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Immune Infiltration-Related Signature Predicts Risk Stratification and Immunotherapy Efficacy in Grade II and III Gliomas.

ABSTRACT: Background: Tumor microenvironment, especially infiltrating immune cell, is crucial for solid tumors including glioma. However, the hub genes as well as their effects on patient prognosis and immunotherapy efficacy remain obscure. Methods: We employed a total of 952 lower grade glioma (LGG) patients from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases, and 24 samples in our hospital for subsequent analyses. Abundances of immune infiltrates were evaluated using CIBERSORT and ImmuCellAI. Their correlations with prognosis were assessed by log-rank test. Immune infiltration-related hub genes were obtained from overlapped differential expressed genes (DEGs) in various subsets of survival-related immune cell types. The risk signature was constructed by Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis. The functional analyses were estimated by GVSA and Gene Set Enrichment Analysis (GSEA) algorithms. And protein-protein interaction enrichment analysis was carried out with the Metascape database integrating STRING, BioGrid, OmniPath, and InWeb_IM. Results: Among the 21 infiltrates, the abundances of five immune infiltrates were correlated with overall survival (OS) in LGG patients. Higher abundances of naïve CD4+ T cells (p = 0.002), activated mast cells (p = 0.015), and monocytes (p = 0.014) were correlated with better prognosis, while higher abundances of resting memory CD4+ T cells (p = 0.015) and M1 macrophages (p = 0.020) correlated with poorer OS. We finally obtained 44 hub genes and constructed an immune infiltration-related signature (IIRS). The IIRS correlates with clinicopathological characteristics and exhibited potential power in predicting the immunotherapy efficacy. The IRRS correlates with cancer related pathways, especially "epithelial-mesenchymal transition (EMT)," and cytotoxic T lymphocytes. Conclusion: Our study constructed and validated a novel signature for risk stratification and prediction of immunotherapy response in grade II and III gliomas, which was closely associated with glioma immune microenvironment and could serve as a promising prognostic biomarker for glioma patients.

SUBMITTER: Luo C

PROVIDER: S-EPMC8603377 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Gliomas are the most common tumors in human brains with unpleasing outcomes. Heme oxygenase-1 (HMOX1, HO-1) was a potential target for human cancers. However, their relationship remains incompletely discussed. Methods: We employed a total of 952 lower grade glioma (LGG) patients from TCGA and CGGA databases, and 29 samples in our hospital for subsequent analyses. Expression, mutational, survival, and immune profiles of HMOX1 were comprehensively evaluated. We constructed a risk signature using the LASSO Cox regression model, and further generated a nomogram model to predict survival of LGG patients. Single-cell transcriptomic sequencing data were also employed to investigated the role of HMOX1 in cancer cells. Results: We found that HMOX1 was overexpressed and was related to poorer survival in gliomas. HMOX1-related genes (HRGs) were involved in immune-related pathways. Patients in the high-risk group exhibited significantly poorer overall survival. The risk score was positively correlated with the abundance of resting memory CD4+ T cells, M1, M2 macrophages, and activated dendritic cells. Additionally, immunotherapy showed potent efficacy in low-risk group. And patients with lower HMOX1 expression were predicted to have better response to immunotherapies, suggesting that immunotherapies combined with HMOX1 inhibition may execute good responses. Moreover, significant correlations were found between HMOX1 expression and single-cell functional states including angiogenesis, hypoxia, and metastasis. Finally, we constructed a nomogram which could predict 1-, 3-, and 5-year survival in LGG patients. Conclusion: HMOX1 is involved in immune infiltration and predicts poor survival in patients with lower grade glioma. Importantly, HMOX1 were related to oncological functional states including angiogenesis, hypoxia, and metastasis. A nomogram integrated with the risk signature was obtained to robustly predict glioma patient outcomes, with the potential to guide clinical decision-making.

Project description:Grade II and III gliomas are heterogeneous and aggressive diseases. More efficient prognosis models and treatment methods are needed. This study aims to construct a new risk model and propose a new strategy for grade II and III gliomas. The data were downloaded from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), gene set enrichment analysis (GSEA), and the EMTome website for analysis. The Human Cell Landscape website and the Genomics of Drug Sensitivity in Cancer website were used for single-cell analysis and drug susceptibility analysis. Gene set enrichment analysis, gene function enrichment analysis, univariate and multivariate Cox regression analyses, Pearson's correlation analysis, log-rank test, Kaplan-Meier survival analysis, and ROC analysis were performed. We constructed an immune-related prognostic model associated with the isocitrate dehydrogenase 1 (IDH1) mutation status. By analyzing the immune microenvironment of patients with different risk scores, we found that high-risk patients were more likely to have an inflammatory immune microenvironment and a higher programmed death ligand-1 (PD-L1) expression level. Epithelial-mesenchymal transition (EMT)-related gene sets were significantly enriched in the high-risk group, and the epithelial-mesenchymal transition phenotype was associated with a decrease in CD8+ T cells and an increase in M2 macrophages. Transforming growth factor-β (TGF-β) signaling was the most important signaling in inducing epithelial-mesenchymal transition, and TGFB1/TGFBR1 was correlated with an increase in CD8+ T cytopenia and M2 macrophages. Survival analysis showed that simultaneous low expression of TGFBR1 and PD-L1 had better survival results. Through single-cell analysis, we found that TGFB1 is closely related to microglia and macrophages, especially M2 macrophages. Finally, we discussed the sensitivity of TGFB1 inhibitors in gliomas using cell line susceptibility data. These results demonstrated a potential immunotherapy strategy in combination with the TGFB1/TGFBR1 inhibitor and PD-1/PD-L1 inhibitor for grade II and III gliomas.

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Immune Infiltration-Related Signature Predicts Risk Stratification and Immunotherapy Efficacy in Grade II and III Gliomas.

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