Comprehensive Molecular Analyses of a Novel Mutational Signature Classification System with Regard to Prognosis, Genomic Alterations, and Immune Landscape in Glioma

Abstract

Background: Glioma is the most common malignant brain tumor with complex carcinogenic process and poor prognosis. The current molecular classification cannot fully elucidate the molecular diversity of glioma.Methods: Using broad public datasets, we performed cluster analysis based on the mutational signatures and further investigated the multidimensional heterogeneity of the novel glioma molecular subtypes. The clinical significance and immune landscape of four clusters also investigated. The nomogram was developed using the mutational clusters and clinical characteristics.Results: Four heterogenous clusters were identified, termed C1, C2, C3, and C4, respectively. These clusters presented distinct molecular features: C1 was characterized by signature 1, PTEN mutation, chromosome seven amplification and chromosome 10 deletion; C2 was characterized by signature 8 and FLG mutation; C3 was characterized by signature 3 and 13, ATRX and TP53 mutations, and 11p15.1, 11p15.5, and 13q14.2 deletions; and C4 was characterized by signature 16, IDH1 mutation and chromosome 1p and 19q deletions. These clusters also varied in biological functions and immune status. We underlined the potential immune escape mechanisms: abundant stromal and immunosuppressive cells infiltration and immune checkpoints (ICPs) blockade in C1; lack of immune cells, low immunogenicity and antigen presentation defect in C2 and C4; and ICPs blockade in C3. Moreover, C4 possessed a better prognosis, and C1 and C3 were more likely to benefit from immunotherapy. A nomogram with excellent performance was also developed for assessing the prognosis of patients with glioma.Conclusion: Our results can enhance the mastery of molecular features and facilitate the precise treatment and clinical management of glioma.

CD8+ T Cell-Based Molecular Classification With Heterogeneous Immunogenomic Landscapes and Clinical Significance of Clear Cell Renal Cell Carcinoma

“…Comprehensive functional enrichment analyses, including GO enrichment analysis, KEGG enrichment analysis, oncogenic signature, immune signature, cell type signature and "hallmark" signature were performed using "clusterprofiler" R package. Hallmark pools specific well-defined biological states or processes and demonstrates coherent expression, which was extensively utilized in medical studies (40)(41)(42)(43)(44). FDR < 0.05 was considered statistically significant.…”

A Novel Lactate Metabolism-Related Gene Signature for Predicting Clinical Outcome and Tumor Microenvironment in Hepatocellular Carcinoma

“…Firstly, we used the ESTIMATE algorithm to calculate the stromal score of all samples ( Yoshihara et al, 2013 ). ESTIMATE is a prevalent R package, which is widely utilized in the cancer-related studies ( Liu et al, 2021c ; 2021d ; 2021e ). Then, the single sample gene set enrichment analysis (ssGSEA) was performed to derive the immune enrichment score based on the 29 immune gene sets ( Bindea et al, 2013 ).…”

Computational Recognition and Clinical Verification of TGF-β-Derived miRNA Signature With Potential Implications in Prognosis and Immunotherapy of Intrahepatic Cholangiocarcinoma

“…Fifty Hallmark gene sets were retrieved from the MSigDB resource (version 7.4, h.all.v7.4.symbols.gmt), which summarize and represent specific well-defined biological states or processes and demonstrate coherent expression (17). These gene sets were extensively utilized in cancer-related studies (18)(19)(20)(21)(22).…”