A prognostic risk prediction model for gastric cancer based on the EFNA4 and ETS1 regulatory axis in tumor cells

Gastric cancer (GC) is a major cause of cancer-related deaths worldwide, and is characterised by intricate molecular mechanisms. However, analysis of its molecular and clinical characteristics is complicated by its histological and etiological heterogeneity. Dysregulation of the PI3K-Akt signalling pathway is common in GC. In this study, we have identified the hub gene Ephrin A4 (EFNA4) in the PI3K-Akt pathway based on transcriptome data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and ETS Proto-Oncogene 1 (ETS1) was a gene related to EFNA4. Using publicly accessible datasets, we conducted bioinformatics analyses to evaluate the expression profiles, functional roles, and prognostic significance of EFNA4 and ETS1 and further explored their relationship in GC. Subsequently, consensus clustering was performed on 373 TCGA-STAD datasets based on the expression matrices of EFNA4 and ETS1 to assess their interconnections with relevant signalling cascades and immune system components. To address the challenges posed by tumour heterogeneity and reveal the expression patterns of EFNA4 and ETS1 in GC tissues, we performed reanalysis of single-cell RNA sequencing (scRNA-seq) data of GC samples. We constructed a tumour-based risk signature for GC based on EFNA4, ETS1, and marker genes of the tumour cell cluster. The prognostic value of the prognosis prediction model was verified using TCGA database to facilitate the clinical application of tumour cell features in GC prognosis. Our study reveals EFNA4 and ETS1 expression patterns in GC, implicating their roles in pathogenesis. An integrated EFNA4-ETS1 prognostic model improves GC risk stratification. Although EFNA4 has been shown to promote metastasis in liver cancer, the contradictory mechanism of its high expression and good prognosis in GC remains to be elucidated, which may involve its antagonistic effects with ETS1, and requires further exploration.

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Journal
Scientific Reports
Published
2025-10-29
DOI
https://doi.org/10.1038/s41598-025-21728-6
Primary Topic
Axon Guidance and Neuronal Signaling
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article
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0.00

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article

A prognostic risk prediction model for gastric cancer based on the EFNA4 and ETS1 regulatory axis in tumor cells

Wenchen Zhang, Jingjing Ye, Yixuan Chen, Wenjiang Deng et al.
Scientific Reports
Axon Guidance and Neuronal Signaling
article

A prognostic risk prediction model for gastric cancer based on the EFNA4 and ETS1 regulatory axis in tumor cells

Wenchen Zhang, Jingjing Ye, Yixuan Chen, Wenjiang Deng, Shupei Li, Junkun Wang, Hui Zhang, Wenbin Wang, Ning Wang, Fengsong Wang, Zhoujuan Yao
article en

Abstract

Gastric cancer (GC) is a major cause of cancer-related deaths worldwide, and is characterised by intricate molecular mechanisms. However, analysis of its molecular and clinical characteristics is complicated by its histological and etiological heterogeneity. Dysregulation of the PI3K-Akt signalling pathway is common in GC. In this study, we have identified the hub gene Ephrin A4 (EFNA4) in the PI3K-Akt pathway based on transcriptome data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and ETS Proto-Oncogene 1 (ETS1) was a gene related to EFNA4. Using publicly accessible datasets, we conducted bioinformatics analyses to evaluate the expression profiles, functional roles, and prognostic significance of EFNA4 and ETS1 and further explored their relationship in GC. Subsequently, consensus clustering was performed on 373 TCGA-STAD datasets based on the expression matrices of EFNA4 and ETS1 to assess their interconnections with relevant signalling cascades and immune system components. To address the challenges posed by tumour heterogeneity and reveal the expression patterns of EFNA4 and ETS1 in GC tissues, we performed reanalysis of single-cell RNA sequencing (scRNA-seq) data of GC samples. We constructed a tumour-based risk signature for GC based on EFNA4, ETS1, and marker genes of the tumour cell cluster. The prognostic value of the prognosis prediction model was verified using TCGA database to facilitate the clinical application of tumour cell features in GC prognosis. Our study reveals EFNA4 and ETS1 expression patterns in GC, implicating their roles in pathogenesis. An integrated EFNA4-ETS1 prognostic model improves GC risk stratification. Although EFNA4 has been shown to promote metastasis in liver cancer, the contradictory mechanism of its high expression and good prognosis in GC remains to be elucidated, which may involve its antagonistic effects with ETS1, and requires further exploration.

Scientific ReportsVol. 15(1)
Harvard University (US), Anhui Medical University (CN), First Affiliated Hospital of Anhui Medical University (CN), Second Affiliated Hospital of Anhui Medical University (CN), Anhui Mental Health Center (CN)
National Natural Science Foundation of China, Anhui Medical University
Openalex Percentile: Top 66%
Axon Guidance and Neuronal Signaling
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