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Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation

The finding of new diagnostic and prognostic markers of local radiation injury, and particularly of the cutaneous radiation syndrome, is crucial for its medical management, in the case of both accidental exposure and radiotherapy side effects. Especially, a fast high-throughput method is still neede...

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Autores principales: Chaze, Thibault, Hornez, Louis, Chambon, Christophe, Haddad, Iman, Vinh, Joelle, Peyrat, Jean-Philippe, Benderitter, Marc, Guipaud, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5302747/
https://www.ncbi.nlm.nih.gov/pubmed/28250398
http://dx.doi.org/10.3390/proteomes1020040
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author Chaze, Thibault
Hornez, Louis
Chambon, Christophe
Haddad, Iman
Vinh, Joelle
Peyrat, Jean-Philippe
Benderitter, Marc
Guipaud, Olivier
author_facet Chaze, Thibault
Hornez, Louis
Chambon, Christophe
Haddad, Iman
Vinh, Joelle
Peyrat, Jean-Philippe
Benderitter, Marc
Guipaud, Olivier
author_sort Chaze, Thibault
collection PubMed
description The finding of new diagnostic and prognostic markers of local radiation injury, and particularly of the cutaneous radiation syndrome, is crucial for its medical management, in the case of both accidental exposure and radiotherapy side effects. Especially, a fast high-throughput method is still needed for triage of people accidentally exposed to ionizing radiation. In this study, we investigated the impact of localized irradiation of the skin on the early alteration of the serum proteome of mice in an effort to discover markers associated with the exposure and severity of impending damage. Using two different large-scale quantitative proteomic approaches, 2D-DIGE-MS and SELDI-TOF-MS, we performed global analyses of serum proteins collected in the clinical latency phase (days 3 and 7) from non-irradiated and locally irradiated mice exposed to high doses of 20, 40 and 80 Gy which will develop respectively erythema, moist desquamation and necrosis. Unsupervised and supervised multivariate statistical analyses (principal component analysis, partial-least square discriminant analysis and Random Forest analysis) using 2D-DIGE quantitative protein data allowed us to discriminate early between non-irradiated and irradiated animals, and between uninjured/slightly injured animals and animals that will develop severe lesions. On the other hand, despite a high number of animal replicates, PLS-DA and Random Forest analyses of SELDI-TOF-MS data failed to reveal sets of MS peaks able to discriminate between the different groups of animals. Our results show that, unlike SELDI-TOF-MS, the 2D-DIGE approach remains a powerful and promising method for the discovery of sets of proteins that could be used for the development of clinical tests for triage and the prognosis of the severity of radiation-induced skin lesions. We propose a list of 15 proteins which constitutes a set of candidate proteins for triage and prognosis of skin lesion outcomes.
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spelling pubmed-53027472017-02-27 Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation Chaze, Thibault Hornez, Louis Chambon, Christophe Haddad, Iman Vinh, Joelle Peyrat, Jean-Philippe Benderitter, Marc Guipaud, Olivier Proteomes Article The finding of new diagnostic and prognostic markers of local radiation injury, and particularly of the cutaneous radiation syndrome, is crucial for its medical management, in the case of both accidental exposure and radiotherapy side effects. Especially, a fast high-throughput method is still needed for triage of people accidentally exposed to ionizing radiation. In this study, we investigated the impact of localized irradiation of the skin on the early alteration of the serum proteome of mice in an effort to discover markers associated with the exposure and severity of impending damage. Using two different large-scale quantitative proteomic approaches, 2D-DIGE-MS and SELDI-TOF-MS, we performed global analyses of serum proteins collected in the clinical latency phase (days 3 and 7) from non-irradiated and locally irradiated mice exposed to high doses of 20, 40 and 80 Gy which will develop respectively erythema, moist desquamation and necrosis. Unsupervised and supervised multivariate statistical analyses (principal component analysis, partial-least square discriminant analysis and Random Forest analysis) using 2D-DIGE quantitative protein data allowed us to discriminate early between non-irradiated and irradiated animals, and between uninjured/slightly injured animals and animals that will develop severe lesions. On the other hand, despite a high number of animal replicates, PLS-DA and Random Forest analyses of SELDI-TOF-MS data failed to reveal sets of MS peaks able to discriminate between the different groups of animals. Our results show that, unlike SELDI-TOF-MS, the 2D-DIGE approach remains a powerful and promising method for the discovery of sets of proteins that could be used for the development of clinical tests for triage and the prognosis of the severity of radiation-induced skin lesions. We propose a list of 15 proteins which constitutes a set of candidate proteins for triage and prognosis of skin lesion outcomes. MDPI 2013-07-10 /pmc/articles/PMC5302747/ /pubmed/28250398 http://dx.doi.org/10.3390/proteomes1020040 Text en © 2013 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Chaze, Thibault
Hornez, Louis
Chambon, Christophe
Haddad, Iman
Vinh, Joelle
Peyrat, Jean-Philippe
Benderitter, Marc
Guipaud, Olivier
Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation
title Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation
title_full Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation
title_fullStr Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation
title_full_unstemmed Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation
title_short Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation
title_sort serum proteome analysis for profiling predictive protein markers associated with the severity of skin lesions induced by ionizing radiation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5302747/
https://www.ncbi.nlm.nih.gov/pubmed/28250398
http://dx.doi.org/10.3390/proteomes1020040
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