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A novel immune-related gene signature predicts survival in esophageal squamous cell carcinoma

BACKGROUND: Immune-related genes (IRGs) are highly relevant to the progression and prognosis of esophageal squamous cell carcinoma (ESCC). A prognostic signature could be reliable in stratifying ESCC patients according to the risk score, which may help manage systematic treatments. In this study, a...

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Autores principales: Xu, Tao, Dai, Tianyang, Zeng, Peiyuan, Guo, Yunfen, He, Kaiming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798451/
https://www.ncbi.nlm.nih.gov/pubmed/35116551
http://dx.doi.org/10.21037/tcr-20-2665
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author Xu, Tao
Dai, Tianyang
Zeng, Peiyuan
Guo, Yunfen
He, Kaiming
author_facet Xu, Tao
Dai, Tianyang
Zeng, Peiyuan
Guo, Yunfen
He, Kaiming
author_sort Xu, Tao
collection PubMed
description BACKGROUND: Immune-related genes (IRGs) are highly relevant to the progression and prognosis of esophageal squamous cell carcinoma (ESCC). A prognostic signature could be reliable in stratifying ESCC patients according to the risk score, which may help manage systematic treatments. In this study, a systematic and reliable immune signature was developed to estimate the prognostic stratification in ESCC. METHODS: Ribonucleic acid (RNA) expression data of 79 ESCC samples from the Cancer Genome Atlas (TCGA) database and 269 normal esophageal mucosal samples from the Genotype-Tissue Expression (GTEx) project database were downloaded from the University of California, Santa Cruz (UCSC) website to form a TCGA-GTEx dataset. First, we screened differentially expressed genes (DEGs) and then filtered IRGs based on the Immunology Database and Analysis Portal (ImmPort) database to obtain immune-related DEGs (IRDEGs). Next, a novel prognostic signature based on IRDEGs was developed using multivariable Cox analysis. Immune infiltration status was evaluated via single-sample gene set enrichment analysis (ssGSEA). ESCC tissues were grouped into three clusters in terms of immune infiltration (Immunity-L, Immunity-M, and Immunity-H) by applying an unsupervised hierarchical clustering algorithm. Finally, the samples were divided into high- and low-risk groups using the median of the risk score scores for GSEA pathway enrichment analysis in the three clusters. RESULTS: The prognostic signature based on IRDEGs (FCER1G, ISG20, and EGFR) performed moderately in prognostic predictions, with a concordance index (C-index) value of 0.73 [95% (confidence interval) CI: 0.63–0.84, P=2.02E-05] and an area under the curve (AUC) value of 0.817. The xenobiotic metabolism pathway was significantly enriched and up-regulated both in the high-risk group of the immunity-M and immunity-H clusters. CONCLUSIONS: The novel immune-related prognostic signature we constructed has a good prognostic, predictive ability and can be used as an independent prognostic indicator. Our study provides clinicians with a quantitative tool to predict the probability of individual survival time and helps clinicians select targets for immunotherapies and individualized treatment strategies for ESCC patients.
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spelling pubmed-87984512022-02-02 A novel immune-related gene signature predicts survival in esophageal squamous cell carcinoma Xu, Tao Dai, Tianyang Zeng, Peiyuan Guo, Yunfen He, Kaiming Transl Cancer Res Original Article BACKGROUND: Immune-related genes (IRGs) are highly relevant to the progression and prognosis of esophageal squamous cell carcinoma (ESCC). A prognostic signature could be reliable in stratifying ESCC patients according to the risk score, which may help manage systematic treatments. In this study, a systematic and reliable immune signature was developed to estimate the prognostic stratification in ESCC. METHODS: Ribonucleic acid (RNA) expression data of 79 ESCC samples from the Cancer Genome Atlas (TCGA) database and 269 normal esophageal mucosal samples from the Genotype-Tissue Expression (GTEx) project database were downloaded from the University of California, Santa Cruz (UCSC) website to form a TCGA-GTEx dataset. First, we screened differentially expressed genes (DEGs) and then filtered IRGs based on the Immunology Database and Analysis Portal (ImmPort) database to obtain immune-related DEGs (IRDEGs). Next, a novel prognostic signature based on IRDEGs was developed using multivariable Cox analysis. Immune infiltration status was evaluated via single-sample gene set enrichment analysis (ssGSEA). ESCC tissues were grouped into three clusters in terms of immune infiltration (Immunity-L, Immunity-M, and Immunity-H) by applying an unsupervised hierarchical clustering algorithm. Finally, the samples were divided into high- and low-risk groups using the median of the risk score scores for GSEA pathway enrichment analysis in the three clusters. RESULTS: The prognostic signature based on IRDEGs (FCER1G, ISG20, and EGFR) performed moderately in prognostic predictions, with a concordance index (C-index) value of 0.73 [95% (confidence interval) CI: 0.63–0.84, P=2.02E-05] and an area under the curve (AUC) value of 0.817. The xenobiotic metabolism pathway was significantly enriched and up-regulated both in the high-risk group of the immunity-M and immunity-H clusters. CONCLUSIONS: The novel immune-related prognostic signature we constructed has a good prognostic, predictive ability and can be used as an independent prognostic indicator. Our study provides clinicians with a quantitative tool to predict the probability of individual survival time and helps clinicians select targets for immunotherapies and individualized treatment strategies for ESCC patients. AME Publishing Company 2021-05 /pmc/articles/PMC8798451/ /pubmed/35116551 http://dx.doi.org/10.21037/tcr-20-2665 Text en 2021 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
spellingShingle Original Article
Xu, Tao
Dai, Tianyang
Zeng, Peiyuan
Guo, Yunfen
He, Kaiming
A novel immune-related gene signature predicts survival in esophageal squamous cell carcinoma
title A novel immune-related gene signature predicts survival in esophageal squamous cell carcinoma
title_full A novel immune-related gene signature predicts survival in esophageal squamous cell carcinoma
title_fullStr A novel immune-related gene signature predicts survival in esophageal squamous cell carcinoma
title_full_unstemmed A novel immune-related gene signature predicts survival in esophageal squamous cell carcinoma
title_short A novel immune-related gene signature predicts survival in esophageal squamous cell carcinoma
title_sort novel immune-related gene signature predicts survival in esophageal squamous cell carcinoma
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798451/
https://www.ncbi.nlm.nih.gov/pubmed/35116551
http://dx.doi.org/10.21037/tcr-20-2665
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