Uncovering the Immune Cell Infiltration Landscape in Low-Grade Glioma for Aiding Immunotherapy

OBJECTIVE: Low-grade glioma (LGG) mainly threatens the elderly population, with undesirable prognoses. This study uncovered the immune cell infiltration (ICI) landscape in LGG. METHODS: RNA-seq profiles of LGG were retrieved from TCGA and CGGA databases. CIBERSORTx and ESTIMATE algorithms were employed to characterize the ICI landscape in LGG tissues. Through unsupervised clustering analysis, ICI subtypes were clustered. ICI scores were computed via principal component analysis (PCA). The differences in survival, tumor-infiltrating immune cells, stromal scores, immune scores, immune checkpoint genes, immune activity genes, and tumor mutation burden (TMB) were assessed between high and low ICI score groups. RESULTS: Three ICI subtypes were constructed in LGG, with distinct survival outcomes, PD-L1 expression, and infiltration levels of immune cells. Furthermore, ICI scores were developed. Both in TCGA and CGGA datasets, low ICI scores were indicative of undesirable outcomes. High ICI scores were significantly correlated to increased infiltration levels of memory B cells, CD8 T cells, CD4 naïve T cells, T follicular helper cells, macrophages M0, and eosinophils, while low ICI scores were characterized by increased infiltration levels of naïve B cells, plasma cells, CD4 memory resting T cells, Tregs, resting NK cells, macrophages M2, and activated dendritic cells. High ICI scores exhibited correlations with lower immune activity genes and immune checkpoint genes. Furthermore, TMB was distinctly reduced in the high ICI score group. CONCLUSION: The ICI scores may serve as a promising prognostic index and predictive indicator for immunotherapies, extending our understanding of immune microenvironment in LGG.