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Biomarkers for Predicting Response to Personalized Immunotherapy in Gastric Cancer
Despite advances in diagnostic imaging, surgical techniques, and systemic therapy, gastric cancer (GC) is the third leading cause of cancer-related death worldwide. Unfortunately, molecular heterogeneity and, consequently, acquired resistance in GC are the major causes of failure in the development...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10487043/ https://www.ncbi.nlm.nih.gov/pubmed/37685320 http://dx.doi.org/10.3390/diagnostics13172782 |
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author | Kim, Moonsik Jeong, Ji Yun Seo, An Na |
author_facet | Kim, Moonsik Jeong, Ji Yun Seo, An Na |
author_sort | Kim, Moonsik |
collection | PubMed |
description | Despite advances in diagnostic imaging, surgical techniques, and systemic therapy, gastric cancer (GC) is the third leading cause of cancer-related death worldwide. Unfortunately, molecular heterogeneity and, consequently, acquired resistance in GC are the major causes of failure in the development of biomarker-guided targeted therapies. However, by showing promising survival benefits in some studies, the recent emergence of immunotherapy in GC has had a significant impact on treatment-selectable procedures. Immune checkpoint inhibitors (ICIs), widely indicated in the treatment of several malignancies, target inhibitory receptors on T lymphocytes, including the programmed cell death protein (PD-1)/programmed death-ligand 1 (PD-L1) axis and cytotoxic T-lymphocyte-associated protein 4 (CTLA4), and release effector T-cells from negative feedback signals. In this article, we review currently available predictive biomarkers (including PD-L1, microsatellite instability, Epstein–Barr virus, and tumor mutational burden) that affect the ICI treatment response, focusing on PD-L1 expression. We further briefly describe other potential biomarkers or mechanisms for predicting the response to ICIs in GC. This review may facilitate the expansion of the understanding of biomarkers for predicting the response to ICIs and help select the appropriate therapeutic approaches for patients with GC. |
format | Online Article Text |
id | pubmed-10487043 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-104870432023-09-09 Biomarkers for Predicting Response to Personalized Immunotherapy in Gastric Cancer Kim, Moonsik Jeong, Ji Yun Seo, An Na Diagnostics (Basel) Review Despite advances in diagnostic imaging, surgical techniques, and systemic therapy, gastric cancer (GC) is the third leading cause of cancer-related death worldwide. Unfortunately, molecular heterogeneity and, consequently, acquired resistance in GC are the major causes of failure in the development of biomarker-guided targeted therapies. However, by showing promising survival benefits in some studies, the recent emergence of immunotherapy in GC has had a significant impact on treatment-selectable procedures. Immune checkpoint inhibitors (ICIs), widely indicated in the treatment of several malignancies, target inhibitory receptors on T lymphocytes, including the programmed cell death protein (PD-1)/programmed death-ligand 1 (PD-L1) axis and cytotoxic T-lymphocyte-associated protein 4 (CTLA4), and release effector T-cells from negative feedback signals. In this article, we review currently available predictive biomarkers (including PD-L1, microsatellite instability, Epstein–Barr virus, and tumor mutational burden) that affect the ICI treatment response, focusing on PD-L1 expression. We further briefly describe other potential biomarkers or mechanisms for predicting the response to ICIs in GC. This review may facilitate the expansion of the understanding of biomarkers for predicting the response to ICIs and help select the appropriate therapeutic approaches for patients with GC. MDPI 2023-08-28 /pmc/articles/PMC10487043/ /pubmed/37685320 http://dx.doi.org/10.3390/diagnostics13172782 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Kim, Moonsik Jeong, Ji Yun Seo, An Na Biomarkers for Predicting Response to Personalized Immunotherapy in Gastric Cancer |
title | Biomarkers for Predicting Response to Personalized Immunotherapy in Gastric Cancer |
title_full | Biomarkers for Predicting Response to Personalized Immunotherapy in Gastric Cancer |
title_fullStr | Biomarkers for Predicting Response to Personalized Immunotherapy in Gastric Cancer |
title_full_unstemmed | Biomarkers for Predicting Response to Personalized Immunotherapy in Gastric Cancer |
title_short | Biomarkers for Predicting Response to Personalized Immunotherapy in Gastric Cancer |
title_sort | biomarkers for predicting response to personalized immunotherapy in gastric cancer |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10487043/ https://www.ncbi.nlm.nih.gov/pubmed/37685320 http://dx.doi.org/10.3390/diagnostics13172782 |
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