TITLE:
Bioinformatics Analysis of the Expression Characteristics, Clinical Associations, and Prognostic Value of SLC7A11 in Glioma
AUTHORS:
Jiayuan Zhang, Zongquan Nie, Ruijie Zheng, Yuxuan Li, Chuanyu Li
KEYWORDS:
Glioma, SLC7A11, Prognostic Analysis, Tumor Immune Microenvironment, Bioinformatics Analysis
JOURNAL NAME:
Journal of Biosciences and Medicines,
Vol.14 No.6,
June
26,
2026
ABSTRACT: Objective: This study aims to investigate the expression characteristics, clinical prognostic value, and association with the tumor immune microenvironment of solute carrier family 7 member 11 (SLC7A11) in glioma through bioinformatics analysis, and to construct a nomogram prediction model based on key clinicopathological variables and SLC7A11 expression levels. The findings provide a theoretical basis for revealing the potential involvement of SLC7A11 in ferroptosis, immune regulation, and metabolic reprogramming during glioma progression, enrich the evidence for SLC7A11 as a potential biomarker in glioma, and offer candidate molecular targets for future immune-metabolism?related intervention strategies. Methods: Transcriptomic data and corresponding clinical information of glioma and normal brain tissues were obtained from the TCGA and GTEx databases. Glioma patients were divided into high- and low-expression groups based on the median expression level of SLC7A11. Chi?square tests were used to compare differences in clinical characteristics, including WHO grade, age, histological type, and survival event rates, between the two groups. GO and KEGG enrichment analyses as well as GSEA were performed to evaluate biological pathways associated with SLC7A11 expression. The ssGSEA algorithm was employed to calculate the infiltration abundances of 24 immune cell types, and Spearman correlation analysis was conducted to examine the relationship between SLC7A11 expression and immune cell infiltration levels. Kaplan–Meier curves were generated for overall survival (OS), disease?specific survival (DSS), and progression?free interval (PFI), and the log?rank test was used to assess between?group differences. Stratified survival analyses based on LGG, GBM, and IDH classification were not performed in this study, and relevant subgroup validation will be addressed in future research. Univariate and multivariate Cox regression models were applied to analyze the independent prognostic value of SLC7A11 and other clinical variables. A nomogram prediction model integrating WHO grade, IDH status, age, and SLC7A11 expression was constructed, and its predictive accuracy for 1?, 3?, and 5?year survival probabilities was evaluated by calibration curves. Results: SLC7A11 expression levels were significantly higher in a variety of tumor tissues than in normal brain tissue. After stratifying glioma patients by the median SLC7A11 expression level, the high?expression group showed a lower WHO grade, younger age, fewer cases of glioblastoma, and a lower rate of overall survival events (all P γδ T cells (Tgd), and significantly negatively correlated with Th2 cells. Survival analysis showed that patients in the high SLC7A11 expression group had significantly better OS, DSS, and PFI than those in the low?expression group (log?rank test P Conclusion: SLC7A11 is expressed at a high level in glioma, and its high expression is significantly associated with a lower WHO grade, a non?glioblastoma phenotype, and longer overall survival. This association challenges the conventional view that SLC7A11 serves as an adverse prognostic marker in most solid tumors. Functional enrichment suggested that the high?expression group was enriched in bile acid metabolism and KRAS signaling downregulation, whereas the low?expression group exhibited activation of EMT and cell cycle pathways. Immune infiltration analysis revealed that SLC7A11 was positively correlated with TFH, Tcm, and Tgd, and negatively correlated with Th2 cells. Although not an independent prognostic factor, the nomogram model incorporating SLC7A11 showed good predictive performance and may serve as a potential complementary marker for prognostic assessment in glioma.