Identification of An Immune-related Signature in Predicting Prognosis of Oral Squamous Cell Carcinoma Patients

Abstract

Background: Immunotherapy is one of the most promising treatment strategies in cancer, including oral squamous cell carcinoma (OSCC). This study aims to identify an immune-related signature to predict clinical outcomes of OSCC patients. Methods: Gene transcriptome data of OSCC tumour and normal tissues and corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA). Tumor Immune Estimation Resource algorithm (ESTIMATE) was used to calculate the immune/stromal-related scores. The immune/stromal scores and associated clinical characteristics of OSCC patients were evaluated. Univariate Cox proportional hazards regression analyses, least absolute shrinkage, and selection operator (LASSO) and receiver operating characteristic (ROC) curve analyses were performed to assess the prognostic prediction capacity. Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO) function annotation were used to analysis the functions of TME related genes.Results: 11 predictor genes were identified in the immune-related signature and overall survival (OS) in the high-risk group significantly shorter than the low-risk group. ROC analysis showed the TME related signature has well ability of predicting the total OS of OSCC patients. What’s more, GSEA and GO function annotation proved that immunity and immune-related pathways are mainly enriched in the high-risk group.Conclusions: We identified an immune-related signature that was closely correlated with the prognosis and immune response to OSCC patients. This signature may have important implications for improving the clinical survival rate of OSCC patients and provide a potential strategy for cancer immunotherapy.