Establishment and Validation of a 5 m6A RNA Methylation Regulatory Gene Prognostic Model in Low-Grade Glioma

Bai, Zhiqun; Wang, Xuemei; Zhang, Zhen

doi:10.3389/fgene.2022.655169

Cited by 8 publications

(5 citation statements)

References 56 publications

(56 reference statements)

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“…Moreover, some m6A based risk score models have also been proposed for predicting the prognosis of glioma patients 32 , 33 . Recently, m6A methylation regulatory genes have been used to classify patients with low-grade gliomas into high- or low-risk subgroups 34 . Similarly, the m6A-related microRNA risk model has been used as a predictive biomarker for prognosis and immunotherapy in low-grade gliomas 35 .…”

Section: Discussionmentioning

confidence: 99%

Systematic integration of m6A regulators and autophagy-related genes in combination with long non-coding RNAs predicts survival in glioblastoma multiforme

Sharma,

Wang,

et al. 2023

Sci Rep

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Glioblastoma multiforme (GBM) is probably the only tumor in which a unique epigenetic alteration, namely methylation of the MGMT gene, possesses direct clinical relevance. Now with the emergence of aberrant N6 methyladenosine (m6A) modifications (the most common epigenetic modification of mRNA, closely linked to the autophagy process) in cancer, the epi-transcriptomic landscape of GBM pathobiology has been expanded. Considering this, herein, we systematically analyzed m6A regulators, assessed their correlation with autophagy-related genes (ATG), and established a long non-coding RNAs (lncRNA)-dependent prognostic signature (m6A-autophagy-lncRNAs) for GBM. Our analysis identified a novel signature of five long non-coding RNAs (lncRNAs: ITGA6-AS1, AC124248.1, NFYC-AS1, AC025171.1, and AC005229.3) associated with survival of GBM patients, and four among them clearly showed cancer-associated potential. We further validated and confirmed the altered expression of two lncRNAs (AC124248.1, AC005229.3) in GBM associated clinical samples using RT-PCR. Concerning the prognostic ability, the obtained signature determined high-/low-risk groups in GBM patients and showed sensitivity to anticancer drugs. Collectively, the m6A-autophagy-lncRNAs signature presented in the study is clinically relevant and is the first attempt to systematically predict the potential interaction between the three key determinants (m6A, autophagy, lncRNA) in cancer, particularly in GBM.

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Section: Discussionmentioning

confidence: 99%

Systematic integration of m6A regulators and autophagy-related genes in combination with long non-coding RNAs predicts survival in glioblastoma multiforme

Sharma,

Wang,

et al. 2023

Sci Rep

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“…The specific role of cuproptosis in LGG remains unclear. Furthermore, although many prognostic signatures have been established based on the patterns of pseudogenes ( 43 ), N6-methylandenosine ( 44 ), immunity ( 45 ), ferroptosis ( 46 ), and pyroptosis ( 47 ) their predictive ability needs to be further improved, and there is still a lack of a prognostic signature based on the characteristics of cuproptosis. In the present study, we systematically investigated the global alterations in 13 CRGs at genetic and transcriptional levels in LGG, established a scoring system consisting of five signature core genes, and eventually constructed a quantitative nomogram by integrating the CRG score and clinicopathological features including grades, IDH status, and age.…”

Section: Discussionmentioning

confidence: 99%

Identification of a novel cuproptosis-related gene signature and integrative analyses in patients with lower-grade gliomas

Bao

Duan

et al. 2022

Front. Immunol.

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BackgroundCuproptosis is a newly discovered unique non-apoptotic programmed cell death distinguished from known death mechanisms like ferroptosis, pyroptosis, and necroptosis. However, the prognostic value of cuproptosis and the correlation between cuproptosis and the tumor microenvironment (TME) in lower-grade gliomas (LGGs) remain unknown.MethodsIn this study, we systematically investigated the genetic and transcriptional variation, prognostic value, and expression patterns of cuproptosis-related genes (CRGs). The CRG score was applied to quantify the cuproptosis subtypes. We then evaluated their values in the TME, prognostic prediction, and therapeutic responses in LGG. Lastly, we collected five paired LGG and matched normal adjacent tissue samples from Sun Yat-sen University Cancer Center (SYSUCC) to verify the expression of signature genes by quantitative real-time PCR (qRT-PCR) and Western blotting (WB).ResultsTwo distinct cuproptosis-related clusters were identified using consensus unsupervised clustering analysis. The correlation between multilayer CRG alterations with clinical characteristics, prognosis, and TME cell infiltration were observed. Then, a well-performed cuproptosis-related risk model (CRG score) was developed to predict LGG patients’ prognosis, which was evaluated and validated in two external cohorts. We classified patients into high- and low-risk groups according to the CRG score and found that patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (P<0.001). A high CRG score implies higher TME scores, more significant TME cell infiltration, and increased mutation burden. Meanwhile, the CRG score was significantly correlated with the cancer stem cell index, chemoradiotherapy sensitivity–related genes and immune checkpoint genes, and chemotherapeutic sensitivity, indicating the association with CRGs and treatment responses. Univariate and multivariate Cox regression analyses revealed that the CRG score was an independent prognostic predictor for LGG patients. Subsequently, a highly accurate predictive model was established for facilitating the clinical application of the CRG score, showing good predictive ability and calibration. Additionally, crucial CRGs were further validated by qRT-PCR and WB.ConclusionCollectively, we demonstrated a comprehensive overview of CRG profiles in LGG and established a novel risk model for LGG patients’ therapy status and prognosis. Our findings highlight the potential clinical implications of CRGs, suggesting that cuproptosis may be the potential therapeutic target for patients with LGG.

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“…Tan et al looked at immune-related genes in LGG and discovered six genetic markers that could help diagnose LGG and predict patient prognoses (11). Bai et al examined N6-adenosine methylation (m6A) methylation-regulated genes in LGG and built a prognostic model based on their findings, to improve prognosis prediction accuracy in LGG patients (12).…”

Section: Introductionmentioning

confidence: 99%

“…Bai et al. examined N6-adenosine methylation (m6A) methylation-regulated genes in LGG and built a prognostic model based on their findings, to improve prognosis prediction accuracy in LGG patients ( 12 ). Using Cox regression analysis, Liu et al.…”

Section: Introductionmentioning

confidence: 99%

Establishment of three heterogeneous subtypes and a risk model of low-grade gliomas based on cell senescence-related genes

Chen

Yang

et al. 2022

Front. Immunol.

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BackgroundCellular senescence is a key element in the occurrence and progression of a variety of tumors. As a result, cellular senescence-related markers can be categorized based on the prognosis status of patients. Due to the heterogeneity and the complexity of the tumor microenvironment (TME), the long-term effectiveness of low-grade glioma (LGG) treatment remains a clinical challenge. Consequently, developing and refining effective treatment approaches to aid with LGG management is critical.MethodsBased on the expressions of cell senescence-related genes (CSRGs) acquired from the cellAge database, consensus clustering was utilized to identify stable molecular subtypes. Clinical features, immune infiltration, route modifications, and genetic changes of various subtypes were also assessed. Following that, the least absolute shrinkage and selection operator (LASSO) regression and univariate Cox regression analysis were used for developing the cell senescence-related risk score (CSRS) model. Finally, a correlation study of the CSRS model with molecular, immunological, and immunotherapy parameters was performed.ResultsC1, C2, and C3, are the three senescence-related subtypes that were identified. Patients belonging to the C1 subtype had poor prognoses and a substantial proportion of them was in the grade G3. The differentially expressed genes (DEGs) among the three subtypes were used to develop the CSRS model. In both the training and independent validation cohort, the model had a high area under the receiver operating characteristic (ROC) curve in predicting the overall survival (OS) of patients. As a result, this model can predict clinical features and responses to immunotherapy in a variety of patients and it is a potential independent prognostic factor for LGG.ConclusionThis research discovered three LGG subtypes related to cell senescence and created a CSRS model for six genes. Cell senescence was highly associated with unfavorable prognosis in LGG. The CSRS model can be used to predict the prognosis of patients and identify patients who would benefit from immunotherapy.

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Establishment and Validation of a 5 m6A RNA Methylation Regulatory Gene Prognostic Model in Low-Grade Glioma

Cited by 8 publications

References 56 publications

Systematic integration of m6A regulators and autophagy-related genes in combination with long non-coding RNAs predicts survival in glioblastoma multiforme

Systematic integration of m6A regulators and autophagy-related genes in combination with long non-coding RNAs predicts survival in glioblastoma multiforme

Identification of a novel cuproptosis-related gene signature and integrative analyses in patients with lower-grade gliomas

Establishment of three heterogeneous subtypes and a risk model of low-grade gliomas based on cell senescence-related genes

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