Novel Therapies for Tongue Squamous Cell Carcinoma Patients with High-Grade Tumors

Background: Tongue squamous cell carcinoma (TSCC) patients with high-grade tumors usually suffer from high occurrence and poor prognosis. The current study aimed at finding the biomarkers related to tumor grades and proposing potential therapies by these biomarkers. Methods: The mRNA expression matrix of TSCC samples from The Cancer Genome Atlas (TCGA) database was analyzed to identify hub proteins related to tumor grades. The mRNA expression patterns of these hub proteins between TSCC and adjacent control samples were validated in three independent TSCC data sets (i.e., GSE9844, GSE30784, and GSE13601). The correlation between cell cycle index and immunotherapy efficacy was tested on the IMvigor210 data set. Based on the structure of hub proteins, virtual screening was applied to compounds to find the potential inhibitors. Results: A total of six cell cycle biomarkers (i.e., BUB1, CCNB2, CDC6, CDC20, CDK1, and MCM2) were selected as hub proteins by protein-protein interaction (PPI) analysis. In the validation data sets, the mRNA expression levels of these hub proteins were higher in tumor samples versus normal controls. The cell cycle index was constructed by the mRNA expression levels of these hub proteins, and patients with a high cell cycle index demonstrated favorable drug response to the immunotherapy. Three small molecules (i.e., ZINC100052685, ZINC8214703, and ZINC85537014) were found to bind with hub proteins and selected as drug candidates. Conclusion: The cell cycle index might provide a novel reference for selecting appropriate cancer patient candidates for immunotherapy. The current research might contribute to the development of precision medicine and improve the prognosis of TSCC.