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ADPRH is a prognosis-related biomarker and correlates with immune infiltrates in low grade glioma.

ABSTRACT: Background: ADPRH is a modulator of CD8+ T cell functions, and dysregulation of ADPRH has been identified to involve in carcinogenesis of cancers. However, the association of ADPRH with low grade glioma (LGG) remains unclear. Methods: The expression of ADPRH in LGG was first analyzed in GLIOVIS and GEPIA databases and then validated by real-time PCR (rt-PCR), immunochemistry and human protein atlas (HPA). Univariate and multivariate Cox analysis and Kaplan-Meier plots were designed to assess the prognostic value of ADPRH in LGG. The correlation of ADPRH and immune infiltration was evaluated by data in TIMER and ESTIMATE databases. Gene set enrichment analysis was conducted to detect biological processes associated with ADPRH. Results: ADPRH was significantly upregulated in LGG in comparison to non-tumor brain samples in transcriptomic and proteomic levels. The high ADPRH expression indicated unfavorable overall survival (OS) and progression-free survival (PFS) in patients with LGG using Kaplan-Meier plots. And multivariate Cox analysis demonstrated the expression level of ADPRH was an independent prognosis-predicting index for OS and PFS of LGG patients in all cohorts separately. Gene Set Enrichment Analysis (GSEA) indicated that high expression of ADPRH was involved in the upregulation of P53 signaling pathway, KRAS signaling pathway, IL6/JAK-STAT3 signaling and TNF-beta signaling pathways. By TIMER and ESTIMATE databases, we identified ADPRH expression had strong correlation with tumor immune infiltrating cells (TIICs). Conclusions: In summary, our findings demonstrated that ADPRH might be a potential prognostic biomarker and correlated with TIICs in LGG.

SUBMITTER: Zhang C

PROVIDER: S-EPMC8040889 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Although ferroptosis has been validated to play a crucial role in some types of tumors, the influence of ferroptosis-related genes (FRGs) on the immune microenvironment in low-grade glioma (LGG) remains unclear. In this research, we screen the FRGs to assess the prognosis value and immune microenvironment in LGG, to provide reliable diagnosis and treatment evidence for the clinic. Methods: A total of 1,239 patients of LGG samples were selected for subsequent analyses from The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and the Repository of Molecular Brain Neoplasia Data datasets. Univariate Cox regression analysis was used to screen for prognostic FRGs. Consensus clustering was utilized to determine ferroptosis subtypes of LGG patients. Next, the prognostic model was constructed based on differentially expressed FRGs and validation in the validating datasets. The immune microenvironment, biological pathway, and hypoxia score were explored by single-sample gene set enrichment analysis. The potential response of chemotherapy and immune checkpoint blockade therapy was also estimated. In addition, the correlation between the risk score and autophagy-related genes was examined by the Pearson correlation coefficient. Results: A total of three ferroptosis subtypes were identified by consensus clustering for prognostic FRGs which exhibited different outcomes, clinicopathological characteristics, and immune microenvironment. Afterward, a prognostic model that performed great predictive ability based on nine prognostic FRGs has been constructed and validated. Moreover, the prognostic model had the potential to screen the sensitivity to chemotherapy and immunotherapy in LGG patients. Finally, we also found that the prognostic model has a great connection to autophagy and hypoxia. Conclusion: We developed a ferroptosis-related prognostic model which strongly linked to diagnosis, treatment, prognosis, and recurrence of LGG. This study also reveals the connection between ferroptosis and tumor immune microenvironment.

Project description:Background: Although low-grade glioma (LGG) has a good prognosis, it is prone to malignant transformation into high-grade glioma. It has been confirmed that the characteristics of inflammatory factors and immune microenvironment are closely related to the occurrence and development of tumors. It is necessary to clarify the role of inflammatory genes and immune infiltration in LGG. Methods: We downloaded the transcriptome gene expression data and corresponding clinical data of LGG patients from the TCGA and GTEX databases to screen prognosis-related differentially expressed inflammatory genes with the difference analysis and single-factor Cox regression analysis. The prognostic risk model was constructed by LASSO Cox regression analysis, which enables us to compare the overall survival rate of high- and low-risk groups in the model by Kaplan-Meier analysis and subsequently draw the risk curve and survival status diagram. We analyzed the accuracy of the prediction model via ROC curves and performed GSEA enrichment analysis. The ssGSEA algorithm was used to calculate the score of immune cell infiltration and the activity of immune-related pathways. The CellMiner database was used to study drug sensitivity. Results: In this study, 3 genes (CALCRL, MMP14, and SELL) were selected from 9 prognosis-related differential inflammation genes through LASSO Cox regression analysis to construct a prognostic risk model. Further analysis showed that the risk score was negatively correlated with the prognosis, and the ROC curve showed that the accuracy of the model was better. The age, grade, and risk score can be used as independent prognostic factors (p < 0.001). GSEA analysis confirmed that 6 immune-related pathways were enriched in the high-risk group. We found that the degree of infiltration of 12 immune cell subpopulations and the scores of 13 immune functions and pathways in the high-risk group were significantly increased by applying the ssGSEA method (p < 0.05). Finally, we explored the relationship between the genes in the model and the susceptibility of drugs. Conclusion: This study analyzed the correlation between the inflammation-related risk model and the immune microenvironment. It is expected to provide a reference for the screening of LGG prognostic markers and the evaluation of immune response.

Project description:BackgroundCell division cycle 6 (CDC6) has been proven to be associated with the initiation and progression of human multiple tumors. However, it's role in glioma, which is ranked as one of the common primary malignant tumor in the central nervous system and is associated with high morbidity and mortality, is unclear.MethodsIn this study, we explored CDC6 gene expression level in pan-cancer. Furthermore, we focused on the relationships between CDC6 expression, its prognostic value, potential biological functions, and immune infiltrates in glioma patients. We also performed vitro experiments to assess the effect of CDC6 expression on proliferative, apoptotic, migrant and invasive abilities of glioma cells.ResultsAs a result, CDC6 expression was upregulated in multiple types of cancer, including glioma. Moreover, high expression of CDC6 was significantly associated with age, IDH status, 1p/19q codeletion status, WHO grade and histological type in glioma (all p < 0.05). Meanwhile, high CDC6 expression was associated with poor overall survival (OS) in glioma patients, especially in different clinical subgroups. Furthermore, a univariate Cox analysis showed that high CDC6 expression was correlated with poor OS in glioma patients. Functional enrichment analysis indicated that CDC6 was mainly involved in pathways related to DNA transcription and cytokine activity, and Gene Set Enrichment Analysis (GSEA) revealed that MAPK pathway, P53 pathway and NF-κB pathway in cancer were differentially enriched in glioma patients with high CDC6 expression. Single-sample gene set enrichment analysis (ssGSEA) showed CDC6 expression in glioma was positively correlated with Th2 cells, Macrophages and Eosinophils, and negative correlations with plasmacytoid dendritic cells, CD8 T cells and NK CD56bright cells, suggesting its role in regulating tumor immunity. Finally, CCK8 assay, flow cytometry and transwell assays showed that silencing CDC6 could significantly inhibit proliferation, migration, invasion, and promoted apoptosis of U87 cells and U251 cells (p < 0.05).ConclusionIn conclusion, high CDC6 expression may serve as a promising biomarker for prognosis and correlated with immune infiltrates, presenting to be a potential immune therapy target in glioma.

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ADPRH is a prognosis-related biomarker and correlates with immune infiltrates in low grade glioma.

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