Exploration of the Perturbation of PKIG in Lung Squamous Cell Carcinoma and the Role in Tumor Microenvironment Based on Bioinformatics Method

Abstract

Background and objective Lung cancer is the leading cause of cancer-related death worldwide, and patients have limited survival benefits from traditional treatments such as surgery, radiotherapy and chemotherapy. As a new treatment for lung cancer, immunotherapy has significantly prolonged the overall survival (OS) of patients. However, only some patients can benefit from it. We need to explore immunotherapy biomarkers more deeply to screen for advantages. Methods The original data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, and the immunological and prognostic genes of lung squamous cell carcinoma (LUSC) were screened using R software and TIMER database. The expression of target genes was studied in TCGA and GEO databases, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and correlation analysis with tumor immune characteristics were performed by R software and TISIDB database. Results We screened out a gene related to immunity and prognosis, cAMP dependent protein kinase inhibitor γ (PKIG), which is significantly differentially expressed in LUSC and normal tissues, and has important reference value for the diagnosis and prognosis assessment of LUSC. PKIG differential genes are mainly concentrated in the regulation of humoral immune response and other processes. The expression of PKIG was positively correlated with the infiltration level of regulatory T cells (Tregs) (r=0.340, P<0.001). In addition, the expression level of PKIG was positively correlated with the expression of chemokines/chemokine receptors such as chemokine C-C motif ligand 2 (CCL2) (r=0.503, P<0.001), CXC chemokine ligand 12 (CXCL12) (r=0.386, P<0.001) and CXC-chemokine receptor 4 (CXCR4) (r=0.492, P<0.001), and immunoinhibitors such as programmed cell death protein 1 (PDCD1) (r=0.359, P<0.001), cytotoxic T-lymphocyte associated antigen 4 (CTLA4) (r=0.375, P<0.001) and T cell immunoglobulin and ITIM domains (TIGIT) (r=0.305, P<0.001) in LUSC. Conclusion The immunological and prognostic gene PKIG in lung squamous cell carcinoma was screened through bioinformatics analysis. PKIG is highly correlated with LUSC prognosis and immune microenvironment, and is expected to be a potential biomolecular marker for LUSC immunotherapy.

Keywords

• lung neoplasms
• bioinformatics
• tumor microenvironment
• immunotherapy
• camp-dependent protein kinase inhibitor γ