Integrative bioinformatics analysis of high-throughput sequencing and in vitro functional analysis leads to uncovering key hub genes in esophageal squamous cell carcinoma

作者：Feng Shen, Xing Liu, Fengjiao Ding, Ziquan Yu, Xinyi Shi, Lushan Cheng, Xuewei Zhang, Chengbao Jing, Zilong Zhao, Hongyou Cao, Bing Zhao, Jing Liu · 发表于：Hereditas · 年份：2025 · DOI：10.1186/s41065-025-00398-4 · 被引用次数：2 · 研究领域：Esophageal Cancer Research and Treatment、Ferroptosis and cancer prognosis、Cancer Immunotherapy and Biomarkers

BACKGROUND: Esophageal squamous cell carcinoma (ESCA) is a type of cancer that starts in the cells lining the esophagus, the tube connecting the throat to the stomach. It is known for its aggressive nature and poor prognosis. Understanding the key factors that drive this cancer is crucial for developing better diagnostic tools and treatments. METHODS: Gene expression profiles of ESCA were analyzed using Gene Expression Omnibus (GEO) datasets (GSE23400, GSE29001, GSE92396, and GSE1420) from the GEO database. Differentially expressed genes (DEGs) were identified using the limma package, and a protein-protein interaction (PPI) network was constructed using the STRING database. Hub genes were identified based on the degree method. Further validation was performed through reverse transcription quantitative PCR (RT-qPCR), mutational and copy number variation (CNV) analysis via the cBioPortal database, promoter methylation analysis using the OncoDB and GSCA databases, survival analysis, immune infiltration analysis through the GSCA database, and functional assays, including knockdown of key genes. RESULTS: We identified four key hub genes, COL3A1, COL4A1, COL5A2, and CXCL8 that play significant roles in ESCA. These genes were highly expressed in ESCA tissues and cell lines, with expression levels significantly (p-value < 0.001) elevated compared to normal controls. Receiver operating characteristic (ROC) curve analysis revealed exceptional diagnostic performance for all four genes, ...