PYCR1 regulates glutamine metabolism to construct an immunosuppressive microenvironment for the progression of clear cell renal cell carcinoma.

Metabolic reprogramming is critical for the setup of the tumor microenvironment (TME). Glutamine has slipped into the focus of research of cancer metabolism, but its role in clear cell renal cell carcinoma (ccRCC) remains vague. Our study aimed to investigate the regulatory mechanism of glutamine in ccRCC and its prognostic value. Gene expression profiles and clinical data of ccRCC patients were obtained from The Cancer Genome Atlas database (TCGA) and Gene Expression Omnibus (GEO) database. Kaplan-Meier survival analysis was used for survival analysis. Consensus clustering was used to extract differentially expressed genes (DEGs) related to glutamine metabolism. Functional analyses, including gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA), were conducted to elucidate the functions and pathways involved in these DEGs. The single-sample GSEA and Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) methods were applied to estimate the immune infiltration in the TMEs of two clusters. The univariate regression and the least absolute shrinkage and selection operator (LASSO) Cox regression were used to construct a prognostic signature. R software was utilized to analyze the expression levels and prognostic values of genes in ccRCC. A total of 19 glutamine metabolic genes (GMGs) were screened out for differential expression analysis of normal and ccRCC tissues. Based on survival-related GMGs, two glutamine metabolic clusters with different clinical and transcriptomic characteristics were identified. Patients in cluster B exhibited worse survivals, higher immune infiltration scores, more significant immunosuppressive cell infiltration, higher expression levels of immune checkpoints, and more enriched oncogenic pathways. Glutamine metabolic index (GMI) was constructed according to the GMGs and survival data. In addition, the expression levels of GMGs were associated with immune cell infiltration and immune checkpoints in the TME of ccRCC. Among the GMGs, PYCR1 was the most powerful regulator of immune TME. Our analysis revealed higher-level glutamine metabolism in ccRCC patients with a worse prognosis. The GMI could predict the prognosis of ccRCC patients with a high accuracy. GMGs, such as PYCR1, may be exploited to design novel immunotherapies for ccRCC. AJCR