Construction of Interferon-Gamma-Related Gene Signature to Characterize the Immune-Inflamed Phenotype of Glioblastoma and Predict Prognosis, Efficacy of Immunotherapy and Radiotherapy

Abstract

Interferon-gamma (IFNG) has profound impacts on tumor-immune interaction and is of great clinical significance for multiple cancers. Exploring the role of IFNG in glioblastoma (GBM) may optimize the current treatment paradigm of this disease. Here, multi-dimensional data of 429 GBM samples were collected. Various bioinformatics algorithms were employed to establish a gene signature that characterizes immunological features, genomic alterations, and clinical characteristics associated with the IFNG response. In this way, a novel IFNG-related gene signature (IFNGrGS, including TGFBI, IL4I1, ACP5, and LUM) has been constructed and validated. Samples with increased IFNGrGS scores were characterized by increased neutrophil and macrophage infiltration and exuberant innate immune responses, while the activated adaptive immune response may be frustrated by multiple immunosuppressive mechanisms. Notably, the IFNG pathway as well as its antagonistic pathways including IL4, IL10, TGF-beta, and VEGF converged on the expression of immune checkpoints. Besides, gene mutations involved in the microenvironment were associated with the IFNGrGS-based stratification, where the heterogeneous prognostic significance of EGFR mutation may be related to the different degrees of IFNG response. Moreover, the IFNGrGS score had solid prognostic value and the potential to screen ICB and radiotherapy sensitive populations. Collectively, our study provided insights into the role of IFNG on the GBM immune microenvironment and offered feasible information for optimizing the treatment of GBM.

HeberFERON distinctively targets Cell Cycle in the glioblastoma-derived cell line U-87MG

“…The best known is the methylation status of O(6)-methylguanine-DNA-methyltransferase (MGMT) as a predictor of temozolomide (Hegi et al 2005) and radiation resistance (Rivera et al 2010). Other has described IFNβ or IFNγ associated gene signatures to predict OS, efficacy of immunotherapy and radiotherapy among glioblastoma patients (Cheng et al 2021, Ji et al 2021). Eventually, these genes signatures should be validated in the clinical practice.…”

Identification of EMT-Related Genes and Prognostic Signature With Significant Implications on Biological Properties and Oncology Treatment of Lower Grade Gliomas

“…This resulted in higher levels of T-cell exhaustion and poorer anti-tumor immunity. In fact, several studies found that some LGG samples in the TCGA cohort had immunological characteristics similar to our C2 subtype, which possessed a poorer prognosis ( Du et al, 2020 ; Wu et al, 2020 ; Ji et al, 2021 ). Also, samples with C2 were more likely to acquire higher stemness levels.…”

Development of a TMErisk model based on immune infiltration in tumour microenvironment to predict prognosis of immune checkpoint inhibitor treatment in hepatocellular carcinoma

“…In addition, we used several currently available gene signatures, including cytolytic activity score [ 17 , 31 ], cytotoxic score (CS) [ 18 ], T cell-related gene expression profile [ 32 ], five-gene T cell signature [ 33 ] and interferon-gamma-related gene signature (IFNGrGS) [ 34 ] to compare the predictive value with the TMErisk score ( Supplementary Figure S6B ). Except for IFNGrGS, they were significantly correlated with the TMErisk score ( R 2 > 0.3) (Supplementary Figure S6A ).…”