Background: The current system to predict the outcome of nylalanine, proline, serine, valine, isoleucine, glycine, and smokers with bladder cancer is insufficient due to complex asparagine) and taurine were observed in bladder cancer genomic and transcriptomic heterogeneities. This study aims smokers. Integration of differential metabolomic gene signa-to identify serum metabolite-associated genes related to sur-ture and transcriptomics data from TCGA cohort revealed an vival in this population. intersection of 17 genes that showed significant correlation Methods: We performed LC/MS-based targeted metabo-with patient survival in bladder cancer smokers. Importantly, lomic analysis for >300 metabolites in serum obtained catechol-O-methyltransferase, iodotyrosine deiodinase, and from two independent cohorts of bladder cancer never tubulin tyrosine ligase showed a significant association with smokers, smokers, healthy smokers, and healthy never patient survival in publicly available bladder cancer smoker smokers. A subset of differential metabolites was validated datasets and did not have any clinical association in never using Biocrates absoluteIDQ p180 Kit. Genes associated smokers. with differential metabolites were integrated with a publicly Conclusions: Serum metabolic profiling of bladder cancer available cohort of The Cancer Genome Atlas (TCGA) to smokers revealed dysregulated amino acid metabolism. It obtain an intersecting signature specific for bladder cancer provides a distinct gene signature that shows a prognostic smokers. value in predicting bladder cancer smoker survival. Results: Forty metabolites (FDR < 0.25) were identified to Impact: Serum metabolic signature–derived genes act as a be differential between bladder cancer never smokers and predictive tool for studying the bladder cancer progression in smokers. Increased abundance of amino acids (tyrosine, phe-smokers.
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