An Inflammation-Immunity Classifier of 11 Chemokines for Prediction of Overall Survival in Head and Neck Squamous Cell Carcinoma.

BACKGROUND Chemokines are important in inflammation, immunity, tumor progression, and metastasis. The purpose of this research was to find an integrated-RNA signature of chemokine family genes to predict the survival prognosis in head and neck squamous carcinoma (HNSC) patients. MATERIAL AND METHODS Relevant data of 504 HNSC patients were extracted from The Cancer Genome Atlas (TCGA) database. Through analyzing RNA sequencing data, the univariate Cox model was used to identify chemokine family genes associated with survival and then to develop a multiple-RNA signature in the training set. The prediction value of this multiple-RNA signature was further verified in the validation and entire sets. The receiver operating characteristic curves were used to assess the predictive value of this multiple-RNA signature. RESULTS Eleven chemokines were included in this prognostic signature. Based on this 11-chemokine signature, we further categorized patients as high or low risk. Compared with low-risk patients, high-risk patients had shorter overall survival (OS) time in the training set [hazard ratio (HR)=3.497, 95% confidence interval (CI)=2.142-5.711, p<0.001], validation set (HR=3.575, 95% CI=1.988-6.390, p<0.001), and entire set (HR=3.416, 95% CI=2.363-4.939, p<0.001). This 11-chemokine signature was an independent prognostic factor for OS in these datasets (p<0.05). The AUC values for predicting overall survival within 48 months in the training, validation, and entire sets were 0.71, 0.69, and 0.69, respectively. CONCLUSIONS This 11-chemokine signature could serve as a reliable prognostic tool for HNSC patients and might be useful to guide individualized treatment or even gene target therapy for high-risk patients.