Identification and Verification of Tumor Immune Microenvironment-Related Prognostic Genes in Kidney Renal Clear Cell Carcinoma

Abstract

Background. The tumor immune microenvironment is vital to kidney renal clear cell carcinoma (KIRC) progression, and immunotherapies have been shown to be effective in the management of KIRC. However, the prognostic genes associated with the tumor immune microenvironment in KIRC have not been fully identified. We obtained the KIRC RNA sequencing data and the clinical characteristics from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. We screened the gene modules associated with the tumor immune microenvironment based on the ESTIMATE algorithm and weighted gene coexpression network analysis (WGCNA). Univariate Cox analysis and the LASSO method were used to construct a prognostic model. Receiver Operating Characteristic (ROC) curve analysis was performed to evaluate the accuracy of our risk model. TIMER and Single-Sample Gene Set Enrichment Analysis (ssGSEA) were used to explore the correlation between prognostic genes and immune cell infiltration. Results. Fifty-four genes in modules were significantly associated with the overall survival (OS) time of patients with KIRC. Furthermore, 12 hub genes were selected to construct the prognostic model. The prognostic model showed superior accuracy in both TCGA and ICGC cohorts using ROC curve analysis. Systematic analysis of immune cell infiltration revealed that nine genes were significantly correlated with levels of tumor-infiltrating immune cells. Conclusions. Our findings indicated that the tumor immune microenvironment was an important determinant of KIRC outcomes and revealed potential biomarkers for predicting patient OS and for targeted immunotherapies.

Identification and Verification of m7G Modification Patterns and Characterization of Tumor Microenvironment Infiltration via Multi-Omics Analysis in Clear Cell Renal Cell Carcinoma

“…The extent of T-cell infiltration is remarkably high in ccRCC ( 72 ), which leads to marked inflammatory features. However, as the most abundant immune cells, CD8 + T cells display impaired anti-tumor effects, which indicates that the immune microenvironment for ccRCC is unique compared with other tumors ( 73 ). It was also reported that epigenetic modification could alter the anti-tumor immune response ( 74 ).…”

Identification of Ligand-Receptor Pairs Associated With Tumour Characteristics in Clear Cell Renal Cell Carcinoma

“…However, the current findings are consistent with previous studies, revealing a significant positive correlation between immune score and malignancy degree in patients with ccRCC in the TCGA-KIRC cohort. High immune score and ESTIMATE scores have been associated with worse prognosis ( 36 , 37 ). Additionally, the high infiltration levels of exhausted CD8 + T cells and immunosuppressive M2-like macrophages have been reported in advanced renal disease ( 8 ), suggesting that immune scores could indicate progressive T cell dysfunction in patients with ccRCC.…”

Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

“…Based on the expression level of immune cell-related genes, the ESTIMATE algorithm was conducted to calculate the stromal score (SS), estimate score (ES), and immune score (IS) (the SS represents the level of stroma content in a tumor; the IS reflects the infiltration of immune cells in a tumor; the estimated score infers tumor purity) among the high- and low-risk groups using the “estimate” package ( 32 ). Single-sample gene set enrichment analysis (ssGSEA) was performed to calculate scores for antitumor immunity and protumor suppression for each sample ( 33 ) using “GSEABase” and “GSVA” packages.…”