Bioinformatics-based discovery of PYGM and TNNC2 as potential biomarkers of head and neck squamous cell carcinoma

Abstract

Abstract Head and neck squamous cell carcinoma (HNSCC) is an aggressive malignancy with high morbidity and mortality rates and ranks as the sixth most common cancer all over the world. Despite numerous advancements in therapeutic methods, the prognosis of HNSCC patients still remains poor. Therefore, there is an urgent need to have a better understanding of the molecular mechanisms underlying HNSCC progression and to identify essential genes that could serve as effective biomarkers and potential treatment targets. In the present study, original data of three independent datasets were downloaded from the Gene Expression Omnibus database (GEO) and R language was applied to screen out the differentially expressed genes (DEGs). PYGM and TNNC2 were finally selected from the overlapping DEGs of three datasets for further analyses. Transcriptional and survival data related to PYGM and TNNC2 was detected through multiple online databases such as Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), cBioportal, and UALCAN. Quantitative real-time polymerase chain reaction (qPCR) analysis was adopted for the validation of PYGM and TNNC2 mRNA level in HNSCC tissues and cell lines. Survival curves were plotted to evaluate the association of these two genes with HNSCC prognosis. It was demonstrated that PYGM and TNNC2 were significantly down-regulated in HNSCC and the aberrant expression of PYGM and TNNC2 were correlated with HNSCC prognosis, implying the potential of exploiting them as therapeutic targets for HNSCC treatment or potential biomarkers for diagnosis and prognosis.