Affiliation:
1. Shaanxi Provincial People’s hospital
2. Xi’an Jiaotong University
3. Chinese PLA General Hospital
Abstract
Abstract
Background
Ephrin-A4 (EFNA4) is present in numerous tissues and is connected to the growth and development of multiple types of cancer. The differences in EFNA4 expression in various types of cancer and its impact on glioblastoma and low-grade glioma (GBMLGG) are not well understood. This research seeks to determine the prognostic value of EFNA4 in predicting the outcomes of GBMLGG and to examine the role of EFNA4 in tumorigenesis in GBMLGG.
Methods
The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were used to examine the differential expression and genetic alterations of EFNA4, and their relationship with patient survival in 33 cancer types. Multiple algorithms were used to examine the correlation between EFNA4 expression and the infiltration of cancer-associated fibroblasts, the immune infiltration landscape, expression of immunomodulatory genes, tumor mutational burden (TMB), and the microsatellite instability (MSI) score of GBMLGG. Univariate and multivariate Cox regression models and a nomogram were developed to forecast the outcomes of patients with GBMLGG. We also established protein-protein interaction networks, identified related functional signaling pathways, and conducted drug sensitivity analyses to examine the role of EFNA4 in the progression of GBMLGG.
Results
In most types of cancer, there was an increase in EFNA4 mRNA expression, which was found to be associated with prognosis. The expression of EFNA4 had a positive correlation with cancer-associated fibroblast infiltration levels in various cancer types, and the levels of EFNA4 expression were markedly elevated in tumor tissues in comparison to normal tissues in GBMLGG. Overexpression of EFNA4 was significantly correlated with tumor progression, a poor prognosis, and high immune scores in GBMLGG. The nomogram and EFNA4 expression status demonstrated their ability to accurately predict the outcomes of patients with GBMLGG. Moreover, it was discovered that the expression of EFNA4 had a considerable correlation with the expression of immunomodulatory genes and biological processes such as immune cell infiltration, the tyrosine kinase signaling pathway, neurotransmitter transmission between synapses, and epithelial-mesenchymal transition in GBMLGG.
Conclusions
The findings of this research indicate that EFNA4 has great potential as both a prognostic biomarker and a target for the therapy for GBMLGG.
Publisher
Research Square Platform LLC