Fig. 3.

ARHGDIB reshapes the immunosuppressive microenvironment in glioma. A The volcano plot illustrates the DEGs between the low-ARHGDIB and high-ARHGDIB groups in TCGA glioma cohort. B GSEA analysis was performed on gliomas with low and high ARHGDIB expression in TCGA cohort; the significance of the enrichment score (ES) was determined using thresholds of a nominal P < 0.05 and an FDR < 25%. (C-H) The ESTIMATE algorithm evaluates the stromal and immune scores in high- vs. low-ARHGDIB groups across multiple cohorts: C TCGA, D CGGA-325, E CGGA-301, F CGGA-693, G Rembrandt, H GSE16011. I and J Pan-cancer analysis of the correlation between ARHGDIB expression levels and immune cell infiltration using the CIBERSORT and ssGSEA algorithms. K and M The lollipop plot illustrates the correlation between ARHGDIB expression levels and the abundance of immune cell infiltration in glioma, based on CIBERSORT algorithms from TCGA (K), CGGA-301 (L), Rembrandt cohort (M). N–S The ssGSEA algorithm was used to evaluate the levels of immune cell infiltration in gliomas of high- vs. low-ARHGDIB groups across multiple cohorts: N TCGA, O CGGA-693, P CGGA-301, Q CGGA-325, R Rembrandt, S GSEA10611. Differences between the two groups were assessed using Student’s t test, with P values indicated above each boxplot using asterisks (**P < 0.01, ***P < 0.001)