObjective:The aim of the study was to explore inter-individual variations,the effects of physiological factors and discover biomarkers of BC using liquid chromatography-high resolution mass spectrometry(LC-HRMS)-based metabolomics.Furthermore,novel biomarkers for NMIBC was discovered in our study.Methods:First morning midstream urine samples were collected.LC-HRMS was applied to explore the influence of age and gender on urine metabolome.Age and gender-matched control subjects were employed to discover biomarkers of BC,NMIBC and low-grade NMIBC.In addition,high-grade NMIBC were distinguished from low-grade NMIBC.Results:In the first part,we explored the urine metabolome in a cohort of 203 health adults,6 patients with benign bladder lesions,and 53 patients with BC.Inter-individual analysis of both healthy controls and BC patients showed that the urine metabolome was relatively stable.Further analysis indicated that sex and age affect inter-individual variations in urine metabolome.To eliminate age and sex interference,additional BC urine metabolomic biomarkers were explored using age and sex-matched urine samples(Test group:44 health adults vs.33 patients with BC).A metabolite panel consisting of trans-2-dodecenoylcamitine,serinyl-valine,feruloyl-2-hydroxyputrescine,and 3-hydroxynonanoyl carnitine was discovered to have good predictive ability for BC with an area under the curve(AUC)of 0.924.External sample(26 control vs.20 BC)validation verified the acceptable accuracy of the model for BC detection.In the second part,a total of 284 subjects were enrolled in our study including 117 healthy adults,80 NMIBC patients without hematuria and 87 NMIBC patients with hematuria.The metabolite panel including dopamine 4-sulfate,MG00/1846Z,9Z,12Z,15Z/00,aspartyl-histidine,tyrosyl-methionine was found in discovery set,which showed the predictive ability to distinct NMIBC group from the control group with AUC of 0.838 in external validation set.Then,AUC of the panel for low-grade NMIBC samples consisted of 3-hydroxy-cis-5-tetradecenoylcarnitine,6-ketoestriol,beta-cortolone,tetrahydrocorticosterone and heptylmalonic acid was 0.899.AUC of the panel for distinction low-grade NMIBC versus high-grade NMIBC with and without hematuria were 0.827 and 0.755,respectively.Conclusion:The influence of physiological factors such as age and gender must be considered during study design.Panels of metabolites were discovered to have potential value for BC,NMIBC and low-grade NMIBC diagnosis as well as for NMIBC grading distinction.