Identification of Genes Associated With Laryngeal Squamous Cell Carcinoma by Weighted Gene Co-Expression Network Analysis

Abstract Background: Laryngeal squamous cell carcinoma (LSCC) is one of the leading malignant cancers of the head and neck. Patients with LSCC infiltration and metastasis have a poor prognosis. There is an urgent need to identify more potential targets for drugs and biomarkers for early diagnosis.Methods: RNA sequence data from LSCC and patient clinic traits were obtained from the Gene Expression Omnibus (GEO) (GSE142083) and The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify the hub genes. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, prognostic values analysis and the tumor-infiltrating immune cell (TIC) abundance profiles estimation were performed.Results: In present study, a total of 432 DEGs, including 199 up-regulated genes and 233 down-regulated genes were screened in GSE142083 dataset. After intersecting with DEGs in TCGA, 211 common DEGs were screened. Using WGCNA, five modules were identified to be closely related to LSCC. After compared with common DEGs and performed with univariate Cox regression analysis, only eight genes, including CEACAM6, FSCN1, INHBA, MYO1B, PLAU, SERPINH1, TJP3 and TNFRSF12A, were screened out to be significantly related to the prognosis of patients diagnosed with LSCC.Conclusions: The results in present study shows that CEACAM6, FSCN1, INHBA, MYO1B, PLAU, SERPINH1, TJP3 and TNFRSF12A have the potential to become new therapeutic targets and biomarkers for LSCC.