IDENTIFICATION OF KEY HUB GENES AND PROGNOSTIC BIOMARKERS IN HEAD AND NECK CANCER THROUGH INTEGRATED TRANSCRIPTOMIC AND NETWORK ANALYSIS

Abstract

Head and neck cancer (HNC) is a heterogeneous malignancy with limited reliable prognostic biomarkers. This study aimed to identify molecular signatures associated with HNC progression using integrative transcriptomic and network analyses. In this study, a total of 896 differentially expressed genes (DEGs) were identified, including 412 up-regulated and 484 down-regulated genes. Up-regulated DEGs were enriched in extracellular matrix (ECM) organization, immune and inflammatory responses, and oncogenic signaling pathways, whereas down-regulated genes were associated with epithelial differentiation and metabolic processes. Protein-protein interaction (PPI) network analysis identified key clusters and 46 hub genes. Among these, a combined four-gene signature (MMP1, SPP1, SERPINE1, and SERPINH1) was consistently up-regulated and centrally connected within the network. Validation confirmed that the combined four-gene signature was significantly overexpressed in HNC and associated with poor overall survival. These findings suggest that coordinated ECM remodeling and tumor microenvironment regulation drive HNC progression. The identified signature represents a potential diagnostic and prognostic biomarker with relevance for clinical application.

Keywords: Transcriptomic Analysis, Head and Neck Cancer, Prognostic Biomarkers, Gene Signature, Network Analysis