A number of key genes have been identified as being linked with the progression and prognosis of squamous lung carcinoma in the GEO and TCGA databases

Abstract Background One of the most common subtypes of lung cancer is lung squamous cell carcinoma (LUSC), which has a poor clinical prognosis and few therapeutic options. Methods Datasets were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) between LUSC and normal tissues were identified by DESeq2, an R software package, and functional analysis was employed using the clusterProfiler, enrichplot, and ggnewscale packages of R software. Protein–protein interaction (PPI) were identified via the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape software. Additionally, 331 DEGs was eliminated using a Cox Univariate analysis of variance with a p-value cutoff of less than 0.02. Hub genes were further validated in the Cancer Genome Atlas (TCGA) database. Subsequently, survival analysis was performed using the Kapla–Meier curve. Results A total of 331 DEGs were identified. These DEGs were mainly enriched in the two pathways: cell cycle and p53 signaling way. According to the degree of protein nodes > 10 in the PPI network, 125 hub genes were identified.By univariate Cox progression analysis, we obtained 37 significant genes, which were then intersected with the PPI results to obtain 9 hub genes. Furthermore, The four genes' Kapla-Meier curves were worked out using a p-value cutoff of 0.05 as the standard. Conclusions The nine hub genes and the development of LUSC may be closely connected and four hub genes may act as independent indicators for LUSC overall survival that have a high predictive value.