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Putting Proteomics Into Immunotherapy for Glioblastoma

In glioblastoma, the most aggressive brain cancer, a complex microenvironment of heterogeneity and immunosuppression, are considerable hurdles to classify the subtypes and promote treatment progression. Treatments for glioblastoma are similar to standard therapies for many other cancers and do not e...

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Autores principales: Chen, Liangyu, Qin, Di, Guo, Xinyu, Wang, Qixue, Li, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7940695/
https://www.ncbi.nlm.nih.gov/pubmed/33708196
http://dx.doi.org/10.3389/fimmu.2021.593255
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author Chen, Liangyu
Qin, Di
Guo, Xinyu
Wang, Qixue
Li, Jie
author_facet Chen, Liangyu
Qin, Di
Guo, Xinyu
Wang, Qixue
Li, Jie
author_sort Chen, Liangyu
collection PubMed
description In glioblastoma, the most aggressive brain cancer, a complex microenvironment of heterogeneity and immunosuppression, are considerable hurdles to classify the subtypes and promote treatment progression. Treatments for glioblastoma are similar to standard therapies for many other cancers and do not effectively prolong the survival of patients, due to the unique location and heterogeneous characteristics of glioblastoma. Immunotherapy has shown a promising effect for many other tumors, but its application for glioma still has some challenges. The recent breakthrough of high-throughput liquid chromatography–mass spectrometry (LC-MS/MS) systems has allowed researchers to update their strategy for identifying and quantifying thousands of proteins in a much shorter time with lesser effort. The protein maps can contribute to generating a complete map of regulatory systems to elucidate tumor mechanisms. In particular, newly developed unicellular proteomics could be used to determine the microenvironment and heterogeneity. In addition, a large scale of differentiated proteins provides more ways to precisely classify tumor subtypes and construct a larger library for biomarkers and biotargets, especially for immunotherapy. A series of advanced proteomic studies have been devoted to the different aspects of immunotherapy for glioma, including monoclonal antibodies, oncolytic viruses, dendritic cell (DC) vaccines, and chimeric antigen receptor (CAR) T cells. Thus, the application of proteomics in immunotherapy may accelerate research on the treatment of glioblastoma. In this review, we evaluate the frontline applications of proteomics strategies for immunotherapy in glioblastoma research.
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spelling pubmed-79406952021-03-10 Putting Proteomics Into Immunotherapy for Glioblastoma Chen, Liangyu Qin, Di Guo, Xinyu Wang, Qixue Li, Jie Front Immunol Immunology In glioblastoma, the most aggressive brain cancer, a complex microenvironment of heterogeneity and immunosuppression, are considerable hurdles to classify the subtypes and promote treatment progression. Treatments for glioblastoma are similar to standard therapies for many other cancers and do not effectively prolong the survival of patients, due to the unique location and heterogeneous characteristics of glioblastoma. Immunotherapy has shown a promising effect for many other tumors, but its application for glioma still has some challenges. The recent breakthrough of high-throughput liquid chromatography–mass spectrometry (LC-MS/MS) systems has allowed researchers to update their strategy for identifying and quantifying thousands of proteins in a much shorter time with lesser effort. The protein maps can contribute to generating a complete map of regulatory systems to elucidate tumor mechanisms. In particular, newly developed unicellular proteomics could be used to determine the microenvironment and heterogeneity. In addition, a large scale of differentiated proteins provides more ways to precisely classify tumor subtypes and construct a larger library for biomarkers and biotargets, especially for immunotherapy. A series of advanced proteomic studies have been devoted to the different aspects of immunotherapy for glioma, including monoclonal antibodies, oncolytic viruses, dendritic cell (DC) vaccines, and chimeric antigen receptor (CAR) T cells. Thus, the application of proteomics in immunotherapy may accelerate research on the treatment of glioblastoma. In this review, we evaluate the frontline applications of proteomics strategies for immunotherapy in glioblastoma research. Frontiers Media S.A. 2021-02-23 /pmc/articles/PMC7940695/ /pubmed/33708196 http://dx.doi.org/10.3389/fimmu.2021.593255 Text en Copyright © 2021 Chen, Qin, Guo, Wang and Li. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Chen, Liangyu
Qin, Di
Guo, Xinyu
Wang, Qixue
Li, Jie
Putting Proteomics Into Immunotherapy for Glioblastoma
title Putting Proteomics Into Immunotherapy for Glioblastoma
title_full Putting Proteomics Into Immunotherapy for Glioblastoma
title_fullStr Putting Proteomics Into Immunotherapy for Glioblastoma
title_full_unstemmed Putting Proteomics Into Immunotherapy for Glioblastoma
title_short Putting Proteomics Into Immunotherapy for Glioblastoma
title_sort putting proteomics into immunotherapy for glioblastoma
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7940695/
https://www.ncbi.nlm.nih.gov/pubmed/33708196
http://dx.doi.org/10.3389/fimmu.2021.593255
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