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Characterization of the Immune Cell Infiltration Landscape in Esophageal Squamous Cell Carcinoma

BACKGROUND: Immunotherapy has achieved remarkable efficacy in treating oesophageal squamous cell carcinoma (ESCC). However, this treatment has limited efficacy in some patients. An increasing number of evidence suggested that immune cells within the tumour microenvironment (TME) are strongly related...

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Autores principales: Sui, Zhilin, Wu, Xianxian, Du, Longde, Wang, Han, Yuan, Lijuan, Zhang, Jian V., Yu, Zhentao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9300817/
https://www.ncbi.nlm.nih.gov/pubmed/35875070
http://dx.doi.org/10.3389/fonc.2022.879326
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author Sui, Zhilin
Wu, Xianxian
Du, Longde
Wang, Han
Yuan, Lijuan
Zhang, Jian V.
Yu, Zhentao
author_facet Sui, Zhilin
Wu, Xianxian
Du, Longde
Wang, Han
Yuan, Lijuan
Zhang, Jian V.
Yu, Zhentao
author_sort Sui, Zhilin
collection PubMed
description BACKGROUND: Immunotherapy has achieved remarkable efficacy in treating oesophageal squamous cell carcinoma (ESCC). However, this treatment has limited efficacy in some patients. An increasing number of evidence suggested that immune cells within the tumour microenvironment (TME) are strongly related to immunotherapy response and patient prognosis. Thus, the landscape of immune cell infiltration (ICI) in ESCC needs to be mapped. METHODS: In the study, the ICI pattern in 206 cases of ESCC was characterised by two algorithms, namely, CIBERSORT and single-sample gene set enrichment analysis (ssGSEA). The ICI score of each specimen was calculated by principal component analysis (PCA) according to ICI signature genes A (ICISGA) and B (ICISGB). The prognostic difference was evaluated by using the Kaplan–Meier method. The related pathways of ICI score were investigated by applying gene set enrichment analysis (GSEA). The R packages of ‘regplot’, ‘timeROC’ and ‘rms’ were applied for the construction of nomogram model. RESULT: Three TME subtypes were identified with no prognostic implication. A total of 333 differentially expressed genes (DEGs) among immune subtypes were determined, among which ICISGA and ICISGB were identified. Finally, ICI scores were constructed, and the patients were grouped into high or low ICI score group. Compared with the low ICI score group, the high ICI score group had better prognosis. GSEA revealed that the high ICI score group referred to multiple signalling pathways, including B cell receptor, Fc gamma R-mediated phagocytosis, NOD-like receptor and TGF-β signalling pathways. In addition, the nomogram model was constructed to evaluate 1-, 3- and 5-year probability of death in an ESCC patient. The ROC and calibration curves indicated that the model has a good discrimination ability. CONCLUSION: We depicted a comprehensive ICI landscape in ESCC. ICI score may be used as a predictor of survival rate, which may be helpful for guiding immunotherapy in the future.
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spelling pubmed-93008172022-07-22 Characterization of the Immune Cell Infiltration Landscape in Esophageal Squamous Cell Carcinoma Sui, Zhilin Wu, Xianxian Du, Longde Wang, Han Yuan, Lijuan Zhang, Jian V. Yu, Zhentao Front Oncol Oncology BACKGROUND: Immunotherapy has achieved remarkable efficacy in treating oesophageal squamous cell carcinoma (ESCC). However, this treatment has limited efficacy in some patients. An increasing number of evidence suggested that immune cells within the tumour microenvironment (TME) are strongly related to immunotherapy response and patient prognosis. Thus, the landscape of immune cell infiltration (ICI) in ESCC needs to be mapped. METHODS: In the study, the ICI pattern in 206 cases of ESCC was characterised by two algorithms, namely, CIBERSORT and single-sample gene set enrichment analysis (ssGSEA). The ICI score of each specimen was calculated by principal component analysis (PCA) according to ICI signature genes A (ICISGA) and B (ICISGB). The prognostic difference was evaluated by using the Kaplan–Meier method. The related pathways of ICI score were investigated by applying gene set enrichment analysis (GSEA). The R packages of ‘regplot’, ‘timeROC’ and ‘rms’ were applied for the construction of nomogram model. RESULT: Three TME subtypes were identified with no prognostic implication. A total of 333 differentially expressed genes (DEGs) among immune subtypes were determined, among which ICISGA and ICISGB were identified. Finally, ICI scores were constructed, and the patients were grouped into high or low ICI score group. Compared with the low ICI score group, the high ICI score group had better prognosis. GSEA revealed that the high ICI score group referred to multiple signalling pathways, including B cell receptor, Fc gamma R-mediated phagocytosis, NOD-like receptor and TGF-β signalling pathways. In addition, the nomogram model was constructed to evaluate 1-, 3- and 5-year probability of death in an ESCC patient. The ROC and calibration curves indicated that the model has a good discrimination ability. CONCLUSION: We depicted a comprehensive ICI landscape in ESCC. ICI score may be used as a predictor of survival rate, which may be helpful for guiding immunotherapy in the future. Frontiers Media S.A. 2022-07-07 /pmc/articles/PMC9300817/ /pubmed/35875070 http://dx.doi.org/10.3389/fonc.2022.879326 Text en Copyright © 2022 Sui, Wu, Du, Wang, Yuan, Zhang and Yu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Sui, Zhilin
Wu, Xianxian
Du, Longde
Wang, Han
Yuan, Lijuan
Zhang, Jian V.
Yu, Zhentao
Characterization of the Immune Cell Infiltration Landscape in Esophageal Squamous Cell Carcinoma
title Characterization of the Immune Cell Infiltration Landscape in Esophageal Squamous Cell Carcinoma
title_full Characterization of the Immune Cell Infiltration Landscape in Esophageal Squamous Cell Carcinoma
title_fullStr Characterization of the Immune Cell Infiltration Landscape in Esophageal Squamous Cell Carcinoma
title_full_unstemmed Characterization of the Immune Cell Infiltration Landscape in Esophageal Squamous Cell Carcinoma
title_short Characterization of the Immune Cell Infiltration Landscape in Esophageal Squamous Cell Carcinoma
title_sort characterization of the immune cell infiltration landscape in esophageal squamous cell carcinoma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9300817/
https://www.ncbi.nlm.nih.gov/pubmed/35875070
http://dx.doi.org/10.3389/fonc.2022.879326
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