TY - JOUR
T1 - Serum metabolic profiling identified a distinct metabolic signature in bladder cancer smokers
T2 - A key metabolic enzyme associated with patient survival
AU - Amara, Chandra Sekhar
AU - Ambati, Chandrashekar R.
AU - Vantaku, Venkatrao
AU - Piyarathna, Danthasinghe Waduge Badrajee
AU - Donepudi, Sri Ramya
AU - Ravi, Shiva Shankar
AU - Arnold, James M.
AU - Putluri, Vasanta
AU - Chatta, Gurkamal
AU - Guru, Khurshid A.
AU - Badr, Hoda
AU - Terris, Martha K.
AU - Bollag, Roni J.
AU - Sreekumar, Arun
AU - Apolo, Andrea B.
AU - Putluri, Nagireddy
N1 - Funding Information:
G. Chatta has received speakers' bureau honoraria from Medimmune and is a consultant/advisory board member for Astra Zeneca. A. Sreekumar reports receiving commercial research funding from Agilent Technologies. No potential conflicts of interest were disclosed by other authors.
Funding Information:
This research was fully supported by NIH/NCI R01CA220297 (to N. Putluri), NIH/NCI R01CA216426 (N. Putluri), and American Cancer Society (ACS) Award 127430-RSG-15-105-01-CNE (N. Putluri), and also partially supported by the following grants: NIH/NCI U01 CA167234 (to A. Sreekumar), UO1 CA179674 (to A. Sreekumar), as well as funds from Alkek Center for Molecular Discovery (to A. Sreekumar). This project was also supported by the Agilent Technologies Center of Excellence (COE) in Mass Spectrometry at Baylor College of Medicine, Metabolomics Core, Prostate Cancer Foundation, Dianna Helis Adrianne Melvin Helis Foundation, Brockman Foundation, Population Sciences Biorepository Core at Baylor College of Medicine with funding from the NIH (P30 CA125123), CPRIT Proteomics and Metabolomics Core Facility (RP170005, to N. Putluri and A. Sreekumar), and Dan L. Duncan Cancer Center. We want to thank Maharajni Perla and Akhil Mandalapu for their input on the analysis.
Funding Information:
Foundation, Brockman Foundation, Population Sciences Biorepository Core at Baylor College of Medicine with funding from the NIH (P30 CA125123), CPRIT Proteomics and Metabolomics Core Facility (RP170005, to N. Putluri and A. Sreekumar), and Dan L. Duncan Cancer Center. We want to thank Maharajni Perla and Akhil Mandalapu for their input on the analysis.
Funding Information:
This research was fully supported by NIH/NCI R01CA220297 (to N. Putluri), NIH/NCI R01CA216426 (N. Putluri), and American Cancer Society (ACS) Award 127430-RSG-15-105-01-CNE (N. Putluri), and also partially supported by the following grants: NIH/NCI U01 CA167234 (to A. Sreekumar), UO1 CA179674 (to A. Sreekumar), as well as funds from Alkek Center for Molecular Discovery (to A. Sreekumar). This project was also supported by the Agilent Technologies Center of Excellence (COE) in Mass Spectrometry at Baylor College of Medicine, Metabolomics Core, Prostate Cancer Foundation, Dianna Helis Adrianne Melvin Helis
Publisher Copyright:
© 2019 American Association for Cancer Research.
PY - 2019/4
Y1 - 2019/4
N2 - 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.
AB - 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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UR - http://www.scopus.com/inward/citedby.url?scp=85063872836&partnerID=8YFLogxK
U2 - 10.1158/1055-9965.EPI-18-0936
DO - 10.1158/1055-9965.EPI-18-0936
M3 - Article
C2 - 30642841
AN - SCOPUS:85063872836
SN - 1055-9965
VL - 28
SP - 770
EP - 781
JO - Cancer Epidemiology Biomarkers and Prevention
JF - Cancer Epidemiology Biomarkers and Prevention
IS - 4
ER -
