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Background <p>Gastroesophageal junction adenocarcinoma (GEJAC) is a highly lethal malignancy, and its molecular mechanisms are still not well understood. Reliable biomarkers for early diagnosis and immunotherapy are urgently needed. This study sought to identify hub genes linked to GEJAC by analyzing datasets from the Gene Expression Omnibus (GEO) and examining their correlation with immune cell infiltration.</p> Methods <p>Transcriptome data of GEJAC samples and matched normal controls were obtained from GEO. Differentially expressed genes were identified, followed by WGCNA to determine hub genes. Functional annotation was carried out through GO, KEGG, and PPI network analysis to elucidate their biological significance. A diagnostic prediction model was established using logistic regression, and its accuracy was validated through ROC curve analysis. Immune cell composition was assessed with the CIBERSORT algorithm, and the associations between hub genes and immune cell subsets were further investigated.</p> Results <p>A total of 392 genes with differential expression were identified, among which 47 overlapping candidates were screened by intersecting WGCNA modules with DEGs. Functional enrichment analysis revealed that these genes were involved in meiotic nuclear division, mitotic cell cycle checkpoint, and the p53 signaling pathway. Five hub genes (TPX2, CCNB2, BUB1, TOP2A, ASPM) were selected for the construction of a diagnostic model, which achieved strong predictive performance (AUC = 0.9). Immune infiltration analysis revealed an inverse relationship between all five hub genes and resting memory CD4 + T cells, as well as a positive relationship with activated memory CD4 + T cells.</p> Conclusion <p>This study identified TPX2, CCNB2, BUB1, TOP2A, and ASPM as potential candidate diagnostic biomarkers for GEJAC at the transcriptomic level. These genes are closely associated with immune cell infiltration, providing new insights into GEJAC pathogenesis and potential targets for immunotherapy.</p>

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Identification of biomarkers associated with diagnosis of gastroesophageal junction adenocarcinoma and their correlation with immune infiltration

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月9日

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  • Jianfu Zhu,
  • Aimin He,
  • Yujing Zhang,
  • Bing Huang,
  • Junli Zhang,
  • Ying Wang,
  • Jingxiao Qin,
  • Zhaohui Zhang

摘要

Background

Gastroesophageal junction adenocarcinoma (GEJAC) is a highly lethal malignancy, and its molecular mechanisms are still not well understood. Reliable biomarkers for early diagnosis and immunotherapy are urgently needed. This study sought to identify hub genes linked to GEJAC by analyzing datasets from the Gene Expression Omnibus (GEO) and examining their correlation with immune cell infiltration.

Methods

Transcriptome data of GEJAC samples and matched normal controls were obtained from GEO. Differentially expressed genes were identified, followed by WGCNA to determine hub genes. Functional annotation was carried out through GO, KEGG, and PPI network analysis to elucidate their biological significance. A diagnostic prediction model was established using logistic regression, and its accuracy was validated through ROC curve analysis. Immune cell composition was assessed with the CIBERSORT algorithm, and the associations between hub genes and immune cell subsets were further investigated.

Results

A total of 392 genes with differential expression were identified, among which 47 overlapping candidates were screened by intersecting WGCNA modules with DEGs. Functional enrichment analysis revealed that these genes were involved in meiotic nuclear division, mitotic cell cycle checkpoint, and the p53 signaling pathway. Five hub genes (TPX2, CCNB2, BUB1, TOP2A, ASPM) were selected for the construction of a diagnostic model, which achieved strong predictive performance (AUC = 0.9). Immune infiltration analysis revealed an inverse relationship between all five hub genes and resting memory CD4 + T cells, as well as a positive relationship with activated memory CD4 + T cells.

Conclusion

This study identified TPX2, CCNB2, BUB1, TOP2A, and ASPM as potential candidate diagnostic biomarkers for GEJAC at the transcriptomic level. These genes are closely associated with immune cell infiltration, providing new insights into GEJAC pathogenesis and potential targets for immunotherapy.