Development of an Immunogenomic Landscape-Based Prognostic Index of Head and Neck Squamous Cell Carcinoma

Abstract

Head and neck squamous cell carcinoma (HNSCC) is the eighth leading cancer by incidence worldwide, with approximately 700,000 new cases in 2018 (accounting for 11% of all cancers). The occurrence and development of tumors are closely related to the immunological function of the body and sensitivity to treatment schemes as well as prognosis. It is urgent for clinicians to systematically study patients’ immune gene maps to help select a treatment plan and analyze the potential to cure HNSCC. Here, the transcriptomic data of HNSCC samples were downloaded from The Cancer Genome Atlas (TCGA), and 4,793 genes differentially expressed in normal and cancer tissues of HNSCC were identified, including 1,182 downregulated and 3,611 upregulated genes. From these genes, 400 differentially expressed immune-related genes (IRGs) were extracted, including 95 downregulated genes and 305 upregulated genes. The prognostic values of IRGs were evaluated by univariate Cox analysis, and 236 genes that were significantly related to the overall survival (OS) of patients were identified. The signaling pathways that play roles in the prognosis of IRGs were investigated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and the expression profiles of IRGs and OS in 499 HNSCC patients based on TCGA dataset were integrated. Potential molecular mechanisms and characteristics of these HNSCC-specific IRGs were further explored with the help of a new prognostic index based on IRGs developed by least absolute shrinkage and selection operator (LASSO) Cox analysis. A total of 64 hub genes (IRGs associated with prognosis) were markedly associated with the clinical outcome of HNSCC patients. KEGG functional enrichment analysis revealed that these genes were actively involved in several pathways, e.g., cytokine–cytokine receptor interaction, T-cell receptor signaling, and natural killer cell-mediated cytotoxicity. IRG-based prognostic signatures performed moderately in prognostic predictions. Interestingly, the prognostic index based on IRGs reflected infiltration by several types of immune cells. These data screened several IRGs of clinical significance and revealed drivers of the immune repertoire, demonstrating the importance of a personalized IRG-based immune signature in the recognition, surveillance, and prognosis of HNSCC.