m5 C regulator-mediated methylation modification patterns and tumor microenvironment infiltration characteristics in acute myeloid leukemia

BACKGROUND

Recently, many studies have been conducted to examine immune response modification at epigenetic level, but the candidate effect of RNA 5-methylcytosine (m5 C) modification on tumor microenvironment (TME) of acute myeloid leukemia (AML) is still unknown at present.

METHODS

We assessed the patterns of m5 C modification among 417 AML cases by using nine m5 C regulators. Thereafter, we associated those identified modification patterns with TME cell infiltration features. Additionally, stepwise regression and LASSO Cox regression analyses were conducted for quantifying patterns of m5 C modification among AML cases to establish the m5 C-score. Meanwhile, we validated the expression of genes in the m5C-score model by qRT-PCR. Finally, the present work analyzed the association between m5 C-score and AML clinical characteristics and prognostic outcomes.

RESULTS

In total, three different patterns of m5 C modification (m5 C-clusters) were identified, and highly differentiated TME cell infiltration features were also identified. On this basis, evaluating patterns of m5 C modification in single cancer samples was important for evaluating the immune/stromal activities in TME and for predicting prognosis. In addition, the m5 C-score was established, which showed a close relation with the overall survival (OS) of test and training set samples. Moreover, multivariate Cox analysis suggested that our constructed m5 C-score served as the independent predicting factor for the prognosis of AML (hazard ratio = 1.57, 95% confidence interval = 1.38-1.79, p < 1e-5 ).

CONCLUSIONS

This study shows that m5 C modification may be one of the key roles in the formation of diversity and complexity of TME. Meanwhile, assessing the patterns of m5 C modification among individual cancer samples is of great importance, which provides insights into cell infiltration features within TME, thereby helping to develop relevant immunotherapy and predict patient prognostic outcomes.

HNEAP Regulates Necroptosis of Cardiomyocytes by Suppressing the m5 C Methylation of Atf7 mRNA

PIWI-interacting RNAs (piRNAs) are highly expressed in various cardiovascular diseases. However, their role in cardiomyocyte death caused by ischemia/reperfusion (I/R) injury, especially necroptosis, remains elusive. In this study, a heart necroptosis-associated piRNA (HNEAP) is found that regulates cardiomyocyte necroptosis by targeting DNA methyltransferase 1 (DNMT1)-mediated 5-methylcytosine (m5 C) methylation of the activating transcription factor 7 (Atf7) mRNA transcript. HNEAP expression level is significantly elevated in hypoxia/reoxygenation (H/R)-exposed cardiomyocytes and I/R-injured mouse hearts. Loss of HNEAP inhibited cardiomyocyte necroptosis and ameliorated cardiac function in mice. Mechanistically, HNEAP directly interacts with DNMT1 and attenuates m5 C methylation of the Atf7 mRNA transcript, which increases Atf7 expression level. ATF7 can further downregulate the transcription of Chmp2a, an inhibitor of necroptosis, resulting in the reduction of Chmp2a level and the progression of cardiomyocyte necroptosis. The findings reveal that piRNA-mediated m5 C methylation is involved in the regulation of cardiomyocyte necroptosis. Thus, the HNEAP-DNMT1-ATF7-CHMP2A axis may be a potential target for attenuating cardiac injury caused by necroptosis in ischemic heart disease.

Identification and analysis of RNA-5-methylcytosine-related key genes in osteoarthritis

BACKGROUND

5-methylcytosine (m5C) modification is widely associated with many biological and pathological processes. However, knowledge of m5C modification in osteoarthritis (OA) remains lacking. Thus, our study aimed to identify common m5C features in OA.

RESULTS

In the present study, we identified 1395 differentially methylated genes (DMGs) and 1673 differentially expressed genes (DEGs) using methylated RNA immunoprecipitation next-generation sequencing (MeRIP-seq) and RNA-sequencing. A co-expression analysis of DMGs and DEGs showed that the expression of 133 genes was significantly affected by m5C methylation. A protein-protein interaction network of the 133 genes was constructed using the STRING database, and the cytoHubba plug-in of Cytoscape was used to hub genes were screen out 11 hub genes, including MMP14, VTN, COL15A1, COL6A2, SPARC, COL5A1, COL6A3, COL6A1, COL8A2, ADAMTS2 and COL7A1. The Pathway enrichment analysis by the ClueGO and CluePedia plugins in Cytoscape showed that the hub genes were significantly enriched in collagen degradation and extracellular matrix degradation.

CONCLUSIONS

Our study indicated that m5C modification might play an important role in OA pathogenesis, and the present study provides worthwhile insight into identifying m5C-related therapeutic targets in OA.

Identification of m5C-related molecular subtypes and prediction models in the prognosis and tumor microenvironment infiltration of soft tissue sarcoma

Background

The epigenetic regulator in cancer progression and immune response has been demonstrated recently. However, the potential implications of 5-methylcytosine (m5C) in soft tissue sarcoma (STS) are unclear.

Methods

The RNA sequence profile of 911 normal and 259 primary STS tissues were obtained from GTEx and TCGA databases, respectively. We systematically analyzed the m5C modification patterns of STS samples based on 11 m5C regulators, and comprehensively correlated these modification patterns with clinical characteristics, prognosis, and tumor microenvironment (TME) cell-infiltrating. Furthermore, an m5C-related signature was generated using Cox proportional hazard model and validated by the GSE17118 cohort.

Results

Two distinct m5C modification patterns (cluster1/2) were discovered. The cluster1 had favorable overall survival, higher immune score, higher expression of most immune checkpoints, and active immune cell infiltration. The GSVA analysis of the P53 pathway, Wnt signaling pathway, G2M checkpoint, mTORC1 signaling, Wnt/β catenin signaling, and PI3K/AKT/mTOR signaling were significantly enriched in the cluster2. Moreover, 1220 genes were differentially expressed between two clusters, and a m5C prognostic signature was constructed with five m5C-related genes. The signature represented an independent prognostic factor and showed the favorable performance in the GSE17118 cohort. Patients in the low-risk group showed higher immunoscore and higher expression of most immune checkpoints. Further GSVA analysis indicated that the levels of P53 pathway, Wnt signaling pathway, and TGF-β signaling pathway were different between low- and high-risk groups. Moreover, a nomogram incorporating m5C signature and clinical variables was established and showed well performance.

Conclusion

This work showed that the m5C modification plays a significant role in the progression of STS and the formation of TME diversity. Evaluating the m5C modification pattern of tumor will enhance our cognition of TME infiltration characterization to guide more effective immunotherapy strategies.

Comprehensive analysis of transcriptomic profiling of 5-methylcytosin modification in placentas from preeclampsia and normotensive pregnancies

Increasing evidence suggests that RNA m5C modification and its regulators have been confirmed to be associated with the pathogenesis of many diseases. However, the distribution and biological functions of m5C in mRNAs of placental tissues remain unknown. we collected placentae from normotensive pregnancies (CTR) and preeclampsia patients (PE) to analyze the transcriptomic profiling of m5C RNA methylation through m5C RNA immunoprecipitation (UMI-MeRIP-Seq). we discovered that overall m5C methylation peaks were decreased in placental tissues from PE patients. And, 2844 aberrant m5C peaks were identified, of which respectively 1304 m5C peaks were upregulated and 1540 peaks were downregulated. The distribution of m5C peaks were mainly located in CDS (coding sequences) regions in placental tissues of both groups, but compared with the CTR group, the m5C peak in PE group before the stop code of CDS was significantly increased and even higher than the peak value after start code in CDS. Differentially methylated genes were mainly enriched in MAPK/cAMP signaling pathway. Moreover, the up-regulated genes with hypermethylated modification were enriched in the processes of hypoxia, inflammation/immune response. Finally, through analyzing the mRNA expression levels of m5C RNA methylation regulators, we found only DNMT3B and TET3 were significantly upregulated in PE samples than in control group. And they are not only negatively correlated with each other, but also closely related to those differentially expressed genes modified by differential methylation.Our findings provide new insights regarding alterations of m5C RNA modification into the pathogenic mechanisms of PE.

5-Methylcytosine (m5C) Modification Patterns and Tumor Immune Infiltration Characteristics in Clear Cell Renal Cell Carcinoma

Recently, studies have revealed the prognostic value of 5-methylcytosine (m5C) in clear cell renal cell carcinoma (ccRCC). However, the role of m5C methylation in ccRCC immune infiltration and the immunotherapeutic response remains unknown. Based on the mRNA expressions of 14 m5C regulators, we evaluated the m5C modification patterns of 530 tumor samples from the TCGA-ccRCC database. We used the principal component analysis (PCA) algorithm to construct individual patient m5Cscores to facilitate individual analysis of m5C modification patterns in ccRCC patients. We finally defined three different m5C modification patterns. Different clinical features and immune heterogeneity existed among the three patterns, and their immune infiltration characteristics could correspond to different immune phenotypes, including the immune-inflamed, immune-excluded, and immune-desert phenotype. We designed the m5Cscore calculated by the PCA algorithm to measure individual patients' m5C modification patterns. The low m5Cscore group presented with a positive prognosis, increased TMB, and immune activation. Additionally, low m5Cscore patients showed an increased response to immune checkpoint inhibitors. We further the value of the m5Cscore in predicting OS verified in four other tumor cohorts. Our findings revealed that m5C methylation modifications are essential in regulating ccRCC immune infiltration. Assessing single ccRCC patients' m5C modification patterns can fully improve our comprehension of tumor immune characteristics and be used to provide effective personalized immunotherapy strategies for clinical use.

Comprehensive Analysis of m5C Methylation Regulatory Genes and Tumor Microenvironment in Prostate Cancer

Background

5-Methylcytidine (m5C) methylation is an emerging epigenetic modification in recent years, which is associated with the development and progression of various cancers. However, the prognostic value of m5C regulatory genes and the correlation between m5C methylation and the tumor microenvironment (TME) in prostate cancer remain unknown.

Methods

In the current study, the genetic and transcriptional alterations and prognostic value of m5C regulatory genes were investigated in The Cancer Genome Atlas and Gene Expression Omnibus datasets. Then, an m5C prognostic model was established by LASSO Cox regression analysis. Gene set variation analyses (GSVA), gene set enrichment analysis (GSEA), clinical relevance, and TME analyses were conducted to explain the biological functions and quantify the TME scores between high-risk and low-risk subgroups. m5C regulatory gene clusters and m5C immune subtypes were identified using consensus unsupervised clustering analysis. The Cell-type Identification By Estimating Relative Subsets of RNA Transcripts algorithm was used to calculate the contents of immune cells.

Results

TET3 was upregulated at transcriptional levels in PCa compared with normal tissues, and a high TET3 expression was associated with poor prognosis. An m5C prognostic model consisting of 3 genes (NSUN2, TET3, and YBX1) was developed and a nomogram was constructed for improving the clinical applicability of the model. Functional analysis revealed the enrichment of pathways and the biological processes associated with RNA regulation and immune function. Significant differences were also found in the expression levels of m5C regulatory genes, TME scores, and immune cell infiltration levels between different risk subgroups. We identified two distinct m5C gene clusters and found their correlation with patient prognosis and immune cell infiltration characteristics. Naive B cells, CD8+ T cells, M1 macrophages and M2 macrophages were obtained and 2 m5C immune subtypes were identified. CTLA4, NSUN6, TET1, and TET3 were differentially expressed between immune subtypes. The expression of CTLA4 was found to be correlated with the degree of immune cell infiltration.

Conclusions

Our comprehensive analysis of m5C regulatory genes in PCa demonstrated their potential roles in the prognosis, clinical features, and TME. These findings may improve our understanding of m5C regulatory genes in the tumor biology of PCa.

Prognostic Risk Model and Tumor Immune Environment Modulation of m5C-Related LncRNAs in Pancreatic Ductal Adenocarcinoma

RNA methylation modification is a key process in epigenetics that regulates posttranscriptional gene expression. With advances in next-generation sequencing technology, 5-methylcytosine (m5C) modification has also been found in multiple RNAs. Long non-coding RNAs (lncRNAs) were proved to have a key role in cancer progression and closely related to the tumor immune microenvironment. Thus, based on the PDAC patients' clinical information and genetic transcriptome data from the TCGA database, we performed a detailed bioinformatic analysis to establish a m5C-related lncRNA prognostic risk model for PDAC patients and discovered the relationship between the risk model and PDAC immune microenvironment. Pearson correlation coefficient analysis was applied to conduct a m5C regulatory gene and m5C-related lncRNA co-expression network. Expression of m5C-related lncRNAs screened by univariate regression analysis with prognostic value showed a significant difference between pancreatic cancer and normal tissues. The least absolute shrinkage and selection operator (LASSO) Cox regression method was applied to determine an 8-m5C-related lncRNA prognostic risk model. We used principal component analysis to indicate that the risk model could distinguish all the samples clearly. The clinical nomogram also accurately predicted 1-, 1.5-, 2-, and 3-year survival time among PDAC patients. Additionally, this risk model was validated in the entire group and sub-test groups using KM analysis and ROC analysis. Combined with the clinical characteristics, the risk score was found to be an independent factor for predicting the survival of PDAC patients. Furthermore, the association between the risk model and tumor immune microenvironment was evaluated via the ESTIMATE R package and CIBERSORT method. Consequently, the results indicated that immune cells were associated with m5C-related lncRNA risk model scores and had different distribution in the high- and low-risk groups. Based on all these analyses, the m5C-related lncRNA risk model could be a reliable prognostic tool and therapeutic target for PDAC patients.

Alteration of mRNA 5-Methylcytosine Modification in Neurons After OGD/R and Potential Roles in Cell Stress Response and Apoptosis

Epigenetic modifications play an important role in central nervous system disorders. As a widespread posttranscriptional RNA modification, the role of the m5C modification in cerebral ischemia-reperfusion injury (IRI) remains poorly defined. Here, we successfully constructed a neuronal oxygen-glucose deprivation/reoxygenation (OGD/R) model and obtained an overview of the transcriptome-wide m5C profiles using RNA-BS-seq. We discovered that the distribution of neuronal m5C modifications was highly conserved, significantly enriched in CG-rich regions and concentrated in the mRNA translation initiation regions. After OGD/R, modification level of m5C increased, whereas the number of methylated mRNA genes decreased. The amount of overlap of m5C sites with the binding sites of most RNA-binding proteins increased significantly, except for that of the RBM3-binding protein. Moreover, hypermethylated genes in neurons were significantly enriched in pathological processes, and the hub hypermethylated genes RPL8 and RPS9 identified by the protein-protein interaction network were significantly related to cerebral injury. Furthermore, the upregulated transcripts with hypermethylated modification were enriched in the processes involved in response to stress and regulation of apoptosis, and these processes were not identified in hypomethylated transcripts. In final, we verified that OGD/R induced neuronal apoptosis in vitro using TUNEL and western blot assays. Our study identified novel m5C mRNAs associated with ischemia-reperfusion in neurons, providing valuable perspectives for future studies on the role of the RNA methylation in cerebral IRI.