EFNA1 is a potential key gene that correlates with immune infiltration in low-grade glioma. Issue 22 (4th June 2021) - Hao, Yong-Ping; Wang, Wen-Yi; Qiao, Qiao; Li, Guang
Abstract : Abstract: 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.