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Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction
Immune checkpoint inhibitors (ICIs) have dramatically enhanced the treatment outcomes for diverse malignancies. Yet, only 15–60% of patients respond significantly. Therefore, accurate responder identification and timely ICI administration are critical issues in tumor ICI therapy. Recent rapid develo...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10236604/ https://www.ncbi.nlm.nih.gov/pubmed/37268978 http://dx.doi.org/10.1186/s40364-023-00498-1 |
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author | Song, Ruixia Liu, Fengsen Ping, Yu Zhang, Yi Wang, Liping |
author_facet | Song, Ruixia Liu, Fengsen Ping, Yu Zhang, Yi Wang, Liping |
author_sort | Song, Ruixia |
collection | PubMed |
description | Immune checkpoint inhibitors (ICIs) have dramatically enhanced the treatment outcomes for diverse malignancies. Yet, only 15–60% of patients respond significantly. Therefore, accurate responder identification and timely ICI administration are critical issues in tumor ICI therapy. Recent rapid developments at the intersection of oncology, immunology, biology, and computer science have provided an abundance of predictive biomarkers for ICI efficacy. These biomarkers can be invasive or non-invasive, depending on the specific sample collection method. Compared with invasive markers, a host of non-invasive markers have been confirmed to have superior availability and accuracy in ICI efficacy prediction. Considering the outstanding advantages of dynamic monitoring of the immunotherapy response and the potential for widespread clinical application, we review the recent research in this field with the aim of contributing to the identification of patients who may derive the greatest benefit from ICI therapy. |
format | Online Article Text |
id | pubmed-10236604 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-102366042023-06-03 Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction Song, Ruixia Liu, Fengsen Ping, Yu Zhang, Yi Wang, Liping Biomark Res Review Immune checkpoint inhibitors (ICIs) have dramatically enhanced the treatment outcomes for diverse malignancies. Yet, only 15–60% of patients respond significantly. Therefore, accurate responder identification and timely ICI administration are critical issues in tumor ICI therapy. Recent rapid developments at the intersection of oncology, immunology, biology, and computer science have provided an abundance of predictive biomarkers for ICI efficacy. These biomarkers can be invasive or non-invasive, depending on the specific sample collection method. Compared with invasive markers, a host of non-invasive markers have been confirmed to have superior availability and accuracy in ICI efficacy prediction. Considering the outstanding advantages of dynamic monitoring of the immunotherapy response and the potential for widespread clinical application, we review the recent research in this field with the aim of contributing to the identification of patients who may derive the greatest benefit from ICI therapy. BioMed Central 2023-06-02 /pmc/articles/PMC10236604/ /pubmed/37268978 http://dx.doi.org/10.1186/s40364-023-00498-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Song, Ruixia Liu, Fengsen Ping, Yu Zhang, Yi Wang, Liping Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction |
title | Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction |
title_full | Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction |
title_fullStr | Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction |
title_full_unstemmed | Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction |
title_short | Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction |
title_sort | potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10236604/ https://www.ncbi.nlm.nih.gov/pubmed/37268978 http://dx.doi.org/10.1186/s40364-023-00498-1 |
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