Dataset Information

Ferroptosis-related NFE2L2 and NOX4 Genes are Potential Risk Prognostic Biomarkers and Correlated with Immunogenic Features in Glioma.

ABSTRACT: Ferroptosis is a newfound mode of regulated cell death that may have potential to associate with prognostic or diagnostic factors in glioma. In this research, 5 genes related to glioma were screened through the FerrDb database, and we analyzed the combination between genes and glioma of survival and prognosis via TCGA, GEPIA, TIMER, and other databases. Survival curve and prognostic analysis showed that the overexpression of NFE2L2 and NOX4, respectively, has a remarkable link with a worse prognosis in glioma. Then, the association between the expression of the two genes and tumor-infiltrating immune cells level was explored based on the GSCA, and the immunity of NFE2L2 and NOX4 based on the TISIDB database was also investigated. In glioma, especially GBM, there is a strong association between gene expression and immune infiltration, even in macrophages, nTreg, and Th2 cells, which play immunosuppressive functions in TME. In conclusion, these results indicate that NFE2L2 and NOX4 could be risk prognosis biomarkers in glioma, and they bound up with immune infiltration and tumor immunity in tumorigenesis.

SUBMITTER: Lin L

PROVIDER: S-EPMC9925512 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Ferroptosis-related NFE2L2 and NOX4 Genes are Potential Risk Prognostic Biomarkers and Correlated with Immunogenic Features in Glioma.

Lin Li L Li Xiaona X Zhu Shunda S Long Qingshan Q Hu Yongzhen Y Zhang Liyang L Liu Zexin Z Li Bo B Li Xuesong X

Cell biochemistry and biophysics 20230111 1

Ferroptosis is a newfound mode of regulated cell death that may have potential to associate with prognostic or diagnostic factors in glioma. In this research, 5 genes related to glioma were screened through the FerrDb database, and we analyzed the combination between genes and glioma of survival and prognosis via TCGA, GEPIA, TIMER, and other databases. Survival curve and prognostic analysis showed that the overexpression of NFE2L2 and NOX4, respectively, has a remarkable link with a worse progn ...[more]

PMID: 36627482

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Project description:BackgroundFerroptosis is a form of programmed cell death (PCD) that has been implicated in cancer progression, although the specific mechanism is not known. Here, we used the latest DepMap release CRISPR data to identify the essential ferroptosis-related genes (FRGs) in glioma and their role in patient outcomes.MethodsRNA-seq and clinical information on glioma cases were obtained from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA). FRGs were obtained from the FerrDb database. CRISPR-screened essential genes (CSEGs) in glioma cell lines were downloaded from the DepMap portal. A series of bioinformatic and machine learning approaches were combined to establish FRG signatures to predict overall survival (OS) in glioma patients. In addition, pathways analysis was used to identify the functional roles of FRGs. Somatic mutation, immune cell infiltration, and immune checkpoint gene expression were analyzed within the risk subgroups. Finally, compounds for reversing high-risk gene signatures were predicted using the GDSC and L1000 datasets.ResultsSeven FRGs (ISCU, NFS1, MTOR, EIF2S1, HSPA5, AURKA, RPL8) were included in the model and the model was found to have good prognostic value (p < 0.001) in both training and validation groups. The risk score was found to be an independent prognostic factor and the model had good efficacy. Subgroup analysis using clinical parameters demonstrated the general applicability of the model. The nomogram indicated that the model could effectively predict 12-, 36-, and 60-months OS and progression-free interval (PFI). The results showed the presence of more aggressive phenotypes (lower numbers of IDH mutations, higher numbers of EGFR and PTEN mutations, greater infiltration of immune suppressive cells, and higher expression of immune checkpoint inhibitors) in the high-risk group. The signaling pathways enriched closely related to the cell cycle and DNA damage repair. Drug predictions showed that patients with higher risk scores may benefit from treatment with RTK pathway inhibitors, including compounds that inhibit RTKs directly or indirectly by targeting downstream PI3K or MAPK pathways.ConclusionIn summary, the proposed cancer essential FRG signature predicts survival and treatment response in glioma.

Project description:BackgroundGliomas are the most common intracranial nervous system tumours that are highly malignant and aggressive, and mitochondria are an important marker of metabolic reprogramming of tumour cells, the prognosis of which cannot be accurately predicted by current histopathology. Therefore, Identify a mitochondrial gene with immune-related features that could be used to predict the prognosis of glioma patients.MethodsGliomas data were downloaded from the TCGA database and mitochondrial-associated genes were obtained from the MITOCARTA 3.0 dataset. The CGGA, kamoun and gravendeel databases were used as external datasets. LASSO(Least absolute shrinkage and selection operator) regression was applied to identify prognostic features, and area and nomograms under the ROC(Receiver Operating Characteristic) curve were used to assess the robustness of the model. Single sample genomic enrichment analysis (ssGSEA) was employed to explore the relationship between model genes and immune infiltration, and drug sensitivity was used to identify targeting drugs. Cellular studies were then performed to demonstrate drug killing against tumours.ResultsCOX assembly mitochondrial protein homolog (CMC1), Cytochrome c oxidase protein 20 homolog (COX20) and Cytochrome b-c1 complex subunit 7 (UQCRB) were identified as prognostic key genes in glioma, with UQCRB, CMC1 progressively increasing and COX20 progressively decreasing with decreasing risk scores. ROC curve analysis of the TCGA training set model yielded AUC (Area Under The Curve) values >0.8 for 1-, 2- and 3-year survival, and the model was associated with both CD8+ T cells and immune checkpoints. Finally, using cellMiner database and molecular docking, it was confirmed that UQCRB binds covalently to Amonafide via lysine at position 78 and threonine at position 82, while cellular assays showed that Amonafide inhibits glioma migration and invasion.ConclusionOur three mitochondrial genomic composition-related features accurately predict Survival in glioma patients, and we also provide glioma chemotherapeutic agents that may be mitochondria-related targets.

Project description:Background: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive disease with unknown etiology and unfavorable prognosis. Ferroptosis is a form of regulated cell death with an iron-dependent way that is involved in the development of various diseases. Whereas the prognostic value of ferroptosis-related genes (FRGs) in IPF remains uncertain and needs to be further elucidated. Methods: The FerrDb database and the previous studies were screened to explore the FRGs. The data of patients with IPF were obtained from the GSE70866 dataset. Wilcoxon's test and univariate Cox regression analysis were applied to identify the FRGs that are differentially expressed between normal and patients with IPF and associated with prognosis. Next, a multigene signature was constructed by the least absolute shrinkage and selection operator (LASSO)-penalized Cox model in the training cohort and evaluated by using calibration and receiver operating characteristic (ROC) curves. Then, 30% of the dataset samples were randomly selected for internal validation. Finally, the potential function and pathways that might be affected by the risk score-related differently expressed genes (DEGs) were further explored. Results: A total of 183 FRGs were identified by the FerrDb database and the previous studies, and 19 of them were differentially expressed in bronchoalveolar lavage fluid (BALF) between IPF and healthy controls and associated with prognosis (p < 0.05). There were five FRGs (aconitase 1 [ACO1], neuroblastoma RAS viral (v-ras) oncogene homolog [NRAS], Ectonucleotide pyrophosphatase/phosphodiesterase 2 [ENPP2], Mucin 1 [MUC1], and ZFP36 ring finger protein [ZFP36]) identified as risk signatures and stratified patients with IPF into the two risk groups. The overall survival rate in patients with high risk was significantly lower than that in patients with low risk (p < 0.001). The calibration and ROC curve analysis confirmed the predictive capacity of this signature, and the results were further verified in the validation group. Risk score-related DEGs were found enriched in ECM-receptor interaction and focal adhesion pathways. Conclusion: The five FRGs in BALF can be used for prognostic prediction in IPF, which may contribute to improving the management strategies of IPF.

Project description:Gliomas are the most common primary intracranial tumors and closely related to circadian clock. Due to the high mortality and morbidity of gliomas, exploring novel diagnostic and early prognostic markers is necessary. Circadian clock genes (CCGs) play important roles in regulating the daily oscillation of biological processes and the development of tumor. Therefore, we explored the influences that the oscillations of circadian clock genes (CCGs) on diagnosis and prognosis of gliomas using bioinformatics. In this work, we systematically analyzed the rhythmic expression of CCGs in brain and found that some CCGs had strong rhythmic expression; the expression levels were significantly different between day and night. Four CCGs (ARNTL, NPAS2, CRY2, and DBP) with rhythmic expression were not only identified as differentially expressed genes but also had significant independent prognostic ability in the overall survival of glioma patients and were highly correlated with glioma prognosis in COX analysis. Besides, we found that CCG-based predictive model demonstrated higher predictive accuracy than that of the traditional grade-based model; this new prediction model can greatly improve the accuracy of glioma prognosis. Importantly, based on the four CCGs' circadian oscillations, we revealed that patients sampled at night had higher predictive ability. This may help detect glioma as early as possible, leading to early cancer intervention. In addition, we explored the mechanism of CCGs affecting the prognosis of glioma. CCGs regulated the cell cycle, DNA damage, Wnt, mTOR, and MAPK signaling pathways. In addition, it also affects prognosis through gene coexpression and immune infiltration. Importantly, ARNTL can rhythmically modulated the cellular sensitivity to clinic drugs, temozolomide. The optimal point of temozolomide administration should be when ARNTL expression is highest, that is, the effect is better at night. In summary, our study provided a basis for optimizing clinical dosing regimens and chronotherapy for glioma. The four key CCGs can serve as potential diagnostic and prognostic biomarkers for glioma patients, and ARNTL also has obvious advantages in the direction of glioma chronotherapy.

Dataset Information

Ferroptosis-related NFE2L2 and NOX4 Genes are Potential Risk Prognostic Biomarkers and Correlated with Immunogenic Features in Glioma.

Publications

Ferroptosis-related NFE2L2 and NOX4 Genes are Potential Risk Prognostic Biomarkers and Correlated with Immunogenic Features in Glioma.

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