Screening of biomarkers in cervical squamous cell carcinomas via gene expression profiling

In the present study, gene expression profiles of high-grade squamous intraepithelial lesions (HSIL) and invasive cervical squamous cell carcinomas (CSCC) were analyzed using bioinformatic tools to identify key genes and potential biomarkers. Analyses of differentially expressed genes (DEGs) were performed for HSIL vs. normal control and invasive CSCC vs. normal control tissues using the Limma package in R. Pathway enrichment analysis was performed using KOBAS. A protein‑protein interaction (PPI) network for the DEGs in invasive CSCC was constructed using String. Functional enrichment analysis was performed for the DEGs in the PPI network using DAVID. Relevant small molecules were predicted using Cmap. A total of 633 and 881 DEGs were identified in HSIL and invasive CSCC, respectively, and the two groups had 305 DEGs in common. Genes associated with the mitogen-activated protein kinase signaling pathway were enriched in the HSIL, while cell cycle-associated genes were over‑represented in invasive CSCC. The PPI network, containing 72 upregulated genes and 434 edges, was illustrated. Functional enrichment analysis showed that the cell cycle was the most significant gene ontology term. A total of six small molecules associated with the pathology of CSCC were identified, including the anti-cancer drug piperlongumine, which showed a negative correlation. The findings of the present study not only enhanced the current understanding of the pathogenesis of CSCC, but may also be a basis for the development of novel therapies.