Serum metabolic profiling identified a distinct metabolic signature in bladder cancer smokers: A key metabolic enzyme associated with patient survival

Chandra Sekhar Amara, Chandrashekar R. Ambati, Venkatrao Vantaku, Danthasinghe Waduge Badrajee Piyarathna, Sri Ramya Donepudi, Shiva Shankar Ravi, James M. Arnold, Vasanta Putluri, Gurkamal Chatta, Khurshid A. Guru, Hoda Badr, Martha Kennedy Terris, Roni Jacob Bollag, Arun Sreekumar, Andrea B. Apolo, Nagireddy Putluri

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)770-781
Number of pages12
JournalCancer Epidemiology Biomarkers and Prevention
Volume28
Issue number4
DOIs
StatePublished - Apr 1 2019

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Urinary Bladder Neoplasms
Survival
Enzymes
Serum
Genes
Atlases
Genome
Amino Acids
Catechol O-Methyltransferase
Iodide Peroxidase
Metabolomics
Isoleucine
Asparagine
Taurine
Valine
Proline
Glycine
Serine
Tyrosine
Neoplasms

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

Cite this

Serum metabolic profiling identified a distinct metabolic signature in bladder cancer smokers : A key metabolic enzyme associated with patient survival. / Amara, Chandra Sekhar; Ambati, Chandrashekar R.; Vantaku, Venkatrao; Piyarathna, Danthasinghe Waduge Badrajee; Donepudi, Sri Ramya; Ravi, Shiva Shankar; Arnold, James M.; Putluri, Vasanta; Chatta, Gurkamal; Guru, Khurshid A.; Badr, Hoda; Terris, Martha Kennedy; Bollag, Roni Jacob; Sreekumar, Arun; Apolo, Andrea B.; Putluri, Nagireddy.

In: Cancer Epidemiology Biomarkers and Prevention, Vol. 28, No. 4, 01.04.2019, p. 770-781.

Research output: Contribution to journalArticle

Amara, CS, Ambati, CR, Vantaku, V, Piyarathna, DWB, Donepudi, SR, Ravi, SS, Arnold, JM, Putluri, V, Chatta, G, Guru, KA, Badr, H, Terris, MK, Bollag, RJ, Sreekumar, A, Apolo, AB & Putluri, N 2019, 'Serum metabolic profiling identified a distinct metabolic signature in bladder cancer smokers: A key metabolic enzyme associated with patient survival' Cancer Epidemiology Biomarkers and Prevention, vol. 28, no. 4, pp. 770-781. https://doi.org/10.1158/1055-9965.EPI-18-0936
Amara, Chandra Sekhar ; Ambati, Chandrashekar R. ; Vantaku, Venkatrao ; Piyarathna, Danthasinghe Waduge Badrajee ; Donepudi, Sri Ramya ; Ravi, Shiva Shankar ; Arnold, James M. ; Putluri, Vasanta ; Chatta, Gurkamal ; Guru, Khurshid A. ; Badr, Hoda ; Terris, Martha Kennedy ; Bollag, Roni Jacob ; Sreekumar, Arun ; Apolo, Andrea B. ; Putluri, Nagireddy. / Serum metabolic profiling identified a distinct metabolic signature in bladder cancer smokers : A key metabolic enzyme associated with patient survival. In: Cancer Epidemiology Biomarkers and Prevention. 2019 ; Vol. 28, No. 4. pp. 770-781.
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abstract = "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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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 Kennedy

AU - Bollag, Roni Jacob

AU - Sreekumar, Arun

AU - Apolo, Andrea B.

AU - Putluri, Nagireddy

PY - 2019/4/1

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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.

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