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Predicting response to immunotherapy in gastric cancer via assessing perineural invasion-mediated inflammation in tumor microenvironment

BACKGROUND: The perineural invasion (PNI)-mediated inflammation of the tumor microenvironment (TME) varies among gastric cancer (GC) patients and exhibits a close relationship with prognosis and immunotherapy. Assessing the neuroinflammation of TME is important in predicting the response to immunoth...

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Autores principales: Li, Xunjun, Wang, Yiyun, Zhai, ZhongYa, Mao, Qingyi, Chen, Dianjie, Xiao, Luxi, Xu, Shuai, Wu, Qilin, Chen, Keming, Hou, Qiantong, He, Qinglie, Shen, Yuyang, Yang, Manchun, Peng, Zishan, He, Siqing, Zhou, Xuanhui, Tan, Haoyang, Luo, Shengwei, Fang, Chuanfa, Li, Guoxin, Chen, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10416472/
https://www.ncbi.nlm.nih.gov/pubmed/37563649
http://dx.doi.org/10.1186/s13046-023-02730-0
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author Li, Xunjun
Wang, Yiyun
Zhai, ZhongYa
Mao, Qingyi
Chen, Dianjie
Xiao, Luxi
Xu, Shuai
Wu, Qilin
Chen, Keming
Hou, Qiantong
He, Qinglie
Shen, Yuyang
Yang, Manchun
Peng, Zishan
He, Siqing
Zhou, Xuanhui
Tan, Haoyang
Luo, Shengwei
Fang, Chuanfa
Li, Guoxin
Chen, Tao
author_facet Li, Xunjun
Wang, Yiyun
Zhai, ZhongYa
Mao, Qingyi
Chen, Dianjie
Xiao, Luxi
Xu, Shuai
Wu, Qilin
Chen, Keming
Hou, Qiantong
He, Qinglie
Shen, Yuyang
Yang, Manchun
Peng, Zishan
He, Siqing
Zhou, Xuanhui
Tan, Haoyang
Luo, Shengwei
Fang, Chuanfa
Li, Guoxin
Chen, Tao
author_sort Li, Xunjun
collection PubMed
description BACKGROUND: The perineural invasion (PNI)-mediated inflammation of the tumor microenvironment (TME) varies among gastric cancer (GC) patients and exhibits a close relationship with prognosis and immunotherapy. Assessing the neuroinflammation of TME is important in predicting the response to immunotherapy in GC patients. METHODS: Fifteen independent cohorts were enrolled in this study. An inflammatory score was developed and validated in GC. Based on PNI-related prognostic inflammatory signatures, patients were divided into Clusters A and B using unsupervised clustering. The characteristics of clusters and the potential regulatory mechanism of key genes were verified by RT-PCR, western-blot, immunohistochemistry and immunofluorescence in cell and tumor tissue samples.The neuroinflammation infiltration (NII) scoring system was developed based on principal component analysis (PCA) and visualized in a nomogram together with other clinical characteristics. RESULTS: Inflammatory scores were higher in GC patients with PNI compared with those without PNI (P < 0.001). NII.clusterB patients with PNI had abundant immune cell infiltration in the TME but worse prognosis compared with patients in the NII.clusterA patients with PNI and non-PNI subgroups. Higher immune checkpoint expression was noted in NII.clusterB-PNI. VCAM1 is a specific signature of NII.clusterB-PNI, which regulates PD-L1 expression by affecting the phosphorylation of STAT3 in GC cells. Patients with PNI and high NII scores may benefit from immunotherapy. Patients with low nomogram scores had a better prognosis than those with high nomogram scores. CONCLUSIONS: Inflammation mediated by PNI is one of the results of tumor-nerve crosstalk, but its impact on the tumor immune microenvironment is complex. Assessing the inflammation features of PNI is a potential method in predicting the response of immunotherapy effectively. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13046-023-02730-0.
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spelling pubmed-104164722023-08-12 Predicting response to immunotherapy in gastric cancer via assessing perineural invasion-mediated inflammation in tumor microenvironment Li, Xunjun Wang, Yiyun Zhai, ZhongYa Mao, Qingyi Chen, Dianjie Xiao, Luxi Xu, Shuai Wu, Qilin Chen, Keming Hou, Qiantong He, Qinglie Shen, Yuyang Yang, Manchun Peng, Zishan He, Siqing Zhou, Xuanhui Tan, Haoyang Luo, Shengwei Fang, Chuanfa Li, Guoxin Chen, Tao J Exp Clin Cancer Res Research BACKGROUND: The perineural invasion (PNI)-mediated inflammation of the tumor microenvironment (TME) varies among gastric cancer (GC) patients and exhibits a close relationship with prognosis and immunotherapy. Assessing the neuroinflammation of TME is important in predicting the response to immunotherapy in GC patients. METHODS: Fifteen independent cohorts were enrolled in this study. An inflammatory score was developed and validated in GC. Based on PNI-related prognostic inflammatory signatures, patients were divided into Clusters A and B using unsupervised clustering. The characteristics of clusters and the potential regulatory mechanism of key genes were verified by RT-PCR, western-blot, immunohistochemistry and immunofluorescence in cell and tumor tissue samples.The neuroinflammation infiltration (NII) scoring system was developed based on principal component analysis (PCA) and visualized in a nomogram together with other clinical characteristics. RESULTS: Inflammatory scores were higher in GC patients with PNI compared with those without PNI (P < 0.001). NII.clusterB patients with PNI had abundant immune cell infiltration in the TME but worse prognosis compared with patients in the NII.clusterA patients with PNI and non-PNI subgroups. Higher immune checkpoint expression was noted in NII.clusterB-PNI. VCAM1 is a specific signature of NII.clusterB-PNI, which regulates PD-L1 expression by affecting the phosphorylation of STAT3 in GC cells. Patients with PNI and high NII scores may benefit from immunotherapy. Patients with low nomogram scores had a better prognosis than those with high nomogram scores. CONCLUSIONS: Inflammation mediated by PNI is one of the results of tumor-nerve crosstalk, but its impact on the tumor immune microenvironment is complex. Assessing the inflammation features of PNI is a potential method in predicting the response of immunotherapy effectively. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13046-023-02730-0. BioMed Central 2023-08-11 /pmc/articles/PMC10416472/ /pubmed/37563649 http://dx.doi.org/10.1186/s13046-023-02730-0 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 Research
Li, Xunjun
Wang, Yiyun
Zhai, ZhongYa
Mao, Qingyi
Chen, Dianjie
Xiao, Luxi
Xu, Shuai
Wu, Qilin
Chen, Keming
Hou, Qiantong
He, Qinglie
Shen, Yuyang
Yang, Manchun
Peng, Zishan
He, Siqing
Zhou, Xuanhui
Tan, Haoyang
Luo, Shengwei
Fang, Chuanfa
Li, Guoxin
Chen, Tao
Predicting response to immunotherapy in gastric cancer via assessing perineural invasion-mediated inflammation in tumor microenvironment
title Predicting response to immunotherapy in gastric cancer via assessing perineural invasion-mediated inflammation in tumor microenvironment
title_full Predicting response to immunotherapy in gastric cancer via assessing perineural invasion-mediated inflammation in tumor microenvironment
title_fullStr Predicting response to immunotherapy in gastric cancer via assessing perineural invasion-mediated inflammation in tumor microenvironment
title_full_unstemmed Predicting response to immunotherapy in gastric cancer via assessing perineural invasion-mediated inflammation in tumor microenvironment
title_short Predicting response to immunotherapy in gastric cancer via assessing perineural invasion-mediated inflammation in tumor microenvironment
title_sort predicting response to immunotherapy in gastric cancer via assessing perineural invasion-mediated inflammation in tumor microenvironment
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10416472/
https://www.ncbi.nlm.nih.gov/pubmed/37563649
http://dx.doi.org/10.1186/s13046-023-02730-0
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