Abstract
Squamous cell carcinoma of the head and neck (SCCHN) is a commonly detected cancer worldwide. Human papillomavirus (HPV) is emerging as an important risk factor affecting SCCHN prognosis. Therefore, identification of HPV status is essential for effective therapies in SCCHN. The aim of this study was to investigate the prognostic value of HPV-associated RNA biomarkers for SCCHN. The clinical data, survival data, and RNA-seq data of SCCHN were downloaded from The Cancer Genome Atlas database. Before the differential expression analysis, the heterogeneity between the 2 groups (HPV+ vs HPV-) of samples was analyzed using principal component analysis. The differentially expressed genes (DEGs) between HPV+ and HPV- SCCHN samples were analyzed using the R edgeR package. The Gene Ontology functional annotations, including biological process, molecular function and cellular component (CC), and Kyoto Encyclopedia of Genes And Genomes pathways enriched by the DEGs were analyzed using DAVID. The obtained matrix was analyzed by weighed gene coexpression network analysis. A total of 350 significant DEGs were identified through differential analysis, and these DEGs were significantly enriched in functions associated with keratinization, and the pathway of neuroactive ligand-receptor interaction. Moreover, 72 hub genes were identified through weighed gene coexpression network analysis. After the hub genes and DEGs were combined, we obtained 422 union genes, including 65 survival-associated genes. After regression analysis, a HPV-related prognostic model was established, which consisted of 8 genes, including Clorf105, CGA, CHRNA2, CRIP3, CTAG2, ENPP6, NEFH, and RNF212. The obtained regression model could be expressed by an equation as follows: risk score = 0.065 × Clorf105 + 0.012 × CGA + 0.01 × CHRNA2 + 0.047 × CRIP3 + 0.043 × CTAG2-0.034 × ENPP6 - 0.003 × NEFH - 0.068 × RNF212. CGA interacted with 3 drugs, and CHRNA2 interacted with 11 drugs. We have identified an 8 HPV-RNA signature associated with the prognosis of SCCHN patients. Such prognostic model might serve as possible candidate biomarker and therapeutic target for SCCHN.