m6A regulator-mediated methylation modification patterns and characteristics of immunity and stemness in low-grade glioma

NSUN4 mediated RNA 5-methylcytosine promotes the malignant progression of glioma through improving the CDC42 mRNA stabilization

5-Methylcytosine (m5C) methylation is a significant post-transcriptional modification that play a crucial role in the development and progression of numerous cancers. Whereas the functions and molecular mechanisms underlying m5C methylation in gliomas remain unclear. This study dedicated to explore changes of m5C levels and the clinical significance of the m5C writer NSUN4 in gliomas. We found that high m5C levels were negatively related to prognosis of patients with glioma. Moreover, gain- and loss-of-function experiments revealed the role of NSUN4 in enhancing m5C modification of mRNA to promote the malignant progression of glioma. Mechanistically speaking, NSUN4-mediated m5C alterations regulated ALYREF binding to CDC42 mRNA, thereby impacting the mRNA stability of CDC42. We also demonstrated that CDC42 promoted glioma proliferation, migration, and invasion by activating the PI3K-AKT signaling pathway. Additionally, rescue experiments proved that CDC42overexpression weaken the inhibitory effect of NSUN4 knockdown on the malignant progression of gliomas in vitro and in vivo. Our findings elucidate that NSUN4-mediated high m5C levels promote ALYREF binding to CDC42 mRNA and regulate its stability, thereby driving the malignant progression of glioma. This provides theoretical support for targeted the treatment of gliomas.

Regulatory roles of N6-methyladenosine (m6A) methylation in RNA processing and non-communicable diseases

Post-transcriptional RNA modification is an emerging epigenetic control mechanism in cells that is important in many different cellular and organismal processes. N6-methyladenosine (m6A) is one of the most prevalent, prolific, and ubiquitous internal transcriptional alterations in eukaryotic mRNAs, making it an important topic in the field of Epigenetics. m6A methylation acts as a dynamical regulatory process that regulates the activity of genes and participates in multiple physiological processes, by supporting multiple aspects of essential mRNA metabolic processes, including pre-mRNA splicing, nuclear export, translation, miRNA synthesis, and stability. Extensive research has linked aberrations in m6A modification and m6A-associated proteins to a wide range of human diseases. However, the impact of m6A on mRNA metabolism and its pathological connection between m6A and other non-communicable diseases, including cardiovascular disease, neurodegenerative disorders, liver diseases, and cancer remains in fragmentation. Here, we review the existing understanding of the overall role of mechanisms by which m6A exerts its activities and address new discoveries that highlight m6A's diverse involvement in gene expression regulation. We discuss m6A deposition on mRNA and its consequences on degradation, translation, and transcription, as well as m6A methylation of non-coding chromosomal-associated RNA species. This study could give new information about the molecular process, early detection, tailored treatment, and predictive evaluation of human non-communicable diseases like cancer. We also explore more about new data that suggests targeting m6A regulators in diseases may have therapeutic advantages.

m6A methylation modification and immune infiltration analysis in osteonecrosis of the femoral head

Osteonecrosis of the femoral head (ONFH) is a elaborate hip disease characterized by collapse of femoral head and osteoarthritis. RNA N6-methyladenosine (m6A) plays a crucial role in a lot of biological processes within eukaryotic cells. However, the role of m6A in the regulation of ONFH remains unclear. In this study, we identified the m6A regulators in ONFH and performed subtype classification. We identified 7 significantly differentially expressed m6A regulators through the analysis of differences between ONFH and normal samples in the Gene Expression Omnibus (GEO) database. A random forest algorithm was employed to monitor these regulators to assess the risk of developing ONFH. We constructed a nomogram based on these 7 regulators. The decision curve analysis suggested that patients can benefit from the nomogram model. We classified the ONFH samples into two m6A models according to these 7 regulators through consensus clustering algorithm. After that, we evaluated those two m6A patterns using principal component analysis. We assessed the scores of those two m6A patterns and their relationship with immune infiltration. We observed a higher m6A score of type A than that of type B. Finally, we performed a cross-validation of crucial m6A regulatory factors in ONFH using external datasets and femoral head bone samples. In conclusion, we believed that the m6A pattern could provide a novel diagnostic strategy and offer new insights for molecularly targeted therapy of ONFH.

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.

m6A demethylase FTO and osteoporosis: potential therapeutic interventions

Osteoporosis is a common bone disease, characterized by a descent in bone mass due to the dysregulation of bone homeostasis. Although different studies have identified an association between osteoporosis and epigenetic alterations in osteogenic genes, the mechanisms of osteoporosis remain unclear. N6-methyladenosine (m6A) modification is a methylated adenosine nucleotide, which regulates the translocation, exporting, translation, and decay of RNA. FTO is the first identified m6A demethylase, which eliminates m6A modifications from RNAs. Variation in FTO disturbs m6A methylation in RNAs to regulate cell proliferation, differentiation, and apoptosis. Besides, FTO as an obesity-associated gene, also affects osteogenesis by regulating adipogenesis. Pharmacological inhibition of FTO markedly altered bone mass, bone mineral density and the distribution of adipose tissue. Small molecules which modulate FTO function are potentially novel remedies to the treatment of osteoporosis by adjusting the m6A levels. This article reviews the roles of m6A demethylase FTO in regulating bone metabolism and osteoporosis.

Identification of m6A-associated genes as prognostic and immune-associated biomarkers in Wilms tumor

OBJECTIVES

Wilms tumor (WT) is a common renal malignant tumor in children. We aimed to investigate the potential prognostic value of m6A-related genes and their relationship to the immune microenvironment in WT.

METHODS

RNA-seq data and clinical information from 121 WT and 6 normal samples were obtained from the University of California Santa Cruz Xena database. We used various bioinformatics analysis tools to analyze these data and verify the expression level of m6A-related genes by experiments.

RESULTS

Four m6A-related genes were successfully screened, including ADGRG2, CPD, CTHRC1, and LRTM2. Kaplan-Meier survival curves showed that the four genes were closely related to the prognosis of WT, which was also confirmed by receiver operator characteristic curves. Subsequently, in the immune microenvironment of WT, we discovered that Th1_cells were positively correlated with ADGRG2, CCR was negatively correlated with CPD, CCR was positively correlated with CTHRC1, APC_co_stimulation, CCR, Macrophages, inflammation-promoting cells, Treg, and Type_II_IFN_Reponse were negatively correlated with LRTM2. Finally, qRT-PCR showed that expression levels of the four genes were upregulated in the nephroblastoma cell lines (G-401, SK-NEP-1, and WT-CLS1) compared with the human embryonic kidney cell lines (293T).

CONCLUSIONS

Taken together, our study first time screened the m6A-related genes and revealed that ADGRG2, CPD, CTHRC1, and LRTM2 are the prognostic and immune-associated biomarkers in WT.

Establishment of a prognostic model based on m6A regulatory factors and stemness of hepatocellular carcinoma using RNA-seq data and scRNA-seq data

BACKGROUND

Hepatocellular carcinoma (HCC) with high incidence and mortality is one of the most common malignant cancers worldwide. Increasing evidence has reported that N6-methyladenosine (m6A) modification has been considered as a major contribution to the occurrence and development of tumors.

METHOD

In our study, we comprehensively analyzed the connection between m6A regulatory factors and cancer stem cells (CSCs) of HCC to establish a clinical tool for predicting its outcome. First, we concluded that the expression level of m6A regulatory factors was related with the stemness of hepatocellular carcinoma. Subsequently, we gained a ten hub regulatory factors that were associated with prognosis of hepatocellular carcinoma by overall survival (OS) analysis using ICGC and TCGA datasets, and these regulatory factors included YTHDF1, IGF2BP1, METTL3, IGF2BP3, HNRNPA2B1, IGF2BP2, RBM15B, HNRNPC, RBMX, and LRPPR. Next, we found that these ten hub m6A regulatory factors were highly expressed in CSCs, and CSCs related pathways were also enriched by the gene set variation analysis (GSVA). Then, correlation, consensus clustering and PCA analysis were performed to reveal potential therapeutic benefits of HCC. Moreover, univariate Cox regression (UNICOX), LASSON and multivariate Cox regression (MULTICOX) analyses were adopted to establish HCC prognosis prediction signature.

RESULTS

Four regulatory factors RBM15B, LRPPRC, IGF2BP1, and IGF2BP3 were picked as valuable prognostic indicators.

CONCLUSION

In summary, these ten hub regulatory factors would be useful therapeutic targets for HCC treatment, and RBM15B/LRPPRC/IGF2BP1/IGF2BP3 prognostic indicators can be used to guide therapy for HCC patients.

Genome-wide identification and functional analysis of dysregulated alternative splicing profiles in sepsis

BACKGROUND

An increasing body of evidence now shows that the long-term mortality of patients with sepsis are associated with various sepsis-related immune cell defects. Alternative splicing (AS), as a sepsis-related immune cell defect, is considered as a potential immunomodulatory therapy target to improve patient outcomes. However, our understanding of the role AS plays in sepsis is currently insufficient.

AIM

This study investigated possible associations between AS and the gene regulatory networks affecting immune cells. We also investigated apoptosis and AS functionality in sepsis pathophysiology.

METHODS

In this study, we assessed publicly available mRNA-seq data that was obtained from the NCBI GEO dataset (GSE154918), which included a healthy group (HLTY), a mild infection group (INF1), asepsis group (Seps), and a septic shock group (Shock). A total of 79 samples (excluding significant outliers) were identified by a poly-A capture method to generate RNA-seq data. The variable splicing events and highly correlated RNA binding protein (RBP) genes in each group were then systematically analyzed.

RESULTS

For the first time, we used systematic RNA-seq analysis of sepsis-related AS and identified 1505 variable AS events that differed significantly (p <= 0.01) across the four groups. In the sepsis group, the genes related to significant AS events, such as, SHISA5 and IFI27, were mostly enriched in the cell apoptosis pathway. Furthermore, we identified differential splicing patterns within each of the four groups. Significant differences in the expression of RNA Binding Protein(RBP) genes were observed between the control group and the sepsis group. RBP gene expression was highly correlated with variant splicing events in sepsis, as determined by co-expression analysis; The expression of DDX24, CBFA2T2, NOP, ILF3, DNMT1, FTO, PPRC1, NOLC1 RBPs were significant reduced in sepsis compared to the healthy group. Finally, we constructed an RBP-AS functional network.

CONCLUSION

Analysis indicated that the RBP-AS functional network serves as a critical post-transcriptional mechanism that regulates the development of sepsis. AS dysregulation is associated with alterations in the regulatory gene expression network that is involved in sepsis. Therefore, the RBP-AS expression network could be useful in refining biomarker predictions in the development of new therapeutic targets for the pathogenesis of sepsis.

M6A regulator methylation patterns and characteristics of immunity in acute ST-segment elevation myocardial infarction

M6A methylation is the most prevalent and abundant RNA modification in mammals. Although there are many studies on the regulatory role of m6A methylation in the immune response, the m6A regulators in the pathogenesis of acute ST-segment elevation myocardial infarction (STEMI) remain unclear. We comprehensively analysed the role of m6A regulators in STEMI and built a predictive model, revealing the relationship between m6A methylations and the immune microenvironment. Differential analysis revealed that 18 of 24 m6A regulators were significantly differentially expressed, and there were substantial interactions between the m6A regulator. Then, we established a classifier and nomogram model based on 6 m6A regulators, which can easily distinguish the STEMI and control samples. Finally, two distinct m6A subtypes were obtained and significantly differentially expressed in terms of infiltrating immunocyte abundance, immune reaction activity and human leukocyte antigen genes. Three hub m6A phenotype related genes (RAC2, RELA, and WAS) in the midnightblue module were identified by weighted gene coexpression network analysis, and were associated with immunity. These findings suggest that m6A modification and the immune microenvironment play a key role in the pathogenesis of STEMI.

The Comprehensive Analysis of m6A-Associated Anoikis Genes in Low-Grade Gliomas

The relationship between N6-methyladenosine (m6A) regulators and anoikis and their effects on low-grade glioma (LGG) is not clear yet. The TCGA-LGG cohort, mRNAseq 325 dataset, and GSE16011 validation set were separately obtained via the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Altas (CGGA), and Gene Expression Omnibus (GEO) databases. In total, 27 m6A-related genes (m6A-RGs) and 508 anoikis-related genes (ANRGs) were extracted from published articles individually. First, differentially expressed genes (DEGs) between LGG and normal samples were sifted out by differential expression analysis. DEGs were respectively intersected with m6A-RGs and ANRGs to acquire differentially expressed m6A-RGs (DE-m6A-RGs) and differentially expressed ANRGs (DE-ANRGs). A correlation analysis of DE-m6A-RGs and DE-ANRGs was performed to obtain DE-m6A-ANRGs. Next, univariate Cox and least absolute shrinkage and selection operator (LASSO) were performed on DE-m6A-ANRGs to sift out risk model genes, and a risk score was gained according to them. Then, gene set enrichment analysis (GSEA) was implemented based on risk model genes. After that, we constructed an independent prognostic model and performed immune infiltration analysis and drug sensitivity analysis. Finally, an mRNA-miRNA-lncRNA regulatory network was constructed. There were 6901 DEGs between LGG and normal samples. Six DE-m6A-RGs and 214 DE-ANRGs were gained through intersecting DEGs with m6A-RGs and ANRGs, respectively. A total of 149 DE-m6A-ANRGs were derived after correlation analysis. Four genes, namely ANXA5, KIF18A, BRCA1, and HOXA10, composed the risk model, and they were involved in apoptosis, fatty acid metabolism, and glycolysis. The age and risk scores were finally sifted out to construct an independent prognostic model. Activated CD4 T cells, gamma delta T cells, and natural killer T cells had the largest positive correlations with risk model genes, while activated B cells were significantly negatively correlated with KIF18A and BRCA1. AT.9283, EXEL.2280, Gilteritinib, and Pracinostat had the largest correlation (absolute value) with a risk score. Four risk model genes (mRNAs), 12 miRNAs, and 21 lncRNAs formed an mRNA-miRNA-lncRNA network, containing HOXA10-hsa-miR-129-5p-LINC00689 and KIF18A-hsa-miR-221-3p-DANCR. Through bioinformatics, we constructed a prognostic model of m6A-associated anoikis genes in LGG, providing new ideas for research related to the prognosis and treatment of LGG.

m6A genotypes and prognostic signature for assessing the prognosis of patients with acute myeloid leukemia

BACKGROUND

N6-methyladenosine (m6A) has been confirmed to function critically in acute myeloid leukemia (AML) progression. Hitherto, the subtyping and prognostic predictive significance of m6A-correlated genes in AML is unclear.

METHOD

From The Cancer Genome Atlas (TCGA-LAML), Therapeutically Applicable Research to Generate Effective Treatments (TARGET-AML) and Gene Expression Omnibus (GEO, GSE71014) databases, we collected the sequencing data of AML patients. The batch effect was removed via limma package for TCGA-LAML and TARGET-AML, and the aggregated samples were AML cohorts. Samples in the AML cohort identified m6A models in AML by consensus clustering based on 23-m6A-related modulators. M6A-related differentially expressed genes (m6ARDEGs) influencing the overall survival (OS) of AML were determined by performing differential expression analysis and univariate COX analysis, and consensus-based clustering was utilized to access AML molecular subtypes. LASSO and multivariate COX analyses were performed to obtain the optimized m6ARDEGs to construct the m6A Prognostic Risk Score (m6APR_Score). Whether the model was robust was evaluated according to Kaplan-Meier (K-M) and receiver operator characteristic (ROC) curves. Further, the abundance of immune cell infiltration was explored in different m6A modification patterns and molecular subtypes and m6APR_Score groupings. Finally, nomogram was constructed to predict OS in AML. Quantitative real-time polymerase chain reaction (RT-qPCR) and cell counting kit-8 (CCK-8) assay were used to validate the genes in m6APR_Score in AML cells.

RESULTS

The m6A models (m6AM1, m6AM2, m6AM3) and molecular subtypes (C1, C2, C3) were identified in the AML cohort, exhibiting different prognosis and immunoreactivity. We recognized novel prognostic biomarkers of AML such as CD83, NRIP1, ACSL1, METTL7B, OGT, and C4orf48. AML patients were grouped into high-m6APR_Score and low-m6APR_Score groups, with the later group showing a better prognosis than former one. Both the AML cohort and the validation cohort GSE71014 demonstrated excellent prediction. Finally, the nomogram accurately predicted the survival of patients suffering from AML. Further, the decision curves showed that both nomogram and m6APR_Score showed excellent prediction. It was confirmed in vitro experiments that mRNA expressions of NRIP1, ACSL1, METTL7B and OGT were elevated, while CD83 and C4orf48 mRNA expressions downregulated in AML cells. A significant increase in the viability of U937 and THP-1 cell lines after inhibition of CD83, while siMETTL7B had contrast results.

CONCLUSION

Our study demonstrated that m6APR_Score and CD83, NRIP1, ACSL1, METTL7B, OGT, and C4orf48 potentially provided novel and promising prognostic support for AML patients.

Oncofetal protein IGF2BPs in human cancer: functions, mechanisms and therapeutic potential

N⁶-methyladenosine (m⁶A) is the most prevalent and well-characterized internal chemical modification in eukaryotic RNA, influencing gene expression and phenotypic changes by controlling RNA fate. Insulin-like growth factor-2 mRNA-binding proteins (IGF2BPs) preferentially function as m⁶A effector proteins, promoting stability and translation of m⁶A-modified RNAs. IGF2BPs, particularly IGF2BP1 and IGF2BP3, are widely recognized as oncofetal proteins predominantly expressed in cancer rather than normal tissues, playing a critical role in tumor initiation and progression. Consequently, IGF2BPs hold potential for clinical applications and serve as a good choice for targeted treatment strategies. In this review, we discuss the functions and mechanisms of IGF2BPs as m⁶A readers and explore the therapeutic potential of targeting IGF2BPs in human cancer.

Integrating machine learning and bioinformatics analysis to m6A regulator-mediated methylation modification models for predicting glioblastoma patients' prognosis and immunotherapy response

BACKGROUND

Epigenetic regulations of immune responses are essential for cancer development and growth. As a critical step, comprehensive and rigorous explorations of m6A methylation are important to determine its prognostic significance, tumor microenvironment (TME) infiltration characteristics and underlying relationship with glioblastoma (GBM).

METHODS

To evaluate m6A modification patterns in GBM, we conducted unsupervised clustering to determine the expression levels of GBM-related m6A regulatory factors and performed differential analysis to obtain m6A-related genes. Consistent clustering was used to generate m6A regulators cluster A and B. Machine learning algorithms were implemented for identifying TME features and predicting the response of GBM patients receiving immunotherapy.

RESULTS

It is found that the m6A regulatory factor significantly regulates the mutation of GBM and TME. Based on Europe, America, and China data, we established m6Ascore through the m6A model. The model accurately predicted the results of 1206 GBM patients from the discovery cohort. Additionally, a high m6A score was associated with poor prognoses. Significant TME features were found among the different m6A score groups, which demonstrated positive correlations with biological functions (i.e., EMT2) and immune checkpoints.

CONCLUSIONS

m6A modification was important to characterize the tumorigenesis and TME infiltration in GBM. The m6Ascore provided GBM patients with valuable and accurate prognosis and prediction of clinical response to various treatment modalities, which could be useful to guide patient treatments.

Ubiquitin-proteasome system-mediated ubiquitination modification patterns and characterization of tumor microenvironment infiltration, stemness and cellular senescence in low-grade glioma

The Ubiquitin-proteasome system (UPS) performs a crucial role in immune activation and tumorigenesis. Nevertheless, the comprehensive role of the ubiquitin-proteasome system in the low-grade glioma (LGG) tumor microenvironment (TME) remains unknown. Ubiquitination modification patterns in LGG patients and corresponding characteristics of tumor immune traits, CSC stemness, and cellular senescence were evaluated via a comprehensive analysis of 20 ubiquitination modification regulators. For quantification of the ubiquitination modification status of individual patients, the UM-score was constructed and associated with TME characteristics, clinical features, cancer stem cell stemness, cellular senescence, prognosis, and immunotherapy efficacy. We identified that alterations in multiple ubiquitination regulators are linked to patient survival and the shaping of the tumor microenvironment. We found two different styles of ubiquitination modification in patients with low-grade glioma (immune-inflamed differentiation and immune-exclude dedifferentiation), characterized by high and low UM-score, and the two regulatory patterns of ubiquitination modification on immunity, stemness feature, and cellular senescence. We demonstrate that the UM-score could forecast the subtype of LGG, the immunologic infiltration traits, the biological process, the stemness feature, and the cellular senescence trait. Notably, the UM-score was related to immunotherapeutic efficacy, implying that modifying ubiquitination modification patterns by targeting ubiquitination modification regulators or ubiquitination modification pattern signature genes to reverse unfavorable TME properties will provide new insights into cancer immunotherapy. This research indicated that the ubiquitin-proteasome system is crucial in the formation of TME complexity and multiformity. The UM-score can determine ubiquitination modification status in individual patients, bringing about more personalized and effective immunotherapeutic tactics.

Integrative analysis to screen novel pyroptosis-related LncRNAs for predicting clinical outcome of glioma and validation in tumor tissue

BACKGROUND

Pyroptosis, also known as inflammatory necrosis, is a programmed cell death that manifests itself as a continuous swelling of cells until the cell membrane breaks, leading to the liberation of cellular contents, which triggers an intense inflammatory response. Pyroptosis might be a panacea for a variety of cancers, which include immunotherapy and chemotherapy-insensitive tumors such as glioma. Several findings have observed that long non-coding RNAs (lncRNAs) modulate the bio-behavior of tumor cells by binding to RNA, DNA and protein. Nevertheless, there are few studies reporting the effect of lncRNAs in pyroptosis processes in glioma.

METHODS

The principal goal of this study was to identify pyroptosis-related lncRNAs (PRLs) utilizing bioinformatic algorithm and to apply PCR techniques for validation in human glioma tissues. The second goal was to establish a prognostic model for predicting the overall survival patients with glioma. Predict algorithm was used to construct prognosis model with good diagnostic precision for potential clinical translation.

RESULTS

Noticeably, molecular subtypes categorized by the PRLs were not distinct from any previously published subtypes of glioma. The immune and mutation landscapes were obviously different from previous subtypes of glioma. Analysis of the sensitivity (IC50) of patients to 30 chemotherapeutic agents identified 22 agents as potential therapeutic agents for patients with low riskscores.

CONCLUSIONS

We established an exact prognostic model according to the expression profile of PRLs, which may facilitate the assessment of patient prognosis and treatment patterns and could be further applied to clinical.

N6-methyladenosine (m6A) as a regulator of carcinogenesis and drug resistance by targeting epithelial-mesenchymal transition and cancer stem cells

Emergence of drug resistance to chemotherapeutic agents is the principal obstacle towards curative cancer treatment in human cancer patients. It is in an urgent to explore the underlying molecular mechanisms to overcome the drug resistance. N6-Methyladenosine (m6A) RNA modification is the most abundant reversible RNA modification and has emerged in recent years to regulate gene expression in eukaryotes. Recent evidence has identified m6A is associated with cancer pathogenesis and drug resistance, contributing to the self-renewal and differentiation of cancer stem cell, tumor epithelial-mesenchymal transition (EMT) and tumor metastasis. Here we reviewed up-to-date knowledge of the relationship between m6A modulation and drug resistance. Furthermore, we illustrated the underlying mechanisms of m6A modulation in drug resistance. Lastly, we discussed the regulation of m6A modulation in EMT and cancer stem cells. Hence, it will help to provide significant therapeutic strategies to overcome drug resistance for cancer patients by changing m6A-related proteins via targeting cancer stem cells and EMT-phenotypic cells.

Role of NAT10-mediated ac4C-modified HSP90AA1 RNA acetylation in ER stress-mediated metastasis and lenvatinib resistance in hepatocellular carcinoma

Emerging evidence showed that epigenetic regulation plays important role in the pathogenesis of HCC. N4-acetocytidine (ac4C) was an acetylation chemical modification of mRNA, and NAT10 is reported to regulate ac4C modification and enhance endoplasmic reticulum stress (ERS) in tumor metastasis. Here, we report a novel mechanism by which NAT10-mediated mRNA ac4C-modified HSP90AA1 regulates metastasis and tumor resistance in ERS of HCC. Immunohistochemical, bioinformatics analyses, and in vitro and in vivo experiments, e.g., acRIP-Seq, RNA-Seq, and double luciferase reporter experiment, were employed to investigate the effect of NAT10 on metastasis and drug resistance in HCC. The increased expression of NAT10 was associated with HCC risk and poor prognosis. Cell and animal experiments showed that NAT10 enhanced the metastasis ability and apoptosis resistance of HCC cells in ERS and ERS state. NAT10 could upregulate the modification level of HSP90AA1 mRNA ac4C, maintain the stability of HSP90AA1, and upregulate the expression of HSP90AA1, which further promotes the metastasis of ERS hepatoma cells and the resistance to apoptosis of Lenvatinib. This study proposes a novel mechanism by which NAT10-mediated mRNA ac4C modification regulates tumor metastasis. In addition, we demonstrated the regulatory effect of NAT10-HSP90AA1 on metastasis and drug resistance of ERS in HCC cells.

Identification of m6a-related signature genes in esophageal squamous cell carcinoma by machine learning method

Background: We aimed to construct and validate the esophageal squamous cell carcinoma (ESCC)-related m6A regulators by means of machine leaning. Methods: We used ESCC RNA-seq data of 66 pairs of ESCC from West China Hospital of Sichuan University and the transcriptome data extracted from The Cancer Genome Atlas (TCGA)-ESCA database to find out the ESCC-related m6A regulators, during which, two machine learning approaches: RF (Random Forest) and SVM (Support Vector Machine) were employed to construct the model of ESCC-related m6A regulators. Calibration curves, clinical decision curves, and clinical impact curves (CIC) were used to evaluate the predictive ability and best-effort ability of the model. Finally, western blot and immunohistochemistry staining were used to assess the expression of prognostic ESCC-related m6A regulators. Results: 2 m6A regulators (YTHDF1 and HNRNPC) were found to be significantly increased in ESCC tissues after screening out through RF machine learning methods from our RNA-seq data and TCGA-ESCA database, respectively, and overlapping the results of the two clusters. A prognostic signature, consisting of YTHDF1 and HNRNPC, was constructed based on our RNA-seq data and validated on TCGA-ESCA database, which can serve as an independent prognostic predictor. Experimental validation including the western and immunohistochemistry staining were further successfully confirmed the results of bioinformatics analysis. Conclusion: We constructed prognostic ESCC-related m6A regulators and validated the model in clinical ESCC cohort as well as in ESCC tissues, which provides reasonable evidence and valuable resources for prognostic stratification and the study of potential targets for ESCC.

Construction of a ferroptosis scoring system and identification of LINC01572 as a novel ferroptosis suppressor in lung adenocarcinoma

Background: Ferroptosis is a novel process of programmed cell death driven by excessive lipid peroxidation that is associated with the development of lung adenocarcinoma. N6-methyladenosine (m6a) modification of multiple genes is involved in regulating the ferroptosis process, while the predictive value of N6-methyladenosine- and ferroptosis-associated lncRNA (FMRlncRNA) in the prognosis of patients remains with LUAD remains unknown. Methods: Unsupervised cluster algorithm was applied to generate subcluster in LUAD according to ferroptosis-associated lncRNA. Stepwise Cox analysis and LASSO algorithm were applied to develop a prognostic model. Cellular location was detected by single-cell analysis. Also, we conducted Gene set enrichment analysis (GSEA) enrichment, immune microenvironment and drug sensitivity analysis. In addition, the expression and function of the LINC01572 were investigated by several in vitro experiments including qRT-PCR, cell viability assays and ferroptosis assays. Results: A novel ferroptosis-associated lncRNAs-based molecular subtype containing two subclusters were determined in LUAD. Then, we successfully created a risk model according to five ferroptosis-associated lncRNAs (LINC00472, MBNL1-AS1, LINC01572, ZFPM2-AS1, and TMPO-AS1). Our nominated model had good stability and predictive function. The expression patterns of five ferroptosis-associated lncRNAs were confirmed by polymerase chain reaction (PCR) in LUAD cell lines. Knockdown of LINC01572 significantly inhibited cell viability and induced ferroptosis in LUAD cell lines. Conclusion: Our data provided a risk score system based on ferroptosis-associated lncRNAs with prognostic value in LUAD. Moreover, LINC01572 may serve as a novel ferroptosis suppressor in LUAD.

Analysis of m6A modulator-mediated methylation modification patterns and the tumor microenvironment in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer. In the development and progression of LUAD, epigenetic aberration plays a crucial role. However, the function of RNA N6-methyladenosine (m⁶A) modifications in the LUAD progression is unknown. The m6A regulator modification patterns in 955 LUAD samples were analyzed comprehensively. Patterns were systematically correlated with the tumor microenvironment (TME) cell-infiltration characteristics. Using principal component analysis algorithms, the m6Ascore was generated to quantify m⁶A modification patterns in individual tumors. Then, their values for predicting prognoses and therapeutic response in LUAD patients were assessed. Three distinct m⁶A modification patterns in LUAD were identified. Among them, the prognosis of m6Acluster C was the best, while the prognosis of m⁶Acluster A was the worst. Interestingly, the characterization of TME cell infiltration and biological behavior differed among the three patterns. To evaluate m⁶A modification patterns within individual tumors, an m⁶Ascore signature was constructed. The results showed that the high m⁶Ascore group was associated with a better prognosis; tumor somatic mutations and tumor microenvironment differed significantly between the high- and low- m⁶Ascore groups. Furthermore, in the cohort with anti-CTLA-4 treatment alone, patients with a high m⁶Ascore had higher ICI scores, which indicated significant therapeutic advantage and clinical benefits.

Construction of m6A-based prognosis signature and prediction for immune and anti-angiogenic response

Background: Increasing evidence illustrated that m6A regulator-mediated modification plays a crucial role in regulating tumor immune and angiogenesis microenvironment. And the combination of immune checkpoint inhibitor and anti-angiogenic therapy has been approved as new first-line therapy for advanced HCC. This study constructed a novel prognosis signature base on m6A-mediated modification and explored the related mechanism in predicting immune and anti-angiogenic responses.

Methods: Gene expression profiles and clinical information were collected from TCGA and GEO. The ssGSEA, MCPCOUNT, and TIMER 2.0 algorithm was used to Estimation of immune cell infiltration. The IC₅₀ of anti-angiogenic drugs in GDSC was calculated by the “pRRophetic” package. IMvigor210 cohort and Liu et al. cohort were used to validate the capability of immunotherapy response. Hepatocellular carcinoma single immune cells sequencing datasets GSE140228 were collected to present the expression landscapes of 5 hub genes in different sites and immune cell subpopulations of HCC patients.

Results: Three m6A clusters with distinct immune and angiogenesis microenvironments were identified by consistent cluster analysis based on the expression of m6A regulators. We further constructed a 5-gene prognosis signature (termed as m6Asig-Score) which could predict both immune and anti-angiogenic responses. We illustrated that high m6Asig-Score is associated with poor prognosis, advanced TNM stage, and high TP53 mutation frequency. Besides, the m6Asig-Score was negatively associated with immune checkpoint inhibitors and anti-angiogenic drug response. We further found that two of the five m6Asig-Score inner genes, B2M and SMOX, were associated with immune cell infiltration, immune response, and the sensitivity to sorafenib, which were validated in two independent immunotherapy cohorts and the Genomics of Drug Sensitivity in Cancer (GDSC) database.

Conclusion: We constructed a novel prognosis signature and identified B2M and SMOX for predicting immune and anti-angiogenic efficacy in HCC, which may guide the combined treatment strategies of immunotherapy and anti-angiogenic therapy in HCC.

PCBP2 Reduced Oxidative Stress-Induced Apoptosis in Glioma through cGAS/STING Pathway by METTL3-Mediated m6A Modification

Purpose

The most prevalent primary malignant tumor of CNS is glioma, which has a dismal prognosis. The theory of oxidative stress is one of the important theories in the study of its occurrence and development mechanism. In this study, the impacts of PCBP2 on glioma sufferers and the possible mechanisms were examined.

Methods

Patients with glioma were obtained from May 2017 to July 2018. Quantitative PCR, microarray analysis, western blot analysis, and immunofluorescence were used in this experiment.

Results

PCBP2 mRNA expression level and protein expression in patients with glioma were upregulated compared with paracancerous tissue. OS and DFS of PCBP2 low expression in patients with glioma were higher than those of PCBP2 high expression. PCBP2 promoted the progression and metastasis of glioma. PCBP2 reduced oxidative stress-induced apoptosis of glioma. PCBP2 suppressed the cGAS/STING pathway of glioma. PCBP2 protein interlinked with cGAS and cGAS was one target for PCBP2. METTL3-mediated m6A modification increases PCBP2 stability.

Conclusion

Along the cGAS-STING signal pathway, PCBP2 decreased the apoptosis that oxidative stress-induced glioma caused, which might be a potential target to suppress oxidative stress-induced apoptosis of glioma.

The regulation and potential roles of m6A modifications in early embryonic development and immune tolerance at the maternal-fetal interface

The immune microenvironment at the maternal-fetal interface was determined by the crosstalk between the trophoblast and maternal-derived cells, which dynamically changed during the whole gestation. Trophoblasts act as innate immune cells and dialogue with maternal-derived cells to ensure early embryonic development, depending on the local immune microenvironment. Therefore, dysfunctions in trophoblasts and maternal decidual cells contribute to pregnancy complications, especially recurrent pregnancy loss in early pregnancy. Since many unknown regulatory factors still affect the complex immune status, exploring new potential aspects that could influence early pregnancy is essential. RNA methylation plays an important role in contributing to the transcriptional regulation of various cells. Sufficient studies have shown the crucial roles of N6-methyladenosine (m6A)- and m6A-associated- regulators in embryogenesis during implantation. They are also essential in regulating innate and adaptive immune cells and the immune response and shaping the local and systemic immune microenvironment. However, the function of m6A modifications at the maternal-fetal interface still lacks wide research. This review highlights the critical functions of m6A in early embryonic development, summarizes the reported research on m6A in regulating immune cells and tumor immune microenvironment, and identifies the potential value of m6A modifications in shaping trophoblasts, decidual immune cells, and the microenvironment at the maternal-fetal interface. The m6A modifications are more likely to contribute to embryogenesis, placentation and shape the immune microenvironment at the maternal-fetal interface. Uncovering these crucial regulatory mechanisms could provide novel therapeutic targets for RNA methylation in early pregnancy.

Cross-talk of four types of RNA modification proteins with adenosine reveals the landscape of multivariate prognostic patterns in breast cancer

Background: Breast cancer (BC) is the most common malignant tumour, and its heterogeneity is one of its major characteristics. N6-methyladenosine (m6A), N1-methyladenosine (m1A), alternative polyadenylation (APA), and adenosine-to-inosine (A-to-I) RNA editing constitute the four most common adenosine-associated RNA modifications and represent the most typical and critical forms of epigenetic regulation contributing to the immunoinflammatory response, tumorigenesis and tumour heterogeneity. However, the cross-talk and potential combined profiles of these RNA-modified proteins (RMPs) in multivariate prognostic patterns of BC remain unknown.

Methods: A total of 48 published RMPs were analysed and found to display significant expression alterations and genomic mutation rates between tumour and normal tissues in the TCGA-BRCA cohort. Data from 4188 BC patients with clinical outcomes were downloaded from the Gene Expression Omnibus (GEO), the Cancer Genome Atlas (TCGA), and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), normalized and merged into one cohort. The prognostic value and interconnections of these RMPs were also studied. The four prognosis-related genes (PRGs) with the greatest prognostic value were then selected to construct diverse RMP-associated prognostic models through univariate Cox (uniCox) regression analysis, differential expression analysis, Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox (multiCox) regression. Alterations in biological functional pathways, genomic mutations, immune infiltrations, RNAss scores and drug sensitivities among different models, as well as their prognostic value, were then explored.

Results: Utilizing a large number of samples and a comprehensive set of genes contributing to adenosine-associated RNA modification, our study revealed the joint potential bio-functions and underlying features of these diverse RMPs and provided effective models (PRG clusters, gene clusters and the risk model) for predicting the clinical outcomes of BC. The individuals with higher risk scores showed poor prognoses, cell cycle function enrichment, upregulation of stemness scores, higher tumour mutation burdens (TMBs), immune activation and specific drug resistance. This work highlights the significance of comprehensively examining post-transcriptional RNA modification genes.

Conclusion: Here, we designed and verified an advanced forecasting model to reveal the underlying links between BC and RMPs and precisely predict the clinical outcomes of multivariate prognostic patterns for individuals.

Tertiary lymphoid structure patterns predicted anti-PD1 therapeutic responses in gastric cancer

OBJECTIVE

Recent studies have highlighted the distinct value of tertiary lymphoid structure (TLS) for immunotherapeutic response prediction. However, it remains unclear whether TLS could play such roles in gastric cancer (GC).

METHODS

In this study, tumor tissue slices from 292 GC patients from Zhongshan Hospital were firstly reviewed to explore the correlation between TLS and clinical characteristics. Subsequently, we curated 38 reported genes that may function as triggers of TLS and performed consensus molecular subtyping in public RNA-seq datasets to determine TLS patterns in GC. Based on the differentially expressed genes acquired from two TLS patterns, we quantified TLS-related genes on the principal component analysis (PCA) algorithm to develop TLS score. A Zhongshan immunotherapy cohort including 13 patients who received programmed cell death 1 (PD1) blockade therapy was established to conduct RNA sequencing analysis and multiplex immunohistochemistry (mIHC) tests using formalin-fixed and paraffin-embedded (FFPE) tissues. The corresponding TLS score and immune cell counts were further compared based on therapeutic response variations.

RESULTS

Mature TLS was revealed as an independent prognostic factor in 292 GC patients. Patients with higher TLS score was characterized by prolonged survival time and superior response to immunotherapy. TLS score was correlated with immunotherapy-related characters, such as microsatellite instability (MSI) and tumor mutation burden (TMB). In addition, RNA-seq data analysis in the Zhongshan immunotherapy cohort indicated that a higher TLS score was correlated with a superior response to PD1 blockade therapy. mIHC tests also revealed that PD1+CD8+ T cell counts were significantly increased in the high-TLS score group.

CONCLUSIONS

This study highlighted that TLS was significantly associated with immune landscape diversity and complexity. Quantitatively evaluating TLS patterns of individual tumor will strengthen our understanding of TME characteristics and promote more effective immunotherapy strategies.

The diagnostic significance of integrating m6A modification and immune microenvironment features based on bioinformatic investigation in aortic dissection

Purpose

The aim of this study was to investigate the role of m6A modification and the immune microenvironment (IME) features in aortic dissection (AD) and establish a clinical diagnostic model for AD based on m6A and IME factors.

Methods

GSE52093, GSE98770, GSE147026, GSE153434, and GSE107844 datasets were downloaded from the GEO database. The expression of 21 m6A genes including m6A writers, erasers, readers, and immune cell infiltrates was analyzed in AD and healthy samples by differential analysis and ssGSEA method, respectively. Both correlation analyses between m6A genes and immune cells were conducted by Pearson and Spearman analysis. XGboost was used to dissect the major m6A genes with significant influences on AD. AD samples were classified into two subgroups via consensus cluster and principal component analysis (PCA) analysis, respectively. Among each subgroup, paramount IME features were evaluated. Random forest (RF) was used to figure out key genes from AD and healthy shared differentially expressed genes (DEGs) and two AD subgroups after gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Finally, we constructed an AD diagnostic model combining important m6A regulatory genes and assessed its efficacy.

Results

Among 21 m6A genes, WTAP, HNRNPC, and FTO were upregulated in AD samples, while IGF2BP1 was downregulated compared with healthy samples. Immune cell infiltrating analysis revealed that YTHDF1 was positively correlated with γδT cell level, while FTO was negatively correlated with activated CD4+ T cell abundance. FTO and IGF2BP1 were identified to be crucial genes that facilitate AD development according to the XGboost algorithm. Notably, patients with AD could be classified into two subgroups among which 21 m6A gene expression profiles and IME features differ from each other via consensus cluster analysis. The RF identified SYNC and MAPK1IP1L as the crucial genes from common 657 shared common genes in 1,141 DEGs between high and low m6A scores of AD groups. Interestingly, the AD diagnostic model coordinating SYNC and MAPK1IP1L with FTO and IGF2BP1 performed well in distinguishing AD samples.

Conclusion

This study indicated that FTO and IGF2BP1 were involved in the IME of AD. Integrating FTO and IGF2BP1 and MAPK1IP1L key genes in AD with a high m6A level context would provide clues for forthcoming AD diagnosis and therapy.

Comprehensive analysis of m6A circRNAs identified in colorectal cancer by MeRIP sequencing

Purpose

To characterize the entire profile of m6A modifications and differential expression patterns for circRNAs in colorectal cancer (CRC).

Methods

First, High-throughput MeRIP-sequencing and RNA-sequencing was used to determine the difference in m6A methylome and expression of circRNA between CRC tissues and tumor-adjacent normal control (NC) tissues. Then, GO and KEGG analysis detected pathways involved in differentially methylated and differentially expressed circRNAs (DEGs). The correlations between m6A status and expression level were calculated using a Pearson correlation analysis. Next, the networks of circRNA-miRNA-mRNA were visualized using the Target Scan and miRanda software. Finally, We describe the relationship of distance between the m6A peak and internal ribosome entry site (IRES) and protein coding potential of circRNAs.

Results

A total of 4340 m6A peaks of circRNAs in CRC tissue and 3216 m6A peaks of circRNAs in NC tissues were detected. A total of 2561 m6A circRNAs in CRC tissues and 2129 m6A circRNAs in NC tissues were detected. Pathway analysis detected that differentially methylated and expressed circRNAs were closely related to cancer. The conjoint analysis of MeRIP-seq and RNA-seq data discovered 30 circRNAs with differentially m6A methylated and synchronously differential expression. RT-qPCR showned circRNAs (has_circ_0032821, has_circ_0019079, has_circ_0093688) were upregulated and circRNAs (hsa_circ_0026782, hsa_circ_0108457) were downregulated in CRC. In the ceRNA network, the 10 hyper-up circRNAs were shown to be associated with 19 miRNAs and regulate 16 mRNAs, 14 hypo-down circRNAs were associated with 30 miRNAs and regulated 27 mRNAs. There was no significant correlation between the level of m6A and the expression of circRNAs. The distance between the m6A peak and IRES was not significantly related to the protein coding potential of circRNAs.

Conclusion

Our study found that there were significant differences in the m6A methylation patterns of circRNAs between CRC and NC tissues. M6A methylation may affect circRNA-miRNA-mRNA co-expression in CRC and further affect the regulation of cancer-related target genes.

Analysis and prognostic significance of tumour immune infiltrates and immune microenvironment of m6A-related lncRNAs in patients with gastric cancer

BACKGROUND

Studies have shown that long noncoding RNAs and N6-methyladenosine play important roles in gastric cancer. The purpose of this study was to determine the correlation and prognostic value of m6A-related lncRNAs and immune infiltration in gastric cancer.

METHODS

We downloaded the clinically related information and RNA-Seq transcriptome data of gastric cancer patients from the TCGA database. Univariate Cox regression analysis and Pearson analysis were used to screen out m6A-related lncRNAs. Consensus cluster analysis was used to divide the sample into two clusters, and LASSO analysis and Cox regression analysis were used to construct a risk scoring model.

RESULTS

A total of 25 lncRNA expression profiles were screened, and gastric cancer patients were divided into different subtypes. Cluster 2 had a better prognosis, but its stromal score, ESTIMATE score and immune score were low. Cluster 1 was rich in resting memory CD4 T cells, regulatory T cells, monocytes, and resting mast cells, and Cluster 2 was rich in activated memory CD4 T cells and follicular helper T cells. Thirteen lncRNAs were selected to construct a risk model, and the prognosis of gastric cancer patients in the high-risk group was poor. The expression of PD-L1 in tumours is significantly higher than that in normal tissues. Univariate and multivariate Cox regression analysis results showed that the overall survival rate was significantly related to stage and the risk score, which can be used as an independent prognostic factor. The results of the heatmap and scatter plot showed that clusters (P = 0.0045) and grade (G1-2, G3, P = 0.0037) were significantly related to prognosis. The relationship between the risk score and immune cell infiltration showed that memory B cells, resting dendritic cells, M0 macrophages, and M2 macrophages were positively correlated with the risk score, while resting mast cells, monocytes, activated NK cells, and follicular helper T cells were negatively correlated with the risk score.

CONCLUSION

The results of this study indicate that m6A-related lncRNAs may play an important role in the prognosis of gastric cancer patients and the tumour immune microenvironment and may provide help for the treatment of gastric cancer patients.

N6-methyladenosine RNA methylation regulator-related alternative splicing gene signature as prognostic predictor and in immune microenvironment characterization of patients with low-grade glioma

Background: N6-methyladenosine (m6A) RNA methylation is an important epigenetic modification affecting alternative splicing (AS) patterns of genes to regulate gene expression. AS drives protein diversity and its imbalance may be an important factor in tumorigenesis. However, the clinical significance of m6A RNA methylation regulator-related AS in the tumor microenvironment has not been investigated in low-grade glioma (LGG).

Methods: We used 12 m6A methylation modulatory genes (WTAP, FTO, HNRNPC, YTHDF2, YTHDF1, YTHDC2, ALKBH5, YTHDC1, ZC3H13, RBM15, METTL14, and METTL3) from The Cancer Genome Atlas (TCGA) database as well as the TCGA-LGG (n = 502) dataset of AS events and transcriptome data. These data were downloaded and subjected to machine learning, bioinformatics, and statistical analyses, including gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Univariate Cox, the Least Absolute Shrinkage and Selection Operator (LASSO), and multivariable Cox regression were used to develop prognostic characteristics. Prognostic values were validated using Kaplan-Maier survival analysis, proportional risk models, ROC curves, and nomograms. The ESTIMATE package, TIMER database, CIBERSORT method, and ssGSEA algorithm in the R package were utilized to explore the role of the immune microenvironment in LGG. Lastly, an AS-splicing factor (SF) regulatory network was examined in the case of considering the role of SFs in regulating AS events.

Results: An aggregate of 3,272 m6A regulator-related AS events in patients with LGG were screened using six machine learning algorithms. We developed eight AS prognostic characteristics based on splice subtypes, which showed an excellent prognostic prediction performance. Furthermore, quantitative prognostic nomograms were developed and showed strong validity in prognostic prediction. In addition, prognostic signatures were substantially associated with tumor immune microenvironment diversity, ICB-related genes, and infiltration status of immune cell subtypes. Specifically, UGP2 has better promise as a prognostic factor for LGG. Finally, splicing regulatory networks revealed the potential functions of SFs.

Conclusion: The present research offers a novel perspective on the role of AS in m6A methylation. We reveal that m6A methylation regulator-related AS events can mediate tumor progression through the immune-microenvironment, which could serve as a viable biological marker for clinical stratification of patients with LGG so as to optimize treatment regimens.

Palmitoyl transferases act as potential regulators of tumor-infiltrating immune cells and glioma progression

High immune-cell infiltration in glioblastomas (GBMs) leads to immunotherapy resistance. Emerging evidence has shown that zinc finger Asp-His-His-Cyc-type (ZDHHC) palmitoyl transferases participate in regulating tumor progression and the immune microenvironment. In the present study, a large cohort of patients with gliomas from The Cancer Genome Atlas (TCGA) and Rembrandt databases was included to perform omics analysis of ZDHHCs in gliomas. CCK-8, flow cytometry, quantitative real-time PCR, western blotting, and transwell assays were performed to determine the effects of ZDHHC inhibition on glioma cells and microglia. We found that five (ZDHHC11, ZDHHC12, ZDHHC15, ZDHHC22, and ZDHHC23) out of 23 ZDHHCs were aberrantly expressed in gliomas and might play their roles through the phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) signaling pathway. Further results indicated that inhibition of ZDHHCs with 2-bromopalmitate (2-BP) suppressed glioma-cell viability and autophagy, as well as promoted apoptosis. Targeting ZDHHCs also promoted the sensitivity of glioma cells to temozolomide (TMZ) chemotherapy. In addition, the inhibition of ZDHHCs weakened the migratory ability of microglia induced by glioma cells in vitro and in vivo. Taken together, our findings suggest that the inhibition of ZDHHCs suppresses glioma-cell viability and microglial infiltration. Targeting ZDHHCs may be promising for glioma treatments.

Multiomics Data Analysis and Identification of Immune-Related Prognostic Signatures With Potential Implications in Prognosis and Immune Checkpoint Blockade Therapy of Glioblastoma

Background

In recent years, glioblastoma multiforme (GBM) has been a concern of many researchers, as it is one of the main drivers of cancer-related deaths worldwide. GBM in general usually does not responding well to immunotherapy due to its unique microenvironment.

Methods

To uncover any further informative immune-related prognostic signatures, we explored the immune-related distinction in the genetic or epigenetic features of the three types (expression profile, somatic mutation, and DNA methylation). Twenty eight immune-related hub genes were identified by Weighted Gene Co-Expression Network Analysis (WGCNA). The findings showed that three genes (IL1R1, TNFSF12, and VDR) were identified to construct an immune-related prognostic model (IRPM) by lasso regression. Then, we used three hub genes to construct an IRPM for GBM and clarify the immunity, mutation, and methylation characteristics.

Results

Survival analysis of patients undergoing anti-program cell death protein 1 (anti-PD-1) therapy showed that overall survival was superior in the low-risk group than in the high-risk group. The high-risk group had an association with epithelial-mesenchymal transition (EMT), high immune cell infiltration, immune activation, a low mutation number, and high methylation, while the low-risk group was adverse status.

Conclusions

In conclusion, IRPM is a promising tool to distinguish the prognosis of patients and molecular and immune characteristics in GBM, and the IRPM risk score can be used to predict patient sensitivity to checkpoint inhibitor blockade therapy. Thus, three immune-related signatures will guide us in improving treatment strategies and developing objective diagnostic tools.

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.

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.

m6A Methylation Patterns and Tumor Microenvironment Infiltration Characterization in Clear-Cell Renal Cell Carcinoma

Increasing evidence suggests the essential regulation of RNA N6-methyladenosine (m6A) modification in carcinogenesis and immune response. Nevertheless, the potential impacts of these modifications on the tumor microenvironment (TME) immune cell infiltration characteristics in clear-cell renal cell carcinoma (ccRCC) remain unclear. Utilizing a consensus clustering algorithm, we determined three m6A modification patterns and identified three m6A-related gene clusters among 569 ccRCC samples, which were associated with different biological functions and clinical outcomes. Thereafter, the m6A score was constructed using m6A-associated signature genes to accurately exploit the m6A modification patterns within individual tumors. The m6A score was further demonstrated to be noticeably related to ccRCC prognosis. In addition, the m6A score was found to be strongly correlated with tumor mutational burden (TMB), microsatellite instability, immune infiltration, immune checkpoint expression, and immunotherapy response, which was also validated in the pan-cancer analyses. Our findings thoroughly elucidated that m6A modification contributes to tumor microenvironment immune-infiltrating characteristics and prognosis in ccRCC. Assessing the m6A modification patterns of individual patients with ccRCC will offer novel insights into TME infiltration and help develop more effective treatment strategies.

Transcriptional Patterns of Lower-Grade Glioma Patients with Distinct Ferroptosis Levels, Immunotherapy Response, and Temozolomide Sensitivity

Background

Many studies have defined a critical role for ferroptosis in cancer progression and therapy, but it is unclear how ferroptosis regulates tumor immunity or tumor microenvironment (TME).

Methods

In this study, 24 ferroptosis-regulators were assessed by nonnegative matrix factorization (NMF) consensus clustering to identify ferroptosis patterns in lower-grade gliomas (LGGs). Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) method and single sample gene set enrichment analysis (ssGSEA) were used to quantify immune cell infiltrations. The PCA algorithm was used to develop the ferroptosis-related score (FRscore) to measure ferroptosis levels.

Results

Two LGG subgroups named ferroptosis-related clusters 1 (FRC1) and 2 (FRC2), with distinct ferroptosis levels, immune infiltrations, and clinical outcomes were determined in 1,407 LGG samples. A well-designed scoring system was developed to evaluate the ferroptosis levels in LGG patients based on the FRSig gene profile and divided patients into low- and high-FRscore subgroups. Patients with low FRscores had lower ferroptosis levels and prolonged survival time and were expected to benefit from immune checkpoint blockade (ICB) therapy and showed higher sensitivity to TMZ chemotherapy. Findings also showed that the PI3K-AKT-mTOR pathway is activated by ferroptosis induction in SW1088 cells.

Conclusions

This study highlights the critical role of ferroptosis in TME formation and shaping, and quantitatively assessing ferroptosis levels in individual tumors can help to define the intratumor microenvironment and formulate precise treatment strategies for LGG patients.

Cross-Talk Between m6A- and m5C-Related lncRNAs to Construct a Novel Signature and Predict the Immune Landscape of Colorectal Cancer Patients

Background

N6-methyladenosine (m⁶A) and 5-methylcytosine (m⁵C) can modify long non-coding RNAs (lncRNAs), thereby affecting tumorigenesis and tumor progression. However, there is a lack of knowledge regarding the potential roles and cross-talk of m⁶A- and m⁵C-related lncRNAs in the tumor microenvironment (TME) and their effect on prognosis.

Methods

We systematically evaluated the expression patterns of m⁶A- and m⁵C-related lncRNAs in 1358 colorectal cancer (CRC) samples from four datasets. Consensus clustering was conducted to identify molecular subtypes of CRC, and the clinical significance, TME, tumor-infiltrating immune cells (TIICs), and immune checkpoints in the different molecular subtypes were analyzed. Finally, we established a m⁶A- and m⁵C-related lncRNA signature and a prognostic nomogram.

Results

We identified 141 m⁶A- and m⁵C-related lncRNAs by co-expression analysis, among which 23 lncRNAs were significantly associated with the overall survival (OS) of CRC patients. Two distinct molecular subtypes (cluster A and cluster B) were identified, and these two distinct molecular subtypes could predict clinicopathological features, prognosis, TME stromal activity, TIICs, immune checkpoints. Next, a m⁶A- and m⁵C-related lncRNA signature for predicting OS was constructed, and its predictive capability in CRC patients was validated. We then constructed a highly accurate nomogram for improving the clinical applicability of the signature. Analyses of clinicopathological features, prognosis, TIICs, cancer stem cell (CSC), and drug response revealed significant differences between two risk groups. In addition, we found that patients with a low-risk score exhibited enhanced response to anti-PD-1/L1 immunotherapy. Functional enrichment analysis showed that these lncRNAs related to the high-risk group were involved in the development and progression of CRC.

Conclusions

We conducted a comprehensive analysis of m⁶A- and m⁵C-related lncRNAs in CRC and revealed their potential functions in predicting tumor-immune-stromal microenvironment, clinicopathological features, and prognosis, and determined their role in immunotherapy. These findings may improve our understanding of the cross-talk between m⁶A- and m⁵C-related lncRNAs in CRC and pave a new road for prognosis assessment and more effective immunotherapy strategies.

The emerging roles of the interaction between m6A modification and c-Myc in driving tumorigenesis and development

N6-methyladenosine (m6A) is an extremely common and conservative posttranscriptional modification, that can specifically target and regulate the expression or stability of a series of tumor-related genes, thus playing critical roles in the occurrence and development of tumors. c-Myc is an important tumorigenic transcription factor that promotes tumorigenesis and development by mainly regulating the expression of downstream target genes. Increasing evidence shows that m6A modification, as well as abnormal expression and regulation of c-Myc, is critical molecular mechanisms driving tumorigenesis and development. Although more evidence has been uncovered about the individual roles of m6A modification or c-Myc in tumors, the interaction between m6A modification and c-Myc in tumorigenesis and development has not been systematically summarized. Therefore, this review is focused on the mutual regulation between m6A modification and c-Myc expression and stability as well as its roles in tumorigenesis and development. We also summarized the potential value of the interaction between m6A modification and m6A expression and stability in tumor diagnosis and treatment, which provides a specific reference for revealing the mechanism of tumor occurrence and development as well as clinical diagnosis and treatment.

The roles of N6-methyladenosine methylation in the regulation of bone development, bone remodeling and osteoporosis

N⁶-methyladenosine (m⁶A), a novel epitranscriptomic RNA modification, plays crucial roles in a variety of biological processes and diseases. Recently, there are growing evidence supporting that m⁶A methylation is essential for bone development and homeostasis through the regulation of key genes by regulating RNA stability, localization, turnover and translation efficiency. In this review, we summarized our current understanding of the functional roles of m⁶A methylation and its related regulators in bone development and bone remodeling. These findings will offer new directions and insights on the further investigations of m⁶A methylation in bone biology. Moreover, we also discussed important advances of m⁶A methylation related regulators as potential therapeutic targets, which allows for novel therapeutic strategies on the medications of bone-related diseases including osteoporosis.

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

Background

An increasing number of RNA modification types other than N⁶-methyladenosine (m⁶A) modification have been detected. Nonetheless, the probable functions of RNA modifications beyond m⁶A in the tumor microenvironment (TME), mesenchymal (MES) transition, immunotherapy, and drug sensitivity remain unclear.

Methods

We analyzed the characteristics of 32 non-m⁶A RNA modification regulators in 539 glioblastoma (GBM) patients and the TME cell infiltration and MES transition patterns. Using principal component analysis, a non-m⁶A epitranscriptome regulator score (RM score) model was established. We estimated the association between RM score and clinical characteristics, TME status, GBM subtypes, and drug and immunotherapy response.

Results

Three definite non-m⁶A RNA modification patterns associated with diverse biological pathways and clinical characteristics were identified. The high RM score group was characterized by a poor prognosis, enhanced immune infiltration, and MES subtype. Further analysis indicated that the high RM score group had a lower tumor mutation burden as well as a weaker response to immunotherapy. The higher RM score group may benefit more from drugs targeting the EGFR and WNT signaling pathways.

Conclusion

Our study exposed the potential relationship of non-m⁶A RNA modification regulators with clinical features, TME status, and GBM subtype and clarified its therapeutic value.

N6-methyladenosine and Neurological Diseases

N6-methyladenosine (m6A) is a dynamic reversible methylation modification of the adenosine N6 position and is the most common chemical epigenetic modification among mRNA post-transcriptional modifications, including methylation, demethylation, and recognition. Post-transcriptional modification involves multiple protein molecules, including METTL3, METTL14, WTAP, KIAA1429, ALKBH5, YTHDF1/2/3, and YTHDC1/2. m6A-related proteins are expressed in almost all cells. However, the abnormal expression of m6A-related proteins may occur in the nervous system, thereby affecting neuritogenesis, brain volume, learning and memory, memory formation and consolidation, etc., and is implicated in the development of diseases, such as Parkinson's disease, Alzheimer's disease, multiple sclerosis, depression, epilepsy, and brain tumors. This review focuses on the functions of m6A in the development of central nervous system diseases, thus contributing to a deeper understanding of disease pathogenesis and providing potential clinical therapeutic targets for neurological diseases.

m6A Regulator Expression Segregates Meningiomas Into Biologically Distinct Subtypes

BACKGROUND

Meningiomas are the most common primary intracranial tumors in adults. According to the 2021 World Health Organization (WHO) classification of central nervous system tumors, approximately 80% of meningiomas are WHO grade 1, that is, histopathologically benign, whereas about 20% are WHO grade 2 or grade 3, showing signs of atypia or malignancy. The dysregulation of N6-methylation (m⁶A) regulators is associated with disorders of diverse critical biological processes in human cancer. This study aimed to explore whether m⁶A regulator expression was associated with meningioma molecular subtypes and immune infiltration.

METHODS

We evaluated the m⁶A modification patterns of 160 meningioma samples based on 19 m⁶A regulators and correlated them with immune infiltration characteristics. Novel molecular subtypes were defined based on prognostic hub gene expression.

RESULTS

Two meningioma clusters were identified based on the expression of 19 m⁶A regulators. In cluster 1, 607 differentially expressed genes (DEGs) were upregulated and 519 were downregulated. A total of 1,126 DEGs comprised three gene expression modules characterized by turquoise, blue, and gray. Functional annotation suggested that the turquoise module was involved in Wnt-related and other important cancer-related pathways. We identified 32 hub genes in this module by constructing a protein-protein interaction network. The meningioma samples were divided into two molecular subtypes. EPN1, EXOSC4, H2AX, and MZT2B not only showed significant differences between meningioma molecular subtypes but also had the potential to be the marker genes of specific meningioma subtypes.

CONCLUSION

m⁶A regulator gene expression may be a novel prognostic marker in meningioma.

N6-Methyladenosine RNA Modification in the Tumor Immune Microenvironment: Novel Implications for Immunotherapy

N6-methyladenosine (m⁶A) methylation is one of the most common modifications of RNA in eukaryotic cells, and is mainly regulated by m⁶A methyltransferases (writers), m⁶A demethylases (erasers), and m⁶A binding proteins (readers). Recently, accumulating evidence has shown that m⁶A methylation plays crucial roles in the regulation of the tumor immune microenvironment, greatly impacting the initiation, progression, and metastasis processes of various cancers. In this review we first briefly summarizes the m⁶A-related concepts and detection methods, and then describes in detail the associations of m⁶A methylation modification with various tumor immune components especially immune cells (e.g., regulatory T cells, dendritic cells, macrophages, and myeloid-derived suppressor cells) in a variety of cancers. We discuss the relationship between m⁶A methylation and cancer occurrence and development with the involvement of tumor immunity highlighted, suggesting novel markers and potential targets for molecular pathological diagnosis and immunotherapy of various cancers.

Integrating m6A Regulators-Mediated Methylation Modification Models and Tumor Immune Microenvironment Characterization in Caucasian and Chinese Low-Grade Gliomas

Background: As an important epigenetic modification, m6A methylation plays an essential role in post-transcriptional regulation and tumor development. It is urgently needed to comprehensively and rigorously explore the prognostic value of m6A regulators and its association with tumor microenvironment (TME) infiltration characterization of low-grade glioma (LGG).

Methods: Based on the expression of 20 m6A regulatory factors, we comprehensively evaluated the m6A modification patterns of LGG after unsupervised clustering. Subsequent analysis of the differences between these groups was performed to obtain m6A-related genes, then consistent clustering was conducted to generate m6AgeneclusterA and m6AgeneclusterB. A Random Forest and machining learning algorithms were used to reduce dimensionality, identify TME characteristics and predict responses for LGG patients receiving immunotherapies.

Results: Evident differential m6A regulators were found in mutation, CNV and TME characteristics of LGG. Based on TCGA and CGGA databases, we identified that m6A regulators clusterA could significantly predict better prognosis (p = 0.00016) which enriched in mTOR signaling pathway, basal transcription factors, accompanied by elevated immune cells infiltration, and decreased IDH and TP53 mutations. We also investigated the distribution of differential genes in m6A regulators clusters which was closely associated with tumor immune microenvironment through three independent cohort comparisons. Next, we established m6Ascore based on previous m6A model, which accurately predicts outcomes in 1089 LGG patients (p < 0.0001) from discovering cohort and 497 LGG patients from testing cohort. Significant TME characteristics, including genome heterogeneity, abidance of immune cells, and clinicopathologic parameters have been found between m6Ascore groups. Importantly, LGG patients with high m6Ascore are confronted with significantly decreased responses to chemotherapies, but benefit more from immunotherapies.

Conclusion: In conclusion, this study first demonstrates that m6A modification is crucial participant in tumorigenesis and TME infiltration characterization of LGG based on large-scale cohorts. The m6Ascore provides useful and accurately predict of prognosis and clinical responses to chemotherapy, immunotherapy and therapeutic strategy development for LGG patients.

Methylation and Expression of the Exercise-Related TLR1 Gene Is Associated With Low Grade Glioma Prognosis and Outcome

Background: Exercise improves function, reduces disability, maintains independence, and improves quality of life for low-grade glioma (LGG) patients. Exercise can also improve the effectiveness of cancer treatment. The goal of this research was to find potential exercise related genes that may be used to predict exercise levels and may be used as a biomarker for cancer outcomes.

Methods: The GSE111551 database was thoroughly examined in this research, and the resulting conclusion of exercise-related genes was reached. The protein interaction network (PPI) was used to examine the differentially expressed genes (DEGs). Then the exercise-related gene TLR1 was chosen. The expression, methylation degree, prognosis, and immune relevance of TLR1 were investigated using bioinformatics. In addition, we verified the role of TLR1 in Glioma cell lines.

Results: LGG patients with reduced TLR1 expression and hypermethylation had a better overall survival (OS) and progression free survival (PFS), using the TCGA database. Low TLR1 expression and hypermethylation of TLR1 were found to be independent biomarkers for OS using Cox regression. Furthermore, the CGGA database was used to confirm the prognostic function of TLR1 in this cancer. Finally, most methylation sites of TLR1 were strongly correlated with immune infiltration and immune checkpoint. Then, reducing TLR1 expression substantially slowed the cell cycle and decreased LGG cell proliferation, emigration, and infiltration in vitro.

Conclusions: Exercise-related gene TLR1 has the potential to be a useful prognostic biomarker, and it is thought to be involved in immune cell infiltration and immunotherapy in LGG.

Function of N6-Methyladenosine Modification in Tumors

N6-Methyladenosine (m6A) modification is a dynamic and reversible methylation modification at the N6-position of adenosine. As one of the most prevalent posttranscriptional methylation modifications of RNA, m6A modification participates in several mRNA processes, including nuclear export, splicing, translation, and degradation. Some proteins, such as METTL3, METTL14, WTAP, ALKBH5, FTO, and YTHDF1/2/3, are involved in methylation. These proteins are subdivided into writers (METTL3, METTL14, WTAP), erasers (ALKBH5, FTO), and readers (YTHDF1/2/3) according to their functions in m6A modification. Several studies have shown that abnormal m6A modification occurs in tumors, including colorectal cancer, liver cancer, breast cancer, nasopharyngeal carcinoma, and gastric cancer. The proteins for m6A modification are involved in tumor proliferation, angiogenesis, metastasis, immunity, and other processes. Herein, the roles of m6A modification in cancer are discussed, which will improve the understanding of tumorigenesis, as well as the diagnosis, treatment, and prognosis of tumors.

N6-Methyladenosine RNA Modification: An Emerging Immunotherapeutic Approach to Turning Up Cold Tumors

Immunotherapy is a novel clinical approach that has shown clinical efficacy in multiple cancers. However, only a fraction of patients respond well to immunotherapy. Immuno-oncological studies have identified the type of tumors that are sensitive to immunotherapy, the so-called hot tumors, while unresponsive tumors, known as “cold tumors,” have the potential to turn into hot ones. Therefore, the mechanisms underlying cold tumor formation must be elucidated, and efforts should be made to turn cold tumors into hot tumors. N⁶-methyladenosine (m⁶A) RNA modification affects the maturation and function of immune cells by controlling mRNA immunogenicity and innate immune components in the tumor microenvironment (TME), suggesting its predominant role in the development of tumors and its potential use as a target to improve cancer immunotherapy. In this review, we first describe the TME, cold and hot tumors, and m⁶A RNA modification. Then, we focus on the role of m⁶A RNA modification in cold tumor formation and regulation. Finally, we discuss the potential clinical implications and immunotherapeutic approaches of m⁶A RNA modification in cancer patients. In conclusion, m⁶A RNA modification is involved in cold tumor formation by regulating immunity, tumor-cell-intrinsic pathways, soluble inhibitory mediators in the TME, increasing metabolic competition, and affecting the tumor mutational burden. Furthermore, m⁶A RNA modification regulators may potentially be used as diagnostic and prognostic biomarkers for different types of cancer. In addition, targeting m⁶A RNA modification may sensitize cancers to immunotherapy, making it a promising immunotherapeutic approach for turning cold tumors into hot ones.

Human Mitochondrial Ribosomal RNA Modification-Based Classification Contributes to Discriminate the Prognosis and Immunotherapy Response of Glioma Patients

Background

Epigenetic regulations of the tumor microenvironment (TME) and immunotherapy have been investigated in recent years. Nevertheless, the potential value of mitochondrial ribosomal RNA (mt-rRNA) modification in regulation of the TME and immunotherapy remains unknown.

Methods

We comprehensively investigated the mt-rRNA-modification patterns in glioma patients based on nine regulators of mt-rRNA. Subsequently, these modification patterns were correlated systematically with immunologic characteristics and immunotherapy. An “mt-rRNA predictor” was constructed and validated in multiple publicly available cohorts to provide guidance for prognosis prediction and immunotherapy of glioma patients.

Results

Two distinct patterns of mt-rRNA modification were determined based on the evidence that nine regulators of mt-rRNA correlated significantly with most clinicopathologic characteristics, immunomodulators, TME, immune-checkpoint blockers (ICBs), and prognosis. Patients with mt-rRNA subtype II presented significantly poorer overall survival/progression-free survival (OS/PFS), but higher tumor mutational burden (TMB), more somatic mutations, and copy number variation (CNV). These two mt-rRNA subtypes had distinct TME patterns and responses to ICB therapy. An mt-rRNA predictor was constructed and validated in four glioma cohorts. The subtype with high mt-rRNA score, characterized by increased TMB, infiltration of immune cells, and activation of immunity, suggested an immune-activated phenotype, and was also linked to greater sensitivity to immunotherapy using anti-programmed cell death protein 1 (PD-1) but resistance to temozolomide.

Conclusions

Regulators of mt-rRNA modification have indispensable roles in the complexity and diversity of the TME and prognosis. This novel classification based on patterns of mt-rRNA modification could provide an effective prognostic predictor and guide more appropriate immunotherapy/chemotherapy strategies for glioma patients.

N6-Methyladenosine-Related lncRNA Signature Predicts the Overall Survival of Colorectal Cancer Patients

Background: The N6-methyladenosine (m6A) RNA modification can modify long non-coding RNAs (lncRNAs), thereby affecting the tumorigenesis and progression of tumors. However, the underlying role of m6A-modified lncRNAs in colorectal cancer (CRC) remains largely unknown. Therefore, our aim was to assess the prognostic value of m6A-modified lncRNAs in CRC patients. Methods: The gene expression and clinicopathological data of CRC were extracted from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was used to investigate the m6A-modified lncRNAs. Consensus clustering was conducted to identify molecular subtypes of CRC, and the clinical significance of molecular subtypes was identified. The least absolute shrinkage and selection operator analysis (LASSO) was applied to establish a risk signature. Finally, a prognostic nomogram with risk score and clinicopathological variables was established. Results: In total, 29 m6A-modified lncRNAs were identified as prognostic lncRNAs. Two molecular clusters were identified and significant differences were found with respect to clinicopathological features and prognosis. Cluster1 is associated with poor overall survival (OS), down-regulation of Programmed cell death ligand-1 (PD-L1) expression, lower immune score, and less immune cell infiltration. Then, an m6A-modified lncRNA signature for predicting OS was constructed in the TCGA training cohort. The signature demonstrated favorable prediction performance in both training and validation sets. Compared with low-risk patients, patients with high risk showed worse clinical outcomes, lower immune scores, and downregulated PD-L1 expression. Further analysis indicated that the signature was an independent prognostic indicator, and then a prognostic nomogram based on risk score, tumor location, and tumor stage was established. Conclusions: Our study identified a seven m6A-modified lncRNA signature and established a prognostic nomogram that reliably predicts OS in CRC. These findings may improve the understanding of m6A modifications in CRC and provide insights into the prognosis and treatment strategy of CRC.