Transcriptomic network analysis and functional evidence identify a candidate EMT hub signature associated with nasopharyngeal carcinoma progression
摘要
Nasopharyngeal carcinoma (NPC) is a clinically aggressive malignancy in which epithelial–mesenchymal transition (EMT) plays a central role in invasion, metastasis, and therapeutic resistance. However, the coordinated transcriptional organization, regulatory mechanisms, and functional relevance of EMT-associated genes in NPC remain insufficiently defined. This study aimed to identify EMT-related hub genes in NPC and integrate multiomics and functional evidence to elucidate their biological and clinical significance. Weighted gene coexpression network analysis was performed on the GSE12452 dataset to identify EMT-associated modules and hub genes. Multiomics validation, including transcriptomic, protein level, methylation, mutation, CNV, survival, and drug response profiling, was conducted using GSCA, HPA, OncoDB, cBioPortal, and GDC databases. miRNA regulators were predicted using TargetScan and validated by dual-luciferase assays. Functional significance was assessed through RT-qPCR, Western blotting, apoptosis, viability, colony formation, and wound healing assays following treatment of NPC cells with afatinib or SB431542. WGCNA identified four EMT hub genes, VIM, SNAI1, ZEB1, and FN1, which were consistently overexpressed in NPC. These genes were hypomethylated, exhibited CNV alterations, and were associated with poor survival and broad drug resistance profiles. Predicted miRNA interactions were experimentally validated. Pharmacologic inhibition of EMT-associated signaling significantly reduced hub gene expression and suppressed malignant phenotypes across multiple NPC cell lines. This integrative analysis identifies VIM, SNAI1, ZEB1, and FN1 as a candidate EMT-associated hub signature linked with NPC progression, prognosis, and drug response patterns. Pharmacological inhibition of EMT-associated signaling reduced hub gene expression and suppressed malignant cellular phenotypes, suggesting that this EMT hub network may have potential value as a prognostic biomarker panel and as a putative therapeutic vulnerability requiring further validation.