International Journal of General Medicine (Jan 2022)
A Bioinformatic Analysis of Immune-Related Prognostic Genes in Clear Cell Renal Cell Carcinoma Based on TCGA and GEO Databases
Abstract
Jianpeng Li,1– 3,* Jinlong Cao,1– 3,* Pan Li,1– 3 Ran Deng,1– 3 Zhiqiang Yao,1– 3 Lijun Ying,1– 3 Junqiang Tian1– 3 1Department of Urology, The Second Hospital of Lanzhou University, Lanzhou, People’s Republic of China; 2Key Laboratory of Gansu Province for Urological Diseases, The Second Hospital of Lanzhou University, Lanzhou, People’s Republic of China; 3Clinical Center of Gansu Province for Nephron-Urology, The Second Hospital of Lanzhou University, Lanzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Junqiang TianDepartment of Urology, The Second Hospital of Lanzhou University, Lanzhou, 730030, People’s Republic of ChinaEmail [email protected]: Clear cell renal cell carcinoma (ccRCC) is a commonly occurring tumor. Through a deeper understanding of the immune regulatory mechanisms in the tumor microenvironment, immunotherapy may serve as a potential treatment for cancer patients. This study aimed at identifying the survival-related immune cells and hub genes, which could be potential targets for immunotherapy in ccRCC.Methods: The gene expression profiles and clinical data of ccRCC patients were extracted from UCSC Xena and Gene Expression Omnibus (GEO) databases. Kaplan–Meier (KM) survival and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were utilized to select the survival-related tumor-infiltrating immune cells. Multivariate Cox regression was utilized to develop a signature based on the tumor-infiltrating immune cells (TIICs). Based on the signature, the risk score was calculated, following which the samples were divided into high-risk and low-risk groups. Differentially expressed genes (DEGs) between the two risk groups were identified. Functional enrichment analysis was performed and cytoHubba plug-in of Cytoscape was used to identify the hub genes. Multiple datasets were utilized to validate these hub genes, including the Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and the Human Protein Atlas (HPA), and the GEO datasets. Finally, a correlation analysis was performed to evaluate the relationship between the hub genes and TIICs.Results: Four immune survival-related cells, including T cell CD4 memory-activated, T cell regulatory (Tregs), eosinophils, and mast cell resting were identified. Nine immune-specific hub genes were identified, which included APOE, CASR, CTLA4, CXCL8, EGF, F2, KNG1, MMP9, and IL6. Furthermore, these hub genes were significantly correlated with clinical traits and closely associated with some TIICs.Conclusion: A total of four survival-related immune cell types and nine hub genes were found to be closely associated with ccRCC. These findings may have implications for the development of novel potential immunotherapeutic targets for ccRCC.Keywords: ccRCC, tumor-infiltrating immune cells, hub genes, TCGA, tumor microenvironment
