Development and validation of cuproptosis-associated prognostic signatures in WHO 2/3 glioma

Ye, Zhang; Zhang, Shenqi; Cai, Jiayang; Ye, Liguo; Gao, Lun; Wang, Yixuan; Tong, Shiao; Sun, Qian; Wu, Yu; Xiong, Xiao-Qing; Chen, Qianxue

doi:10.3389/fonc.2022.967159

Cited by 15 publications

(15 citation statements)

References 20 publications

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“…CKGs have different roles among different tumors. DLD was considered as a risk factor in studies of different tumors such as uveal melanoma(UVM), glioma, and LUAD [ 129 , 139 , 143 , 183 ]. In contrast, LIAS was analyzed as a protective factor in studies of UVM, glioma, and pancreatic adenocarcinoma(PAAD) [ 139 , 142 , 156 – 158 ].…”

Section: Introductionmentioning

confidence: 99%

Cuproptosis: mechanisms and links with cancers

et al. 2023

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Cuproptosis was a copper-dependent and unique kind of cell death that was separate from existing other forms of cell death. The last decade has witnessed a considerable increase in investigations of programmed cell death, and whether copper induced cell death was an independent form of cell death has long been argued until mechanism of cuproptosis has been revealed. After that, increasing number of researchers attempted to identify the relationship between cuproptosis and the process of cancer. Thus, in this review, we systematically detailed the systemic and cellular metabolic processes of copper and the copper-related tumor signaling pathways. Moreover, we not only focus on the discovery process of cuproptosis and its mechanism, but also outline the association between cuproptosis and cancers. Finally, we further highlight the possible therapeutic direction of employing copper ion ionophores with cuproptosis-inducing functions in combination with small molecule drugs for targeted therapy to treat specific cancers.

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Section: Introductionmentioning

confidence: 99%

Cuproptosis: mechanisms and links with cancers

et al. 2023

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“…In addition, the researchers preliminarily identified 12 CRGs, such as CDKN2A, PDHB, GLS, LIPT1, FDX1, DLD, MTF1, ATP7B, LIAS, DLAT, PDHA1, and SLC31A1 ( 3 ). In the past several months, prognostic models based on cuproptosis have been published in many kinds of tumors, such as head and neck squamous cell carcinoma ( 4 ), triple-negative breast cancer ( 5 ), lung adenocarcinoma ( 6 ), renal clear cell carcinoma ( 7 ), melanoma ( 8 ), hepatocellular carcinoma ( 9 ), and low-grade glioma ( 10 ), which accurately predict prognosis, tumor immune microenvironment, and response to chemotherapy or immunotherapy. However, no cuproptosis-related prognostic model has been reported in GBM.…”

Section: Introductionmentioning

confidence: 99%

“…In glioma, Wang et al developed a cuproptosis-related-model in light of six genes, including H19, CHI3L1, CYTOR, IGFBP2, and C5orf38, and its 1-year AUC value was 0.898 (24). research has been reported in low-grade glioma (25) and WHO 2/3 glioma(10). However, no cuproptosis-related prognostic model has been reported in GBM.…”

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confidence: 99%

Construction and validation of a cuproptosis-related prognostic model for glioblastoma

Zhang

Xie²,

Liu³

et al. 2023

Front. Immunol.

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BackgroundCuproptosis, a newly reported type of programmed cell death, takes part in the regulation of tumor progression, treatment response, and prognosis. But the specific effect of cuproptosis-related genes (CRGs) on glioblastoma (GBM) is still unclear.MethodsThe transcriptome data and corresponding clinical data of GBM samples were downloaded from the TCGA and GEO databases. R software and R packages were used to perform statistical analysis, consensus cluster analysis, survival analysis, Cox regression analysis, Lasso regression analysis, and tumor microenvironment analysis. The mRNA and protein expression levels of model-related genes were detected by RT-qPCR and Western blot assays, respectively.ResultsThe expression profile of CRGs in 209 GBM samples from two separate datasets was obtained. Two cuproptosis subtypes, CRGcluster A and CRGcluster B, were identified by consensus cluster analysis. There were apparent differences in prognosis, tumor microenvironment, and immune checkpoint expression levels between the two subtypes, and there were 79 prognostic differentially expressed genes (DEGs). According to the prognostic DEGs, two gene subtypes, geneCluster A and geneCluster B, were identified, and a prognostic risk score model was constructed and validated. This model consists of five prognostic DEGs, including PDIA4, DUSP6, PTPRN, PILRB, and CBLN1. Ultimately, to improve the applicability of the model, a nomogram was established. Patients with GBM in the low-risk cluster have a higher mutation burden and predict a longer OS than in the high-risk group. Moreover, the risk score was related to drug sensitivity and negatively correlated with the CSC index.ConclusionWe successfully constructed a cuproptosis-related prognostic model, which can independently predict the prognosis of GBM patients. These results further complement the understanding of cuproptosis and provide new theoretical support for developing a more effective treatment strategy.

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“…In addition, the expression level of FDX1 was confirmed to be closely related to immune infiltration ( 75 ). Zhang Y. et al found that FDX1 is an independent prognostic factor and potential prognostic biomarker of WHO grade II/III glioma ( 76 ). Wang X et al found that the high expression of FDX1 was significantly correlated with the overall survival rate of Renal Cell Carcinoma (RCC) ( p < 0.05).…”

Section: Discussionmentioning

confidence: 99%

Cuproptosis key gene FDX1 is a prognostic biomarker and associated with immune infiltration in glioma

Zhou

Zhang

et al. 2022

Front. Med.

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Recent studies have found that the protein encoded by the FDX1 gene is involved in mediating Cuproptosis as a regulator of protein lipoylation and related to immune response process of tumors. However, the specific biological function of FDX1 in glioma is currently unclear. To explore the potential function of FDX1, this study explored the correlation between the expression of FDX1 in cancers and survival prognosis by analyzing the public databases of GEPIA and Cbioportal. Immune infiltration was analyzed by the TIMER2.0 database in tumors. The possible biological processes and functions of FDX1-related in glioma were annotated through gene enrichment. Relationship between Cuproptosis and autophagy was explored through gene co-expression studies. Summary and conclusions of this study: (1) FDX1 is highly expressed in gliomas and associated with poor prognosis in low-grade gliomas (LGG). (2) Gene annotation indicates that FDX1 is mainly involved in the tumor protein lipoylation and cell death. (3) FDX1 expression is positively correlated with the infiltration of immune cells. (4) LIPT2 and NNAT, two other genes involved in lipoylation, may be unidentified marker gene for Cuproptosis. And the Cuproptosis genes related to FDX1 were positively correlated with the expression of autophagy marker genes Atg5, Atg12, and BECN-1. This evidence suggests that there may be some interaction between FDX1 mediated Cuproptosis and autophagy. In summary, FDX1 may serve as a potential immunotherapy target and prognostic marker for Glioma.

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Development and validation of cuproptosis-associated prognostic signatures in WHO 2/3 glioma

Cited by 15 publications

References 20 publications

Cuproptosis: mechanisms and links with cancers

Cuproptosis: mechanisms and links with cancers

Construction and validation of a cuproptosis-related prognostic model for glioblastoma

Cuproptosis key gene FDX1 is a prognostic biomarker and associated with immune infiltration in glioma

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