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An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals

Glioblastomas (GBM) are largely incurable as they diffusely infiltrate adjacent brain tissues and are difficult to diagnose at early stages. Biomarkers derived from serum, which can be obtained by minimally invasive procedures, may help in early diagnosis, prognosis and treatment monitoring. To deve...

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Autores principales: Nijaguna, Mamatha B., Patil, Vikas, Hegde, Alangar S., Chandramouli, Bangalore A., Arivazhagan, Arimappamagan, Santosh, Vani, Somasundaram, Kumaravel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4577083/
https://www.ncbi.nlm.nih.gov/pubmed/26390214
http://dx.doi.org/10.1371/journal.pone.0137524
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author Nijaguna, Mamatha B.
Patil, Vikas
Hegde, Alangar S.
Chandramouli, Bangalore A.
Arivazhagan, Arimappamagan
Santosh, Vani
Somasundaram, Kumaravel
author_facet Nijaguna, Mamatha B.
Patil, Vikas
Hegde, Alangar S.
Chandramouli, Bangalore A.
Arivazhagan, Arimappamagan
Santosh, Vani
Somasundaram, Kumaravel
author_sort Nijaguna, Mamatha B.
collection PubMed
description Glioblastomas (GBM) are largely incurable as they diffusely infiltrate adjacent brain tissues and are difficult to diagnose at early stages. Biomarkers derived from serum, which can be obtained by minimally invasive procedures, may help in early diagnosis, prognosis and treatment monitoring. To develop a serum cytokine signature, we profiled 48 cytokines in sera derived from normal healthy individuals (n = 26) and different grades of glioma patients (n = 194). We divided the normal and grade IV glioma/GBM serum samples randomly into equal sized training and test sets. In the training set, the Prediction Analysis for Microarrays (PAM) identified a panel of 18 cytokines that could discriminate GBM sera from normal sera with maximum accuracy (95.40%) and minimum error (4.60%). The 18-cytokine signature obtained in the training set discriminated GBM sera from normal sera in the test set as well (accuracy 96.55%; error 3.45%). Interestingly, the 18-cytokine signature also differentiated grade II/Diffuse Astrocytoma (DA) and grade III/Anaplastic Astrocytoma (AA) sera from normal sera very efficiently (DA vs. normal–accuracy 96.00%, error 4.00%; AA vs. normal–accuracy 95.83%, error 4.17%). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using 18 cytokines resulted in the enrichment of two pathways, cytokine-cytokine receptor interaction and JAK-STAT pathways with high significance. Thus our study identified an 18-cytokine signature for distinguishing glioma sera from normal healthy individual sera and also demonstrated the importance of their differential abundance in glioma biology.
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spelling pubmed-45770832015-09-25 An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals Nijaguna, Mamatha B. Patil, Vikas Hegde, Alangar S. Chandramouli, Bangalore A. Arivazhagan, Arimappamagan Santosh, Vani Somasundaram, Kumaravel PLoS One Research Article Glioblastomas (GBM) are largely incurable as they diffusely infiltrate adjacent brain tissues and are difficult to diagnose at early stages. Biomarkers derived from serum, which can be obtained by minimally invasive procedures, may help in early diagnosis, prognosis and treatment monitoring. To develop a serum cytokine signature, we profiled 48 cytokines in sera derived from normal healthy individuals (n = 26) and different grades of glioma patients (n = 194). We divided the normal and grade IV glioma/GBM serum samples randomly into equal sized training and test sets. In the training set, the Prediction Analysis for Microarrays (PAM) identified a panel of 18 cytokines that could discriminate GBM sera from normal sera with maximum accuracy (95.40%) and minimum error (4.60%). The 18-cytokine signature obtained in the training set discriminated GBM sera from normal sera in the test set as well (accuracy 96.55%; error 3.45%). Interestingly, the 18-cytokine signature also differentiated grade II/Diffuse Astrocytoma (DA) and grade III/Anaplastic Astrocytoma (AA) sera from normal sera very efficiently (DA vs. normal–accuracy 96.00%, error 4.00%; AA vs. normal–accuracy 95.83%, error 4.17%). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using 18 cytokines resulted in the enrichment of two pathways, cytokine-cytokine receptor interaction and JAK-STAT pathways with high significance. Thus our study identified an 18-cytokine signature for distinguishing glioma sera from normal healthy individual sera and also demonstrated the importance of their differential abundance in glioma biology. Public Library of Science 2015-09-21 /pmc/articles/PMC4577083/ /pubmed/26390214 http://dx.doi.org/10.1371/journal.pone.0137524 Text en © 2015 Nijaguna et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Nijaguna, Mamatha B.
Patil, Vikas
Hegde, Alangar S.
Chandramouli, Bangalore A.
Arivazhagan, Arimappamagan
Santosh, Vani
Somasundaram, Kumaravel
An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals
title An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals
title_full An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals
title_fullStr An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals
title_full_unstemmed An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals
title_short An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals
title_sort eighteen serum cytokine signature for discriminating glioma from normal healthy individuals
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4577083/
https://www.ncbi.nlm.nih.gov/pubmed/26390214
http://dx.doi.org/10.1371/journal.pone.0137524
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