Significance of as a biomarker for clinical prognosis, immune infiltration, and drug therapy in lung squamous cell carcinoma.

Background: This study was performed to determine the biological processes in which is involved and thus its role in the development of lung squamous cell carcinoma (LUSC) toward improving the prognosis and treatment of LUSC.

Methods: Raw RNA sequencing (RNA-seq) data of LUSC from The Cancer Genome Atlas (TCGA) were used in bioinformatics analysis to characterize expression levels in tumor and normal tissues. Survival analysis of Kaplan-Meier curve, the time-dependent receiver operating characteristic (ROC) curve, and a nomogram were used to analyze the prognosis value of for LUSC in terms of overall survival (OS) and progression-free survival (PFS). Then, differentially expressed genes (DEGs) were identified, and Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Enrichment Analysis (GSEA) were used to clarify the biological mechanisms potentially involved in the development of LUSC. Moreover, the correlation between the expression level and tumor mutation burden (TMB), tumor microenvironment (TME), and immune cell infiltration revealed that participates in the development of LUSC. Finally, we studied the effects of on drug therapy. To validate the protein and gene expression levels of in LUSC, we employed immunohistochemistry(IHC) datasets, The Gene Expression Omnibus (GEO) database, and qRT-PCR analysis.

Results: expression levels were significantly lower in LUSC than in normal lung tissue. It significantly differed in gender, stage and N classification. The survival analysis revealed that high expression of had shorter OS and PFS in LUSC. The multivariate Cox regression hazard model showed the expression as an independent prognostic factor. Then, the nomogram predicted LUSC prognosis. There are 51 upregulated DEGs and 49 downregulated DEGs in the high-level groups. GO, KEGG and GSEA analysis revealed that DEGs were enriched in cell cycle and DNA replication.The TME results show that expression was positively associated with mast cells resting, neutrophils, monocytes, T cells CD4 memory resting, and M2 macrophages but negatively associated with M1 macrophages. The TMB correlated negatively with expression. The pharmacotherapy had great sensitivity in the low-level group, the immunotherapy is no significant difference in the low-level and high-level groups. The analysis of GEO data demonstrated concurrence with TCGA results. IHC revealed protein expression in tumor tissues of both LUAD and LUSC. Meanwhile qRT-PCR analysis indicated a significantly lower expression level in LUSC compared to LUAD. These qRT-PCR findings were consistent with co-expression analysis of .

Conclusion: We conclude that is a potential biomarker for prognosis and treatment LUSC. A new insights of in LUSC is still needed further research.