The Non-N6-Methyladenosine Epitranscriptome Patterns and Characteristics of Tumor Microenvironment Infiltration and Mesenchymal Transition in Glioblastoma

Xu, Jianye; Gao, Zijie; Liu, Kaining; Fan, Yan; Zhang, Zongpu; Xue, Hao; Guo, Xing; Zhang, Ping; Deng, Lin; Wang, Shaobo; Wang, Huizhi; Wang, Qingtong; Zhao, Rongrong; Li, Gang

doi:10.3389/fimmu.2021.809808

Cited by 12 publications

(11 citation statements)

References 86 publications

(89 reference statements)

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“…In pathologic analysis, we found that HGGs had higher KDELR1 expression than LGGs. In addition, previous studies (35)(36)(37) have demonstrated that mesenchymal-subtype gliomas are associated with poor prognosis, which are confirmed by our finding that mesenchymal -subtype gliomas had a higher expression level of KDELR1 than proneural subtype gliomas. Subsequently, we further explored whether the expression of KDELR1 is related to recurrence.…”

Section: Discussionsupporting

confidence: 90%

KDELR1 Is an Independent Prognostic Predictor and Correlates With Immunity in Glioma

Yuan

Yang²,

Qi³

et al. 2022

Front. Oncol.

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BackgroundGliomas are the most malignant central nervous system tumors. With the development of sequencing technology, more potential biomarkers related to the treatment, prognosis, and molecular classification of glioma have been identified. Here, we intend to investigate the potential biological function and clinical value of a new biomarker in glioma.MethodsKDELR1 expression data and the corresponding clinical information were downloaded from public databases and then preprocessed using R language. Correlation, Kaplan–Meier survival, and Cox regression analyses were performed to explore the clinical significance of KDELR1 in glioma patients. Furthermore, the immune infiltration and microenvironment parameters were evaluated via TIMER and CIBERSORT. Immunohistochemistry was conducted to confirm the KDELR1 expression and its correlation with immunity infiltration and prognosis.ResultsKDELR1 was upregulated in glioma samples compared with normal brain tissues, and its expression was significantly correlated with age, the World Health Organization (WHO) grade, recurrence, necrosis, microvascular proliferation, molecular classification, isocitrate dehydrogenase (IDH) mutation, and 1p/19q codeletion status. In addition, survival analysis showed that glioma patients with KDELR1 overexpression had shorter overall survival (OS) and disease-free survival times, and Cox regression analysis revealed that KDELR1 acted as an independent prognostic factor of OS in glioma patients. Gene set enrichment analysis indicated a significant enrichment of metabolism-associated pathways. KDELR1 expression was positively associated with immune infiltration (including infiltration by CD8+ T cells, CD4+ T cells, macrophages, and so on) and microenvironment parameters (including stromal, immune, and ESTIMATE scores) in gliomas. The expression of KDELR1 and its correlation with the tumor grade and prognosis were confirmed by immunohistochemistry in clinical samples (n = 119, P < 0.05).ConclusionsTaken together, these findings suggest that KDELR1 is correlated with the tumor grade, molecular classifications, and immune infiltration; highlighting that KDELR1 is a novel and promising biomarker for molecular classification, treatment, and prognostic assessment may further indicate the treating effect of immune therapy.

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Section: Discussionsupporting

confidence: 90%

KDELR1 Is an Independent Prognostic Predictor and Correlates With Immunity in Glioma

Yuan

Yang²,

Qi³

et al. 2022

Front. Oncol.

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“…Generally, M1-type macrophages play pro-inflammatory and anti-tumor functions, but tumor-associated macrophages (TAMs) in the TME are M2-type. Xu et al (2021a) elucidated the mechanism by which hypoxia and glioma affected autophagy and M2-like macrophage polarization through exosomes, thereby promoting the formation of an immunosuppressive microenvironment.…”

Section: Discussionmentioning

confidence: 99%

“…There are over 150 known RNA modifications, which include N6-methyladenosine (m6A), N7-methylguanosine (m7G), 5-methylcytidine (m5C), pseudouridine (Ψ), N6,2′-O-dimethyladenosine (m6Am), N1-methyladenosine (m1A), alternative polyadenylation (APA), 2′-O-methylated nucleotides (Nm), N4-acetylcytidine (ac4C), adenosine-to-inosine RNA editing (I), and cytidine-to-uridine RNA editing (U), all of which contribute to normal development and homeostasis and their dysregulation is known to cause various diseases including cancer ( Boccaletto et al, 2022 ; Zhao et al, 2017b ; Frye et al, 2018 ; Roundtree et al, 2017 ; Barbieri et al, 2017 ; Barbieri and Kouzarides, 2020 ). Previous studies have focused more on m6A, one of the most common modified forms in eukaryotic cells, which have been demonstrated to play a role in embryogenesis, neurogenesis, hematopoiesis, and tumorigenesis in some studies ( Zhao et al, 2017a ; Zhang et al, 2017 ; Barbieri et al, 2017 ; Xu et al, 2021a ). However, in recent years, modifications in non-m6A forms have also attracted increasing attention.…”

Section: Introductionmentioning

confidence: 99%

Integrative pan-cancer analysis and clinical characterization of the N7-methylguanosine (m7G) RNA modification regulators in human cancers

Zhang

Zhu

et al. 2022

Front. Genet.

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Background: RNA modification is one of the epigenetic mechanisms that regulates post-transcriptional gene expression, and abnormal RNA modifications have been reported to play important roles in tumorigenesis. N7-methylguanosine (m7G) is an essential modification at the 5′ cap of human mRNA. However, a systematic and pan-cancer analysis of the clinical relevance of m7G related regulatory genes is still lacking.Methods: We used univariate Cox model and Kaplan-Meier analysis to generate the forest plot of OS, PFI, DSS and identified the correlation between the altered expression of m7G regulators and patient survival in 33 cancer types from the TCGA and GTEx databases. Then, the “estimate” R-package, ssGSEA and CIBERSORT were used to depict the pan-cancer immune landscape. Through Spearman’s correlation test, we analyzed the correlation between m7G regulators and the tumor microenvironment (TME), immune subtype, and drug sensitivity of the tumors, which was further validated in NSCLC. We also assessed the changes in the expression of m7G related regulatory genes in NSCLC with regards to the genetic and transcriptional aspects and evaluated the correlation of METTL1 and WDR4 expression with TMB, MSI and immunotherapy in pan-cancer.Results: High expression of most of the m7G regulators was significantly associated with worse prognosis. Correlation analyses revealed that the expression of majority of the m7G regulators was correlated with tumor immune infiltration and tumor stem cell scores. Drug sensitivity analysis showed that the expression of CYFP1,2 was closely related to drug sensitivity for various anticancer agents (p < 0.001). Analysis of the pan-cancer immune subtype revealed significant differences in the expression of m7G regulators between different immune subtypes (p < 0.001). Additionally, the types and proportions of mutations in METTL1 and WDR4 and their relevance to immunotherapy were further described.Conclusion: Our study is the first to evaluate the correlation between the altered expression of m7G regulators and patient survival, the degree of immune infiltration, TME and drug sensitivity in pan-cancer datasets.

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“…Under normal circumstances, it is now widely accepted that immune cells in the tumor microenvironment (TME) can distinguish and eradicate cancer cells, which is referred to as immunosurveillance ( 12 , 14 ). However, cancer cells can modulate the host immune system to evade immune surveillance by recruiting immunosuppressive cell populations and downregulating tumor immunogenicity ( 15 , 16 ). Stemness is used to evaluate the similarity of tumor cells to stem cells ( 17 ).…”

Section: Introductionmentioning

confidence: 99%

Identification and validation of an anoikis-associated gene signature to predict clinical character, stemness, IDH mutation, and immune filtration in glioblastoma

et al. 2022

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BackgroundGlioblastoma (GBM) is the most prominent and aggressive primary brain tumor in adults. Anoikis is a specific form of programmed cell death that plays a key role in tumor invasion and metastasis. The presence of anti-anoikis factors is associated with tumor aggressiveness and drug resistance.MethodsThe non-negative matrix factorization algorithm was used for effective dimension reduction for integrated datasets. Differences in the tumor microenvironment (TME), stemness indices, and clinical characteristics between the two clusters were analyzed. Difference analysis, weighted gene coexpression network analysis (WGCNA), univariate Cox regression, and least absolute shrinkage and selection operator regression were leveraged to screen prognosis-related genes and construct a risk score model. Immunohistochemistry was performed to evaluate the expression of representative genes in clinical specimens. The relationship between the risk score and the TME, stemness, clinical traits, and immunotherapy response was assessed in GBM and pancancer.ResultsTwo definite clusters were identified on the basis of anoikis-related gene expression. Patients with GBM assigned to C1 were characterized by shortened overall survival, higher suppressive immune infiltration levels, and lower stemness indices. We further constructed a risk scoring model to quantify the regulatory patterns of anoikis-related genes. The higher risk score group was characterized by a poor prognosis, the infiltration of suppressive immune cells and a differentiated phenotype, whereas the lower risk score group exhibited the opposite effects. In addition, patients in the lower risk score group exhibited a higher frequency of isocitrate dehydrogenase (IDH) mutations and a more sensitive response to immunotherapy. Drug sensitivity analysis was performed, revealing that the higher risk group may benefit more from drugs targeting the PI3K/mTOR signaling pathway.ConclusionWe revealed potential relationships between anoikis-related genes and clinical features, TME, stemness, IDH mutation, and immunotherapy and elucidated their therapeutic value.

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The Non-N6-Methyladenosine Epitranscriptome Patterns and Characteristics of Tumor Microenvironment Infiltration and Mesenchymal Transition in Glioblastoma

Cited by 12 publications

References 86 publications

KDELR1 Is an Independent Prognostic Predictor and Correlates With Immunity in Glioma

KDELR1 Is an Independent Prognostic Predictor and Correlates With Immunity in Glioma

Integrative pan-cancer analysis and clinical characterization of the N7-methylguanosine (m7G) RNA modification regulators in human cancers

Identification and validation of an anoikis-associated gene signature to predict clinical character, stemness, IDH mutation, and immune filtration in glioblastoma

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