Abstract
Objective: Lymphovascular invasion (LOI), a key pathological feature of head and neck squamous cell carcinoma (HNSCC), predicts poor survival. However, the associated clinical characteristics remain uncertain, and the molecular mechanisms are largely unknown. Methods: Weighted gene co-expression network analysis was performed to construct gene co-expression networks and investigate the relationship between modules and LOI clinical trait. Functional enrichment and KEGG pathway enrichment analysis were performed for differentially expressed genesusing DAVID database. The protein-protein interaction network was constructed using Cytoscape software, and module analysis was performed using MCODE. Survival analysis and unsupervised hierarchical clustering were used to evaluate the relationships among LOI-associated genomic subtype, clinicopathological features and patient outcomes. And the potential targeted LOI molecular agents were identified with DrugBank. Results: 10 co-expression modules in two key modules (turquoise and pink) associated with tumor LOI were identified. Functional enrichment and KEGG analysis identified turquoise and pink modules played significant roles in the progression of HNSCC. The 24 genes in two modules were identified as hub genes. Clustering analysis with seven hub genes set further divided cases into subtypes 1 and 2, which were significantly associated with pathology-determined LOI status in both cohorts. The 10-year overall survival of subtype 2 was significantly worse than that of subtype 1. Conclusions: Our research revealed the key co-expression modules and identified seven prognostic biomarkers, including CCNA2, CNFN, DEPDC1, KIF18, KIF23, PRC1, TTK, which provide some new insights into LOI of HNSCC. Additionally, the small molecular agents may be a candidate drug for treating LOI.
Weighted gene co-expression network analysis and prognostic analysis identifies hub genes and the molecular mechanism related to head and neck squamous cell carcinoma
