Inflammatory response-related genes predict prognosis in patients with HNSCC

Background: Head and neck squamous cell carcinoma (HNSCC) is the most common malignancy of the head and neck, and the inflammatory microenvironment can impact the prognosis of HNSCC. However, the contribution of inflammation to tumour progression has not been fully elucidated. Methods: The mRNA expression profiles and corresponding clinical data of HNSCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) Cox analysis model was used to identify prognostic genes. The overall survival (OS) between high- and low-risk patients was compared by Kaplan-Meier analysis. The independent predictors of OS were determined by univariate and multivariate Cox analyses. Single-sample gene set enrichment analysis (ssGSEA) was used to assess immune cell infiltration and immune-related pathway activity. GSEA was used to analyse Gene Ontology (GO) terms and Kyoto encyclopaedia of Genes and Genomes (KEGG) pathways. The Gene Expression Profiling Interactive Analysis (GEPIA) database was used to examine prognostic genes in HNSCC patients. Immunohistochemistry was used to verify the protein expression of prognostic genes in HNSCC samples. Results: An inflammatory response-related gene signature was constructed by LASSO Cox regression analysis. HNSCC patients in the high-risk group showed significantly reduced OS compared with those in the low-risk group. The predictive capacity of the prognostic gene signature was confirmed by ROC curve analysis. Multivariate Cox analysis revealed that the risk score was an independent predictor for OS. Functional analysis indicated that the immune status was markedly different between the two risk groups. The risk score was significantly related to tumour stage and immune subtype. The expression levels of the prognostic genes were significantly related to the sensitivity of cancer cells to antitumour drugs. Furthermore, high expression of the prognostic genes significantly predicted poor prognosis of HNSCC patients. Conclusions: The novel signature containing 9 inflammatory response-related genes reflects the immune status of HNSCC and can be used for prognosis prediction. Furthermore, the genes may be potential targets for HNSCC treatment.