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Temporal characterization of serum metabolite signatures in lung cancer patients undergoing treatment

Lung cancer causes more deaths in men and women than any other cancer related disease. Currently, few effective strategies exist to predict how patients will respond to treatment. We evaluated the serum metabolomic profiles of 25 lung cancer patients undergoing chemotherapy ± radiation to evaluate t...

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Autores principales: Hao, Desirée, Sarfaraz, M. Omair, Farshidfar, Farshad, Bebb, D. Gwyn, Lee, Camelia Y., Card, Cynthia M., David, Marilyn, Weljie, Aalim M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4819600/
https://www.ncbi.nlm.nih.gov/pubmed/27073350
http://dx.doi.org/10.1007/s11306-016-0961-5
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author Hao, Desirée
Sarfaraz, M. Omair
Farshidfar, Farshad
Bebb, D. Gwyn
Lee, Camelia Y.
Card, Cynthia M.
David, Marilyn
Weljie, Aalim M.
author_facet Hao, Desirée
Sarfaraz, M. Omair
Farshidfar, Farshad
Bebb, D. Gwyn
Lee, Camelia Y.
Card, Cynthia M.
David, Marilyn
Weljie, Aalim M.
author_sort Hao, Desirée
collection PubMed
description Lung cancer causes more deaths in men and women than any other cancer related disease. Currently, few effective strategies exist to predict how patients will respond to treatment. We evaluated the serum metabolomic profiles of 25 lung cancer patients undergoing chemotherapy ± radiation to evaluate the feasibility of metabolites as temporal biomarkers of clinical outcomes. Serial serum specimens collected prospectively from lung cancer patients were analyzed using both nuclear magnetic resonance ((1)H-NMR) spectroscopy and gas chromatography mass spectrometry (GC–MS). Multivariate statistical analysis consisted of unsupervised principal component analysis or orthogonal partial least squares discriminant analysis with significance assessed using a cross-validated ANOVA. The metabolite profiles were reflective of the temporal distinction between patient samples before during and after receiving therapy ((1)H-NMR, p < 0.001: and GC–MS p < 0.01). Disease progression and survival were strongly correlative with the GC–MS metabolite data whereas stage and cancer type were associated with (1)H-NMR data. Metabolites such as hydroxylamine, tridecan-1-ol, octadecan-1-ol, were indicative of survival (GC–MS p < 0.05) and metabolites such as tagatose, hydroxylamine, glucopyranose, and threonine that were reflective of progression (GC–MS p < 0.05). Metabolite profiles have the potential to act as prognostic markers of clinical outcomes for lung cancer patients. Serial (1)H-NMR measurements appear to detect metabolites diagnostic of tumor pathology, while GC–MS provided data better related to prognostic clinical outcomes, possibility due to physiochemical bias related to specific biochemical pathways. These results warrant further study in a larger cohort and with various treatment options. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-016-0961-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-48196002016-04-10 Temporal characterization of serum metabolite signatures in lung cancer patients undergoing treatment Hao, Desirée Sarfaraz, M. Omair Farshidfar, Farshad Bebb, D. Gwyn Lee, Camelia Y. Card, Cynthia M. David, Marilyn Weljie, Aalim M. Metabolomics Original Article Lung cancer causes more deaths in men and women than any other cancer related disease. Currently, few effective strategies exist to predict how patients will respond to treatment. We evaluated the serum metabolomic profiles of 25 lung cancer patients undergoing chemotherapy ± radiation to evaluate the feasibility of metabolites as temporal biomarkers of clinical outcomes. Serial serum specimens collected prospectively from lung cancer patients were analyzed using both nuclear magnetic resonance ((1)H-NMR) spectroscopy and gas chromatography mass spectrometry (GC–MS). Multivariate statistical analysis consisted of unsupervised principal component analysis or orthogonal partial least squares discriminant analysis with significance assessed using a cross-validated ANOVA. The metabolite profiles were reflective of the temporal distinction between patient samples before during and after receiving therapy ((1)H-NMR, p < 0.001: and GC–MS p < 0.01). Disease progression and survival were strongly correlative with the GC–MS metabolite data whereas stage and cancer type were associated with (1)H-NMR data. Metabolites such as hydroxylamine, tridecan-1-ol, octadecan-1-ol, were indicative of survival (GC–MS p < 0.05) and metabolites such as tagatose, hydroxylamine, glucopyranose, and threonine that were reflective of progression (GC–MS p < 0.05). Metabolite profiles have the potential to act as prognostic markers of clinical outcomes for lung cancer patients. Serial (1)H-NMR measurements appear to detect metabolites diagnostic of tumor pathology, while GC–MS provided data better related to prognostic clinical outcomes, possibility due to physiochemical bias related to specific biochemical pathways. These results warrant further study in a larger cohort and with various treatment options. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-016-0961-5) contains supplementary material, which is available to authorized users. Springer US 2016-02-27 2016 /pmc/articles/PMC4819600/ /pubmed/27073350 http://dx.doi.org/10.1007/s11306-016-0961-5 Text en © Springer Science+Business Media New York 2016
spellingShingle Original Article
Hao, Desirée
Sarfaraz, M. Omair
Farshidfar, Farshad
Bebb, D. Gwyn
Lee, Camelia Y.
Card, Cynthia M.
David, Marilyn
Weljie, Aalim M.
Temporal characterization of serum metabolite signatures in lung cancer patients undergoing treatment
title Temporal characterization of serum metabolite signatures in lung cancer patients undergoing treatment
title_full Temporal characterization of serum metabolite signatures in lung cancer patients undergoing treatment
title_fullStr Temporal characterization of serum metabolite signatures in lung cancer patients undergoing treatment
title_full_unstemmed Temporal characterization of serum metabolite signatures in lung cancer patients undergoing treatment
title_short Temporal characterization of serum metabolite signatures in lung cancer patients undergoing treatment
title_sort temporal characterization of serum metabolite signatures in lung cancer patients undergoing treatment
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4819600/
https://www.ncbi.nlm.nih.gov/pubmed/27073350
http://dx.doi.org/10.1007/s11306-016-0961-5
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