Cargando…

Predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment

A single biomarker is not adequate to identify patients with gastric cancer (GC) who have the potential to benefit from anti-PD-1/PD-L1 therapy, presumably owing to the complexity of the tumour microenvironment. The predictive value of tumour-infiltrating immune cells (TIICs) has not been definitive...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Yang, Jia, Keren, Sun, Yu, Zhang, Cheng, Li, Yilin, Zhang, Li, Chen, Zifan, Zhang, Jiangdong, Hu, Yajie, Yuan, Jiajia, Zhao, Xingwang, Li, Yanyan, Gong, Jifang, Dong, Bin, Zhang, Xiaotian, Li, Jian, Shen, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9388563/
https://www.ncbi.nlm.nih.gov/pubmed/35982052
http://dx.doi.org/10.1038/s41467-022-32570-z
_version_ 1784770248505819136
author Chen, Yang
Jia, Keren
Sun, Yu
Zhang, Cheng
Li, Yilin
Zhang, Li
Chen, Zifan
Zhang, Jiangdong
Hu, Yajie
Yuan, Jiajia
Zhao, Xingwang
Li, Yanyan
Gong, Jifang
Dong, Bin
Zhang, Xiaotian
Li, Jian
Shen, Lin
author_facet Chen, Yang
Jia, Keren
Sun, Yu
Zhang, Cheng
Li, Yilin
Zhang, Li
Chen, Zifan
Zhang, Jiangdong
Hu, Yajie
Yuan, Jiajia
Zhao, Xingwang
Li, Yanyan
Gong, Jifang
Dong, Bin
Zhang, Xiaotian
Li, Jian
Shen, Lin
author_sort Chen, Yang
collection PubMed
description A single biomarker is not adequate to identify patients with gastric cancer (GC) who have the potential to benefit from anti-PD-1/PD-L1 therapy, presumably owing to the complexity of the tumour microenvironment. The predictive value of tumour-infiltrating immune cells (TIICs) has not been definitively established with regard to their density and spatial organisation. Here, multiplex immunohistochemistry is used to quantify in situ biomarkers at sub-cellular resolution in 80 patients with GC. To predict the response to immunotherapy, we establish a multi-dimensional TIIC signature by considering the density of CD4(+)FoxP3(−)PD-L1(+), CD8(+)PD-1(−)LAG3(−), and CD68(+)STING(+) cells and the spatial organisation of CD8(+)PD-1(+)LAG3(−) T cells. The TIIC signature enables prediction of the response of patients with GC to anti-PD-1/PD-L1 immunotherapy and patient survival. Our findings demonstrate that a multi-dimensional TIIC signature may be relevant for the selection of patients who could benefit the most from anti-PD-1/PD-L1 immunotherapy.
format Online
Article
Text
id pubmed-9388563
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-93885632022-08-20 Predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment Chen, Yang Jia, Keren Sun, Yu Zhang, Cheng Li, Yilin Zhang, Li Chen, Zifan Zhang, Jiangdong Hu, Yajie Yuan, Jiajia Zhao, Xingwang Li, Yanyan Gong, Jifang Dong, Bin Zhang, Xiaotian Li, Jian Shen, Lin Nat Commun Article A single biomarker is not adequate to identify patients with gastric cancer (GC) who have the potential to benefit from anti-PD-1/PD-L1 therapy, presumably owing to the complexity of the tumour microenvironment. The predictive value of tumour-infiltrating immune cells (TIICs) has not been definitively established with regard to their density and spatial organisation. Here, multiplex immunohistochemistry is used to quantify in situ biomarkers at sub-cellular resolution in 80 patients with GC. To predict the response to immunotherapy, we establish a multi-dimensional TIIC signature by considering the density of CD4(+)FoxP3(−)PD-L1(+), CD8(+)PD-1(−)LAG3(−), and CD68(+)STING(+) cells and the spatial organisation of CD8(+)PD-1(+)LAG3(−) T cells. The TIIC signature enables prediction of the response of patients with GC to anti-PD-1/PD-L1 immunotherapy and patient survival. Our findings demonstrate that a multi-dimensional TIIC signature may be relevant for the selection of patients who could benefit the most from anti-PD-1/PD-L1 immunotherapy. Nature Publishing Group UK 2022-08-18 /pmc/articles/PMC9388563/ /pubmed/35982052 http://dx.doi.org/10.1038/s41467-022-32570-z Text en © The Author(s) 2022 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Chen, Yang
Jia, Keren
Sun, Yu
Zhang, Cheng
Li, Yilin
Zhang, Li
Chen, Zifan
Zhang, Jiangdong
Hu, Yajie
Yuan, Jiajia
Zhao, Xingwang
Li, Yanyan
Gong, Jifang
Dong, Bin
Zhang, Xiaotian
Li, Jian
Shen, Lin
Predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment
title Predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment
title_full Predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment
title_fullStr Predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment
title_full_unstemmed Predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment
title_short Predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment
title_sort predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9388563/
https://www.ncbi.nlm.nih.gov/pubmed/35982052
http://dx.doi.org/10.1038/s41467-022-32570-z
work_keys_str_mv AT chenyang predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT jiakeren predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT sunyu predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT zhangcheng predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT liyilin predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT zhangli predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT chenzifan predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT zhangjiangdong predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT huyajie predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT yuanjiajia predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT zhaoxingwang predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT liyanyan predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT gongjifang predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT dongbin predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT zhangxiaotian predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT lijian predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment
AT shenlin predictingresponsetoimmunotherapyingastriccancerviamultidimensionalanalysesofthetumourimmunemicroenvironment