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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2016
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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. |
format | Online Article Text |
id | pubmed-4819600 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
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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