ISG20 promotes local tumor immunity and contributes to poor survival in human glioma

Gao, Mengqi; Lin, Yi; Liu, Xing; Li, Yiming; Zhang, Chuanbao; Wang, Zheng; Wang, Zhiliang; Wang, Yulin; Guo, Zongze

R language (v. 3.4.3), SPSS software (v. 22.0), and GraphPad Prism (v. 7.0) for Windows were used for statistical analyses and generating figures. GBM and LGG samples from the CGGA and TCGA datasets were analyzed respectively. Genes with significantly different expression between groups with distinct IDH status were estimated by a two-tailed Student's t-test. The Significance Analysis of Microarrays (SAM) package of R was performed to control the FDR. Values of p < 0.05 and FDR < 0.01 were considered statistically significant. Genes that showed consistent differential expression in both the GBM and LGG cohorts from the two datasets were extracted. We then calculated the prognostic value of these differentially expressed genes using the survival package of R. A multivariate Cox proportional hazard model was performed for evaluating the independent prognostic variables. Kaplan-Meier curves were employed to depict survival distributions. Genes and immune cells correlated with ISG20 expression were explored by Pearson's correlation coefficient (r) using R considering the effect of variant grades or IDH status. An absolute r-value of greater than 0.4 was considered to indicate a forcefully significant correlation with ISG20.