Comparative profiling of immune genes improves the prognoses of lower grade gliomas

The landscape of 402 immune-related gene pairs (IPGs). (A) The 402 IPGs were composed of 110 favorable genes (FGs), 88 unfavorable genes (UGs), and 34, 2 role genes. (B–D) The distribution of immune genes from the GSEA and ImmPort databases for the FGs, UGs, and 2 role genes. (E) The gene co-expression network comprised of 232 unique immune genes in 402 immune-related gene pairs. The CD3G, ADAMDEC1, HOXA9, HIST1H2BG, CCR4, CRH, and SERPINB12 genes showed the highest connection degrees in the network. Biological function analyses of FGs (F) and UGs (G).

The accuracy of the hazard ratio (HR) scoring model in prognosis predictions. (A) The composition of different subgroups defined by the HR scores of HOXA9-RGs. (B) The Kaplan-Meier estimate showed the survival curves of patients in HOXA9-RGs in the 0 score and 28 score groups. (C) Similar to panel B, the Kaplan-Meier estimate showed the survival curves of patients in the low HOXA9-RGs score group (scores of 0−4) and high HOXA9-RGs score group (scores of 15−8). (D) The HR scores of HOXA9-RGs were separated by every 10 scores plus the minimum and maximum scores. The Kaplan-Meier curves of patients in 5 scored cohorts. (E–H) The CRH-RGs scoring model for predicting the overall survival of lower grade gliomas.

Identification of the 10 immune-related gene pair (IGP) signature for lower grade glioma patients. (A) One-thousand times cross-validation for tuning parameter selection in the LASSO Cox regression model. (B) LASSO coefficient profiles of 10 IGPs by the largest value of lambda (1se). (C) The hazard ratios and the 95% confidence intervals using univariate analyses, and the values of coefficients using Lasso analyses of 10 IGPs. The dichotomized immune signature risk score allowed the segmentation of patients into high and low risk groups in the Chinese Glioma Genome Atlas (CGGA) RNAseq cohort (D), CGGA microarray cohort (E), and The Cancer Genome Atlas RNAseq cohort (F).

The association between immune signature and tumor immune infiltration characteristics. (A) The landscape of clinical, molecular features, and tumor microenvironment (TME) cells together with immune risk score (a, The association between risk score and continuous variables was assessed using Pearson’s correlation tests. b, The distribution of risk score between 2 groups was assessed using one-way analysis of variance). (B) The distribution characteristics of TME cells between low and high immune risk score groups. The scattered dots represent TME cell values and the thick lines represent the median value (*,**, ***, and **** represent P < 0.05, P < 0.01, P < 0.001, and P < 0.0001, respectively). (C) The normalized expression value of immune activation-relevant genes in the 2 groups. (D) The normalized expression values of immune checkpoint-relevant genes in the 2 groups. (E) The relationship between immune risk scores and T-cell-related metagenes.