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EFNA1 is a potential key gene that correlates with immune infiltration in low-grade glioma

EFNA1 is a key gene that is associated with the pathogenesis of several human cancers. However, the prognostic role of EFNA1 in many cancers and the relationship between EFNA1 and tumor-infiltrating lymphocytes in different cancers remain unclear. The expression levels of EFNA1 in 33 types of cancer...

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Autores principales: Hao, Yong-Ping, Wang, Wen-Yi, Qiao, Qiao, Li, Guang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8183727/
https://www.ncbi.nlm.nih.gov/pubmed/34087884
http://dx.doi.org/10.1097/MD.0000000000026188
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author Hao, Yong-Ping
Wang, Wen-Yi
Qiao, Qiao
Li, Guang
author_facet Hao, Yong-Ping
Wang, Wen-Yi
Qiao, Qiao
Li, Guang
author_sort Hao, Yong-Ping
collection PubMed
description EFNA1 is a key gene that is associated with the pathogenesis of several human cancers. However, the prognostic role of EFNA1 in many cancers and the relationship between EFNA1 and tumor-infiltrating lymphocytes in different cancers remain unclear. The expression levels of EFNA1 in 33 types of cancer in the TCGA (The Cancer Genome Atlas) database were collected via the UCSC Xena browser. The clinical data of LGG (low grade glioma) patients were downloaded from the TCGA database. The glioma data from the CGGA (Chinese Glioma Genome Atlas) database were also downloaded to verify the results. Kaplan–Meier and Cox regression analyses were used to investigate the prognostic value of EFNA1 in different cancers using R software. We verified the differential expression of EFNA1 in glioma and normal brain tissue via gene expression profiling interactive analysis. We evaluated the relationship between the expression level of EFNA1 and the clinicopathological features of LGG patients via the Wilcoxon signed-rank test. The immune infiltration levels were evaluated via tumor immune estimation resource (TIMER) and CIBERSORT, and the correlations between EFNA1 and immune cell levels were investigated via TIMER. Finally, we conducted gene set enrichment analysis (GSEA) to explore the potential mechanisms. Data from the TCGA database showed that EFNA1 was differentially expressed in many kinds of cancers when compared with normal tissues. Upregulated EFNA1 expression in esophageal carcinoma (ESCA), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), and LGG correlated with shorter patient overall survival (OS) times. The Cox regression analysis revealed that the expression of EFNA1 was also a risk factor for the disease-specific survival (DSS) and progression-free interval (PFI) of LGG patients. The multiple Cox regression analysis revealed that EFNA1 was an independent prognostic factor for LGG patients. In addition, EFNA1 expression was increased in the WHO grade III group and the 1p19q non-codeletion group. Moreover, EFNA1 expression was positively correlated with the levels of infiltrating CD4+ T cells, myeloid dendritic cells and neutrophils in LGG. GSEA suggested that several GO and kyoto encyclopedia of genes and genomes (KEGG) items associated with nervous system function and apoptotic pathway were significantly enriched in the EFNA1-low and EFNA1-high expression phenotypes. EFNA1 may play a pivotal role in the development of LGG and may serve as a potential marker for LGG prognosis and therapy.
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spelling pubmed-81837272021-06-07 EFNA1 is a potential key gene that correlates with immune infiltration in low-grade glioma Hao, Yong-Ping Wang, Wen-Yi Qiao, Qiao Li, Guang Medicine (Baltimore) 3500 EFNA1 is a key gene that is associated with the pathogenesis of several human cancers. However, the prognostic role of EFNA1 in many cancers and the relationship between EFNA1 and tumor-infiltrating lymphocytes in different cancers remain unclear. The expression levels of EFNA1 in 33 types of cancer in the TCGA (The Cancer Genome Atlas) database were collected via the UCSC Xena browser. The clinical data of LGG (low grade glioma) patients were downloaded from the TCGA database. The glioma data from the CGGA (Chinese Glioma Genome Atlas) database were also downloaded to verify the results. Kaplan–Meier and Cox regression analyses were used to investigate the prognostic value of EFNA1 in different cancers using R software. We verified the differential expression of EFNA1 in glioma and normal brain tissue via gene expression profiling interactive analysis. We evaluated the relationship between the expression level of EFNA1 and the clinicopathological features of LGG patients via the Wilcoxon signed-rank test. The immune infiltration levels were evaluated via tumor immune estimation resource (TIMER) and CIBERSORT, and the correlations between EFNA1 and immune cell levels were investigated via TIMER. Finally, we conducted gene set enrichment analysis (GSEA) to explore the potential mechanisms. Data from the TCGA database showed that EFNA1 was differentially expressed in many kinds of cancers when compared with normal tissues. Upregulated EFNA1 expression in esophageal carcinoma (ESCA), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), and LGG correlated with shorter patient overall survival (OS) times. The Cox regression analysis revealed that the expression of EFNA1 was also a risk factor for the disease-specific survival (DSS) and progression-free interval (PFI) of LGG patients. The multiple Cox regression analysis revealed that EFNA1 was an independent prognostic factor for LGG patients. In addition, EFNA1 expression was increased in the WHO grade III group and the 1p19q non-codeletion group. Moreover, EFNA1 expression was positively correlated with the levels of infiltrating CD4+ T cells, myeloid dendritic cells and neutrophils in LGG. GSEA suggested that several GO and kyoto encyclopedia of genes and genomes (KEGG) items associated with nervous system function and apoptotic pathway were significantly enriched in the EFNA1-low and EFNA1-high expression phenotypes. EFNA1 may play a pivotal role in the development of LGG and may serve as a potential marker for LGG prognosis and therapy. Lippincott Williams & Wilkins 2021-06-04 /pmc/articles/PMC8183727/ /pubmed/34087884 http://dx.doi.org/10.1097/MD.0000000000026188 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
spellingShingle 3500
Hao, Yong-Ping
Wang, Wen-Yi
Qiao, Qiao
Li, Guang
EFNA1 is a potential key gene that correlates with immune infiltration in low-grade glioma
title EFNA1 is a potential key gene that correlates with immune infiltration in low-grade glioma
title_full EFNA1 is a potential key gene that correlates with immune infiltration in low-grade glioma
title_fullStr EFNA1 is a potential key gene that correlates with immune infiltration in low-grade glioma
title_full_unstemmed EFNA1 is a potential key gene that correlates with immune infiltration in low-grade glioma
title_short EFNA1 is a potential key gene that correlates with immune infiltration in low-grade glioma
title_sort efna1 is a potential key gene that correlates with immune infiltration in low-grade glioma
topic 3500
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8183727/
https://www.ncbi.nlm.nih.gov/pubmed/34087884
http://dx.doi.org/10.1097/MD.0000000000026188
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