A <scp>pyroptosis‐related</scp> signature predicts prognosis and indicates immune microenvironment infiltration in glioma

Chen, Jia; Chen, Shanwei; Li, Bingxian; Zhou, Shaojiong; Lin, Han

doi:10.1002/cam4.5247

Cited by 5 publications

(6 citation statements)

References 64 publications

(123 reference statements)

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“…The performance of our prognostic model was compared with partially existing risk models using respective formulas in CGGA301 cohort (Supplementary Figure 5). AUCs and Cindex showed that our three-gene prognostic model achieved similarly great predictive performance compared with existing models (16)(17)(18). Despite the presence of higher accuracy in other models, their models contained more genes and lack of samples validation, which restricted the clinical applications (15,19).…”

Section: Discussionmentioning

confidence: 93%

“…Currently, numerous prognostic models based on specific hallmark have been developed in glioma, but most of them contain more genes and lack of validation of clinical samples. Real clinical samples validation was usually confined in the level of gene expression, rather than the prognostic model, which actually do not have enough persuasion (15)(16)(17)(18)(19). In this study, we constructed a necroptosis-related prognostic model that comprised of three genes (EZH2, LEF1 and CASP1).…”

Section: Discussionmentioning

confidence: 99%

“…Although numerous prognostic models for glioma have been developed, most of them contain more genes. Real clinical samples validation was usually confined in the level of gene expression, rather than the prognostic model, which actually do not have enough persuasion (15)(16)(17)(18)(19).…”

Section: Introductionmentioning

confidence: 99%

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A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma

Yuan

Jin²,

Chen³

et al. 2022

Front. Immunol.

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BackgroundGlioma is a highly aggressive brain cancer with a poor prognosis. Necroptosis is a form of programmed cell death occurring during tumor development and in immune microenvironments. The prognostic value of necroptosis in glioma is unclear. This study aimed to develop a prognostic glioma model based on necroptosis.MethodsA necroptosis-related risk model was constructed by Cox regression analysis based on The Cancer Genome Atlas (TCGA) training set, validated in two Chinese Glioma Genome Atlas (CGGA) validation sets. We explored the differences in immune infiltration and immune checkpoint genes between low and high risk groups and constructed a nomogram. Moreover, we compiled a third validation cohort including 43 glioma patients. The expression of necroptosis-related genes was verified in matched tissues using immunochemical staining in the third cohort, and we analyzed their relationship to clinicopathological features.ResultsThree necroptosis-related differentially expressed genes (EZH2, LEF1, and CASP1) were selected to construct the prognostic model. Glioma patients with a high risk score in the TCGA and CGGA cohorts had significantly shorter overall survival. The necroptosis-related risk model and nomogram exhibited good predictive performance in the TCGA training set and the CGGA validation sets. Furthermore, patients in the high risk group had higher immune infiltration status and higher expression of immune checkpoint genes, which was positively correlated with poorer outcomes. In the third validation cohort, the expression levels of the three proteins encoded by EZH2, LEF1, and CASP1 in glioma tissues were significantly higher than those from paracancerous tissues. They were also closely associated with disease severity and prognosis.ConclusionsOur necroptosis-related risk model can be used to predict the prognosis of glioma patients and improve prognostic accuracy, which may provide potential therapeutic targets and a theoretical basis for treatment.

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Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

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A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma

Yuan

Jin²,

Chen³

et al. 2022

Front. Immunol.

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“…And interestingly, the results indicated that glioma therapeutic response and immunosuppressive microenvironment are associated with high-risk scores. Previous studies have constructed multiple predictive signature to predict OS of gliomas, including aging-related genes signature [57] , chemokine-based signature [58] , and pyroptosis-related signature [59] . We compared the performance of these risk signatures with our FARGS using a previously reported method [60] .…”

Section: Discussionmentioning

confidence: 99%

A prognostic gene signature based on focal adhesion related genes for gliomas and identification of the role of RAP1B in glioma progression

Wang,

Zhou,

Wang

et al. 2023

Preprint

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Background The most common malignant primary brain tumor in adults is the gliomas, characterized by extremely variable overall survival (OS) for patients. Although it has been found that focal adhesion genes are associated with clinical prognosis in glioma patients, this marker is rarely used clinically. Methods We systematically characterized mRNA expression of focal adhesion related genes in gliomas and explored their expression signature based on 938 samples from TCGA dataset and CGGA dataset. Glioma samples were clustered using mRNA expression of focal adhesion genes using an unsupervised clustering method. Subsequently, based on prognosis-associated genes, the focal adhesion related gene signature (FARGS) was constructed by least absolute shrinkage and selection operator (LASSO) Cox regression. Additionally, multiple bioinformatics methods were used to examine the value of FARGS in predicting patient outcomes, clinical features, oncogenic pathways, tumor immune microenvironment and drug response. Furthermore, in vitro and in vivo experiments were conducted to validate the role of RAP1B in U87 glioma cells. Results According to LASSO Cox regression analysis, a 9-FARG signature was found to be strongly linked with OS in glioma patients, characterized by a high-risk and a low-risk score pattern. The FARGS was found to be tightly linked with malignant molecular biomarkers, including IDH wild-type, unmethylated MGMTp, and non-codeletion of 1p19q. Furthermore, the high-risk group exhibited an enrichment of multiple oncogenic biological pathways. Interestingly, the results presented that the FARGS has a strong association with therapeutic response and tumor immunosuppressive microenvironment in gliomas, including immune infiltrations of M2-type macrophages, MDSCs and Tregs, and elevated immunosuppressors’ mRNA expression. Lastly, the oncogenic role of RAP1B in U87 glioma cells was also functionally confirmed. Conclusions In conclusion, we reported a novel FARGS with promising survival prediction for glioma patients, as well as confirmation of RAP1B's oncogenic role.

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“…Clinical data also show that glioma patients expressing high level of pyroptosis-related genes(PRGs) have worse outcomes and are at greater risk of metastasis [37]. Moreover, compared to low-grade gliomas, high-grade gliomas have higher expression of PRGs probably associated with their malignant progression [38].…”

Section: Long-term Chronic Inflammation Modulates the Tmementioning

confidence: 99%

Programmed cell death disrupts inflammatory tumor microenvironment (TME) and promotes glioblastoma evolution

Liang,

Gu,

Kang

et al. 2024

Cell Commun Signal

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Glioblastoma (GBM) is the most common malignant brain tumor and has a dismal prognosis even under the current first-line treatment, with a 5-year survival rate less than 7%. Therefore, it is important to understand the mechanism of treatment resistance and develop new anti-tumor strategies. Induction of programmed cell death (PCD) has become a promising anti-tumor strategy, but its effectiveness in treating GBM remains controversial. On the one hand, PCD triggers tumor cell death and then release mediators to draw in immune cells, creating a pro-inflammatory tumor microenvironment (TME). One the other hand, mounting evidence suggests that PCD and inflammatory TME will force tumor cells to evolve under survival stress, leading to tumor recurrence. The purpose of this review is to summarize the role of PCD and inflammatory TME in the tumor evolution of GBM and promising methods to overcome tumor evolution.

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A pyroptosis‐related signature predicts prognosis and indicates immune microenvironment infiltration in glioma

Cited by 5 publications

References 64 publications

A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma

A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma

A prognostic gene signature based on focal adhesion related genes for gliomas and identification of the role of RAP1B in glioma progression

Programmed cell death disrupts inflammatory tumor microenvironment (TME) and promotes glioblastoma evolution

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