m6A RNA methylation regulators contribute to malignant progression and have clinical prognostic impact in gliomas

Transcription Factor TFAP2B Exerts Neuroprotective Effects Targeting BNIP3-Mediated Mitophagy in Ischemia/Reperfusion Injury

Cerebral ischemia-reperfusion injury (CIRI) leads to malignant brain edema, blood-brain barrier destruction, and neuronal apoptosis. N6-methyladenosine (m6A) RNA modification in CIRI was still limited explored. In this study, MeRIP- and RNA-sequencing were performed of middle cerebral artery occlusion and reperfusion (MCAO/R) rats to find novel potential molecular targets. Transcription factor TFAP2B stood out of which its m6A abundance decreased associated with a marked reduction of its mRNA based on cojoint interactive bioinformatics analysis of the MeRIP- and RNA-sequencing data. It was suggested TFAP2B could have a role in CIRI. Functionally, overexpression of TFAP2B in cultured primary neurons could effectively improve the cell survival and pro-survival autophagy in parallel with reduced cell apoptosis during OGD/R in vitro. Through the RNA-sequencing of TFAP2B overexpressed primary neurons and subsequent validation experiments, it was found that mitophagy receptor BNIP3 was one of the important targets of TFAP2B in OGD/R neurons through which TFAP2B could bind to its promoter region for transcriptional activation of BNIP3, thereby enhancing BNIP3-mediated mitophagy to protect against OGD/R injury of neurons. Lastly, TFAP2B was demonstrated to alleviate the MCAO/R damage to a certain extent in vivo. Although it failed to confirm TFAP2B dysregulation was m6A dependent in current research, this is the first research of TFAP2B in CIRI field with important guiding significance.

Unveiling the role of RNA methylation in glioma: Mechanisms, prognostic biomarkers, and therapeutic targets

Gliomas, the most prevalent malignant brain tumors in the central nervous system, are marked by rapid growth, high recurrence rates, and poor prognosis. Glioblastoma (GBM) stands out as the most aggressive subtype, characterized by significant heterogeneity. The etiology of gliomas remains elusive. RNA modifications, particularly reversible methylation, play a crucial role in regulating transcription and translation throughout the RNA lifecycle. Increasing evidence highlights the prevalence of RNA methylation in primary central nervous system malignancies, underscoring its pivotal role in glioma pathogenesis. This review focuses on recent findings regarding changes in RNA methylation expression and their effects on glioma development and progression, including N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1-methyladenosine (m1A), and N7-methylguanosine (m7G). Given the extensive roles of RNA methylation in gliomas, the potential of RNA methylation-related regulators as prognostic markers and therapeutic targets was also explored, aiming to enhance clinical management and improve patient outcomes.

UBE2D3 regulated by WTAP-mediated m6A modification inhibits temozolomide chemosensitivity in glioblastoma

To explore how the ubiquitin-conjugating enzyme E2D3 (UBE2D3) influences temozolomide (TMZ) resistance in glioblastoma (GBM), and to clarify the association between UBE2D3 and WTAP. The UBE2D3 protein expression in GBM tissues were detected using immunohistochemistry (IHC) through tissue microarrays. The potential pathways of UBE2D3 in TCGA-GBM were predicted via Gene Set Enrichment Analysis (GSEA). To investigate UBE2D3's role in TMZ resistance, GBM cells were transduced with UBE2D3 shRNA or overexpression lentivirus, followed by assessments of CCK-8, flow cytometry, comet assay, and western blot analysis. Furthermore, a subcutaneous tumor model was established in nude mice using U87 cells transduced with interfering lentivirus to observe tumor growth and assess cell apoptosis using TUNEL staining. Mechanically, m6A content analysis, m6A methylated RNA immunoprecipitation quantitative PCR, reporter gene assay, mRNA stability measurements, RNA immunoprecipitation, quantitative Real-Time PCR, and Western blot assays were carried out to verify the role of WTAP/IGF2BP1 in regulating UBE2D3 expression. UBE2D3 exhibited elevated expression levels in GBM tissues compared with normal brain tissues and was associated with the DNA repair signaling pathway. In both in vitro and in vivo studies, it was demonstrated that TMZ treatment combined with reduced UBE2D3 expression further suppressed U87 cell viability and tumor growth, with a notable increase in apoptosis rate and DNA damage. Conversely, the overexpression of UBE2D3 had the opposite impact. Furthermore, our findings revealed that WTAP promotes the m6A modification of UBE2D3 via an IGF2BP1-dependent mechanism. The WTAP-IGF2BP1 axis regulates UBE2D3 stability in an m6A-dependent manner, influencing tumor malignancy and TMZ chemosensitivity in GBM via the DNA repair signaling pathway.

Identification of a methyltransferase-related long noncoding RNA signature as a novel prognosis biomarker for lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) accounts for a high proportion of tumor deaths globally, while methyltransferase-related lncRNAs in LUAD were poorly studied.

METHODS

In our study, we focused on two distinct cohorts, TCGA-LUAD and GSE3021, to establish a signature of methyltransferase-related long non-coding RNAs (MeRlncRNAs) in LUAD. We employed univariate Cox and LASSO regression analyses as our main analytical tools. The GSE30219 cohort served as the validation cohort for our findings. Furthermore, to explore the differential pathway enrichments between groups stratified by risk, we utilized Gene Set Enrichment Analysis (GSEA). Additionally, single-sample GSEA (ssGSEA) was conducted to assess the immune infiltration landscape within each sample. Reverse transcription quantitative PCR (RT-qPCR) was also performed to verify the expression of prognostic lncRNAs in both clinically normal and LUAD samples.

RESULTS

In LUAD, we identified a set of 32 MeRlncRNAs. We further narrowed our focus to six prognostic lncRNAs to develop gene signatures. The TCGA-LUAD cohort and GSE30219 were utilized to validate the risk score model derived from these signatures. Our analysis showed that the risk score served as an independent prognostic factor, linked to immune-related pathways. Additionally, the analysis of immune infiltration revealed that the immune landscape in high-risk groups was suppressed, which could contribute to poorer prognoses. We also constructed a regulatory network comprising 6 prognostic lncRNAs, 19 miRNAs, and 21 mRNAs. Confirmatory RT-qPCR results aligned with public database findings, verifying the expression of these prognostic lncRNAs in the samples.

CONCLUSION

The prognostic gene signature of LUAD associated with MeRlncRNAs that we provided, may offer us a comprehensive picture of the prognosis prediction for LUAD patients.

D-2-HG Inhibits IDH1mut Glioma Growth via FTO Inhibition and Resultant m6A Hypermethylation

IDH1mut gliomas produce high levels of D-2-hydroxyglutarate (D-2-HG), an oncometabolite capable of inhibiting α-ketoglutarate-dependent dioxygenases critical to a range of cellular functions involved in gliomagenesis. IDH1mut gliomas also exhibit slower growth rates and improved treatment sensitivity compared with their IDH1wt counterparts. This study explores the mechanism driving apparent reduced growth in IDH1mut gliomas. Specifically, we investigated the relationship between IDH1mut and the RNA N6-methyladenosine (m6A) demethylases FTO and ALKBH5, and their potential for therapeutic targeting. We investigated the role of D-2-HG and m6A in tumor proliferation/viability using glioma patient tumor samples, patient-derived gliomaspheres, and U87 cells, as well as with mouse intracranial IDH1wt gliomasphere xenografts. Methylation RNA immunoprecipitation sequencing (MeRIP-seq) RNA sequencing was used to identify m6A-enriched transcripts in IDH1mut glioma. We show that IDH1mut production of D-2-HG is capable of reducing glioma cell growth via inhibition of the m6A epitranscriptomic regulator, FTO, with resultant m6A hypermethylation of a set of mRNA transcripts. On the basis of unbiased MeRIP-seq epitranscriptomic profiling, we identify ATF5 as a hypermethylated, downregulated transcript that potentially contributes to increased apoptosis. We further demonstrate how targeting this pathway genetically and pharmacologically reduces the proliferative potential of malignant IDH1wt gliomas, both in vitro and in vivo. Our work provides evidence that selective inhibition of the m6A epitranscriptomic regulator FTO attenuates growth in IDH1wt glioma, recapitulating the clinically favorable growth phenotype seen in the IDH1mut subtype.

SIGNIFICANCE

We show that IDH1mut-generated D-2-HG can reduce glioma growth via inhibition of the m6A demethylase, FTO. FTO inhibition represents a potential therapeutic target for IDH1wt gliomas and possibly in conjunction with IDH1mut inhibitors for the treatment of IDH1mut glioma. Future studies are necessary to demonstrate the role of ATF5 downregulation in the indolent phenotype of IDH1mut gliomas, as well as to identify other involved gene transcripts deregulated by m6A hypermethylation.

Analysis of m6A regulators related immune characteristics in ankylosing spondylitis by integrated bioinformatics and computational strategies

N6-methyladenosine (m6A) modification, as a common epigenetic modification, has been widely studied in autoimmune diseases. However, the role of m6A in the regulation of the immune microenvironment of ankylosing spondylitis (AS) remains unclear. Therefore, we aimed to investigate the effect of m6A modification on the immune microenvironment of AS. We first evaluated RNA modification patterns mediated by 26 m6A regulators in 52 AS samples and 20 healthy samples. Thereafter, an m6A related classifier composed of seven genes was constructed and could effectively distinguish healthy and AS samples. Then, the correlation between m6A regulators and immune characteristics were investigated, including infiltrating immunocytes, immune reactions activity, and human leukocyte antigen (HLA) genes expression. The results indicated that m6A regulators was closely correlated with immune characteristics. For example, EIF3A was significantly related to infiltrating immunocytes; IGF2BP2 and EIF3A were significant regulators in immune reaction of TGF-β family member, and the expression of HLA-DPA1 and HLA-E were affected by EIF3A and ALKBH5. Next, two distinct m6A expression patterns were identified through unsupervised clustering analysis, and diverse immune characteristics were found between them. A total of 5889 m6A phenotype-related genes were obtained between the two expression patterns, and their biological functions were revealed. Finally, we validated the expression status of m6A modification regulators using two additional datasets. Our findings illustrate that m6A modifications play a critical role in the diversity and complexity of the AS immune microenvironment.

Role of N6-methyladenosine methylation in glioma: recent insights and future directions

Glioma is the most pervasive intracranial tumor in the central nervous system (CNS), with glioblastoma (GBM) being the most malignant type having a highly heterogeneous cancer cell population. There is a significantly high mortality rate in GBM patients. Molecular biomarkers related to GBM malignancy may have prognostic values in predicting survival outcomes and therapeutic responses, especially in patients with high-grade gliomas. In particular, N6-methyladenine (m6A) mRNA modification is the most abundant form of post-transcriptional RNA modification in mammals and is involved in regulating mRNA translation and degradation. Cumulative findings indicate that m6A methylation plays a crucial part in neurogenesis and glioma pathogenesis. In this review, we summarize recent advances regarding the functional significance of m6A modification and its regulatory factors in glioma occurrence and progression. Significant advancement of m6A methylation-associated regulators as potential therapeutic targets is also discussed.

The epitranscriptome of high-grade gliomas: a promising therapeutic target with implications from the tumor microenvironment to endogenous retroviruses

Glioblastoma (GBM) comprises 45.6% of all primary malignant brain cancers and is one of the most common and aggressive intracranial tumors in adults. Intratumoral heterogeneity with a wide range of proteomic, genetic, and epigenetic dysregulation contributes to treatment resistance and poor prognosis, thus demanding novel therapeutic approaches. To date, numerous clinical trials have been developed to target the proteome and epigenome of high-grade gliomas with promising results. However, studying RNA modifications, or RNA epitranscriptomics, is a new frontier within neuro-oncology. RNA epitranscriptomics was discovered in the 1970s, but in the last decade, the extent of modification of mRNA and various non-coding RNAs has emerged and been implicated in transposable element activation and many other oncogenic processes within the tumor microenvironment. This review provides background information and discusses the therapeutic potential of agents modulating epitranscriptomics in high-grade gliomas. A particular emphasis will be placed on how combination therapies that include immune agents targeting hERV-mediated viral mimicry could improve the treatment of GBM.

Insights into the regulatory role of RNA methylation modifications in glioma

Epitranscriptomic abnormalities, which are highly prevalent in primary central nervous system malignancies, have been identified as crucial contributors to the development and progression of gliomas. RNA epitranscriptomic modifications, particularly the reversible modification methylation, have been observed throughout the RNA cycle. Epitranscriptomic modifications, which regulate RNA transcription and translation, have profound biological implications. These modifications are associated with the development of several cancer types. Notably, three main protein types-writers, erasers, and readers, in conjunction with other related proteins, mediate these epitranscriptomic changes. This review primarily focuses on the role of recently identified RNA methylation modifications in gliomas, such as N6-methyladenosine (m6A), 5-methylcytosine (m5C), N7-methylguanosine (m7G), and N1-methyladenosine (m1A). We delved into their corresponding writers, erasers, readers, and related binding proteins to propose new approaches and prognostic indicators for patients with glioma.

Identification of M5c regulator-medicated methylation modification patterns for prognosis and immune microenvironment in glioma

Glioma is a common intracranial tumor and is generally associated with poor prognosis. Recently, numerous studies illustrated the importance of 5-methylcytosine (m5C) RNA modification to tumorigenesis. However, the prognostic value and immune correlation of m5C in glioma remain unclear. We obtained RNA expression and clinical information from The Cancer Genome Atlas (TCGA) and The Chinese Glioma Genome Atlas (CGGA) datasets to analyze. Nonnegative matrix factorization (NMF) was used to classify patients into two subgroups and compare these patients in survival and clinicopathological characteristics. CIBERSORT and single-sample gene-set algorithm (ssGSEA) methods were used to investigate the relationship between m5C and the immune environment. The Weighted correlation network analysis (WGCNA) and univariate Cox proportional hazard model (CoxPH) were used to construct a m5C-related signature. Most of m5C RNA methylation regulators presented differential expression and prognostic values. There were obvious relationships between immune infiltration cells and m5C regulators, especially NSUN7. In the m5C-related module from WGCNA, we found SEPT3, CHI3L1, PLBD1, PHYHIPL, SAMD8, RAP1B, B3GNT5, RER1, PTPN7, SLC39A1, and MXI1 were prognostic factors for glioma, and they were used to construct the signature. The great significance of m5C-related signature in predicting the survival of patients with glioma was confirmed in the validation sets and CGGA cohort.

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

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.

A combined clinical and specific genes' model to predict live birth for in vitro fertilization and embryo transfer patients

BACKGROUND

We aimed to develop an accurate model to predict live birth for patients receiving in vitro fertilization and embryo transfer (IVF-ET) treatment.

METHODS

This is a prospective nested case-control study. Women aged between 18 and 38 years, whose body mass index (BMI) were between the range of 18.5-24 kg/m2, who had an endometrium of ≥ 8 mm at the thickest were enrolled from 2018/9 to 2020/8. All patients received IVF-ET treatment and were followed up until Jan. 2022 when they had reproductive outcomes. Endometrial samples during the window of implantation (LH + 6 to 9 days) were subjected to analyze specific endometrial receptivity genes' expression using real-time PCR (RT-PCR). Patients were divided into live birth group and non-live birth group based on IVF-ET outcomes. Clinical signatures relevant to live birth were collected, analyzed, and used to establish a predictive model for live birth by univariate analysis (clinical model). Specific endometrial receptivity genes' expression was analyzed, selected, and used to construct a predictive model for live birth by The Least Absolute Shrinkage and Selection Operator (LASSO) analysis (gene model). Finally, significant clinical factors and genes were used to construct a combined model for predicting live birth using multivariate logistical regression (combined model). Different models' Area Under Curve (AUC) were compared to identify the most predictive model.

RESULTS

Thirty-nine patients were enrolled in the study, twenty-four patients had live births, fifteen did not. In univariate analysis, the odds of live birth for women with ovulation dysfunction was 4 times higher than that for women with other IVF-ET indications (OR = 4.0, 95% CI: 1.125 - 8.910, P = 0.018). Age, body mass index, duration of infertility, primary infertility, repeated implantation failure, antral follicle counting, ovarian sensitivity index, anti-Mullerian hormone, controlled ovarian hyperstimulation protocol and duration, total dose of FSH/hMG, number of oocytes retrieved, regiment of endometrial preparation, endometrium thickness before embryo transfer, type of embryo transferred were not associated with live birth (P > 0.05). Only ovulation dysfunction was used to construct the clinical model and its AUC was 0.688. In lasso analysis, GAST, GPX3, THBS2 were found to promote the risk of live birth. AUCs for GAST, GPX3, THBS2 reached to 0.736, 0.672, and 0.678, respectively. The gene model was established based on these three genes and its AUC was 0.772. Ovulation dysfunction, GAST, GPX3, and THBS2 were finally used to construct the combined model, reaching the highest AUC (AUC = 0.842).

CONCLUSIONS

Compared to the single model, the combined model of clinical (Ovulation dysfunction) and specific genes (GAST, GPX3, THBS2) was more accurate to predict live birth for IVF-ET patients.

CRISPR-Cas9 knockout screening identifies KIAA1429 as an essential gene in Ewing sarcoma

BACKGROUND

Ewing sarcoma (ES) is an aggressive childhood bone and soft tissue cancer. KIAA1429 is one type of N6-methyladenosine (m6A) writer that plays a tumor-progressive role in various cancers, but the role of KIAA1429 in ES remains to be elucidated. The aim of the study was to investigate the role of KIAA1429 in ES.

METHODS

We performed a multi-omic screen including CRISPR-Cas9 functional genomic and transcriptomic approaches, and identified that KIAA1429 played a significant role in ES progression. Gene knockdown, quantitative real-time PCR (Q-RT-PCR), immunoblotting, CellTiter-Glo assays, clonogenic assays, a subcutaneous xenograft model and immunohistochemistry were used to assess the functional role of KIAA1429 in ES. We mainly conducted RNA sequencing (RNA-seq) in ES cells to analyze the downstream regulatory mechanism of KIAA1429. An integrative analysis of chromatin immunoprecipitation sequencing (ChIP-seq) and RNA-seq indicated the upstream regulatory mechanism of KIAA1429.

RESULTS

In vitro and in vivo CRISPR-Cas9 knockout screening identified KIAA1429 as an ES-dependent gene. Genetic suppression of KIAA1429 inhibited ES cell proliferation and tumorigenicity both in vitro and in vivo. Further studies revealed that KIAA1429 promotes ES tumorigenesis by regulating the ribosome-associated cell cycle and cancer-related inflammation. Interestingly, we found that STAT3 was a target of KIAA1429 and that a STAT3 inhibitor reduced KIAA1429 transcript levels, indicating positive feedback between KIAA1429 and STAT3. Finally, we found that NKX2-2 bound to the KIAA1429 promoter and transactivated KIAA1429.

CONCLUSION

Our study systematically analyzed ES-dependent epigenetic/transcriptional regulatory genes and identified KIAA1429 as a biomarker of tumor progression in ES, providing a potential therapeutic target for treating ES.

GR-m6A: Prediction of N6-methyladenosine sites in mammals with molecular graph and residual network

RNA N6-methyladenine (m6A), which is produced by the methylation of the N6 position of eukaryotic adenine, is a relatively common post-transcriptional modification on the surface of the molecule, which frequently plays a crucial role in biological processes. Biological experimental methods to identify m6A have been studied and implemented in recent years, but they cannot be promoted widely due to drawbacks such as the time and cost of reagents and equipment. Therefore, researchers have proposed computational strategies for identifying m6A sites, but these strategies do not account for the mechanism of methylation occurrence or the structure of RNA molecules. This study, therefore, proposed a novel deep learning model for predicting m6A sites, GR-m6A, which predicts m6A sites by extracting features from the physicochemical properties and spatial structure of molecules via residual networks. In GR-m6A, each RNA base string is represented by SMILES as two matrices comprising topology structural information and node attributes with molecular physicochemical characteristics. The feature encoding matrix was then obtained by fusing the topology matrix and the node matrix in accordance with the graphical convolutional network principle. Correspondingly, the more discriminative features were extracted from the encoding matrix using the residual neural network and predicted using a multilayer perceptron. As evident from the 5-fold cross-validation and independent validation, the GR-m6A model outperformed other existing methods. Thus, we hope that GR-m6A can aid researchers in predicting mammalian m6A loci. The source code and database are available at https://github.com/YingLiangjxau/GR-m6A.

m6A modification and its role in neural development and neurological diseases

N6-methyladenosine (m6A) methylation, the most prevalent post-transcriptional modification in eukaryotes, represents a highly dynamic and reversible process that is regulated by m6A methyltransferases, m6A demethylases and RNA-binding proteins during RNA metabolism, which affects RNA function. Notably, m6A modification is significantly enriched in the brain and exerts regulatory roles in neurogenesis and neurodevelopment through various mechanisms, further influencing the occurrence and progression of neurological disorders. This study systematically summarizes and discusses the latest findings on common m6A regulators, examining their expression, function and mechanisms in neurodevelopment and neurological diseases. Additionally, we explore the potential of m6A modification in diagnosing and treating neurological disorders, aiming to provide new insights into the molecular mechanisms and potential therapeutic strategies for neurological disorders.

Glutamine and amino acid metabolism as a prognostic signature and therapeutic target in endometrial cancer

INTRODUCTION

Endometrial cancer (EC) is the most common female reproductive system cancer in developed countries with growing incidence and associated mortality, which may be due to the growing prevalence of obesity. Metabolism reprogramming including glucose, amino acid, and lipid remodeling is a hallmark of tumors. Glutamine metabolism has been reported to participate in tumor proliferation and development. This study aimed to develop a glutamine metabolism-related prognostic model for EC and explore potential targets for cancer treatment.

METHOD

Transcriptomic data and survival outcome of EC were retrieved from The Cancer Genome Atlas (TCGA). Differentially expressed genes related to glutamine metabolism were recognized and utilized to build a prognostic model by univariate and multivariate Cox regressions. The model was confirmed in the training, testing, and the entire cohort. A nomogram combing prognostic model and clinicopathologic features was established and tested. Moreover, we explored the effect of a key metabolic enzyme, PHGDH, on the biological behavior of EC cell lines and xenograft model.

RESULTS

Five glutamine metabolism-related genes, including PHGDH, OTC, ASRGL1, ASNS, and NR1H4, were involved in prognostic model construction. Kaplan-Meier curve suggested that patients recognized as high risk underwent inferior outcomes. The receiver operating characteristic (ROC) curve showed the model was sufficient to predict survival. Enrichment analysis recognized DNA replication and repair dysfunction in high-risk patients whereas immune relevance analysis revealed low immune scores in the high-risk group. Finally, a nomogram integrating the prognostic model and clinical factors was created and verified. Further, knockdown of PHGDH showed cell growth inhibition, increasing apoptosis, and reduced migration. Promisingly, NCT-503, a PHGDH inhibitor, significantly repressed tumor growth in vivo (p = 0.0002).

CONCLUSION

Our work established and validated a glutamine metabolism-related prognostic model that favorably evaluates the prognosis of EC patients. DNA replication and repair may be the crucial point that linked glutamine metabolism, amino acid metabolism, and EC progression. High-risk patients stratified by the model may not be sufficient for immune therapy. PHGDH might be a crucial target that links serine metabolism, glutamine metabolism as well as EC progression.

High Expression of CDCA7 in the Prognosis of Glioma and Its Relationship with Ferroptosis and Immunity

CDCA7 is a copy number amplification gene that promotes tumorigenesis. However, the clinical relevance and potential mechanisms of CDCA7 in glioma are unclear. CDCA7 expression level data were obtained from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases, and the enriched genes and related signaling pathways were explored. Data on genes in CDCA7-related signaling pathways and nine marker genes of ferroptosis were retrieved and a protein-protein interaction (PPI) network analysis was performed. The correlation of CDCA7 to ferroptosis and tumor infiltration of 22 kinds of human immune cells and the association between CDCA7 and immune checkpoint molecules were analyzed. CDCA7 was significantly increased in gliomas in comparison to healthy tissues. Gene Ontology (GO) and gene set enrichment analysis (GSEA) revealed the impact of CDCA7 expression on multiple biological processes and signaling pathways. CDCA7 may affect ferroptosis by interacting with genes in the cell cycle pathway and P53 pathway. The increase in CDCA7 was positively correlated with multiple ferroptosis suppressor genes and genes involved in tumor-infiltrating immune cells and immune checkpoint molecules in glioma. CDCA7 can be a new prognostic factor for glioma, which is closely related to ferroptosis, tumor immune cell infiltration, and immune checkpoint.

The Regulation of m6A Modification in Glioblastoma: Functional Mechanisms and Therapeutic Approaches

Glioblastoma is the most prevalent primary brain tumour and invariably confers a poor prognosis. The immense intra-tumoral heterogeneity of glioblastoma and its ability to rapidly develop treatment resistance are key barriers to successful therapy. As such, there is an urgent need for the greater understanding of the tumour biology in order to guide the development of novel therapeutics in this field. N6-methyladenosine (m6A) is the most abundant of the RNA modifications in eukaryotes. Studies have demonstrated that the regulation of this RNA modification is altered in glioblastoma and may serve to regulate diverse mechanisms including glioma stem-cell self-renewal, tumorigenesis, invasion and treatment evasion. However, the precise mechanisms by which m6A modifications exert their functional effects are poorly understood. This review summarises the evidence for the disordered regulation of m6A in glioblastoma and discusses the downstream functional effects of m6A modification on RNA fate. The wide-ranging biological consequences of m6A modification raises the hope that novel cancer therapies can be targeted against this mechanism.

An eleven-gene risk model associated with lymph node metastasis predicts overall survival in lung adenocarcinoma

Lung adenocarcinoma (LUAD) occupies major causes of tumor death. Identifying potential prognostic risk genes is crucial to predict the overall survival of patients with LUAD. In this study, we constructed and proved an 11-gene risk signature. This prognostic signature divided LUAD patients into low- and high-risk groups. The model outperformed in prognostic accuracy at varying follow-up times (AUC for 3 years: 0.699, 5 years: 0.713, and 7 years: 0.716). Two GEO datasets also indicate the great accuracy of the risk signature (AUC = 782 and 771, respectively). Multivariate analysis identified 4 independent risk factors including stage N (HR 1.320, 95% CI 1.102-1.581, P = 0.003), stage T (HR 3.159, 95% CI 1.920-3.959, P < 0.001), tumor status (HR 5.688, 95% CI 3.883-8.334, P < 0.001), and the 11-gene risk model (HR 2.823, 95% CI 1.928-4.133, P < 0.001). The performance of the nomogram was good in the TCGA database (AUC = 0.806, 0.798, and 0.818 for 3-, 5- and 7-year survival). The subgroup analysis in different age, gender, tumor status, clinical stage, and recurrence stratifications indicated that the accuracy was high in different subgroups (all P < 0.05). Briefly, our work established an 11-gene risk model and a nomogram merging the model with clinicopathological characteristics to facilitate individual prediction of LUAD patients for clinicians.

m6A regulator-mediated RNA methylation modification patterns are involved in the regulation of the immune microenvironment in ischaemic cardiomyopathy

The role of RNA N6-methyladenosine (m6A) modification in the regulation of the immune microenvironment in ischaemic cardiomyopathy (ICM) remains largely unclear. This study first identified differential m6A regulators between ICM and healthy samples, and then systematically evaluated the effects of m6A modification on the characteristics of the immune microenvironment in ICM, including the infiltration of immune cells, the human leukocyte antigen (HLA) gene, and HALLMARKS pathways. A total of seven key m6A regulators, including WTAP, ZCH3H13, YTHDC1, FMR1, FTO, RBM15 and YTHDF3, were identified using a random forest classifier. A diagnostic nomogram based on these seven key m6A regulators could effectively distinguish patients with ICM from healthy subjects. We further identified two distinct m6A modification patterns (m6A cluster-A and m6A cluster-B) that are mediated by these seven regulators. Meanwhile, we also noted that one m6A regulator, WTAP, was gradually upregulated, while the others were gradually downregulated in the m6A cluster-A vs. m6A cluster-B vs. healthy subjects. In addition, we observed that the degree of infiltration of the activated dendritic cells, macrophages, natural killer (NK) T cells, and type-17 T helper (Th17) cells gradually increased in m6A cluster-A vs. m6A cluster-B vs. healthy subjects. Furthermore, m6A regulators, including FTO, YTHDC1, YTHDF3, FMR1, ZC3H13, and RBM15 were significantly negatively correlated with the above-mentioned immune cells. Additionally, several differential HLA genes and HALLMARKS signalling pathways between the m6A cluster-A and m6A cluster-B groups were also identified. These results suggest that m6A modification plays a key role in the complexity and diversity of the immune microenvironment in ICM, and seven key m6A regulators, including WTAP, ZCH3H13, YTHDC1, FMR1, FTO, RBM15, and YTHDF3, may be novel biomarkers for the accurate diagnosis of ICM. Immunotyping of patients with ICM will help to develop immunotherapy strategies with a higher level of accuracy for patients with a significant immune response.

Comprehensive analyses of molecular features, prognostic values, and regulatory functionalities of m6A-modified long non-coding RNAs in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) has a high incidence and recurrence rate. N6-methyladenosine (m⁶A) modification of RNA has become a promising epigenetic marker in tumors. The dysregulation of both RNA m⁶A levels and m⁶A regulator expression levels reportedly affects essential biological processes in various tumors. Long non-coding RNAs (lncRNAs), a subgroup of RNAs over 200 nucleotides in length that do not code for protein, can be modified and regulated by m⁶A, but the relevant profile in LUAD remains unclear.

RESULTS

The m⁶A levels of total RNA were decreased in LUAD tumor tissues and cells. Multiple m⁶A regulators were abnormally expressed at both the RNA and protein levels, and were related in expression patterns and functionally synergistic. Our microarray revealed 2846 m⁶A-modified lncRNA transcripts as well as its molecular features, 143 of which were differentially m⁶A-modified and manifested a negative correlation between expression levels and m⁶A modification levels. More than half of the differentially m⁶A-modified lncRNAs associated with dysregulated expression. The 6-MRlncRNA risk signature was a reliable indicator for assessing survival time of LUAD patients. The competitive endogenous regulatory network suggested a potential m⁶A-induced pathogenicity in LUAD.

CONCLUSIONS

These data have demonstrated that differential RNA m⁶A modification and m⁶A regulator expression levels were identified in LUAD patients. In addition, this study provides evidence increasing the understanding of molecular features, prognostic values, and regulatory functionalities of m⁶A-modified lncRNAs in LUAD.

Landscape analysis of m6A modification regulators related biological functions and immune characteristics in myasthenia gravis

BACKGROUND

N6-methyladenosine (m6A) modification has been recognized to play fundamental roles in the development of autoimmune diseases. However, the implication of m6A modification in myasthenia gravis (MG) remains largely unknown. Thus, we aimed to systematically explore the potential functions and related immune characteristics of m6A regulators in MG.

METHODS

The GSE85452 dataset with MG and healthy samples was downloaded from Gene Expression Omnibus (GEO) database. m6A modification regulators were manually curated. The targets of m6A regulators were obtained from m6A2Target database. The differential expressed m6A regulators in GSE85452 dataset were identified by "limma" package and were validated by RT-PCR. Function enrichment analysis of dysregulated m6A regulators was performed using "clusterProfiler" package. Correlation analysis was applied for analyzing the relationships between m6A regulators and immune characteristics. Unsupervised clustering analysis was used to identify distinct m6A modification subtypes. The differences between subtypes were analyzed, including the expression level of all genes and the enrichment degree of immune characteristics. Weighted gene co-expression network analysis (WGCNA) was conducted to obtain modules associated with m6A modification subtypes.

RESULTS

We found that CBLL1, RBM15 and YTHDF1 were upregulated in MG samples of GSE85452 dataset, and the results were verified by RT-PCR in blood samples from19 MG patients and 19 controls. The targeted genes common modified by CBLL1, RBM15, and YTHDF1 were mainly enriched in histone modification and Wnt signaling pathway. Correlation analysis showed that three dysregulated m6A regulators were closely associated with immune characteristics. Among them, RBM15 possessed the strongest correlation with immune characteristics, including CD56dim natural killer cell (r = 0.77, P = 0.0023), T follicular helper cell (r = - 0.86, P = 0.0002), Interferon Receptor (r = 0.78, P = 0.0017), and HLA-DOA (r = 0.64, P = 0.0200). Further two distinct m6A modification patterns mediated by three dysregulated m6A regulators was identified. Bioinformatics analysis found that there were 3029 differentially expressed genes and different immune characteristics between two m6A modification patterns. Finally, WGCNA analysis obtained a total of 12 modules and yellow module was the most positively correlated to subtype-2.

CONCLUSION

Our findings suggested that m6A RNA modification had an important effect on immunity molecular mechanism of MG and provided a new perspective into understanding the pathogenesis of MG.

Identification of m6A regulator-mediated RNA methylation modification patterns and key immune-related genes involved in atrial fibrillation

The role of m6A in the regulation of the immune microenvironment in atrial fibrillation (AF) remains unclear. This study systematically evaluated the RNA modification patterns mediated by differential m6A regulators in 62 AF samples, identified the pattern of immune cell infiltration in AF and identified several immune-related genes associated with AF. A total of six key differential m6A regulators between healthy subjects and AF patients were identified by the random forest classifier. Three distinct RNA modification patterns (m6A cluster-A, -B and -C) among AF samples were identified based on the expression of 6 key m6A regulators. Differential infiltrating immune cells and HALLMARKS signaling pathways between normal and AF samples as well as among samples with three distinct m6A modification patterns were identified. A total of 16 overlapping key genes were identified by weighted gene coexpression network analysis (WGCNA) combined with two machine learning methods. The expression levels of the NCF2 and HCST genes were different between controls and AF patient samples as well as among samples with the distinct m6A modification patterns. RT-qPCR also proved that the expression of NCF2 and HCST was significantly increased in AF patients compared with control participants. These results suggested that m6A modification plays a key role in the complexity and diversity of the immune microenvironment of AF. Immunotyping of patients with AF will help to develop more accurate immunotherapy strategies for those with a significant immune response. The NCF2 and HCST genes may be novel biomarkers for the accurate diagnosis and immunotherapy of AF.

Understanding the Epitranscriptome for Avant-Garde Brain Tumour Diagnostics

RNA modifications are diverse, dynamic, and reversible transcript alterations rapidly gaining attention due to their newly defined RNA regulatory roles in cellular pathways and pathogenic mechanisms. The exciting emerging field of 'epitranscriptomics' is predominantly centred on studying the most abundant mRNA modification, N6-methyladenine (m⁶A). The m⁶A mark, similar to many other RNA modifications, is strictly regulated by so-called 'writer', 'reader', and 'eraser' protein species. The abundance of genes coding for the expression of these regulator proteins and m⁶A levels shows great potential as diagnostic and predictive tools across several cancer fields. This review explores our current understanding of RNA modifications in glioma biology and the potential of epitranscriptomics to develop new diagnostic and predictive classification tools that can stratify these highly complex and heterogeneous brain tumours.

m6A RNA Methylation Decreases Atherosclerotic Vulnerable Plaque Through Inducing T Cells

INTRODUCTION

Knockdown of fat mass and obesity-associated gene (FTO) can induce N6-methyladenosine (m⁶A) ribonucleic acid (RNA) methylation. The objective of this study was to explore the effect of m 6A RNA methylation on atherosclerotic vulnerable plaque by FTO knockdown.

METHODS

A total of 50 New Zealand white rabbits were randomly divided into pure high-fat group, sham operation group, vulnerable plaque group, empty load group, and FTO knockdown group (10 rabbits/group).

RESULTS

Flow cytometry showed that helper T (Th) cells in the FTO knockdown group accounted for a significantly higher proportion of lymphocytes than in the vulnerable plaque group and empty load group (P<0.05). Th cells were screened by cell flow. The level of m⁶A RNA methylation in the FTO knockdown group was significantly higher than in the vulnerable plaque group and empty load group (P<0.05). The levels of total cholesterol, triglyceride, and low-density lipoprotein C were higher at the 12^th week than at the 1^st week, but the high-density lipoprotein C level was lower at the 12^th week than at the 1^st week. At the 12th week, the interleukin-7 level was significantly lower in the adeno-associated virus-9 (AVV9)-FTO short hairpin RNA group than in the control and AVV9-green fluorescent protein groups (P<0.001).

CONCLUSION

After successfully establishing a vascular parkinsonism rabbit model, m⁶A RNA methylation can decrease Th cells and vulnerable atherosclerotic plaques.

Molecular pathology and clinical implications of diffuse glioma

ABSTRACT

The prognosis for diffusely infiltrating gliomas at World Health Organization (WHO) grade 2-4 remains dismal due to their heterogeneity. The rapid development of genome-wide molecular-profiling-associated studies has greatly promoted the accuracy of glioma classification. Thus, the latest version of the WHO classification of the central nervous system tumors published in 2021 has incorporated more molecular biomarkers together with histological features for the diagnosis of gliomas. Advanced usage of molecular pathology in clinical diagnostic practice provides also new opportunities for the therapy of patients with glioma, including surgery, radiotherapy and chemotherapy, targeted therapy, immunotherapy, and more precision clinical trials. Herein, we highlight the updates in the classification of gliomas according to the latest WHO guidelines and summarize the clinically relevant molecular markers by focusing on their applications in clinical practice. We also review the advances in molecular features of gliomas, which can facilitate the development of glioma therapies, thereby discussing the challenges and future directions of molecular pathology toward precision medicine for patients with glioma.

Identification of immune characteristic landscapes related to autophagy in ischemic stroke

Ischemic stroke (IS) is a common and grievous nervous system disease. Both autophagy activation and immune response after cerebral ischemia play important roles in the development of IS. Many studies have revealed a close interplay between autophagy and immunity. However, little is known about how autophagy influences the immune characteristics of IS. Hence, the study aims to systematically explore the role of autophagy and its impact on immune characteristics in IS. We first compared the expression differences of autophagy genes in a training set and identified 20 dysregulated autophagy genes between healthy and IS samples. An autophagy-related classifier composed of seven genes was further established and could well distinguish healthy and IS samples. Then, the association between autophagy and immune characteristics, including infiltrating immunocytes, activity of immune reactions, and HLA gene expression, was investigated. The results showed that autophagy closely correlated with immune characteristics, such as NAMPT and ARNT significantly related to infiltrating immunocytes; PPP1R15A and CASP3 significantly related to activity of immune reactions; and NAMPT and ATG16L2 significantly related to HLA genes. Next, two distinct autophagy expression patterns were identified by unsupervised clustering analysis, and diverse immune characteristics were discovered between them. A total of 5481 autophagy phenotype-related genes were obtained between two expression patterns, and their biological functions revealed that these genes were involved in immune-related biological pathways. Finally, five dysregulated autophagy genes (FOS, MAP1LC3B, ERO1L, ARNT, and PPP1R15A) were proved between IS and healthy samples using another two validation sets. Our results illustrated that autophagy had a dramatic effect on the immunity of IS and provided a novel sight into understanding the pathogenesis of IS.

A Risk Signature Consisting of Eight m6A Methylation Regulators Predicts the Prognosis of Glioma

Glioma progression seriously correlates to the epigenetic context. This study aims to identify glioma subtypes by clustering analysis of patients using the multi-omics data of N6-methyladenosine (m⁶A) methylation regulators and to construct a risk signature for investigating the role of m⁶A methylation regulators in the prognosis of glioma. Multi-omics data of glioma and normal control tissues were obtained through The Cancer Genome Atlas (TCGA) database. The clustering analysis of multi-omics data of patients was conducted using the R package iClusterPlus software. The risk model was constructed by univariate and multivariate Cox analysis, and the glioma expression data and related clinical data were obtained by Chinese Glioma Genome Atlas (CGGA) datasets to verify the risk model. By analyzing the glioma data in TCGA, we found that the risk signature could be constructed according to the eight genes with m⁶A methylation modification function, including ALKBH5, HNRNPA2B1, IGF2BP2, IGF2BP3, RBM15, WTAP, YTHDF1, and YTHDF2. Meanwhile, we found that IGF2BP2 and IGF2BP3 were highly expressed in glioma subtypes with high-risk scores and closely related to the prognosis of glioma patients. m⁶A methylation regulators, especially IGF2BP2 and IGF2BP3, play important roles in the malignant progression of glioma. The risk signature constructed by eight m⁶A methylation regulators can predict the prognosis of glioma. IGF2BP2 and IGF2BP3 may be the key regulatory factors of m⁶A methylation regulators involved in the occurrence and development of glioma, and can serve as molecular markers for the prognosis of glioma.

Identification of pyroptosis-related immune signature and drugs for ischemic stroke

Background: Ischemic stroke (IS) is a common and serious neurological disease, and multiple pathways of cell apoptosis are implicated in its pathogenesis. Recently, extensive studies have indicated that pyroptosis is involved in various diseases, especially cerebrovascular diseases. However, the exact mechanism of interaction between pyroptosis and IS is scarcely understood. Thus, we aimed to investigate the impact of pyroptosis on IS-mediated systemic inflammation.

Methods: First, the RNA regulation patterns mediated by 33 pyroptosis-related genes identified in 20 IS samples and 20 matched-control samples were systematically evaluated. Second, a series of bioinformatics algorithms were used to investigate the contribution of PRGs to IS pathogenesis. We determined three composition classifiers of PRGs which potentially distinguished healthy samples from IS samples according to the risk score using single-variable logistic regression, LASSO-Cox regression, and multivariable logistic regression analyses. Third, 20 IS patients were classified by unsupervised consistent cluster analysis in relation to pyroptosis. The association between pyroptosis and systemic inflammation characteristics was explored, which was inclusive of immune reaction gene sets, infiltrating immunocytes and human leukocyte antigen genes.

Results: We identified that AIM2, SCAF11, and TNF can regulate immuno-inflammatory responses after strokes via the production of inflammatory factors and activation of the immune cells. Meanwhile, we identified distinct expression patterns mediated by pyroptosis and revealed their immune characteristics, differentially expressed genes, signaling pathways, and target drugs.

Conclusion: Our findings lay a foundation for further research on pyroptosis and IS systemic inflammation, to improve IS prognosis and its responses to immunotherapy.

Identification and construction of a prognostic risk model based on multi-RNA methylation regulators in cervical cancer

AIM

Cervical cancer is one of the most aggressive female cancers. RNA methylation is a necessary epigenetic modification in biological process. This study aimed to construct an RNA methylation regulator-based risk model for predicting the prognosis of cervical cancer patients.

METHODS

The transcriptome profiles of cervical cancer data were obtained from The Cancer Genome Atlas (TCGA) and GSE44001. An RNA methylation-related risk model was constructed and assessed by the Least absolute shrinkage and selection operator (Lasso)-penalized Cox regression model and receiver operating characteristic (ROC). Kaplan-Meier and Cox regression analyses were used to evaluate the prognostic effect of the risk model and calculated scores. The immune infiltration difference was further analyzed between the subgroups with a single-sample gene set enrichment analysis (ssGSEA).

RESULTS

A total of 63 methylation modulators were included in this study, and 618 cervical cancer patients were identified from TCGA and GSE44001. Differential expression genes profiling RNA methylation regulators between normal and tumor samples were distinct. A four-gene signature panel was constructed to predict the prognostic risk. The predictive ability was satisfactory. Cervical cancer patients were classified into high- or low-risk subgroups according to the median risk score. Moreover, the immune infiltration patterns between them differed.

CONCLUSIONS

A risk model including four RNA methylation regulators was constructed, which will provide new perspectives for further investigation of the relationship between RNA methylation and cervical cancer.

Identification and Validation of Immune Markers in Coronary Heart Disease

Background

Coronary heart disease (CHD) is an ischemic heart disease involving a variety of immune factors. This study was aimed at investigating unique immune and m6A patterns in patients with CHD by gene expression in peripheral blood mononuclear cells (PBMCs) and at identifying novel immune biomarkers.

Methods

The CIBERSORT algorithm and single-sample gene set enrichment analysis (ssGSEA) were applied to assess the population of specific infiltrating immunocytes. Weighted Gene Coexpression Network Analysis (WGCNA) was utilized on immune genes matching CHD. A prediction model based on core immune genes was constructed and verified by a machine learning model. Unsupervised cluster analysis identified various immune patterns in the CHD group according to the abundance of immune cells. Methylation of N6 adenosine- (m6A-) related gene was identified from the literature, and t-distributed stochastic neighbor embedding (t-SNE) analysis was used to determine the rationality of the m6A classification. The association between m6A-related genes and various immune cells was estimated using heat maps.

Results

22/28 immune-associated cells differed between the CHD and normal groups, and a significant difference was detected in the expression of 21 m6A-related genes. The proportion of immune-related cells (activated CD4+ T cells and CD8+ T cells) in the peripheral blood of the CHD group was lower than that of the normal group. The immune genes were divided into four modules, of which the turquoise modules showed a significant association with coronary heart disease. Eight hub immune genes (PDGFRA, GNLY, OSMR, NUDT6, FGFR2, IL2RB, TPM2, and S100A1) can well distinguish the CHD group from the normal group. Two different immune patterns were identified in the CHD group. Interestingly, a significant association was detected between the m6A-related genes and immune cell abundance.

Conclusion

In conclusion, we identified different immune and m6A patterns in CHD. Thus, it could be speculated that the immune system plays a crucial role in CHD, and m6A is correlated with immune genes.

Multivariate Analysis of RNA Chemistry Marks Uncovers Epitranscriptomics-Based Biomarker Signature for Adult Diffuse Glioma Diagnostics

One of the main challenges in cancer management relates to the discovery of reliable biomarkers, which could guide decision-making and predict treatment outcome. In particular, the rise and democratization of high-throughput molecular profiling technologies bolstered the discovery of “biomarker signatures” that could maximize the prediction performance. Such an approach was largely employed from diverse OMICs data (i.e., genomics, transcriptomics, proteomics, metabolomics) but not from epitranscriptomics, which encompasses more than 100 biochemical modifications driving the post-transcriptional fate of RNA: stability, splicing, storage, and translation. We and others have studied chemical marks in isolation and associated them with cancer evolution, adaptation, as well as the response to conventional therapy. In this study, we have designed a unique pipeline combining multiplex analysis of the epitranscriptomic landscape by high-performance liquid chromatography coupled to tandem mass spectrometry with statistical multivariate analysis and machine learning approaches in order to identify biomarker signatures that could guide precision medicine and improve disease diagnosis. We applied this approach to analyze a cohort of adult diffuse glioma patients and demonstrate the existence of an “epitranscriptomics-based signature” that permits glioma grades to be discriminated and predicted with unmet accuracy. This study demonstrates that epitranscriptomics (co)evolves along cancer progression and opens new prospects in the field of omics molecular profiling and personalized medicine.

Post-Transcriptional Modifications of RNA as Regulators of Apoptosis in Glioblastoma

This review is devoted to changes in the post-transcriptional maturation of RNA in human glioblastoma cells, which leads to disruption of the normal course of apoptosis in them. The review thoroughly highlights the latest information on both post-transcriptional modifications of certain regulatory RNAs, associated with the process of apoptosis, presents data on the features of apoptosis in glioblastoma cells, and shows the relationship between regulatory RNAs and the apoptosis in tumor cells. In conclusion, potential target candidates are presented that are necessary for the development of new drugs for the treatment of glioblastoma.

Methyladenosine Modification in RNAs: From Regulatory Roles to Therapeutic Implications in Cancer

Simple Summary

Cancer remains a burden to the public health all over the world. An increasing number of studies have concentrated on the role of methyladenosine modifications on cancers. Methyladenosine modifications mainly include N6-methyladenosine (m⁶A), N1-methyladenosine (m¹A), and 2’-O-methyladenosine (m⁶A_m), of which dynamic changes could modulate the metabolism of RNAs in eukaryotic cells. Mounting evidence has confirmed the crucial role of methyladenosine modification in cancer, offering possibilities for cancer therapy. In this review, we discussed the regulatory role of methyladenosine modification on cancer, as well as their potential for treatment.

Abstract

Methyladenosine modifications are the most abundant RNA modifications, including N6-methyladenosine (m⁶A), N1-methyladenosine (m¹A), and 2’-O-methyladenosine (m⁶A_m). As reversible epigenetic modifications, methyladenosine modifications in eukaryotic RNAs are not invariable. Drastic alterations of m⁶A are found in a variety of diseases, including cancers. Dynamic changes of m⁶A modification induced by abnormal methyltransferase, demethylases, and readers can regulate cancer progression via interfering with the splicing, localization, translation, and stability of mRNAs. Meanwhile, m⁶A, m¹A, and m⁶A_m modifications also exert regulatory effects on noncoding RNAs in cancer progression. In this paper, we reviewed recent findings concerning the underlying biomechanism of methyladenosine modifications in oncogenesis and metastasis and discussed the therapeutic potential of methyladenosine modifications in cancer treatments.

Establishment and Validation of a Ferroptosis-Related lncRNA Signature for Prognosis Prediction in Lower-Grade Glioma

Background

The prognosis of lower-grade glioma (LGG) is highly variable, and more accurate predictors are still needed. The aim of our study was to explore the prognostic value of ferroptosis-related long non-coding RNAs (lncRNAs) in LGG and to develop a novel risk signature for predicting survival with LGG.

Methods

We first integrated multiple datasets to screen for prognostic ferroptosis-related lncRNAs in LGG. A least absolute shrinkage and selection operator (LASSO) analysis was then utilized to develop a risk signature for prognostic prediction. Based on the results of multivariate Cox analysis, a prognostic nomogram model for LGG was constructed. Finally, functional enrichment analysis, single-sample gene set enrichment analysis (ssGSEA), immunity, and m6A correlation analyses were conducted to explore the possible mechanisms by which these ferroptosis-related lncRNAs affect survival with LGG.

Results

A total of 11 ferroptosis-related lncRNAs related to the prognosis of LGG were identified. Based on prognostic lncRNAs, a risk signature consisting of 8 lncRNAs was constructed and demonstrated good predictive performance in both the training and validation cohorts. Correlation analysis suggested that the risk signature was closely linked to clinical features. The nomogram model we constructed by combining the risk signature and clinical parameters proved to be more accurate in predicting the prognosis of LGG. In addition, there were differences in the levels of immune cell infiltration, immune-related functions, immune checkpoints, and m6A-related gene expression between the high- and low-risk groups.

Conclusion

In summary, our ferroptosis-related lncRNA signature exhibits good performance in predicting the prognosis of LGG. This study may provide useful insight into the treatment of LGG.

Construction of m6A-Related lncRNA Prognostic Signature Model and Immunomodulatory Effect in Glioblastoma Multiforme

Background

Glioblastoma multiforme (GBM), the most prevalent and aggressive of primary malignant central nervous system tumors (grade IV), has a poor clinical prognosis. This study aimed to assess and predict the survival of GBM patients by establishing an m6A-related lncRNA signaling model and to validate its validity, accuracy and applicability.

Methods

RNA sequencing data and clinical data of GBM patients were obtained from TCGA data. First, m6A-associated lncRNAs were screened and lncRNAs associated with overall survival in GBM patients were obtained. Subsequently, the signal model was established using LASSO regression analysis, and its accuracy and validity are further verified. Finally, GO enrichment analysis was performed, and the influence of this signature on the immune regulation response and anticancer drug sensitivity of GBM patients was discussed.

Results

The signature constructed by four lncRNAs AC005229.3, SOX21-AS1, AL133523.1, and AC004847.1 is obtained. Furthermore, the signature proved to be effective and accurate in predicting and assessing the survival of GBM patients and could function independently of other clinical characteristics (Age, Gender and IDH1 mutation). Finally, Immunosuppression-related factors, including APC co-inhibition, T-cell co-inhibition, CCR and Check-point, were found to be significantly up-regulated in GBM patients in the high-risk group. Some chemotherapeutic drugs (Doxorubicin and Methotrexate) and targeted drugs (AZD8055, BI.2536, GW843682X and Vorinostat) were shown to have higher IC50 values in patients in the high-risk group.

Conclusion

We constructed an m6A-associated lncRNA risk model to predict the prognosis of GBM patients and provide new ideas for the treatment of GBM. Further biological experiments can be conducted on this basis to validate the clinical value of the model.

Comprehensive analyses indicated the association between m6A related long non-coding RNAs and various pathways in glioma

BACKGROUND

Glioma is one of the most malignant brain tumors and diseases. N6-methyladenosine modification (m6A) is the most abundant and prevalent internal chemical modification of mRNA and long non-coding RNAs (lncRNAs) in eukaryotes. Nevertheless, the correlated pathways and clinical utilization of m6A-related lncRNAs have not been fully evaluated in glioma.

METHODS

Public RNA-sequencing and clinical annotation data were retrieved from TCGA, CGGA and GEO database. Differential expression analysis and univariate Cox regression analysis were performed to identify the m6A-related and differentially expressed lncRNAs with prognostic function (m6A-DELPF). The consensus clustering was performed to identify the expression pattern of m6A-DELPF. LASSO Cox regression analysis was performed to construct the lncRNA-based signature. The CIBERSORT and ESTIMATE algorithms were performed to analyze immune infiltration and tumor microenvironment, respectively. Immunotherapy sensitivity analysis was performed using data from TCIA. The small molecule drugs prediction analysis was performed using The Connectivity Map (CMap) database and STITCH database. A competing endogenous RNAs (ceRNA) network was constructed based on miRcode, miRDB, miRTarBase, TargetScan database.

RESULTS

Two clusters (cluster1 and cluster2) were identified after unsupervised cluster analysis based on m6A-DELPF. Additionally, a 15-gene prognostic signature namely m6A-DELPFS was constructed. Analyses of epithelial-mesenchymal-transition score, tumor microenvironment, immune infiltration, clinical characterization analysis, and putative drug prediction were performed to confirm the clinical utility and efficacy of m6A-DELPFS. The potential mechanisms including tumor immune microenvironment of m6A-DELPF influence the initiation and progression of glioma. A clinically accessible nomogram was also constructed based on the m6A-DELPF and other survival-relevant clinical parameters. Two miRNAs and 114 mRNAs were identified as the downstream of seven m6A-related lncRNAs in a ceRNA network.

CONCLUSION

Our present research confirmed the clinical value of m6A related lncRNAs and their high correlation with tumor immunity, tumor microenvironment, tumor mutation burden and drug sensitivity in glioma.

An m6A/m5C/m1A/m7G-Related Long Non-coding RNA Signature to Predict Prognosis and Immune Features of Glioma

Background: Gliomas are the most common and fatal malignant type of tumor of the central nervous system. RNA post-transcriptional modifications, as a frontier and hotspot in the field of epigenetics, have attracted increased attention in recent years. Among such modifications, methylation is most abundant, and encompasses N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1 methyladenosine (m1A), and 7-methylguanosine (m7G) methylation.

Methods: RNA-sequencing data from healthy tissue and low-grade glioma samples were downloaded from of The Cancer Genome Atlas database along with clinical information and mutation data from glioblastoma tumor samples. Forty-nine m6A/m5C/m1A/m7G-related genes were identified and an m6A/m5C/m1A/m7G-lncRNA signature of co-expressed long non-coding RNAs selected. Least absolute shrinkage and selection operator Cox regression analysis was used to identify 12 m6A/m5C/m1A/m7G-related lncRNAs associated with the prognostic characteristics of glioma and their correlation with immune function and drug sensitivity analyzed. Furthermore, the Chinese Glioma Genome Atlas dataset was used for model validation.

Results: A total of 12 m6A/m5C/m1A/m7G-related genes (AL080276.2, AC092111.1, SOX21-AS1, DNAJC9-AS1, AC025171.1, AL356019.2, AC017104.1, AC099850.3, UNC5B-AS1, AC006064.2, AC010319.4, and AC016822.1) were used to construct a survival and prognosis model, which had good independent prediction ability for patients with glioma. Patients were divided into low and high m6A/m5C/m1A/m7G-LS groups, the latter of which had poor prognosis. In addition, the m6A/m5C/m1A/m7G-LS enabled improved interpretation of the results of enrichment analysis, as well as informing immunotherapy response and drug sensitivity of patients with glioma in different subgroups.

Conclusion: In this study we constructed an m6A/m5C/m1A/m7G-LS and established a nomogram model, which can accurately predict the prognosis of patients with glioma and provides direction toward promising immunotherapy strategies for the future.

Identification of Implications of Angiogenesis and m6A Modification on Immunosuppression and Therapeutic Sensitivity in Low-Grade Glioma by Network Computational Analysis of Subtypes and Signatures

Angiogenesis is a complex process in the immunosuppressed low-grade gliomas (LGG) microenvironment and is regulated by multiple factors. N⁶-methyladenosine (m6A), modified by the m6A modification regulators (“writers” “readers” and “erasers”), can drive LGG formation. In the hypoxic environment of intracranial tumor immune microenvironment (TIME), m6A modifications in glioma stem cells are predominantly distributed around neovascularization and synergize with complex perivascular pathological ecology to mediate the immunosuppressive phenotype of TIME. The exact mechanism of this phenomenon remains unknown. Herein, we elucidated the relevance of the angiogenesis-related genes (ARGs) and m6A regulators (MAGs) and their influencing mechanism from a macro perspective. Based on the expression pattern of MAGs, we divided patients with LGG into two robust categories via consensus clustering, and further annotated the malignant related mechanisms and corresponding targeted agents. The two subgroups (CL1, CL2) demonstrated a significant correlation with prognosis and clinical-pathology features. Moreover, WGCNA has also uncovered the hub genes and related mechanisms of MAGs affecting clinical characters. Clustering analysis revealed a synergistic promoting effect of M6A and angiogenesis on immunosuppression. Based on the expression patterns of MAGs, we established a high-performance gene-signature (MASig). MASig revealed somatic mutational mechanisms by which MAGs affect the sensitivity to treatment in LGG patients. In conclusion, the MAGs were critical participants in the malignant process of LGG, with a vital potential in the prognosis stratification, prediction of outcome, and therapeutic sensitivity of LGG. Findings based on these strategies may facilitate the development of objective diagnosis and treatment systems to quantify patient survival and other outcomes, and in some cases, to identify potential unexplored targeted therapies.

YTHDF2 promotes temozolomide resistance in glioblastoma by activation of the Akt and NF-κB signalling pathways via inhibiting EPHB3 and TNFAIP3

Objectives

Temozolomide (TMZ) resistance is a key factor that restricts the therapeutic effect of glioblastoma (GBM). YTH‐domain family member 2 (YTHDF2) is highly expressed in GBM tissues, while the mechanism of YTHDF2 in TMZ resistance in GBM remains not fully elucidated.

Methods

The YTHDF2 expression in TMZ‐resistant tissues and cells was detected. Kaplan–Meier analysis was employed to evaluate the prognostic value of YTHDF2 in GBM. Effect of YTHDF2 in TMZ resistance in GBM was explored via corresponding experiments. RNA sequence, FISH in conjugation with fluorescent immunostaining, RNA immunoprecipitation, dual‐luciferase reporter gene and immunofluorescence were applied to investigate the mechanism of YTHDF2 that boosted TMZ resistance in GBM.

Results

YTHDF2 was up‐regulated in TMZ‐resistant tissues and cells, and patients with high expression of YTHDF2 showed lower survival rate than the patients with low expression of YTHDF2. The elevated YTHDF2 expression boosted TMZ resistance in GBM cells, and the decreased YTHDF2 expression enhanced TMZ sensitivity in TMZ‐resistant GBM cells. Mechanically, YTHDF2 bound to the N6‐methyladenosine (m⁶A) sites in the 3′UTR of EPHB3 and TNFAIP3 to decrease the mRNA stability. YTHDF2 activated the PI3K/Akt and NF‐κB signals through inhibiting expression of EPHB3 and TNFAIP3, and the inhibition of the two pathways attenuated YTHDF2‐mediated TMZ resistance.

Conclusion

YTHDF2 enhanced TMZ resistance in GBM by activation of the PI3K/Akt and NF‐κB signalling pathways via inhibition of EPHB3 and TNFAIP3.

Roles of the m6A Modification of RNA in the Glioblastoma Microenvironment as Revealed by Single-Cell Analyses

Purpose

Glioblastoma multiforme (GBM) is a common and aggressive form of brain tumor. The N⁶-methyladenosine (m⁶A) mRNA modification plays multiple roles in many biological processes and disease states. However, the relationship between m⁶A modifications and the tumor microenvironment in GBM remains unclear, especially at the single-cell level.

Experimental Design

Single-cell and bulk RNA-sequencing data were acquired from the GEO and TCGA databases, respectively. We used bioinformatics and statistical tools to analyze associations between m⁶A regulators and multiple factors.

Results

HNRNPA2B1 and HNRNPC were extensively expressed in the GBM microenvironment. m⁶A regulators promoted the stemness state in GBM cancer cells. Immune-related BP terms were enriched in modules of m⁶A-related genes. Cell communication analysis identified genes in the GALECTIN signaling network in GBM samples, and expression of these genes (LGALS9, CD44, CD45, and HAVCR2) correlated with that of m⁶A regulators. Validation experiments revealed that MDK in MK signaling network promoted migration and immunosuppressive polarization of macrophage. Expression of m⁶A regulators correlated with ICPs in GBM cancer cells, M2 macrophages and T/NK cells. Bulk RNA-seq analysis identified two expression patterns (low m⁶A/high ICP and high m⁶A/low ICP) with different predicted immune infiltration and responses to ICP inhibitors. A predictive nomogram model to distinguish these 2 clusters was constructed and validated with excellent performance.

Conclusion

At the single-cell level, m⁶A modification facilitates the stemness state in GBM cancer cells and promotes an immunosuppressive microenvironment through ICPs and the GALECTIN signaling pathway network. And we also identified two m⁶A-ICP expression patterns. These findings could lead to novel treatment strategies for GBM patients.

Expression and Potential Biomarkers of Regulators for M7G RNA Modification in Gliomas

Gliomas are the most frequent primary malignant brain tumors of the central nervous system, causing significant impairment and death. There is mounting evidence that N7 methylguanosine (m7G) RNA dysmethylation plays a significant role in the development and progression of cancer. However, the expression patterns and function of the m7G RNA methylation regulator in gliomas are yet unknown. The goal of this study was to examine the expression patterns of 31 critical regulators linked with m7G RNA methylation and their prognostic significance in gliomas. To begin, we systematically analyzed patient clinical and prognostic data and mRNA gene expression data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. We found that 17 key regulators of m7G RNA methylation showed significantly higher expression levels in gliomas. We then divided the sample into two subgroups by consensus clustering. Cluster 2 had a poorer prognosis than cluster 1 and was associated with a higher histological grade. In addition, cluster 2 was significantly enriched for cancer-related pathways. Based on this discovery, we developed a risk model involving three m7G methylation regulators. Patients were divided into high-risk and low-risk groups based on risk scores. Overall survival (OS) was significantly lower in the high-risk group than in the low-risk group. Further analysis showed that the risk score was an independent prognostic factor for gliomas.

Modulation of Tumor Immune Microenvironment and Prognostic Value of Ferroptosis-Related Genes, and Candidate Target Drugs in Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is the most common type of malignant brain tumor, among which IDH1-wild type GBM has a poor prognosis. Recent studies have shown that ferroptosis-related genes (FRGs) are correlated with the development and progression of cancer. In GBM, the role of FRGs associated with IDH1 status as biological indicators and therapeutic targets remains to be clarified. Ten of FRGs (STEAP3, HSPB1, MAP1LC3A, SOCS1, LOX, CAPG, CP, GDF15, CDKN1A, and CD44) associated with IDH1 status in GBM were identified as key genes through screening by survival analysis and Random Forest using The Cancer Genome Atlas (TCGA) datasets, and the protein expressions of key genes were verified. Transwell and qPCR results showed that ferroptosis promoted the migration of glioblastoma cells and affected the expression of key genes. Our study established the ferroptosis-related prognostic model for GBM patients based on ten key genes by a different modeling method from previous study, the GSVA algorithm. Further, we took the methods of functional enrichment analysis, clinical characteristics, immune cell infiltration, immunomodulator, ESTIMATE and single nucleotide variant (SNV) analysis to study the molecular mechanisms of prognostic model and key genes. The results showed that ten key genes were strongly associated with immune-related factors and were significantly involved in the p53 signaling pathway, senescence and autophagy in cancer, and in the negative regulation of protein kinase activity. Moreover, potential therapeutic drugs were identified by Virtual Screening and Molecular Docking. Our study indicated that the novel ferrotosis-related prognostic model for GBM patients and key genes possessed the prognostic and therapeutic values.

Identification of N6-Methyladenosine-Related lncRNAs as a Prognostic Signature in Glioma

N6-methyladenosine (m6A) modification is the most abundant modification in long noncoding RNAs (lncRNAs). Current studies have shown that the abnormal expression of m6A-related genes is closely associated with the tumorigenesis and progression of glioma. However, the role of m6A-related lncRNAs in glioma development is still unclear. Herein, we screened 566 m6A-related lncRNAs in glioma from The Cancer Genome Atlas (TCGA) database. The expression pattern of these lncRNAs could cluster samples into two groups, in which various classical tumor-related functions and the tumor immune microenvironment were significantly different. Subsequently, a nine-factor m6A-related lncRNA prognostic signature (MLPS) was constructed by using a LASSO regression analysis in the training set and was validated in the test set and independent datasets. The AUC values of the MLPS were 0.881, 0.918 and 0.887 for 1-, 3- and 5-year survival in the training set, respectively, and 0.856, 0.916 and 0.909 for 1-, 3-, and 5-year survival in the test set, respectively. Stratification analyses of the MLPS illustrated its prognostic performance in gliomas with different characteristics. Correlation analyses showed that the infiltrations of monocytes and tumor-associated macrophages (TAMs) were significantly relevant to the risk score in the MLPS. Moreover, we detected the expression of four MLPS factors with defined sequences in glioma and normal cells by using RT-PCR. Afterwards, we investigated the functions of LNCTAM34A (one of the MLPS factors) in glioma cells, which have rarely been reported. Via in vitro experiments, LNCTAM34A was demonstrated to promote the proliferation, migration and epithelial-mesenchymal transition (EMT) of glioma cells. Overall, our study revealed the critical role of m6A-related lncRNAs in glioma and elucidated that LNCTAM34A could promote glioma proliferation, migration and EMT.

RNA 5-Methylcytosine Regulators Contribute to Metabolism Heterogeneity and Predict Prognosis in Ovarian Cancer

5-Methylcytosine (m⁵C) is an abundant and highly conserved modification in RNAs. The dysregulation of RNA m⁵C methylation has been reported in cancers, but the regulatory network in ovarian cancer of RNA m⁵C methylation-related genes and its implication in metabolic regulation remain largely unexplored. In this study, RNA-sequencing data and clinical information of 374 ovarian cancer patients were downloaded from The Cancer Genome Atlas database, and a total of 14 RNA m⁵C regulators were included. Through unsupervised consensus clustering, two clusters with different m⁵C modification patterns were identified with distinct survivals. According to enrichment analyses, glycosaminoglycan and collagen metabolism–related pathways were specifically activated in cluster 1, whereas fatty acid metabolism–related pathways were enriched in cluster 2, which had better overall survival (OS). Besides the metabolism heterogeneity, the higher sensitivity to platinum and paclitaxel in cluster 2 can further explain the improved OS. Ultimately, a least absolute shrinkage and selection operator prediction model formed by ALYREF, NOP2, and TET2 toward OS was constructed. In conclusion, distinct m⁵C modification pattern exhibited metabolism heterogeneity, different chemotherapy sensitivity, and consequently survival difference, providing evidence for risk stratification.

SPI1-induced downregulation of FTO promotes GBM progression by regulating pri-miR-10a processing in an m6A-dependent manner

As one of the most common post-transcriptional modifications of mRNAs and noncoding RNAs, N⁶-methyladenosine (m⁶A) modification regulates almost every aspect of RNA metabolism. Evidence indicates that dysregulation of m⁶A modification and associated proteins contributes to glioblastoma (GBM) progression. However, the function of fat mass and obesity-associated protein (FTO), an m⁶A demethylase, has not been systematically and comprehensively explored in GBM. Here, we found that decreased FTO expression in clinical specimens correlated with higher glioma grades and poorer clinical outcomes. Functionally, FTO inhibited growth and invasion in GBM cells in vitro and in vivo. Mechanistically, FTO regulated the m⁶A modification of primary microRNA-10a (pri-miR-10a), which could be recognized by reader HNRNPA2B1, recruiting the microRNA microprocessor complex protein DGCR8 and mediating pri-miR-10a processing. Furthermore, the transcriptional activity of FTO was inhibited by the transcription factor SPI1, which could be specifically disrupted by the SPI1 inhibitor DB2313. Treatment with this inhibitor restored endogenous FTO expression and decreased GBM tumor burden, suggesting that FTO may serve as a novel prognostic indicator and therapeutic molecular target of GBM.

The N6-Methylandenosine-Related Gene BIRC5 as a Prognostic Biomarker Correlated With Cell Migration and Immune Cell Infiltrates in Low Grade Glioma

Gliomas account for 75% of all primary malignant brain tumors in adults and are associated with high mortality. Emerging evidence has demonstrated that baculoviral inhibitor of apoptosis repeat containing 5 (BIRC5) plays a critical role in cell apoptosis and the progression of diverse cancers. However, no studies have yet focused on the immunological function and mechanisms of upstream BIRC5 regulation in the progression of low-grade gliomas (LGG). Here, we evaluated BIRC5 expression and clinical characteristics in people with LGG using the Chinese Glioma Genome Atlas, The Cancer Genome Atlas, Gene Expression Omnibus, Rembrandt, and Gravendeel databases. We used Kaplan–Meier statistics and receiver operating characteristic (ROC) curves to analyze the prognostic value of BIRC5 in LGG. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment terms were also explored to identify functional roles of BIRC5. The Tumor Immune Estimation Resource (TIMER) and Tumor Immune System Interaction (TISIDB) databases were used to examine the correlation between BIRC5 expression and immune cell infiltration in LGG. The Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal (CTRP) databases were used to examine the potential drugs targeting BIRC5. We used transwell and wound healing assays to determine the biological functions of BIRC5 in glioma cell migration. Our results demonstrated that BIRC5 was highly expressed in LGG and the expression level correlated with tumor grade, prognosis, histological subtype, isocitrate dehydrogenase 1 (IDH1) mutation, 1p/19q chromosomal co-deletion, chemotherapy status, and O[6]-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. GO and KEGG analysis showed that BIRC5 is primarily involved in cell proliferation and immune response-related signaling pathways. We also found that BIRC5 was significantly correlated with m6A modification and diverse drug sensitivity. TIMER and TISIDB database analysis showed that BIRC5 expression is associated with infiltration of diverse immune cells and immune modulation in LGG. BIRC5 knockdown inhibited LGG cell migration. Collectively, our results demonstrate that BIRC5 is correlated with cell migration and immune infiltration in LGG and may be a useful prognostic biomarker.

PGM1 and ENO1 Promote the Malignant Progression of Bladder Cancer via Comprehensive Analysis of the m6A Signature and Tumor Immune Infiltration

Background

While N⁶-methyladenosine (m6A) modification of RNA and the tumor immune microenvironment both influence the progression of cancer, little attention has been paid to interactions between these two factors. Thus, we systematically explored potential biomarkers in the malignant progression of bladder urothelial carcinoma (BLCA) via combining expression of m6A methylation regulators with tumor immune infiltration.

Methods

We extracted m6A regulators from published literature, downloaded BLCA RNA-seq and clinical information from the Cancer Genome Atlas database, and integrated three main bioinformatic methods and qPCR to explore the biological variations in the malignant progression of BLCA.

Results

FTO, IGF2BP3, and YTHDC1 have a significant difference in bladder cancer and prognosis. Two subgroups (clusters 1 and 2) were identified according to three key m6A regulators; cluster 1 was preferentially associated with poor prognosis and immune infiltration relative to cluster 2 significantly. We further identified PGM1 and ENO1 as potential prognostic biomarkers, as they were correlated with FTO and IGF2BP3 positively but with YTHDC1, negatively. M2 macrophage and TFH cells were highly infiltrated in BLCA and were associated with BLCA prognosis. Finally, PGM1 and ENO1 were correlated with M2 macrophage and TFH cells and their surface markers CD163and CXCR5.

Conclusions

PGM1 and ENO1 are highly correlated with the malignant progression of BLCA, and the expression of these genes may be new indicators for the diagnosis and prognosis of BLCA.