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Quantitative Proteomic Analysis of Meningiomas for the Identification of Surrogate Protein Markers
Meningiomas are the most common non-glial tumors of the brain and spine. Pathophysiology and definite histological grading of meningiomas are frequently found to be deceptive due to their unusual morphological features and locations. Here for the first time we report a comprehensive serum proteomic...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5382771/ https://www.ncbi.nlm.nih.gov/pubmed/25413266 http://dx.doi.org/10.1038/srep07140 |
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author | Sharma, Samridhi Ray, Sandipan Moiyadi, Aliasgar Sridhar, Epari Srivastava, Sanjeeva |
author_facet | Sharma, Samridhi Ray, Sandipan Moiyadi, Aliasgar Sridhar, Epari Srivastava, Sanjeeva |
author_sort | Sharma, Samridhi |
collection | PubMed |
description | Meningiomas are the most common non-glial tumors of the brain and spine. Pathophysiology and definite histological grading of meningiomas are frequently found to be deceptive due to their unusual morphological features and locations. Here for the first time we report a comprehensive serum proteomic analysis of different grades of meningiomas by using multiple quantitative proteomic and immunoassay-based approaches to obtain mechanistic insights about disease pathogenesis and identify grade specific protein signatures. In silico functional analysis revealed modulation of different vital physiological pathways including complement and coagulation cascades, metabolism of lipids and lipoproteins, immune signaling, cell growth and apoptosis and integrin signaling in meningiomas. ROC curve analysis demonstrated apolipoprotein E and A-I and hemopexin as efficient predictors for meningiomas. Identified proteins like vimentin, alpha-2-macroglobulin, apolipoprotein B and A-I and antithrombin-III, which exhibited a sequential increase in different malignancy grades of meningiomas, could serve as potential predictive markers. |
format | Online Article Text |
id | pubmed-5382771 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53827712017-04-11 Quantitative Proteomic Analysis of Meningiomas for the Identification of Surrogate Protein Markers Sharma, Samridhi Ray, Sandipan Moiyadi, Aliasgar Sridhar, Epari Srivastava, Sanjeeva Sci Rep Article Meningiomas are the most common non-glial tumors of the brain and spine. Pathophysiology and definite histological grading of meningiomas are frequently found to be deceptive due to their unusual morphological features and locations. Here for the first time we report a comprehensive serum proteomic analysis of different grades of meningiomas by using multiple quantitative proteomic and immunoassay-based approaches to obtain mechanistic insights about disease pathogenesis and identify grade specific protein signatures. In silico functional analysis revealed modulation of different vital physiological pathways including complement and coagulation cascades, metabolism of lipids and lipoproteins, immune signaling, cell growth and apoptosis and integrin signaling in meningiomas. ROC curve analysis demonstrated apolipoprotein E and A-I and hemopexin as efficient predictors for meningiomas. Identified proteins like vimentin, alpha-2-macroglobulin, apolipoprotein B and A-I and antithrombin-III, which exhibited a sequential increase in different malignancy grades of meningiomas, could serve as potential predictive markers. Nature Publishing Group 2014-11-21 /pmc/articles/PMC5382771/ /pubmed/25413266 http://dx.doi.org/10.1038/srep07140 Text en Copyright © 2014, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Sharma, Samridhi Ray, Sandipan Moiyadi, Aliasgar Sridhar, Epari Srivastava, Sanjeeva Quantitative Proteomic Analysis of Meningiomas for the Identification of Surrogate Protein Markers |
title | Quantitative Proteomic Analysis of Meningiomas for the Identification of Surrogate Protein Markers |
title_full | Quantitative Proteomic Analysis of Meningiomas for the Identification of Surrogate Protein Markers |
title_fullStr | Quantitative Proteomic Analysis of Meningiomas for the Identification of Surrogate Protein Markers |
title_full_unstemmed | Quantitative Proteomic Analysis of Meningiomas for the Identification of Surrogate Protein Markers |
title_short | Quantitative Proteomic Analysis of Meningiomas for the Identification of Surrogate Protein Markers |
title_sort | quantitative proteomic analysis of meningiomas for the identification of surrogate protein markers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5382771/ https://www.ncbi.nlm.nih.gov/pubmed/25413266 http://dx.doi.org/10.1038/srep07140 |
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