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Predictive biomarkers for cancer immunotherapy with immune checkpoint inhibitors

Although the clinical development of immune checkpoint inhibitors (ICIs) therapy has ushered in a new era of anti-tumor therapy, with sustained responses and significant survival advantages observed in multiple tumors, most patients do not benefit. Therefore, more and more attention has been paid to...

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Detalles Bibliográficos
Autores principales: Bai, Rilan, Lv, Zheng, Xu, Dongsheng, Cui, Jiuwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450548/
https://www.ncbi.nlm.nih.gov/pubmed/32864131
http://dx.doi.org/10.1186/s40364-020-00209-0
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author Bai, Rilan
Lv, Zheng
Xu, Dongsheng
Cui, Jiuwei
author_facet Bai, Rilan
Lv, Zheng
Xu, Dongsheng
Cui, Jiuwei
author_sort Bai, Rilan
collection PubMed
description Although the clinical development of immune checkpoint inhibitors (ICIs) therapy has ushered in a new era of anti-tumor therapy, with sustained responses and significant survival advantages observed in multiple tumors, most patients do not benefit. Therefore, more and more attention has been paid to the identification and development of predictive biomarkers for the response of ICIs, and more in-depth and comprehensive understanding has been continuously explored in recent years. Predictive markers of ICIs efficacy have been gradually explored from the expression of intermolecular interactions within tumor cells to the expression of various molecules and cells in tumor microenvironment, and been extended to the exploration of circulating and host systemic markers. With the development of high-throughput sequencing and microarray technology, a variety of biomarker strategies have been deeply explored and gradually achieved the process from the identification of single marker to the development of multifactorial synergistic predictive markers. Comprehensive predictive-models developed by integrating different types of data based on different components of tumor-host interactions is the direction of future research and will have a profound impact in the field of precision immuno-oncology. In this review, we deeply analyze the exploration course and research progress of predictive biomarkers as an adjunctive tool to tumor immunotherapy in effectively identifying the efficacy of ICIs, and discuss their future directions in achieving precision immuno-oncology.
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spelling pubmed-74505482020-08-28 Predictive biomarkers for cancer immunotherapy with immune checkpoint inhibitors Bai, Rilan Lv, Zheng Xu, Dongsheng Cui, Jiuwei Biomark Res Review Although the clinical development of immune checkpoint inhibitors (ICIs) therapy has ushered in a new era of anti-tumor therapy, with sustained responses and significant survival advantages observed in multiple tumors, most patients do not benefit. Therefore, more and more attention has been paid to the identification and development of predictive biomarkers for the response of ICIs, and more in-depth and comprehensive understanding has been continuously explored in recent years. Predictive markers of ICIs efficacy have been gradually explored from the expression of intermolecular interactions within tumor cells to the expression of various molecules and cells in tumor microenvironment, and been extended to the exploration of circulating and host systemic markers. With the development of high-throughput sequencing and microarray technology, a variety of biomarker strategies have been deeply explored and gradually achieved the process from the identification of single marker to the development of multifactorial synergistic predictive markers. Comprehensive predictive-models developed by integrating different types of data based on different components of tumor-host interactions is the direction of future research and will have a profound impact in the field of precision immuno-oncology. In this review, we deeply analyze the exploration course and research progress of predictive biomarkers as an adjunctive tool to tumor immunotherapy in effectively identifying the efficacy of ICIs, and discuss their future directions in achieving precision immuno-oncology. BioMed Central 2020-08-26 /pmc/articles/PMC7450548/ /pubmed/32864131 http://dx.doi.org/10.1186/s40364-020-00209-0 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Review
Bai, Rilan
Lv, Zheng
Xu, Dongsheng
Cui, Jiuwei
Predictive biomarkers for cancer immunotherapy with immune checkpoint inhibitors
title Predictive biomarkers for cancer immunotherapy with immune checkpoint inhibitors
title_full Predictive biomarkers for cancer immunotherapy with immune checkpoint inhibitors
title_fullStr Predictive biomarkers for cancer immunotherapy with immune checkpoint inhibitors
title_full_unstemmed Predictive biomarkers for cancer immunotherapy with immune checkpoint inhibitors
title_short Predictive biomarkers for cancer immunotherapy with immune checkpoint inhibitors
title_sort predictive biomarkers for cancer immunotherapy with immune checkpoint inhibitors
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450548/
https://www.ncbi.nlm.nih.gov/pubmed/32864131
http://dx.doi.org/10.1186/s40364-020-00209-0
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