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

m6A-Dependent ITIH1 Regulated by TGF-β Acts as a Target for Hepatocellular Carcinoma Progression

Both the transforming growth factor beta (TGF-β) signaling pathway and N6-methyladenosine (m6A) modification for mRNA play an important role in hepatocellular carcinoma (HCC) progression. However, the relationship between TGF-β and m6A in hepatocellular carcinoma (HCC) remains unclear. Here, it is found that TGF-β can promote the liquid phase separation of METTL3, which further leads to the reduction of mRNA stability of ITIH1. As a secreted protein, ITIH1 can act as a ligand of integrin α5β1 to antagonize fibronectin, induce the inhibition of focal adhesion kinase signaling pathway, and inhibit the progression of HCC. In the preclinical model (mouse model, patient-derived organoid, patient-derived xenografts), purified recombinant ITIH1 (r-ITIH1) protein can be targeted for HCC. More importantly, r-ITIH1 can play a synergistic role in targeting HCC with TGF-β inhibitor. The downstream ITIH1 regulatory mechanism of TGF-β and m6A modification is revealed, and ITIH1 can be translational as a potential target for HCC.

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.

DNA methylation regulator-based molecular subtyping and tumor microenvironment characterization in hepatocellular carcinoma

Backgroud

Although recent studies have reported the regulation of the immune response in hepatocellular carcinoma (HCC) through DNA methylation, the comprehensive impact methylation modifications on tumor microenvironment characteristics and immunotherapy efficacy has not been fully elucidated.

Methods

In this research, we conducted a comprehensive assessment of the patterns of DNA methylation regulators and the profiles of the tumor microenvironment (TME) in HCC, focusing on 21 specific DNA methylation regulators. We subsequently developed a unique scoring system, a DNA methylation score (DMscore), to assess the individual DNA methylation modifications among the three distinct methylation patterns for differentially expressed genes (DEGs).

Results

Three distinct methylation modification patterns were identified with distinct TME infiltration characteristics. We demonstrated that the DMscore could predict patient subtype, TME infiltration, and patient prognosis. A low DMscore, characterized by an elevated tumor mutation burden (TMB), hepatitis B virus (HBV)/hepatitis C virus (HCV) infection, and immune activation, indicates an inflamed tumor microenvironment phenotype with a 5-year survival rate of 7.8%. Moreover, a low DMscore appeared to increase the efficacy of immunotherapy in the anti-CTLA-4/PD-1/PD-L1 cohort.

Conclusions

In brief, this research has enhanced our understanding of the correlation between modifications in DNA methylation patterns and the profile of the tumor microenvironment in individuals diagnosed with HCC. The DMscore may serve as an alternative biomarker for survival and efficacy of immunotherapy in patients with HCC.

Decoding m6A mRNA methylation by reader proteins in liver diseases

N6-methyladenosine (m6A) is a dynamic and reversible epigenetic regulation. As the most prevalent internal post-transcriptional modification in eukaryotic RNA, it participates in the regulation of gene expression through various mechanisms, such as mRNA splicing, nuclear export, localization, translation efficiency, mRNA stability, and structural transformation. The involvement of m6A in the regulation of gene expression depends on the specific recognition of m6A-modified RNA by reader proteins. In the pathogenesis and treatment of liver disease, studies have found that the expression levels of key genes that promote or inhibit the development of liver disease are regulated by m6A modification, in which abnormal expression of reader proteins determines the fate of these gene transcripts. In this review, we introduce m6A readers, summarize the recognition and regulatory mechanisms of m6A readers on mRNA, and focus on the biological functions and mechanisms of m6A readers in liver cancer, viral hepatitis, non-alcoholic fatty liver disease (NAFLD), hepatic fibrosis (HF), acute liver injury (ALI), and other liver diseases. This information is expected to be of high value to researchers deciphering the links between m6A readers and human liver diseases.

Cuprotosis clusters predict prognosis and immunotherapy response in low-grade glioma

Cuprotosis, an emerging mode of cell death, has recently caught the attention of researchers worldwide. However, its impact on low-grade glioma (LGG) patients has not been fully explored. To gain a deeper insight into the relationship between cuprotosis and LGG patients' prognosis, we conducted this study in which LGG patients were divided into two clusters based on the expression of 18 cuprotosis-related genes. We found that LGG patients in cluster A had better prognosis than those in cluster B. The two clusters also differed in terms of immune cell infiltration and biological functions. Moreover, we identified differentially expressed genes (DEGs) between the two clusters and developed a cuprotosis-related prognostic signature through the least absolute shrinkage and selection operator (LASSO) analysis in the TCGA training cohort. This signature divided LGG patients into high- and low-risk groups, with the high-risk group having significantly shorter overall survival (OS) time than the low-risk group. Its predictive reliability for prognosis in LGG patients was confirmed by the TCGA internal validation cohort, CGGA325 cohort and CGGA693 cohort. Additionally, a nomogram was used to predict the 1-, 3-, and 5-year OS rates of each patient. The analysis of immune checkpoints and tumor mutation burden (TMB) has revealed that individuals belonging to high-risk groups have a greater chance of benefiting from immunotherapy. Functional experiments confirmed that interfering with the signature gene TNFRSF11B inhibited LGG cell proliferation and migration. Overall, this study shed light on the importance of cuprotosis in LGG patient prognosis. The cuprotosis-related prognostic signature is a reliable predictor for patient outcomes and immunotherapeutic response and can help to develop new therapies for LGG.

m6A methylation modification and immune cell infiltration: implications for targeting the catalytic subunit m6A-METTL complex in gastrointestinal cancer immunotherapy

N6-methyladenosine (m6A) methylation modification is a ubiquitous RNA modification involved in the regulation of various cellular processes, including regulation of RNA stability, metabolism, splicing and translation. Gastrointestinal (GI) cancers are some of the world's most common and fatal cancers. Emerging evidence has shown that m6A modification is dynamically regulated by a complex network of enzymes and that the catalytic subunit m6A-METTL complex (MAC)-METTL3/14, a core component of m6A methyltransferases, participates in the development and progression of GI cancers. Furthermore, it has been shown that METTL3/14 modulates immune cell infiltration in an m6A-dependent manner in TIME (Tumor immune microenvironment), thereby altering the response of cancer cells to ICIs (Immune checkpoint inhibitors). Immunotherapy has emerged as a promising approach for treating GI cancers. Moreover, targeting the expression of METTL3/14 and its downstream genes may improve patient response to immunotherapy. Therefore, understanding the role of MAC in the pathogenesis of GI cancers and its impact on immune cell infiltration may provide new insights into the development of effective therapeutic strategies for GI cancers.

Diagnostic value and immune infiltration characterization of YTHDF2 as a critical m6A regulator in osteoarthritic synovitis

BACKGROUND

N6-methyladenosine (m6A) is a universal RNA modification pattern regulated by multiple m6A regulators. In osteoarthritis (OA), m6A regulators influence disease progression by regulating cartilage degradation. However, the function of m6A regulators in synovial tissue remains unclear. In this work, we investigated the biological significance of m6A regulators in osteoarthritic synovitis.

METHODS

Datasets were acquired from Gene Expression Omnibus. Differential analysis of merged data identified the differentially expressed m6A regulators. Machine learning models were used to evaluate genetic importance. To predict disease risk, a nomogram was constructed based on above m6A regulators. Cluster analysis divided the OA sample into different subgroups. Immune infiltration revealed the immune m6A regulators, which were validated using clinical samples. Eventually, a competing endogenous RNA (ceRNA) network was constructed.

RESULTS

We acquired five differentially expressed m6A regulators and a random forest model. The nomogram accurately predicted disease risk. We identified 122 differentially expressed genes between two m6A subgroups. The analysis of immune infiltration showed that YTHDF2 was an immune-related m6A regulator closely related with macrophages. In clinical samples, the protein and mRNA contents of YTHDF2 were consistent with the results of bioinformatic analysis. The ceRNA network based on YTHDF2 revealed 75 lncRNA nodes and 19 miRNA nodes.

CONCLUSION

YTHDF2 has a high diagnostic value in the synovitis of OA and significantly influences the immune status of patients. Hence, YTHDF2, a critical m6A regulator, may provide a biomarker for diagnosis and immune therapy of osteoarthritic synovitis.

N6-methyladenosine RNA modification in PD-1/PD-L1: Novel implications for immunotherapy

Cancer immunotherapy has been shown to achieve significant antitumor effects in a variety of malignancies. Out of all the immune checkpoint molecules, PD-1/PD-L1 inhibitor therapy has achieved great success. However, only some cancer patients benefit from this treatment strategy owing to drug resistance. Therefore, identifying the underlying modulators of the PD-1/PD-L1 pathway to completely comprehend the mechanisms of anti-PD-1/PD-L1 treatment is crucially important. Recent research has validated that m6A modification plays a critical role in the PD-1/PD-L1 axis, thus regulating the immune response and immunotherapy strategies. In this review, we summarized the latest research on the regulation of m6A modification in PD-1/PD-L1 pathways in cancer proliferation, invasion, and prognosis based on different kinds of cancers and discussed the possible mechanisms. We also reviewed m6A-associated lncRNAs in the regulation of the PD-1/PD-L1 pathway. More importantly, we outlined the influence of m6A modulation on anti-PD-1 therapy and m6A-related molecules that could predict the curative effect of anti-PD-1/PD-L1 therapy. Further studies exploring the definitive regulation of m6A on the PD1/PD-1 pathway and immunotherapy are needed, which may address some of the current limitations in immunotherapy.

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

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

Recent Advances in RNA m6A Modification in Solid Tumors and Tumor Immunity

An analogous field to epigenetics is referred to as epitranscriptomics, which focuses on the study of post-transcriptional chemical modifications in RNA. RNA molecules, including mRNA, tRNA, rRNA, and other non-coding RNA molecules, can be edited with numerous modifications. The most prevalent modification in eukaryotic mRNA is N6-methyladenosine (m6A), which is a reversible modification found in over 7000 human genes. Recent technological advances have accelerated the characterization of these modifications, and they have been shown to play important roles in many biological processes, including pathogenic processes such as cancer. In this chapter, we discuss the role of m6A mRNA modification in cancer with a focus on solid tumor biology and immunity. m6A RNA methylation and its regulatory proteins can play context-dependent roles in solid tumor development and progression by modulating RNA metabolism to drive oncogenic or tumor-suppressive cellular pathways. m6A RNA methylation also plays dynamic roles within both immune cells and tumor cells to mediate the anti-tumor immune response. Finally, an emerging area of research within epitranscriptomics studies the role of m6A RNA methylation in promoting sensitivity or resistance to cancer therapies, including chemotherapy, targeted therapy, and immunotherapy. Overall, our understanding of m6A RNA methylation in solid tumors has advanced significantly, and continued research is needed both to fill gaps in knowledge and to identify potential areas of focus for therapeutic development.

N7-methylguanosine methylation-related regulator genes as biological markers in predicting prognosis for melanoma

The aim of this study is to find those N7-methylguanosine (m7G) methylation-related regulator genes (m7GMRRGs) which were associated with melanoma prognosis and use them to develop a prognostic prediction model. Clinical information was retrieved online from The Cancer Gene Atlas (TCGA) and the Gene Expression Omnibus (GEO). R software was used to extract m⁷GMRRGs by differential expression analysis. To create a prognostic risk model, univariate and multivariate Cox regression analyses were employed for the evaluation of the prognostic significance of m⁷G methylation modifiers. Internal validation using cohort from TCGA (training set) and external validation using cohort from GEO (validation set) of the model were carried out. The model's predictive performance was confirmed by using the Kaplan-Meier, univariate, and multivariate Cox regression, and receiver operating characteristic curve (ROC) by constructing column line plots incorporating clinical factor characteristics. Immune infiltration analyses were performed to assess the immune function of m⁷GMRRGs. Drug sensitivity analysis was conducted to study chemotherapeutic drug treatment cues. Prognostic models using four m⁷GMRRGs (EIF4E3, LARP1, NCBP3, and IFIT5) showed good prognostic power in training and validation sets. The area under the curve (AUC) at 1, 3, and 5 years for GEO-melanoma were 0.689, 0.704, and 0.726, respectively. The prediction model could distinctly classify patients with melanoma into different risk subgroups (P < 0.001 for TCGA-melanoma and P < 0.05 for GEO-melanoma). Clinical characteristics were taken into account in Cox regression and AUC analysis, which highlighted that the risk score served as an independent risk factor determining the prognosis of patients with melanoma. Immuno-infiltration analysis showed that m⁷GMRRGs could potentially regulate CD8⁺ T cells as well as regulatory T cells (Treg cells). Results of our study indicate a association between m⁷GMRRGs and melanoma prognosis, and the prognostic prediction model using m⁷GMRRGs may predict the prognosis of patients with melanoma well. Nevertheless, these results may provide a clue for potential better options of melanoma treatment but need further validation in futural studies.

Crosstalk of Eight Types of RNA Modification Regulators Defines Tumor Microenvironments, Cancer Hallmarks, and Prognosis of Lung Adenocarcinoma

RNA modification has become an exciting underexplored field in recent years. In lung adenocarcinoma (LUAD), m⁶A was the best characterized and most studied RNA modification, while knowledge about other kinds of RNA modifications in LUAD is limited. In our study, we included a total of 100 RNA modification regulators of eight types of cancer-related RNA modifications (m⁶A, m¹A, m⁵C, Nm, m⁷G, Ψ, A-to-I, and mcm⁵s²U) to systematically profile their specific roles in LUAD. By gene mutation and expression analysis, we identified extensive dysregulations and complicated interactions of 100 RNA modification regulators in LUAD. Based on unsupervised clustering analysis, gene set variation analysis (GSVA), and single-sample gene-set enrichment analysis (ssGSEA), two RNA modification patterns in LUAD were defined to show distinct biological characteristics. The favorable prognostic pattern was enriched with infiltrated immune cells, including activated B cells, CD8 T cells, eosinophil cells, dendritic cells, and natural killer cells, while the unfavorable prognostic pattern was enriched with cancer hallmarks, including hypoxia, epithelial-mesenchymal transition (EMT), angiogenesis, PI3K-AKT-mTOR pathway, MYC pathway, and glycolysis pathway. We also constructed an RNA modification score (RMScore) based on five critical genes (CYP17A1, NTSR1, PITX3, KRT6A, and ANLN) to evaluate the RNA modification status of individual LUAD patients. RMScore was revealed to be related to the infiltrated immune cells and cancer hallmarks and was an independent prognostic factor in the TCGA-LUAD cohort and two external GEO-LUAD cohorts. Our study was the first to comprehensively investigate the dysregulations, crosstalk, and potential prognostic value of eight types of RNA modifications in LUAD. Our results highlighted the significance of eight types of RNA modifications in tumor microenvironments and cancer hallmarks and provided novel prognostic biomarkers and potential therapeutic targets in the management of LUAD patients in the future.

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.

m7G Methylation-Related Genes as Biomarkers for Predicting Overall Survival Outcomes for Hepatocellular Carcinoma

Aim: The search for prognostic biomarkers and the construction of a prognostic risk model for hepatocellular carcinoma (HCC) based on N7-methyladenosine (m7G) methylation regulators. Methods: HCC transcriptomic data and clinical data were obtained from The Cancer Genome Atlas database and Shanghai Ninth People's Hospital, respectively. m7G methylation regulators were extracted, differential expression analysis was performed using the R software "limma" package, and one-way Cox regression analysis was used to screen for prognostic associations of m7G regulators. Using multi-factor Cox regression analysis, a prognostic risk model for HCC was constructed. Each patient's risk score was calculated using the model, and patients were divided into high- and low-risk groups according to the median risk score. Cox regression analysis was used to verify the validity of the model in the prognostic assessment of HCC in conjunction with clinicopathological characteristics. Results: The prognostic model was built using the seven genes, namely, CYFIP1, EIF4E2, EIF4G3, GEMIN5, NCBP2, NUDT10, and WDR4. The Kaplan-Meier survival analysis showed poorer 5-years overall survival in the high-risk group compared with the low-risk group, and the receiver-operating characteristic (ROC) curve suggested good model prediction (area under the curve AUC = 0.775, 0.820, and 0.839 at 1, 3, and 5 years). The Cox regression analysis included model risk scores and clinicopathological characteristics, and the results showed that a high-risk score was the only independent risk factor for the prognosis of patients with HCC. Conclusions: The developed bioinformatics-based prognostic risk model for HCC was found to have good predictive power.

Comprehensive analysis of m6A regulator-based methylation modification patterns characterized by distinct immune profiles in colon adenocarcinomas

Mounting evidences have indicated that RNA N⁶-methyladenosine (m⁶A) modification played important roles in tumor formation and growth. However, it is rarely reported that m⁶A modifications are involved in the immune regulation and tumor microenvironment (TME) formation. In this study, we aimed to investigate the correlation between m⁶A modifications and TME regulation of colon adenocarcinoma (COAD) by bioinformatic analysis. NMF algorithm was applied to carry out consensus molecular subtype analysis on 36 selected m⁶A regulators regarding methylation modification, to identify m⁶A modification patterns and characteristics of m⁶A related genes in colon adenocarcinoma (COAD). Further, the relative infiltration levels of different immune cell subsets were quantified by ssGSEA and CIBERSORT algorithms, and a m⁶Sig scoring scheme was constructed to predict the prognosis and evaluate the response to immunotherapy in the patients with COAD. Among 579 COAD samples, we identified three different m⁶A modification patterns which were related to different biological pathways and clinical outcomes. Then, a scoring scheme termed "m⁶Sig score" was developed based on m⁶A-related characteristic genes, and was utilized to score patients with COAD into groups. We found that COAD patients with lower m⁶Sig scores exhibited prolonged survival and potentiated immune infiltration, which were associated with higher tumor mutation load, lower PD-L1 expression, and higher mutation rates of SMG (such as TTN and KRAS). Moreover, analysis regarding evaluation of immune response revealed that the patients with lower m⁶Sig scores had higher Immunophenoscore. Collectively, our study provided in depth insight into the interactions between m⁶A modification and regulation of TME. In addition, the quantitative evaluation of m⁶A modification patterns in our results may have implications in further immunotherapy for individual COAD patients.

m6A Regulator-Mediated RNA Methylation Modification Patterns Regulate the Immune Microenvironment in Osteoarthritis

Epigenetic regulation, particularly RNA n6 methyl adenosine (m6A) modification, plays an important role in the immune response. However, the regulatory role of m6A in the immune microenvironment in osteoarthritis (OA) remains unclear. Accordingly, we systematically studied RNA modification patterns mediated by 23 m6A regulators in 38 samples and discussed the characteristics of the immune microenvironment modified by m6A. Next, we constructed a novel OA m6A nomogram, an m6A-transcription factor-miRNA network, and a drug network. Healthy and OA samples showed distinct m6A regulatory factor expression patterns. YTHDF3 expression was upregulated in OA samples and positively correlated with type II helper cells and TGFb family member receptors. Furthermore, three different RNA modification patterns were mediated by 23 m6A regulatory factors; in Mode 3, the expression levels of YTHDF3, type II T helper cells, and TGFb family member receptors were upregulated. Pathways related to endoplasmic reticulum oxidative stress and mitochondrial autophagy showed a strong correlation with the regulatory factors associated with Mode 3 and 23 m6A regulatory factors. Through RT-qPCR we validated that SREBF2 and EGR1 as transcription factors of YTHDF3 and IGF2BP3 are closely associated with the development of OA, hsa-miR-340 as a miRNA for YTHDF3 and IGF2BP3 was involved in the development of OA, we also detected the protein expression levels of IGF2BP3, YTHDF3, EGR1 and SREBF2 by western blotting, and the results were consistent with PCR. Overall, the constructed nomogram can facilitate the prediction of OA risk.