A Novel Immune Gene-Related Prognostic Score Predicts Survival and Immunotherapy Response in Glioma.
Xuehui LuoQi WangHanmin TangYuetong ChenXinyue LiJie ChenXinyue ZhangYuesen LiJiahao SunSuxia HanPublished in: Medicina (Kaunas, Lithuania) (2022)
Background and Objectives: The clinical prognosis and survival prediction of glioma based on gene signatures derived from heterogeneous tumor cells are unsatisfactory. This study aimed to construct an immune gene-related prognostic score model to predict the prognosis of glioma and identify patients who may benefit from immunotherapy. Methods: 23 immune-related genes (IRGs) associated with glioma prognosis were identified through weighted gene co-expression network analysis (WGCNA) and Univariate Cox regression analysis based on large-scale RNA-seq data. Eight IRGs were retained as candidate predictors and formed an immune gene-related prognostic score (IGRPS) by multifactorial Cox regression analysis. The potential efficacy of immune checkpoint blockade (ICB) therapy of different subgroups was compared by The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm. We further adopted a series of bioinformatic methods to characterize the differences in clinicopathological features and the immune microenvironment between the different risk groups. Finally, a nomogram integrating IGRPS and clinicopathological characteristics was built to accurately predict the prognosis of glioma. Results: Patients in the low-risk group had a better prognosis than those in the high-risk group. Patients in the high-risk group showed higher TIDE scores and poorer responses to ICB therapy, while patients in the low-risk group may benefit more from ICB therapy. The distribution of age and tumor grade between the two subgroups was significantly different. Patients with low IGRPS harbor a high proportion of natural killer cells and are sensitive to ICB treatment. While patients with high IGRPS display relatively poor prognosis, a higher expression level of DNA mismatch repair genes, high infiltrating of immunosuppressive cells, and poor ICB therapeutic outcomes. Conclusions: We demonstrated that the IGRPS model can independently predict the clinical prognosis as well as the ICB therapy responses of glioma patients, thus having important implications on the design of immune-based therapeutic strategies.
Keyphrases
- poor prognosis
- end stage renal disease
- newly diagnosed
- ejection fraction
- genome wide
- chronic kidney disease
- copy number
- peritoneal dialysis
- oxidative stress
- magnetic resonance
- dna methylation
- machine learning
- type diabetes
- patient reported outcomes
- deep learning
- genome wide identification
- computed tomography
- squamous cell carcinoma
- metabolic syndrome
- long non coding rna
- cell death
- induced apoptosis
- adipose tissue
- bone marrow
- contrast enhanced
- cell proliferation
- cell cycle arrest
- patient reported
- circulating tumor cells