Expression of m6A Regulators Correlated With Immune Microenvironment Predicts Therapeutic Efficacy and Prognosis in Gliomas

M6A-mediated molecular patterns and tumor microenvironment infiltration characterization in nasopharyngeal carcinoma

N6-methyladenosine (m6A) is the most predominant RNA epigenetic regulation in eukaryotic cells. Numerous evidence revealed that m6A modification exerts a crucial role in the regulation of tumor microenvironment (TME) cell infiltration in several tumors. Nevertheless, the potential role and mechanism of m6A modification in nasopharyngeal carcinoma (NPC) remains unknown. mRNA expression data and clinical information from GSE102349, and GSE53819 datasets obtained from Gene Expression Omnibus (GEO) was used for differential gene expression and subsequent analysis. Consensus clustering was used to identify m6A-related molecular patterns of 88 NPC samples based on prognostic m6A regulators using Univariate Cox analysis. The TME cell-infiltrating characteristics of each m6A-related subclass were explored using single-sample gene set enrichment (ssGSEA) algorithm and CIBERSORT algotithm. DEGs between two m6A-related subclasses were screened using edgeR package. The prognostic signature and predicated nomogram were constructed based on the m6A-related DEGs. The cell infiltration and expression of prognostic signature in NPC was determined using immunohistochemistry (IHC) analysis. Chi-square test was used to analysis the significance of difference of the categorical variables. And survival analysis was performed using Kaplan-Meier plots and log-rank tests. The NPC samples were divided into two m6A-related subclasses. The TME cell-infiltrating characteristics analyses indicated that cluster 1 is characterized by immune-related and metabolism pathways activation, better response to anit-PD1 and anti-CTLA4 treatment and chemotherapy. And cluster 2 is characterized by stromal activation, low expression of HLA family and immune checkpoints, and a worse response to anti-PD1 and anti-CTLA4 treatment and chemotherapy. Furthermore, we identified 1558 DEGs between two m6A-related subclasses and constructed prognostic signatures to predicate the progression-free survival (PFS) for NPC patients. Compared to non-tumor samples, REEP2, TMSB15A, DSEL, and ID4 were upregulated in NPC samples. High expression of REEP2 and TMSB15A showed poor survival in NPC patients. The interaction between REEP2, TMSB15A, DSEL, ID4, and m6A regulators was detected. Our finding indicated that m6A modification plays an important role in the regulation of TME heterogeneity and complexity.

Insight into the regulatory mechanism of m6A modification: From MAFLD to hepatocellular carcinoma

In recent years, there has been a significant increase in the incidence of metabolic-associated fatty liver disease (MAFLD), which has been attributed to the increasing prevalence of type 2 diabetes mellitus (T2DM) and obesity. MAFLD affects more than one-third of adults worldwide, making it the most prevalent liver disease globally. Moreover, MAFLD is considered a significant risk factor for hepatocellular carcinoma (HCC), with MAFLD-related HCC cases increasing. Approximately 1 in 6 HCC patients are believed to have MAFLD, and nearly 40 % of these HCC patients do not progress to cirrhosis, indicating direct transformation from MAFLD to HCC. N6-methyladenosine (m6A) is commonly distributed in eukaryotic mRNA and plays a crucial role in normal development and disease progression, particularly in tumors. Numerous studies have highlighted the close association between abnormal m6A modification and cellular metabolic alterations, underscoring its importance in the onset and progression of MAFLD. However, the specific impact of m6A modification on the progression of MAFLD to HCC remains unclear. Can targeting m6A effectively halt the progression of MAFLD-related HCC? In this review, we investigated the pivotal role of abnormal m6A modification in the transition from MAFLD to HCC, explored the potential of m6A modification as a therapeutic target for MAFLD-related HCC, and proposed possible directions for future investigations.

Identification of significant m6A regulators and immune microenvironment characterization in ischemic stroke

The role of m6A modification in the regulation of the immune microenvironment (IME) of ischemic stroke (IS) is barely known. Thus, we aim to investigate the impact of m6A modification on the IME of IS and its diagnostic value in IS. We comprehensively assessed the m6A modification patterns, the relationship between these modification patterns and the characteristics of the IME. The m6A modification patterns of individual IS sample were quantified by m6Ascore. The performance of m6A phenotype-related genes as potential biomarkers was evaluated by the area under the receiver operating characteristic curve. Experimental validation was also performed by qRT-PCR. Six dysregulated m6A regulators were identified and a classification model consisting of four key m6A regulators (METLL3, RBMX, RBM15B, YTDHF3) could distinguish IS and healthy control samples well. METTL3 and YTHDF3 are closely related to circulating neutrophil abundance. Two distinct m6A modification patterns were determined which differed in immunocyte abundance. We also identified six m6A phenotype-related genes (APOBEC3A, PTMA, FCGR3A, LOC440926, LOC649946, and FTH1L11), and further explored their biological function. Among them, APOBEC3A, FCGR3A, and FTH1L11 were positively associated with neutrophil abundance. APOBEC3A and FCGR3A were stable diagnostic m6A-associated genes in both the discovery and validation cohorts. This study reveals that m6A modification plays a non-negligible role in the formation of a diversified and complex IME in IS. The m6A phenotype-related genes could be diagnostic biomarkers of IS.

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.

Link between m6A modification and infiltration characterization of tumor microenvironment in lung adenocarcinoma

N6-methyladenosine (m6A) RNA methylation plays a pivotal role in immune responses and the onset and advancement of cancer. Nonetheless, the precise impact of m6A modification in lung adenocarcinoma (LUAD) and its associated tumor microenvironment (TME) remains to be fully elucidated. Here, we distinguished distinct m6A modification patterns within two separate LUAD cohorts using a set of 21 m6A regulators. The TME characteristics associated with these two patterns align with the immune-inflamed and immune-excluded phenotypes, respectively. We identified 2064 m6A-related genes, which were used as a basis to divide all LUAD samples into three distinct m6A gene clusters. We applied a scoring system to evaluate the m6A gene signature of the m6A modification pattern in individual patients. To authenticate the categorization significance of m6A modification patterns, we established a correlation between m6A score and TME infiltration profiling, tumor somatic mutations, and responses to immunotherapy. A high level of m6A modification may be associated with the aggressiveness and poor prognosis of LUAD. Further studies should investigate the mechanism of action of m6A regulators and m6A-related genes to improve the diagnosis and treatment of patients with LUAD.

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.

Integrative analysis of multi-omics data reveals a pseudouridine-related lncRNA signature for prediction of glioma prognosis and chemoradiotherapy sensitivity

BACKGROUND

Glioblastoma is the most common type of glioma with a high incidence and poor prognosis, and effective medical treatment remains challenging. Pseudouridine (Ψ) is the first post-transcriptional modification discovered and one of the most abundant modifications to RNA. However, the prognostic value of Ψ-related lncRNAs (ΨrLs) for glioma patients has never been systematically evaluated. This study aims to construct a risk model based on ΨrLs signature and to validate the predictive efficiency of the model.

METHOD

Transcriptomic data, genomic data, and relevant clinical data of glioma patients were extracted from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). ΨrLs with significant correlation with Ψ-related genes were identified, and univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression were used to further select biomarkers and construct a ΨrLs signature risk model. Then, the expression of lncRNAs of ΨrLs signature in multiple glioma cell lines was detected by qPCR. Further, ROC analysis, stratification analysis, correlation analysis, survival analysis, nomogram, enrichment analysis, immune infiltration analysis, chemoradiotherapy sensitivity analysis, somatic mutation, and recurrent copy number variation (CNV) analysis were used to validate the predictive efficiency of ΨrLs signature in TCGA and CGGA datasets.

RESULTS

A four-lncRNA ΨrLs signature (DNAJC27-AS1, GDNF-AS1, ZBTB20-AS4, and DNMBP-AS1) risk model was constructed. By ROC analysis, stratified analysis, correlation analysis, survival analysis, and nomogram, the signature showed satisfactory predictive efficiency. Functional enrichment analysis revealed the differences in immune-related biological processes between high- and low-risk groups. Immune infiltration analysis showed that the high-risk group had lower tumor purity and higher stromal, immune and ESTIMATE scores. Mitoxantrone was identified as effective drug for low-risk group of glioma patients. Key genes in glioma development, including IDH1, EGFR, PTEN, etc., were differentially mutated between risk groups. The main recurrent CNVs in low-risk groups were 19q13.42 deletion and 7q34 amplification; 10q23.31 deletion and 12q14.1 in the high-risk group.

CONCLUSIONS

Our study identified a four-lncRNA ΨrLs signature that effectively predicts the prognosis of glioma patients and may serve as a diagnostic tool. Risk scores of glioma patients generated by the signature is associated with immune-related biological processes and chemoradiotherapy sensitivity. These findings may inform the development of more targeted and effective therapies for glioma patients.

An N6-methyladenosine regulation- and mRNAsi-related prognostic index reveals the distinct immune microenvironment and immunotherapy responses in lower-grade glioma

BACKGROUND

N6-methyladenosine (m6A) modification is involved in tumorigenesis and progression as well as closely correlated with stem cell differentiation and pluripotency. Moreover, tumor progression includes the acquisition of stemness characteristics and accumulating loss of differentiation phenotype. Therefore, we integrated m6A modification and stemness indicator mRNAsi to classify patients and predict prognosis for LGG.

METHODS

We performed consensus clustering, weighted gene co-expression network analysis, and least absolute shrinkage and selection operator Cox regression analysis to identify an m6A regulation- and mRNAsi-related prognostic index (MRMRPI). Based on this prognostic index, we also explored the differences in immune microenvironments between high- and low-risk populations. Next, immunotherapy responses were also predicted. Moreover, single-cell RNA sequencing data was further used to verify the expression of these genes in MRMRPI. At last, the tumor-promoting and tumor-associated macrophage polarization roles of TIMP1 in LGG were validated by in vitro experiments.

RESULTS

Ten genes (DGCR10, CYP2E1, CSMD3, HOXB3, CABP4, AVIL, PTCRA, TIMP1, CLEC18A, and SAMD9) were identified to construct the MRMRPI, which was able to successfully classify patients into high- and low-risk group. Significant differences in prognosis, immune microenvironment, and immunotherapy responses were found between distinct groups. A nomogram integrating the MRMRPI and other prognostic factors were also developed to accurately predict prognosis. Moreover, in vitro experiments illustrated that inhibition of TIMP1 could inhibit the proliferation, migration, and invasion of LGG cells and also inhibit the polarization of tumor-associated macrophages.

CONCLUSION

These findings provide novel insights into understanding the interactions of m6A methylation regulation and tumor stemness on LGG development and contribute to guiding more precise immunotherapy strategies.

Comprehensive analysis of m6A RNA methylation modification patterns and the immune microenvironment in osteoarthritis

Background

Osteoarthritis (OA) is the most common joint degenerative disease, and so far, there is no effective therapy to prevent or delay its development. Considerable attention is now being given to the impact of m6A RNA methylation modification on the disease immune regulation. However, much remains unknown about the function of m6A modification in OA.

Methods

A total of 63 OA and 59 healthy samples were applied to comprehensively examine the m6A regulators mediated RNA methylation modification pattern in OA, and evaluate the impacts of distinct patterns on the characteristics of OA immune microenvironment, including immune infiltration cells, immune responses and human leukocyte antigen (HLAs) genes expression. In addition, we screened out the m6A phenotype-related genes and further explored their potential biological functions. At last, we verified the expression of key m6A regulators and their associations with immune cells, in vitro.

Results

Most of m6A regulators was differentially expressed in OA samples compared to the normal tissues. Based on six hub-m6A regulators identified as abnormally expressed in OA samples, we developed a classifier to distinguish OA patients from healthy individuals. We noted that immune characteristics of OA were correlated with m6A regulators. For instance, YTHDF2 had a strongest significantly positive correlation with regulatory T cells (Tregs) and IGFBP2 was strongest negatively associated with dendritic cells (DCs), which were confirmed by the immunohistochemistry (IHC) staining. Two distinct m6A modification patterns were determined: pattern B had higher infiltrating immunocytes and more active immune responses than pattern A, and two patterns differed in the expression of HLA genes. We also identified 1,592 m6A phenotype-related genes that could mediate the OA synovitis and cartilage degradation by the PI3K-Akt signaling pathway. Quantitative real-time polymerase chain reaction (qRT-PCR) results indicated that IGFBP2 was significantly overexpressed, while YTHDF2 mRNA expression was decreased in OA samples, which was consistent with our findings.

Conclusion

Our research proves the essential impact of m6A RNA methylation modification on the OA immune microenvironment, and helps to explain the regulatory mechanism behind it, which may open up a new direction for more precise immunotherapy of osteoarthritis.

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.

PDPN contributes to constructing immunosuppressive microenvironment in IDH wildtype glioma

The tumor immunosuppressive microenvironment (IME) significantly affects tumor occurrence, progression, and prognosis, but the underlying molecular mechanisms remain to make known. We investigated the prognostic significance of PDPN and its role in IME in glioma. Weighted gene co-expression network analysis (WGCNA) found PDPN closely related to IDH wildtype status and higher immune score. Correlation analysis suggested PDPN was highly positively relevant to immune checkpoints expression and immune checkpoints block responding status. Correlation analysis together with verification in vitro suggested PDPN highly positively relevant tumor-associated neutrophils (TANs) and tumor-associated macrophages (TAMs). Least absolute shrinkage and selection operator (LASSO) regression employed to develop the prediction model with TANs and TAMs markers showed that high risk scores predicted worse prognosis. We highlight that PDPN overexpression is an independent prognostic indicator, and promotes macrophage M2 polarization and neutrophil degranulation, ultimately devotes to the formation of an immunosuppressive tumor microenvironment. Our findings contribute to re-recognizing the role of PDPN in IDH wildtype gliomas and implicate promising target therapy combined with immunotherapy for this highly malignant tumor.

Comprehensive analysis of prognosis of patients with GBM based on 4 m6A-related lncRNAs and immune cell infiltration

Objective

To investigate the immune cell infiltration status in glioblastoma multiforme (GBM) and construct a novel prognostic risk model that can predict patients' prognosis.

Methods

The Cancer Genome Atlas (TCGA) database was used to obtain RNA-sequence information and relevant clinical data. We performed Pearson correlation, univariate Cox regression to screen m6A-related prognostic lncRNA. GMB patients' samples were separated into different clusters through the ConsensusClusterPlus package. The risk score model was established through LASSO regression analysis. Besides, KEGG pathway enrichment analysis was implemented. CIBERSORT algorithm was used to analyze the difference of 22 types of immune cell infiltration in different cluster of GBM patient. Cox regression analyses were used to verify the independence of the model and correlation analysis was performed to demonstrate the link between our model and clinical characteristics of GBM patients. Experiments were used to validate the differential expression of the model lncRNA in patients with different prognosis.

Results

17 lncRNA related to prognosis were screened from 1021 m6A-related lncRNAs. Further, four m6A-related lncRNAs that were significantly correlated with GBM prognosis were selected to establish our prognostic risk model, which had excellent accuracy and can independently predict the prognosis of GBM patients. The infiltration fractions of T regulatory cells, T cells CD4 memory activated and neutrophils were positively associated with risk score, which suggested a significant relationship between the model and tumor immune microenvironment.

Conclusion

The m6A-related RNA risk model offered potential for identifying biomarkers of therapy and predicting prognosis of GBM patients.

The role of RNA modification in the generation of acquired drug resistance in glioma

Glioma is the most common malignant tumor in the central nervous system. The clinical treatment strategy is mainly surgery combined with concurrent temozolomide chemotherapy, but patients can develop drug resistance during treatment, which severely limits its therapeutic efficacy. Epigenetic regulation at the RNA level is plastic and adaptable, and it can induce a variety of tumor responses to drugs. The regulators of RNA modification include methyltransferases, demethylases, and methylation binding proteins; these are also considered to play an important role in the development, prognosis, and therapeutic response of gliomas, which provides a basis for finding new targets of epigenetic drugs and resetting the sensitivity of tumor cells to temozolomide. This review discusses the relationship between the development of adaptive drug resistance and RNA modification in glioma and summarizes the progress of several major RNA modification strategies in this field, especially RNA m6A modification, m5C modification, and adenosine-to-inosine editing.

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.

The expression pattern of immune-related genes and characterization of tumor immune microenvironment: predicting prognosis and immunotherapeutic effects in cutaneous melanoma

Background

Increasing evidences have revealed the tumor immune microenvironment not only has vital impacts on the origin, progression, and metastasis of tumors significantly but also influences the response to immunotherapy. Nonetheless, to date, the well-rounded expression pattern of immune-related genes in cutaneous melanoma and the comprehensive characterization of tumor immune microenvironment remain not clearly elucidated.

Method

We comprehensively evaluated the well-rounded expression pattern of immune-related genes of 686 patients with cutaneous melanoma based on immune-related genes with prognostic value and systematically correlated the expression pattern of these genes with the comprehensive characterization of tumor immune microenvironment. The IRGscore was constructed to quantify immunological function of individual using principal component analysis algorithms.

Result

Three distinct immune subtypes were determined with obvious survival differences. Melanoma patients with high IRGscore was characterized by comprehensive suppression of immune function, showing much poorer prognosis and efficacy for immunotherapy, while the low IRGscore means the robust activation of immune function and the better effect of immunotherapy, which may be responsible for a better prognosis. Besides, the prognostic ability of IRGscore was further validated by the independent dataset of stomach cancers. Furthermore, the predictive effect of immunotherapeutic benefits of IRGscore was demonstrated by the independent dataset of melanoma patients accepting immunotherapy and another predictive model for immunotherapy.

Conclusion

IRGscore could serve as an independent immunotherapeutic and prognostic predictor, thereby facilitating the identification of appropriate candidates with cutaneous melanoma for immunotherapy and the formulation of individualized therapeutic approaches.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02767-z.

Integrated analysis of inflammatory response subtype-related signature to predict clinical outcomes, immune status and drug targets in lower-grade glioma

Background: The inflammatory response in the tumor immune microenvironment has implications for the progression and prognosis in glioma. However, few inflammatory response-related biomarkers for lower-grade glioma (LGG) prognosis and immune infiltration have been identified. We aimed to construct and identify the prognostic value of an inflammatory response-related signature, immune infiltration, and drug targets for LGG.

Methods: The transcriptomic and clinical data of LGG samples and 200 inflammatory response genes were obtained from public databases. The LGG samples were separated into two inflammatory response-related subtypes based on differentially expressed inflammatory response genes between LGG and normal brain tissue. Next, inflammatory response-related genes (IRRGs) were determined through a difference analysis between the aforementioned two subtypes. An inflammatory response-related prognostic model was constructed using IRRGs by using univariate Cox regression and Lasso regression analyses and validated in an external database (CGGA database). ssGSEA and ESTIMATE algorithms were conducted to evaluate immune infiltration. Additionally, we performed integrated analyses to investigate the correlation between the prognostic signature and N 6-methyladenosine mRNA status, stemness index, and drug sensitivity. We finally selected MSR1 from the prognostic signature for further experimental validation.

Results: A total of nine IRRGs were identified to construct the prognostic signature for LGG. LGG patients in the high-risk group presented significantly reduced overall survival than those in the low-risk group. An ROC analysis confirmed the predictive power of the prognostic model. Multivariate analyses identified the risk score as an independent predictor for the overall survival. ssGSEA revealed that the immune status was definitely disparate between two risk subgroups, and immune checkpoints such as PD-1, PD-L1, and CTLA4 were significantly expressed higher in the high-risk group. The risk score was strongly correlated with tumor stemness and m6A. The expression levels of the genes in the signature were significantly associated with the sensitivity of tumor cells to anti-tumor drugs. Finally, the knockdown of MSR1 suppressed LGG cell migration, invasion, epithelial–mesenchymal transition, and proliferation.

Conclusion: The study constructed a novel signature composed of nine IRRGs to predict the prognosis, potential drug targets, and impact immune infiltration status in LGG, which hold promise for screening prognostic biomarkers and guiding immunotherapy for LGG.

m6A RNA methylation-mediated NDUFA4 promotes cell proliferation and metabolism in gastric cancer

Gastric cancer (GC) is a malignancy with poor prognosis. NDUFA4 is reported to correlate with the progression of GC. However, its underlying mechanism in GC is unknown. Our study was to reveal the pathogenic mechanism of NDUFA4 in GC. NDUFA4 expression was explored in single-cell and bulk RNA-seq data as well as GC tissue microarray. Mitochondrial respiration and glycolysis were estimated by oxygen consumption rate and extracellular acidification rate, respectively. The interaction between NDUFA4 and METTL3 was validated by RNA immunoprecipitation. Flow cytometry was used to estimate cell cycle, apoptosis and mitochondrial activities. NDUFA4 was highly expressed in GC and its high expression indicated a poor prognosis. The knockdown of NDUFA4 could reduce cell proliferation and inhibit tumor growth. Meanwhile, NDUFA4 could promote glycolytic and oxidative metabolism in GC cells, whereas the inhibition of glycolysis suppressed the proliferation and tumor growth of GC. Besides, NDUFA4 inhibited ROS level and promoted MMP level in GC cells, whereas the inhibition of mitochondrial fission could reverse NDUFA4-induced glycolytic and oxidative metabolism and tumor growth of GC. Additionally, METTL3 could increase the m6A level of NDUFA4 mRNA via the m6A reader IGF2BP1 to promote NDUFA4 expression in GC cells. Our study revealed that NDUFA4 was increased by m6A methylation and could promote GC development via enhancing cell glycolysis and mitochondrial fission. NDUFA4 was a potential target for GC treatment.

Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma

Background: Glioma is the most prevalent malignant intracranial tumor. Many studies have shown that angiogenesis plays a crucial role in glioma tumorigenesis, metastasis, and prognosis. In this study, we conducted a comprehensive analysis of angiogenesis-related genes (ARGs) in glioma.

Methods: RNA-sequencing data of glioma patients were obtained from TCGA and CGGA databases. Via consensus clustering analysis, ARGs in the sequencing data were distinctly classified into two subgroups. We performed univariate Cox regression analysis to determine prognostic differentially expressed ARGs and least absolute shrinkage and selection operator Cox regression to construct a 14-ARG risk signature. The CIBERSORT algorithm was used to explore immune cell infiltration, and the ESTIMATE algorithm was applied to calculate immune and stromal scores.

Results: We found that the 14-ARG signature reflected the infiltration characteristics of different immune cells in the tumor immune microenvironment. Additionally, total tumor mutational burden increased significantly in the high-risk group. We combined the 14-ARG signature with patient clinicopathological data to construct a nomogram for predicting 1-, 3-, and 5-year overall survival with good accuracy. The predictive value of the prognostic model was verified in the CGGA cohort. SPP1 was a potential biomarker of glioma risk and was involved in the proliferation, invasion, and angiogenesis of glioma cells.

Conclusion: In conclusion, we established and validated a novel ARG risk signature that independently predicted the clinical outcomes of glioma patients and was associated with the tumor immune microenvironment.

Regulation of N6-methyladenosine (m6A) RNA methylation in microglia-mediated inflammation and ischemic stroke

N6-methyladenosine (m6A) is the most abundant post-transcription modification, widely occurring in eukaryotic mRNA and non-coding RNA. m6A modification is highly enriched in the mammalian brain and is associated with neurological diseases like Alzheimer’s disease (AD) and Parkinson’s disease (PD). Ischemic stroke (IS) was discovered to alter the cerebral m6A epi-transcriptome, which might have functional implications in post-stroke pathophysiology. Moreover, it is observed that m6A modification could regulate microglia’s pro-inflammatory and anti-inflammatory responses. Given the critical regulatory role of microglia in the inflammatory processes in the central nervous system (CNS), we speculate that m6A modification could modulate the post-stroke microglial inflammatory responses. This review summarizes the vital regulatory roles of m6A modification in microglia-mediated inflammation and IS. Stroke is associated with a high recurrence rate, understanding the relationship between m6A modification and stroke may help stroke rehabilitation and develop novel therapies in the future.

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.

A signature based on m6A pattern and tumor microenvironment infiltration in clear cell renal cell carcinoma

BACKGROUND

RNA N6-methyladenosine (m6A) has been found to have a critical impact on clear cell renal cell carcinoma (ccRCC) by affecting the tumor microenvironment (TME) and immune cell (IC) infiltration and is related to the treatment and survival rate of patients with ccRCC. However, the mechanism of m6A in TME and IC infiltration remained unclear.

METHODS

Nonnegative Matrix Factorization (NMF) clustering was performed on 650 ccRCC cases from the Cancer Genome Atlas (TCGA) and the Gene-Expression Omnibus (GEO) datasets. The immune infiltration was generated by the single-sample gene-set enrichment analysis (ssGSEA) algorithm. Survival analyses were performed using the Kaplan-Meier method, and the significance of the differences was determined using the log-rank test. The m6A score was constructed based on the expression of m6A regulators to quantify m6A modification. The package "survminer R" was employed to layer patients' low and high scores groups and predict the immunotherapy response.

RESULTS

Three different patterns of m6A modification were established, and significant differences in TME and IC infiltration features were found in these three patterns. Survival analysis demonstrated that m6A cluster A and m6A gene cluster A experienced a longer survival time. Evaluation of m6A modification patterns in individual tumors was initiated by the m6A score. The low m6A score subtype was characterized by increased tumor mutation burden (TMB) and immune infiltration, whereas a high m6A score with a lack of immune cell infiltration showed significantly better overall survival. m6A score was also associated with the expression of programmed cell death protein 1 (PD-L1) and cytotoxic T lymphocyte antigen 4 (CTLA-4). Patients in the high m6A score group had high PD-L1 expression and low CTLA-4 expression. Significant differences in prognosis were identified among types of different TMB and m6A scores, where low TMB and high m6A score had longer survival time.

CONCLUSIONS

This research indicated that m6A modification greatly affected TME and IC infiltration. Physicians can develop practical immunotherapy strategies for patients with ccRCC by evaluating m6A-associated genes.

Expression Patterns of Necroptosis-Related Genes: Predicting Prognosis and Immunotherapeutic Effects in Cutaneous Melanoma

Background

Increasing evidence has shown a strong correlation between necroptosis and antitumor immunity. However, precise expression patterns of necroptosis-related genes in cutaneous melanoma (CM) have not been clearly elucidated nor have their effects on the immune cell infiltration in the tumor microenvironment.

Method

We investigated the expression patterns of necroptosis-related genes of individuals with cutaneous melanoma based on 67 necroptotic genes and methodically associated the expression patterns with the comprehensive characterization of tumor immune microenvironment. Using principal component analysis methods, the NRG score was developed to quantify the expression patterns of necroptotic genes in CM patients.

Result

Three different necroptotic subtypes were determined with marked survival differences, showing distinct characteristics of immune cell infiltration. The high NRG score group with comprehensive immunosuppression was characterized by the worse immunotherapeutic efficacy and the poor prognosis, while the low NRG score group indicated a robust activation of immune function and a better response to immunotherapy, which may be responsible for a better prognosis. Furthermore, the predictive ability of the NRG score on prognosis and immunotherapeutic benefits was further revalidated using the other independent datasets of cutaneous melanoma. The results indicated that patients with low NRG scores exhibited prolonged survival. Surprisingly, all patients with CM with clinical response, including complete response/partial response, belonged to the low NRG score group.

Conclusion

Our present work revealed the close association between expression patterns of necroptosis-associated genes and tumor immune microenvironment. NRG score can serve as a potential predictor to independently assess patients' prognosis with CM and effectively estimate the response to immunological therapy, thus facilitating the identification of appropriate candidates with CM for immunotherapy and the formulation of individualized therapeutic approaches.

The significance of m6A RNA methylation modification in prognosis and tumor microenvironment immune infiltration of cervical cancer

Recent studies have highlighted that N6-methyladenosine (m6A) plays a significant role in tumorigenicity and progression. However, the mechanism of m6A modifications in the tumor microenvironment (TME) immune cell infiltration in cervical cancer (CC) remains unclear. Clinical and RNA sequencing data of 25 m6A RNA methylation regulators were acquired from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. LASSO Cox regression analysis was used to generate a prognostic risk signature. m6A modification patterns were identified based on the expression of 25 m6A regulators, and their correlation with TME immune cell-infiltrating characterization was analyzed. Principal component analysis was used to construct an m6A-scoring signature (m6A score) to evaluate the m6A modification patterns of individual CC samples and guide the selection of more effective immunotherapeutic strategies. Genetic and expression alterations of 25 m6A regulators were highly heterogeneous between CC and normal tissues. METTL14 and IGF2BP1 were selected to conduct the prognostic risk signature. Three m6A modification patterns were identified in 659 CC samples, which were associated with distinct clinical outcomes and biological pathways. The TME immune cell-infiltrating characterization of the three m6A modification patterns was highly consistent with 3 tumor immune phenotypes, including immune-excluded, immune-inflamed, and immune-desert phenotypes. Due to the heterogeneity of m6A modification patterns, an m6A scoring signature was established to evaluate the m6A modification patterns of individual CC samples. Univariate and multivariate Cox regression analyses revealed that the m6A score is a robust and independent prognostic biomarker for assessing the prognosis of CC patients. A low m6A score, characterized by higher somatic mutation and higher expression of proliferation-related and DNA repair-related genes, indicated poor overall survival. Activation of immune infiltration was exhibited by the high m6A score, which was likely to have a good response and clinical benefits to antiPD-1/L1 immunotherapy. This study highlights the prognostic value of 25 m6A regulators in CC. The m6A modification is related to immune regulation and the formation of TME heterogeneity and complexity. An m6A scoring signature to clarify the individual m6A modification pattern could enhance our understanding of TME immune cell-infiltrating characterization and guide immunotherapy strategies.

A Novel Defined Endoplasmic Reticulum Stress-Related lncRNA Signature for Prognosis Prediction and Immune Therapy in Glioma

Gliomas are a group of the most aggressive primary central nervous system tumors with limited treatment options. The abnormal expression of long non-coding RNA (lncRNA) is related to the prognosis of glioma. However, the role of endoplasmic reticulum (ER) stress-associated lncRNAs in glioma prognosis has not been reported. In this paper, we obtained ER stress-related lncRNAs by co-expression analysis, and then a risk signature composed of 6 ER stress-related lncRNAs was constructed using Cox regression analysis. Glioma samples in The Cancer Genome Atlas (TCGA) were separated into high- and low-risk groups based on the median risk score. Compared with the low-risk group, patients in the high-risk group had shorter survival times. Additionally, we verified the predictive ability of these candidate lncRNAs in the testing set. Three glioma patient subgroups (cluster 1/2/3) were identified by consensus clustering. We further analysed the abundance of immune-infiltrating cells and the expression levels of immune checkpoint molecules in both three subgroups and two risk groups, respectively. Immunotherapy and anticancer drug response prediction showed that ER stress-related lncRNA risk signature positively correlates with responding to immune checkpoints and chemosensitivity. Functional analysis showed that these gene sets are enriched in the malignant process of tumors. Finally, LINC00519 was chosen for functional experiments. The silence of LINC00519 restrained the migration and invasion of glioma cells. Hence, those results indicated that ER stress-related lncRNA risk signature could be a potential treatment target and a prognosis biomarker for glioma patients.

Prognostic Role of M6A-Associated Immune Genes and Cluster-Related Tumor Microenvironment Analysis: A Multi-Omics Practice in Stomach Adenocarcinoma

N6-methylandrostenedione (m6A) methylation plays a very important role in the development of malignant tumors. The immune system is the key point in the progression of tumors, particularly in terms of tumor treatment and drug resistance. Tumor immunotherapy has now become a hot spot and a new approach for tumor treatment. However, as far as the stomach adenocarcinoma (STAD) is concerned, the in-depth research is still a gap in the m6A-associated immune markers. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases is extremely important for our research, where we obtained gene mutation, gene expression data and relevant clinical information of STAD patients. Firstly, the samples from GEO were used as external validation groups, while the TCGA samples were divided into a training group and an internal validation group randomly. Using the way of Single factor COX-LASSO- and multi-factor Cox to construct the prognostic model. Then, all samples were subjected to cluster analysis to generate high and low expression groups of immune gene. Meanwhile, we also collected the correlation between these types and tumor microenvironment. On this basis, a web version of the dynamic nomogram APP was developed. In addition, we performed microenvironmental correlation, copy number variation and mutation analyses for model genes. The prognostic model for STAD developed here demonstrated a very strong predictive ability. The results of cluster analysis manifested that the immune gene low expression group had lower survival rate and higher degree of immune infiltration. Therefore, the immune gene low expression group was associated with lower survival rates and a higher degree of immune infiltration. Gene set enrichment analysis suggested that the potential mechanism might be related to the activation of immunosuppressive functions and multiple signaling pathways. Correspondingly, the web version of the dynamic nomogram APP produced by the DynNom package has successfully achieved rapid and accurate calculation of patient survival rates. Finally, the multi-omics analysis of model genes further enriched the research content. Interference of RAB19 was confirmed to facilitate migration of STAD cells in vitro, while its overexpression inhibited these features. The prognostic model for STAD constructed in this study is accurate and efficient based on multi-omics analysis and experimental validation. Additionally, the results of the correlation analysis between the tumor microenvironment and m6Ascore are the basics of further exploration of the pathophysiological mechanism in STAD.

RNA modification patterns based on major RNA modifications define tumor microenvironment characteristics in glioblastoma

RNA modifications play a major role in tumorigenicity and progression, but the expression and function in glioblastoma (GBM) have not been well described. In this study, we developed a GBM score based on the differentially expressed genes (DEGs) between groups showing RNA modification patterns. We assessed the association between the GBM score and tumor microenvironment (TME) characteristics. Based on the gene expression of these regulators, we identified two clusters with distinct RNA modification patterns. Kaplan–Meier survival curves showed that patients in cluster 1 had worse survival than those in cluster 2. Kaplan–Meier and multivariate Cox regression analyses showed that GBM scores (based on DEGs between RNA modification patterns) are an independent predictive biomarker for patient prognosis. Besides, we found that samples with high scores were significantly associated with epithelial-to-mesenchymal transition and immune checkpoints, while samples with low scores were associated with cell cycle regulation. Importantly, GBM-score markedly positively correlated drug resistance, while negatively correlated with drug sensitive. The responders of anti-PD-1/PD-L1 immunotherapy tend to have a lower GBM score than non-responders. In conclusion, our comprehensive analysis of multiple RNA modifications in GBM revealed that RNA modification regulators were closely correlated with TME.

Integrative Analyses of m6A Regulators Identify that METTL3 is Associated with HPV Status and Immunosuppressive Microenvironment in HPV-related Cancers

Although m6A modifications are associated with tumor progression, and anti-tumor immune responses, the role of m6A regulators in HPV-related carcinogenesis has not been well resolved. To provide evidence for the role of m6A regulators in HPV-related carcinogenesis and identify potential therapeutic targets for HPV-related cancers, integrative analyses of m6A regulators in 1,485 head and neck squamous cell carcinoma (HNSC) patients and 507 cervical squamous cell carcinoma (CESC) patients was performed and identified that an m6A regulator, METTL3, was highly expressed in tumors and was related to the poor prognosis in HNSC and CESC. In HPV-positive tumors, METTL3 was positively associated with tumor HPV status, such as HPV integration status, E6 and unspliced-E6 expression, and p16 expression. Further analysis demonstrated that METTL3 ^high status was negatively correlated with tumor immune cell infiltrations and facilitated the expression of immunosuppressive immune checkpoint molecules (i.e., PD-L1). Cell-derived xenograft models demonstrated that METTL3 inhibitor combined with anti-PD1 therapy promoted immunotherapy of CESC in vivo. Overall, this study identified that METTL3 ^high status, is associated with poor prognosis and HPV status, and serves as a mediator of the immunosuppressive tumor microenvironment in HPV-associated cancer, which provides a promising therapeutic target for anti-cancer immunotherapy.

A novel DNA damage and repair-related gene signature to improve predictive capacity of overall survival for patients with gliomas

Gliomas, as the most lethal and malignant brain tumours in adults, remain a major challenge worldwide. DNA damage and repair‐related genes (DDRRGs) appear to play a significant role in gliomas, but the studies of DDRRGs are still insufficient. Herein, we systematically explored and analysed 1547 DDRRGs in 938 glioma samples from TCGA and CGGA datasets. Using least absolute shrinkage and selection operator (LASSO) Cox regression analysis, we identified a 16‐DDRRG signature, characterized by high‐risk and low‐risk patterns. This risk model harbours robust predictive capability for overall survival of glioma patients. We found the high‐risk score is strongly associated with well‐known malignant features of gliomas, such as the mesenchymal subtype, IDH‐wildtype, 1p/19q non‐codeletion and MGMT promoter unmethylated status. In addition, we found that the high‐risk score is also linked with multiple oncogenic pathways and therapeutic resistance. Significantly, we found the high‐risk group has higher enrichment of immunosuppressive cells (M2‐type macrophages, Tregs and MDSCs) and immune inhibition biomarkers (PD‐1, PD‐L1 and CTLA‐4). Lastly, we proved that SMC4, which has the highest positive regression coefficient in our risk model, is strongly linked with malignant progression and TMZ resistance of gliomas in a E2F1‐dependent manner.

Bioinformatics Analysis of the Characteristics and Correlation of m6A Methylation in Breast Cancer Progression

Growing cutting-edge study has demonstrated the RNA m6A methylation's critical role in regulating tumorigenesis and progression all over the world, while it is still a mystery whether RNA m6A methylation has a positive impact on breast cancer treatment. In this article, we utilize bioinformatics to analyze three data sets including TCGA-BRCA, GSE96058, and GSE25066 and discover that breast cancer samples could be divided into 4 subtypes, which are quiescent, m6A methylation, protein-binding, and mixed, clarified by the expression level of m6A-related genes. R-survival analysis results also prove that the survival rate of breast cancer samples of the four subtypes significantly varies and remarkable differences in the number of exons' skip among the four subtypes can be seen according to the analysis of breast cancer gene expression characteristics. The degree of TP53 mutation and copy number loss is most obvious in the protein-binding subtype when it comes to tumor driver genes. Among the DNA damage repair genes, there is a sharp increase in the copy number of RAD54B of the protein-binding subtype, but fewer mutations in other DNA damage repair-related genes and copy number deletion is everywhere. Results of m6A methylation influencing on the proportion of infiltrated immune cells also indicate significant differences of the four m6A subgroups in macrophages M0 and mast cells resting which are closely correlated to patient prognosis. In addition, findings of the highest tumor stemness index and the lowest in the m6A methylated type in breast cancer samples can prove the critical role of the high expression of m6A reader protein in the progression of breast cancer.

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.

A Novel m1A-Score Model Correlated With the Immune Microenvironment Predicts Prognosis in Hepatocellular Carcinoma

RNA methylation plays crucial roles in gene expression and has been indicated to be involved in tumorigenesis, while it is still unclear whether m1A modifications have potential roles in the prognosis of hepatocellular carcinoma (HCC). In this study, we comprehensively analyzed RNA sequencing (RNA-seq) data and clinical information using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We collected 10 m1A regulators and performed consensus clustering to determine m1A modification patterns in HCC. The CIBERSORT method was utilized to evaluate the level of immune cell infiltration. Principal component analysis was used to construct the m1A-score model. In the TCGA-LIHC cohort, the expression of all 10 m1A regulators was higher in tumor tissues than in normal control tissues, and 8 of 10 genes were closely related to the prognosis of HCC patients. Two distinct m1A methylation modification patterns (Clusters C1 and C2) were identified by the 10 regulators and were associated with different overall survival, TNM stage and tumor microenvironment (TME) characteristics. Based on the differentially expressed genes (DEGs) between C1 and C2, we identified three gene clusters (Clusters A, B and C). C1 with a better prognosis was mainly distributed in Cluster C, while Cluster A contained the fewest samples of C1. An m1A-score model was constructed using five m1A regulators related to prognosis. Patients with higher m1A scores showed a poorer prognosis than those with lower scores in the TCGA-LIHC and GSE14520 datasets. In conclusions, our study showed the vital role of m1A modification in the TME and progression of HCC. Quantitative evaluation of the m1A modification patterns of individual patients facilitates the development of more effective biomarkers for predicting the prognosis of patients with HCC.

Comprehensive characterization of m6A methylation and its impact on prognosis, genome instability, and tumor microenvironment in hepatocellular carcinoma

Background

N6-methyladenosine (m6A) RNA regulation was recently reported to be important in carcinogenesis and cancer development. However, the characteristics of m6A modification and its correlations with clinical features, genome instability, tumor microenvironments (TMEs), and immunotherapy responses in hepatocellular carcinoma (HCC) have not been fully explored.

Methods

We systematically analyzed the m6A regulator-based expression patterns of 486 patients with HCC from The Cancer Genome Atlas and Gene Expression Omnibus databases, and correlated these patterns with clinical outcomes, somatic mutations, TME cell infiltration, and immunotherapy responses. The m6A score was developed by principal component analysis to evaluate m6A modifications in individual patients.

Results

M6A regulators were dysregulated in HCC samples, among which 18 m6A regulators were identified as risk factors for prognosis. Three m6A regulator-based expression patterns, namely m6A clusters, were determined among HCC patients by m6A regulators with different m6A scores, somatic mutation counts, and specific TME features. Additionally, three distinct m6A regulator-associated gene-based expression patterns were also identified based on prognosis-associated genes that were differentially expressed among the three m6A clusters, showing similar properties as the m6A regulator-based expression patterns. Higher m6A scores were correlated with older age, advanced stages, lower overall survival, higher somatic mutation counts, elevated PD-L1 expression levels, and poorer responses to immune checkpoint inhibitors. The m6A score was validated as an independent and valuable prognostic factor for HCC.

Conclusion

M6A modification is correlated with genome instability and TME in HCC. Evaluating m6A regulator-based expression patterns and the m6A score of individual tumors may help identify candidate biomarkers for prognosis prediction and immunotherapeutic strategy selection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01207-x.

5-Methylcytosine Related LncRNAs Reveal Immune Characteristics, Predict Prognosis and Oncology Treatment Outcome in Lower-Grade Gliomas

5-Methylcytosine (m5C) methylation is an important RNA modification pattern that can participate in oncogenesis and progression of cancers by affecting RNA stability, expression of oncogenes, and the activity of cancer signaling pathways. Alterations in the expression pattern of long non-coding RNAs (lncRNAs) are potentially correlated with abnormalities in the m5C regulation features of cancers. Our aim was to reveal the mechanisms by which lncRNAs regulated the m5C process, to explore the impact of aberrant regulation of m5C on the biological properties of lower-grade gliomas (LGG), and to optimize current therapeutic. By searching 1017 LGG samples from the Cancer Genome Atlas and Chinese Glioma Genome Atlas, we first clarified the potential impact of m5C regulators on LGG prognosis in this study and used univariate Cox analysis and least absolute shrinkage and selection operator regression to explore clinically meaningful lncRNAs. Consequently, we identified four lncRNAs, including LINC00265, CIRBP-AS1, GDNF-AS1, and ZBTB20-AS4, and established a novel m5C-related lncRNAs signature (m5CrLS) that was effective in predicting prognosis. Notably, mutation rate, WHO class II, IDH mutation, 1p/19q co-deletion and MGMT promoter methylation were increased in the low m5CrLS score group. Patients with increased m5CrLS scores mostly showed activation of tumor malignancy-related pathways, increased immune infiltrating cells, and decreased anti-tumor immune function. Besides, the relatively high expression of immune checkpoints also revealed the immunosuppressed state of patients with high m5CrLS scores. In particular, m5CrLS stratification was sensitive to assess the efficacy of LGG to temozolomide and the responsiveness of immune checkpoint blockade. In conclusion, our results revealed the molecular basis of LGG, provided valuable clues for our understanding of m5C-related lncRNAs, and filled a gap between epigenetics and tumor microenvironment.

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.

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.

Comprehensive Analysis of N6-Methyladenosine (m6A) Methylation in Neuromyelitis Optica Spectrum Disorders

Background: N⁶-Methyladenosine (m⁶A) methylation is the most prevalent internal posttranscriptional modification on mammalian mRNA. But its role in neuromyelitis optica spectrum disorders (NMOSD) is not known. Aims: To explore the mechanism of m⁶A in NMOSD patients. Methods: This study assessed the m⁶A methylation levels in blood from two groups: NMOSD patients and healthy controls. Methylated RNA immunoprecipitation Sequencing (MeRIP-seq) and RNA-seq were performed to assess differences in m⁶A methylation between NMOSD patients and healthy controls. Ultra-high performance liquid chromatography coupled with triple quadruple mass spectrometry (UPLC-QQQ-MS) method was performed to check m⁶A level. Differential m⁶A methylation genes were validated by MeRIP-qPCR. Results: Compared with that in the control group, the total m6A level was decreased in the NMOSD group. Genes with upregulated methylation were primarily enriched in processes associated with RNA splicing, mRNA processing, and innate immune response, while genes with downregulated methylation were enriched in processes associated with the regulation of transcription, DNA-templating, and the positive regulation of I-kappa B kinase/NF-kappa B signalling. Conclusion: These findings demonstrate that differential m⁶A methylation may act on functional genes to regulate immune homeostasis in NMOSD.

m6A Regulator-Mediated Methylation Modification Patterns and Tumor Microenvironment Infiltration Characterization in Acute Myeloid Leukemia

Recent studies have demonstrated epigenetic regulation of immune responses. Nevertheless, the underlying effect of RNA N6-methyladenosine (m6A) modifications on tumor microenvironment cell infiltration remains elusive. In this study, we thoroughly assessed m6A modification patterns of 255 myeloid leukemia specimens based on 23 m6A regulators. Consensus clustering of the 23 m6A regulators was performed to determine three distinct m6A modification patterns that were remarkably consistent with three immunophenotypes of tumors: immunorejection, immune activation, and immune inertness. Further evaluation and prognostic analysis of the m6A modification patterns of individual tumors revealed that low m6A score was characterized by increased mutational burden, immune activation, and survival rates, whereas high m6A score was characterized by poorer survival rates and the absence of effective immune infiltration. In addition, this study investigated the association between m6A regulators and antitumor immune responses and discovered higher expression of the immune regulators PD-L1, PD-L2, MRP1, and MRP2 in low m6A scores. Generally, the expression pattern of m6A regulators was remarkably associated with prognostic results and antitumor immune responses in acute myeloid leukemia and may be an underlying target and biological marker for immune therapies.

Analysis of Multi-Layer RNA Modification Patterns for the Characterization of Tumor Immune Microenvironment in Hepatocellular Carcinoma

Background: RNA modifications have emerged as important posttranscriptional changes in multiple tumor cellular processes and tumorigenesis, including hepatocellular carcinoma (HCC). However, the potential roles and the interaction between regulators of RNA modifications and the tumor microenvironment (TME) are unclear in HCC. Methods: The gene expression profiles of 26 RNA modification "writers" were investigated in the TCGA cohort. The unsupervised clustering approach was used to class these RNA modification regulators. The characteristics of immune cell infiltration from TME for each cluster was tested by the CIBERSORT method. Additionally, we established a scoring model to evaluate the RNA modification characteristics of individual tumors. The associations between the scoring model and genetic as well as clinical characteristics, drug sensitivity, and response to immunotherapy were also analyzed. Results: We mapped the somatic mutations and somatic copy number variation of the RNA modification regulators. The expression of all selected regulators was detected, and two modification patterns were identified that featured distinct immune cell infiltration characteristics. Subsequently, we developed a score model (termed as WM-Score model). Furthermore, the survival analysis showed that the WM-Score value was associated with HCC patient prognosis. The results of the ROC curves analysis and multivariate analysis all confirmed that the WM-Score value was strongly associated with anti-cancer drug resistance and therapeutic efficacy of immunotherapy, thus could be used as an independent risk factor in HCC. Conclusion: Our research identified two RNA modification patterns characterized by distinct TME, and the WM-Score model was developed that might serve as reliable prognostic and immunotherapeutic effect predictor of HCC.

Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer

Pancreatic cancer (PAAD) is one of the most malignant cancers and immune microenvironment has been proved to be involved in pathogenesis of PAAD. m6A modification, related to the expression of m6A regulators, participates in the development of multiple cancers. However, the correlation between m6A regulators and immune microenvironment was largely unknown in PAAD. And because of the small sample size of pancreatic cancer in the TCGA database, it is not enough to draw a convincing conclusion. In the present study, we downloaded seven pancreatic cancer datasets with survival data and removed batch effects among these datasets to be used as the PAAD cohort to analyze the immune landscape of PAAD and the expression pattern of m6A regulators and divided the integrated dataset into cluster 1 and cluster 2 by consensus clustering for m6A regulators. Lower m6A regulators were found to be related to higher immune cell infiltration and a better survival. Moreover, we identified six m6A regulators and constructed the prognostic signature of m6A regulators. Patients with low-risk score had a higher response to immune checkpoint inhibitor and a longer overall survival. To figure out the underlying mechanism, we analyzed the cancer immunity cycle, most altered genes, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) in risk subtypes. In summary, the present study proved m6A regulators modulated the PAAD immune microenvironment. And risk scores served as predictive indicator for immunotherapy and played a prognostic role for PAAD patients. Our study provided novel therapeutic targets to improve immunotherapy efficacy.

Construction of a Novel Signature and Prediction of the Immune Landscape in Soft Tissue Sarcomas Based on N6-Methylandenosine-Related LncRNAs

Background: N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) are critically involved in cancer development. However, the roles and clinical significance of m6A-related lncRNAs in soft tissue sarcomas (STS) are inconclusive, thereby warranting further investigations.

Methods: Transcriptome profiling data were extracted from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx). Consensus clustering was employed to divide patients into clusters and Kaplan–Meier analysis was used to explore the prognostic differences between the subgroups. Gene set enrichment analysis (GSEA) was conducted to identify the biological processes and signaling pathways associated with m6A-Related lncRNAs. Finally, patients were randomly divided into training and validation cohorts, and least absolute shrinkage and selection operator (LASSO) Cox regression was conducted to establish the m6A-related lncRNA-based risk signature.

Results: A total of 259 STS patients from TCGA-SARC dataset were enrolled in our study. Thirteen m6A-Related lncRNAs were identified to be closely related to the prognosis of STS patients. Patients were divided into two clusters, and patients in cluster 2 had a better overall survival (OS) than those in cluster 1. Patients in different clusters also showed differences in immune scores, infiltrating immune cells, and immune checkpoint expression. Patients were further classified into high-risk and low-risk subgroups according to risk scores, and high-risk patients were found to have a worse prognosis. The receiver operating characteristic (ROC) curve indicated that the risk signature displayed excellent performance at predicting the prognosis of patients with STS. Further, the risk signature was remarkably connected with the immune microenvironment and chemosensitivity in STS.

Conclusion: Our study demonstrated that m6A-related lncRNAs were significantly associated with prognosis and tumor immune microenvironment and could function as independent prognosis-specific predictors in STS, thereby providing novel insights into the roles of m6A-related lncRNAs in STS.

Potentiality of α-fetoprotein (AFP) and soluble intercellular adhesion molecule-1 (sICAM-1) in prognosis prediction and immunotherapy response for patients with hepatocellular carcinoma

The α-fetoprotein (AFP) and soluble intercellular adhesion molecule-1 (sICAM-1) have certain diagnostic value, but their potential value in prognosis prediction, especially immunotherapy response prediction, remains unclear in liver cancer. Through the tumor-free survival (TFS) and overall survival (OS) rates analyses of serum AFP and sICAM-1 levels in 87 patients with primary hepatocellular carcinoma (HCC), the patients whose AFP and sICAM-1 levels were normal (AFP < 20 μg/L or sICAM-1 < 1000 μg/L) before surgery or recovered to normal after surgery exhibited a lower tumor recurrence rate and better OS than patients with elevated serum levels of the two markers. Combined analysis showed that patients with synchronously elevated levels of AFP and sICAM-1 showed the lowest TFS and OS. In addition, the RNA-seq data and clinical information of The Cancer Genome Atlas Liver Hepatocellular Carcinoma were collected to analyze the predictive values of AFP and ICAM-1 in the diagnosis, prognosis and immunotherapy of HCC. The results indicated that the combined application of the two indicators had higher accuracy in both the diagnosis and prognostic prediction of HCC by receiver operating characteristic curves. AFP and ICAM-1 were significantly correlated with multiple immune cells in HCC samples but not in normal samples. The patients with low expression of the two indicators were most likely to benefit from the immune checkpoint blockade therapy. In conclusion, AFP and ICAM-1 play vital roles in the diagnosis, prognostic prediction, and immunotherapy of HCC, suggesting that they are considered as prognostic predictors in clinical practice.

m6A regulator-mediated RNA methylation modification patterns and immune microenvironment infiltration characterization in severe asthma

N6‐methyladenosine (m6A) modification is one of the most prevalent RNA modification forms of eukaryotic mRNA and is an important post‐transcriptional mechanism for regulating genes. However, the role of m6A modification in the regulation of severe asthma has never been reported. Thus, we aimed to investigate the m6A regulator‐mediated RNA methylation modification patterns and immune microenvironment infiltration characterization in severe asthma. In this study, 87 healthy controls and 344 severe asthma cases from the U‐BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) programme were used to systematically evaluate the m6A modification patterns mediated by 27 m6A regulators and to investigate the effects of m6A modification on immune microenvironment characteristics. We found that 16 m6A regulators were abnormal and identified two key m6A regulators (YTHDF3 and YTHDC1) and three m6A modification patterns. The study of infiltration characteristics of immune microenvironment found that pattern 2 had more infiltrating immune cells and more active immune response. Besides, it was found that the eosinophils which are very important for severe asthma were affected by YTHDF3 and EIF3B. We also verified key m6A regulators with merip‐seq and found that they were mainly distributed in exons and enriched in 3′UTR. In conclusion, our findings suggested that m6A modification plays a key role in severe asthma, and may be able to guide the future strategy of immunotherapy.

Comprehensive analyses of glycolysis-related lncRNAs for ovarian cancer patients

Background

Not only glycolysis but also lncRNAs play a significant role in the growth, proliferation, invasion and metastasis of of ovarian cancer (OC). However, researches about glycolysis -related lncRNAs (GRLs) remain unclear in OC. Herein, we first constructed a GRL-based risk model for patients with OC.

Methods

The processed RNA sequencing (RNA-seq) profiles with clinicopathological data were downloaded from TCGA and glycolysis-related genes (GRGs) were obtained from MSigDB. Pearson correlation coefficient between glycolysis-related genes (GRGs) and annotated lncRNAs (|r| > 0.4 and p < 0.05) were calculated to identify GRLs. After screening prognostic GRLs, a risk model based on five GRLs was constructed using Univariate and Cox regression. The identified risk model was validated by two validation sets. Further, the differences in clinicopathology, biological function, hypoxia score, immune microenvironment, immune checkpoint, immune checkpoint blockade, chemotherapy drug sensitivity, N6-methyladenosine (m6A) regulators, and ferroptosis-related genes between risk groups were explored by abundant algorithms. Finally, we established networks based on co-expression, ceRNA, cis and trans interaction.

Results

A total of 535 GRLs were gained and 35 GRLs with significant prognostic value were identified. The prognostic signature containing five GRLs was constructed and validated and can predict prognosis. The nomogram proved the accuracy of the model for predicting prognosis. After computing hypoxia score of each sample by ssGSEA, we found patients with higher risk scores exhibited higher hypoxia score and high hypoxia score was a risk factor. It was revealed that a total of 21 microenvironment cells (such as Central memory CD4 T cell, Neutrophil, Regulatory T cell and so on) and Stromal score had significant differences between the two groups. Four immune checkpoint genes (CD274, LAG3, VTCN1, and CD47) showed disparate expression levels in the two groups. Besides, 16 m6A regulators and 126 ferroptosis-related genes were expressed higher in the low-risk group. GSEA revealed that the risk groups were associated with tumor-related pathways. The two risk groups were confirmed to be sensitive to several chemotherapeutic agents and patients in the low-risk group were more sensitive to ICB therapy. The networks based on co-expression, ceRNA, cis and trans interaction provided insights into the regulatory mechanisms of GRLs.

Conclusions

Our identified and validated risk model based on five GRLs is an independent prognostic factor for OC patients. Through comprehensive analyses, findings of our study uncovered potential biomarker and therapeutic target for the risk model based on the GRLs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00881-2.

CD74 Correlated With Malignancies and Immune Microenvironment in Gliomas

Background: Cluster of differentiation 74 (CD74) is found to be highly involved in the development of various types of cancers and could affect the activities of infiltrated cells in the tumor microenvironment. However, these studies only focus on a few types of immune cells. Our study aims to comprehensively explore the role of CD74 in glioma prognosis and immune microenvironment. Methods: A total of 40 glioma specimens were collected in this study. We extracted data from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene-Expression Omnibus (GEO) databases to explore the expression pattern of CD74 in gliomas. gene sets enrichment analysis and gene set variation analysis analyses were conducted to characterize the immune features of CD74. ESTIMATE, ssGSEA, Tumor IMmune Estimation Resource, and CIBERSORT algorithms were applied to assess the immune infiltration. Kaplan-Meier analysis was used for survival analysis. Receiver operating characteristic analysis was used to evaluate the predictive accuracy of CD74 in glioma diagnosis and prognosis. Results: A total of 2,399 glioma patients were included in our study. CD74 was highly expressed in glioma tissue compared to normal brain tissue and its expression was significantly higher in the high-grade glioma compared to the lower grade glioma at transcriptional and translational levels. Besides, CD74 was positively associated with immune checkpoints and inflammatory cytokines as well as immune processes including cytokine secretion and leukocyte activation. The high expression of CD74 indicated a high infiltration of immune cells such as macrophages, dendritic cells, and neutrophils. Moreover, patients with high expression of CD74 had poor prognoses. CD74 had moderate predictive accuracy in the diagnosis of glioblastoma and prediction of survival. Conclusions: In conclusion, our study revealed that the high expression of CD74 was associated with poor prognosis and high immune infiltration. CD74 could be used as a potential target for glioma treatment and as a biomarker to predict the prognosis of glioma patients.

m6A regulator-mediated methylation modification patterns and tumor microenvironment infiltration characterization in hepatocellular carcinoma

Background: There is increasing evidence of the epigenetic regulation of the immune response in cancer. However, the specific functions and mechanisms of RNA N6-methyladenosine (m6A) modification in the cell infiltration in the hepatocellular carcinoma (HCC) tumor microenvironment (TME) is unknown.

Methods: We systematically analyzed the m6A-modification patterns of 371 HCC samples based on 23 m6A regulators, and determined their correlation with TME cell-infiltrating characteristics. Principal-component analysis algorithms was used to calculate the m6Ascore and clarify the m6A-modification patterns of individual tumors.

Results: Three different m6A-modification patterns were identified in HCC, wherein the m6Acluster B and m6Acluster A had the best and worst prognosis, respectively. These three patterns had different TME cell infiltration characteristics and biological behavior. An m6A-scoring signature was constructed to evaluate the m6A-modification patterns within individual tumors. A low m6Ascore was associated with a low overall survival and high clinical stage. Moreover, the m6A-scoring signature was characterized by distinct immunotherapeutic landscapes; a high m6A score indicated a higher immune checkpoint inhibitor score in the anti-PD-1 treatment alone, anti-CTLA-4 treatment alone, or combined anti-CTLA-4/PD-1 treatment cohorts, which reflected significant treatment and clinical benefits.

Conclusions: Our study highlights the significant role of the m6A modification in the HCC TME. A scoring signature to clarify the individual m6A-modification pattern would help us understand the HCC TME infiltration characterization and, thus, would guide the selection of more effective immunotherapeutic strategies.

Quantification of m6A RNA methylation modulators pattern was a potential biomarker for prognosis and associated with tumor immune microenvironment of pancreatic adenocarcinoma

BACKGROUND

m6A is the most prevalent and abundant form of mRNA modifications and is closely related to tumor proliferation, differentiation, and tumorigenesis. In this study, we try to conduct an effective prediction model to investigated the function of m6A RNA methylation modulators in pancreatic adenocarcinoma and estimated the potential association between m6A RNA methylation modulators and tumor microenvironment infiltration for optimization of treatment.

METHODS

Expression of 28 m6A RNA methylation modulators and clinical data of patients with pancreatic adenocarcinoma and normal samples were obtained from TCGA and GTEx database. Differences in the expression of 28 m6A RNA methylation modulators between tumour (n = 40) and healthy (n = 167) samples were compared by Wilcoxon test. LASSO Cox regression was used to select m6A RNA methylation modulators to analyze the relationship between expression and clinical characteristics by univariate and multivariate regression. A risk score prognosis model was conducted based on the expression of select m6A RNA methylation modulators. Bioinformatics analysis was used to explore the association between the m6Ascore and the composition of infiltrating immune cells between high and low m6Ascore group by CIBERSORT algorithm. Evaluation of m6Ascore for immunotherapy was analyzed via the IPS and three immunotherapy cohort. Besides, the biological signaling pathways of the m6A RNA methylation modulators were examined by gene set enrichment analysis (GSEA).

RESULTS

Expression of 28 m6A RNA methylation modulators were upregulated in patients with PAAD except for MTEEL3. An m6Ascore prognosis model was established, including KIAA1429, IGF2BP2, IGF2BP3, METTL3, EIF3H and LRPPRC was used to predict the prognosis of patients with PAAD, the high risk score was an independent prognostic indicator for pancreatic adenocarcinoma, and a high risk score presented a lower overall survival. In addition, m6Ascore was related with the immune cell infiltration of PAAD. Patients with a high m6Ascore had lower infiltration of Tregs and CD8+T cells but a higher resting CD4+ T infiltration. Patients with a low m6Ascore displayed a low abundance of PD-1, CTLA-4 and TIGIT, however, the IPS showed no difference between the two groups. The m6Ascore applied in three immunotherapy cohort (GSE78220, TCGA-SKCM, and IMvigor210) did not exhibit a good prediction for estimating the patients' response to immunotherapy, so it may need more researches to figure out whether the m6A modulator prognosis model would benefit the prediction of pancreatic patients' response to immunotherapy.

CONCLUSION

Modulators involved in m6A RNA methylation were associated with the development of pancreatic cancer. An m6Ascore based on the expression of IGF2BP2, IGF2BP3, KIAA1429, METTL3, EIF3H and LRPPRC is proposed as an indicator of TME status and is instrumental in predicting the prognosis of pancreatic cancer patients.

Significance of N6-Methyladenosine RNA Methylation Regulators in Immune Infiltrates of Ovarian Cancer

N6-methyladenosine (m6A) RNA methylation regulators play an important role in the occurrence and development of tumors. Here, we aimed to identify the potential roles of m6A RNA methylation regulators in immune infiltrates of ovarian cancer. We obtained two distinct m6A patterns (m6Acluster.A and m6Acluster.B) based on the expression levels of all 21 m6A RNA methylation regulators from The Cancer Genome Atlas (TCGA) database using a consensus clustering algorithm. Differential analysis of m6Acluster.A and m6Acluster.B identified 196 m6A-related genes. We further validated the m6A regulation mechanism based on the 196 m6A-related genes using another consensus clustering algorithm. Considering individual differences, principal component analysis algorithms were used to calculate an m6A score for each sample in order to quantify the m6A patterns. A low m6A score was associated with immune activation and enhanced response to immune checkpoint inhibitors, whereas a high m6A score was associated with tumor progression. Finally, we successfully verified the correlation between m6A regulators and immune microenvironment in OC using our microarray analysis data. In summary, m6A regulators play non-negligible roles in immune infiltrates of ovarian cancer. Our investigation of m6A patterns may help to guide future immunotherapy strategies for advanced ovarian cancer.

The interplay between m6A modification and non-coding RNA in cancer stemness modulation: mechanisms, signaling pathways, and clinical implications

Cancer stemness, mainly consisting of chemo-resistance, radio-resistance, tumorigenesis, metastasis, tumor self-renewal, cancer metabolism reprogramming, and tumor immuno-microenvironment remodeling, play crucial roles in the cancer progression process and has become the hotspot of cancer research field in recent years. Nowadays, the exact molecular mechanisms of cancer stemness have not been fully understood. Extensive studies have recently implicated that non-coding RNA (ncRNA) plays vital roles in modulating cancer stemness. Notably, N6-methyladenosine (m6A) modification is of crucial importance for RNAs to exert their biological functions, including RNA splicing, stability, translation, degradation, and export. Emerging evidence has revealed that m6A modification can govern the expressions and functions of ncRNAs, consequently controlling cancer stemness properties. However, the interaction mechanisms between ncRNAs and m6A modification in cancer stemness modulation are rarely investigated. In this review, we elucidate the recent findings on the relationships of m6A modification, ncRNAs, and cancer stemness. We also focus on some key signaling pathways such as Wnt/β-catenin signaling, MAPK signaling, Hippo signaling, and JAK/STAT3 signaling to illustrate the underlying interplay mechanisms between m6A modification and ncRNAs in cancer stemness. In particular, we briefly highlight the clinical potential of ncRNAs and m6A modifiers as promising biomarkers and therapeutic targets for indicating cancer stemness properties and improving the diagnostic precision for a wide variety of cancers.

Bioinformatic Analyses Identify a Prognostic Autophagy-Related Long Non-coding RNA Signature Associated With Immune Microenvironment in Diffuse Gliomas

Background

Autophagy and long non-coding RNA (lncRNA) play a critical role in tumor progression and microenvironment. However, the role of autophagy-related lncRNAs (ARLs) in glioma microenvironment remains unclear.

Methods

A total of 988 diffuse glioma samples were extracted from TCGA and CGGA databases. Consensus clustering was applied to reveal different subgroups of diffuse gliomas. Kaplan-Meier analysis was used to evaluate survival differences between groups. The infiltration of immune cells was estimated by ssGSEA, TIMER, and CIBERSORT algorithms. The construction of ARL signature was conducted using principal component analysis.

Results

Consensus clustering revealed two clusters of diffuse gliomas, in which cluster 1 was associated with poor prognosis and enriched with malignant subtypes of gliomas. Moreover, cluster 1 exhibited high apoptotic and immune characteristics, and it had a low purity and high infiltration of several immune cells. The constructed ARL signature showed a promising accuracy in predicting the prognosis of glioma patients. ARL score was significantly elevated in the malignant subtype of glioma and the high ARL score indicated a poor prognosis. Besides, the high ARL score notably indicated low tumor purity and high infiltration of macrophages and neutrophils.

Conclusion

Our study developed and validated a novel ARL signature for the classification of diffuse glioma, which was closely associated with glioma immune microenvironment and could serve as a promising prognostic biomarker for glioma patients.

M5C regulator-mediated methylation modification patterns and tumor microenvironment infiltration characterization in lung adenocarcinoma

Background

In recent years, immunotherapy has made great progress, and the regulatory role of epigenetics has been verified. However, the role of 5-methylcytosine (m⁵C) in the tumor microenvironment (TME) and immunotherapy response remains unclear.

Methods

Based on 11 m⁵C regulators, we evaluated the m⁵C modification patterns of 572 lung adenocarcinoma (LUAD) patients. The m⁵C score was constructed by principal component analysis (PCA) algorithms in order to quantify the m⁵C modification pattern of individual LUAD patients.

Results

Two m⁵C methylation modification patterns were identified according to 11 m⁵C regulators. The two patterns had a remarkably distinct TME immune cell infiltration characterization. Next, 226 differentially expressed genes (DEGs) related to the m⁵C phenotype were screened. Patients were divided into three different gene cluster subtypes based on these genes, which had different TME immune cell infiltration and prognosis characteristics. The m⁵C score was constructed to quantify the m⁵C modification pattern of individual LUAD patients. We found that the high m⁵C score group had a better prognosis. The role of the m⁵C score in predicting prognosis was also verified in the dataset GSE31210.

Conclusions

Our study revealed that m⁵C modification played a significant role in TME regulation of LUAD. Investigation of the m⁵C regulation mode may have some implications for tumor immunotherapy in the future.