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Biomarkers for response to immune checkpoint inhibitors in gastrointestinal cancers
Gastrointestinal (GI) cancers account for a large proportion of cancer deaths worldwide and pose a major public health challenge. Immunotherapy is considered to be one of the prominent and successful approaches in cancer treatment in recent years. Among them, immune checkpoint inhibitor (ICI) therap...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790411/ https://www.ncbi.nlm.nih.gov/pubmed/35116101 http://dx.doi.org/10.4251/wjgo.v14.i1.19 |
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author | Li, Meng Kaili, Denis Shi, Lei |
author_facet | Li, Meng Kaili, Denis Shi, Lei |
author_sort | Li, Meng |
collection | PubMed |
description | Gastrointestinal (GI) cancers account for a large proportion of cancer deaths worldwide and pose a major public health challenge. Immunotherapy is considered to be one of the prominent and successful approaches in cancer treatment in recent years. Among them, immune checkpoint inhibitor (ICI) therapy, has received widespread attention, and many clinical findings support the feasibility of ICIs, with sustained responses and significantly prolonged lifespan observed in a wide range of tumors. However, patients treated with ICIs have not fully benefited, and therefore, the identification and development of biomarkers for predicting ICI treatment response have received further attention and exploration. From tumor genome to molecular interactions in the tumor microenvironment, and further expanding to circulating biomarkers and patient characteristics, the exploration of biomarkers is evolving with high-throughput sequencing as well as bioinformatics. More large-scale prospective and specific studies are needed to explore biomarkers in GI cancers. In this review, we summarize the known biomarkers used in ICI therapy for GI tumors. In addition, some ICI biomarkers applied to other tumors are included to provide insights and further validation for GI tumors. Moreover, we present single-cell analysis and machine learning approaches that have emerged in recent years. Although there are no clear applications yet, it can be expected that these techniques will play an important role in the application of biomarker prediction. |
format | Online Article Text |
id | pubmed-8790411 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-87904112022-02-02 Biomarkers for response to immune checkpoint inhibitors in gastrointestinal cancers Li, Meng Kaili, Denis Shi, Lei World J Gastrointest Oncol Review Gastrointestinal (GI) cancers account for a large proportion of cancer deaths worldwide and pose a major public health challenge. Immunotherapy is considered to be one of the prominent and successful approaches in cancer treatment in recent years. Among them, immune checkpoint inhibitor (ICI) therapy, has received widespread attention, and many clinical findings support the feasibility of ICIs, with sustained responses and significantly prolonged lifespan observed in a wide range of tumors. However, patients treated with ICIs have not fully benefited, and therefore, the identification and development of biomarkers for predicting ICI treatment response have received further attention and exploration. From tumor genome to molecular interactions in the tumor microenvironment, and further expanding to circulating biomarkers and patient characteristics, the exploration of biomarkers is evolving with high-throughput sequencing as well as bioinformatics. More large-scale prospective and specific studies are needed to explore biomarkers in GI cancers. In this review, we summarize the known biomarkers used in ICI therapy for GI tumors. In addition, some ICI biomarkers applied to other tumors are included to provide insights and further validation for GI tumors. Moreover, we present single-cell analysis and machine learning approaches that have emerged in recent years. Although there are no clear applications yet, it can be expected that these techniques will play an important role in the application of biomarker prediction. Baishideng Publishing Group Inc 2022-01-15 2022-01-15 /pmc/articles/PMC8790411/ /pubmed/35116101 http://dx.doi.org/10.4251/wjgo.v14.i1.19 Text en ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/ |
spellingShingle | Review Li, Meng Kaili, Denis Shi, Lei Biomarkers for response to immune checkpoint inhibitors in gastrointestinal cancers |
title | Biomarkers for response to immune checkpoint inhibitors in gastrointestinal cancers |
title_full | Biomarkers for response to immune checkpoint inhibitors in gastrointestinal cancers |
title_fullStr | Biomarkers for response to immune checkpoint inhibitors in gastrointestinal cancers |
title_full_unstemmed | Biomarkers for response to immune checkpoint inhibitors in gastrointestinal cancers |
title_short | Biomarkers for response to immune checkpoint inhibitors in gastrointestinal cancers |
title_sort | biomarkers for response to immune checkpoint inhibitors in gastrointestinal cancers |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790411/ https://www.ncbi.nlm.nih.gov/pubmed/35116101 http://dx.doi.org/10.4251/wjgo.v14.i1.19 |
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