A Bioinformatics-based Study Investigating the Crrelation Between RGS22 Expression and Immune Cell Infiltration in Lung Adenocarcinoma

Abstract

Objective To investigate the correlation between regulator of G protein signaling 22 (RGS22) and immune cell infiltration in lung adenocarcinoma (LUAD) through bioinformatics analysis, it is to identify novel potential biomarkers for auxiliary diagnosis and therapy. Methods Gene expression data and relevant clinical data were downloaded from The Cancer Genome Atlas (TCGA) database to analyze the correlation between RGS22 expression and tumor immune cell infiltration in LUAD. In addition, external validation in an independent cohort was performed using public datasets from the Gene Expression Omnibus (GEO). Results The study found that RGS22 was downregulated in LUAD tumor tissues, which was associated with shorter overall survival in patients. This results were validated in both the TCGA cohort (n = 527, P = 0.004) and the GEO cohort (n = 398, P = 3.01×10 -6 ). The expression of RGS22 was positively correlated with the infiltration levels of various immune cells, including dendritic cells and CD4 + T cells. Therefore, these findings revealed that RGS22 influences the prognosis of LUAD by affecting the infiltration levels of immune cells. Conclusion RGS22 maybe become a new biomarker for the early diagnosis and prognosis of LUAD.