Construction of a new predictive model in head and neck squamous cell carcinoma based on the investigation of extracellular matrix‑associated genes

A key aspect influencing immune cell infiltration is the composition of the extracellular matrix (ECM). Therefore, investigating the association between ECM‑associated proteins and immune cell infiltration is key for the identification of new biomarkers to distinguish ‘immune‑hot’ solid tumors and predict patient prognosis. A total of 513 head and neck squamous cell carcinoma (HNSCC) cases as training samples from The Cancer Genome Atlas and an additional 270 as testing samples from the Gene Expression Omnibus were obtained for use in the present study. Using a single‑sample Gene Set Enrichment Analysis method, the 513 training samples were divided into Cluster 1 and Cluster 2. Subsequently, the present analysis uncovered 1,573 differentially expressed genes distinguishing the two clusters. After performing an intersection analysis with 751 ECM‑associated genes, 103 differentially expressed ECM‑associated genes were identified. Least absolute shrinkage and selection operator‑Cox and multivariate Cox regression analyses were employed to identify candidate ECM risk genes (P<0.05) and to construct a predictive model. Finally, a nomogram and a three gene (cerebellin 2, galectin‑10 and cathepsin G) predictive model were developed. Therefore, the present prognostic risk score model can evaluate the immune infiltration, predict the prognosis of HNSCC, and potentially guide more personalized immunotherapy interventions‌.