Integrated Bioinformatics and Experimental Validation Identifies Prognostic Hub Genes in Esophageal Squamous Cell Carcinoma (ESCC)

Background: Esophageal squamous cell carcinoma (ESCC) is a highly aggressive malignancy with a poor prognosis and a 5-year survival rate below 20%. Late diagnosis, frequent recurrence, and therapeutic resistance are major clinical challenges. Thus, there is an urgent need to identify novel biomarkers and therapeutic targets to improve patient outcomes. Methods Genes with differentially expressed genes (DEGs) in ESCC tissue against normal tissue, as well as were identified through an integrative analysis of microarray data retrieved from the Gene Expression Omnibus (GEO) database (GSE23400 and GSE157804). The STRING database was employed to construct protein–protein interaction (PPI) networks, and Kaplan–Meier plotter was utilized to identify the hub genes that were significance in prognostic. The relative expression levels of hub genes by real-time method were assessed in ESCC tissue compared to normal tissue. Results Signal transducer and activator of transcription 1 (STAT1) and lysyl oxidase (LOX), were shared across microarray datasets and were associated with poor prognosis in ESCC. In concordance with Boxplot analyses, real-time PCR results revealed a significant upregulate STAT1 and LOX expression in ESCC tissue sample (p = 0.0002 and p = 0.0045, respectively) compare to non-cancerous tissue. Conclusions Finally, two hub genes, STAT1 and LOX, are suitable candidates for advancing targeted therapeutic approaches for ESCC in the future. STAT1 and LOX emerge as key prognostic hub genes in ESCC, linking transcriptional regulation and ECM remodeling to tumor progression. These findings provide a foundation for further mechanistic studies and potential development of targeted therapies in ESCC.