Effect of m6A RNA Methylation Regulators on Malignant Progression and Prognosis in Renal Clear Cell Carcinoma

PLAUR facilitates the progression of clear cell renal cell carcinoma by activating the PI3K/AKT/mTOR signaling pathway

Background

PLAUR has been found upregulated in various tumors and closely correlated with the malignant phenotype of tumor cells. The aim of this study was to investigate the relationship between PLAUR and clear cell renal cell carcinoma (ccRCC) and its potential mechanism of promoting tumor progression.

Methods

The expression levels and clinical significance of PLAUR, along with the associated signaling pathways, were extensively investigated in ccRCC samples obtained from The Cancer Genome Atlas (TCGA). PLAUR expression in 20 pairs of ccRCC tumor tissues and the adjacent tissues was assessed using qRT-PCR and IHC staining. Additionally, a series of in vitro experiments were conducted to investigate the impact of PLAUR suppression on cellular proliferation, migration, invasion, cell cycle progression, and apoptosis in ccRCC. The Western blot analysis was employed to investigate the expression levels of pivotal genes associated with the PI3K/AKT/mTOR signaling pathway.

Results

The expression of PLAUR was significantly upregulated in ccRCC compared to normal renal tissues, and higher PLAUR expression in ccRCC was associated with a poorer prognosis than low expression. The in-vitro functional investigations demonstrated that knockdown of PLAUR significantly attenuated the proliferation, migration, and invasion capabilities of ccRCC cells. Concurrently, PLAUR knockdown effectively induced cellular apoptosis, modulated the cell cycle, inhibited the EMT process, and attenuated the activation of the PI3K/AKT/mTOR signaling pathway. PLAUR may represent a key mechanism underlying ccRCC progression.

Conclusions

The involvement of PLAUR in ccRCC progression may be achieved through the activation of the PI3K/AKT/mTOR signaling pathway, making it a reliable biomarker for the identification and prediction of ccRCC.

m6A RNA Methylation and Implications for Hepatic Lipid Metabolism

This review presents a summary of recent progress in research on the N6-methyladenosine (m6A) modification and regulatory roles in hepatic lipid metabolism. As the most abundant internal modification of eukaryotic RNA, the m6A modification is a dynamic and reversible process of the m6A enzyme system, which includes writers, erasers, and readers. m6A methylation depressed lipid synthesis and facilitated lipolysis in liver. The depletion of m6A methyltransferase Mettl14/Mettl3 raised fatty acid synthase (FAS), stearoyl-CoA desaturase-1 (SCD1), acetyl-CoA carboxylase (ACC), and elongase of very long chain fatty acids 6 (ELOVL6) in rodent liver, causing increases in liver weight, triglyceride (TG) production, and content in hepatocytes. FTO catalyzed m6A demethylation and the suppression m6A reader YTHDC2 promoted hepatocellular TG generation and hepatic steatosis in C57BL/6 mice through sterol regulatory element-binding protein 1c (SREBP-1c) signaling pathway, which upregulated the lipogenic genes FAS, SCD1, ACC, recombinant acetyl coenzyme a carboxylase alpha, and cell death-inducing DNA fragmentation factor-like effector C (CIDEC). Furthermore, FTO overexpression did not only enhance mitochondrial fusion to impair mitochondrial function and lipid oxidation but also promoted lipid peroxidation, accompanied by excessive TG in hepatocytes and rodent liver. Elevated m6A modification potently suppressed hepatic lipid accumulation, while the shrinkage of m6A modification arose hepatic lipid deposition. These findings have highlighted the beneficial role of m6A RNA methylation in hepatic lipid metabolism, potentially protecting liver from lipid metabolic disorders.

Von Hippel Lindau tumor suppressor controls m6A-dependent gene expression in renal tumorigenesis

N6-Methyladenosine (m6A) is the most abundant posttranscriptional modification, and its contribution to cancer evolution has recently been appreciated. Renal cancer is the most common adult genitourinary cancer, approximately 85% of which is accounted for by the clear cell renal cell carcinoma (ccRCC) subtype characterized by VHL loss. However, it is unclear whether VHL loss in ccRCC affects m6A patterns. In this study, we demonstrate that VHL binds and promotes METTL3/METTL14 complex formation while VHL depletion suppresses m6A modification, which is distinctive from its canonical E3 ligase role. m6A RNA immunoprecipitation sequencing (RIP-Seq) coupled with RNA-Seq allows us to identify a selection of genes whose expression may be regulated by VHL-m6A signaling. Specifically, PIK3R3 is identified to be a critical gene whose mRNA stability is regulated by VHL in a m6A-dependent but HIF-independent manner. Functionally, PIK3R3 depletion promotes renal cancer cell growth and orthotopic tumor growth while its overexpression leads to decreased tumorigenesis. Mechanistically, the VHL-m6A-regulated PIK3R3 suppresses tumor growth by restraining PI3K/AKT activity. Taken together, we propose a mechanism by which VHL regulates m6A through modulation of METTL3/METTL14 complex formation, thereby promoting PIK3R3 mRNA stability and protein levels that are critical for regulating ccRCC tumorigenesis.

METTL3 facilitates renal cell carcinoma progression by PLOD2 m6A-methylation under prolonged hypoxia

N6-methyladenosine (m6A) is the most prevalent reversible modification in eukaryotic mRNA, and it plays a critical role in tumor progression. The purpose of this study was to investigate the function and regulatory mechanisms of the methyltransferase METTL3 in renal cell carcinoma (RCC). METTL3 expression was upregulated and predicted a poor prognosis in patients with advanced RCC. METTL3 facilitated the proliferation, migration, and invasion of RCC cells, depending on its methylase activity. METTL3 positively regulated the expression of PLOD2, and both genes were triggered under prolonged hypoxia. Mechanistically, hypoxia-induced the binding of HIF-1α to the METTL3 promoter, which enhanced its transcriptional activity. METTL3-mediated m6A modifications of PLOD2 mRNA at 3'UTR region, promoting the translation of PLOD2 protein. Furthermore, silencing METTL3 impaired RCC progression in vitro. In vivo, administration of highly potent and selective METTL3 inhibitor STM2457 showed anti-tumor effects, whereas AAV9-mediated re-transduction of PLOD2 largely abolished the above phenomenon in a subcutaneous mouse model. These findings reveal that hypoxia and HIF-driven METTL3 transcription promote RCC progression by increasing PLOD2 expression in an m6A-dependent manner, suggesting that METTL3 may serve as a novel pharmaceutical intervention for RCC.

A cellular senescence-related genes model allows for prognosis and treatment stratification of cervical cancer: a bioinformatics analysis and external verification

BACKGROUND

Cervical cancer (CC) is highly lethal and aggressive with an increasing trend of mortality for females. Molecular characterization-based methods hold great promise for improving the diagnostic accuracy and for predicting treatment response.

METHODS

The mRNAs expression data of CC patients and cellular senescence-related genes were obtained from the Cancer Genome Atlas (TCGA) and CellAge databases, respectively. Differentially expressed genes (DEGs) of senescence related genes between tumor and normal tissues were used for Least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model. Univariate and LASSO regression analyses were applied to establish a predictive nomogram. The performance of the nomogram were evaluated by Kaplan-Meier curve, receiver operating characteristic (ROC), Harrell's concordance index (C-index), and calibration curve. GSE44001 and GSE52903 were used for external validation.

RESULTS

We established a cellular senescence-related genes-based stratified model, and a multivariable-based nomogram, which could accurately predict the prognosis of CC patients in the TCGA database. The Kaplan-Meier curve indicated that patients in the low-risk group had considerably better overall survival (OS, P =2.021e-05). The area under the ROC curve (AUC) of this model was 0.743 for OS. Multivariate analysis found that the 6-gene risk signature (HR=3.166, 95%CI: 1.660-6.041, P<0.001) was an independent risk factor for CC patients. We then designed an OS-associated nomogram that included the risk signature and clinicopathological factors. The AUC reached 0.860 for predicting 5-year OS. The nomogram showed excellent consistency between the predictions and actual survival observations. Two external GEO validations were corresponding to the gene expression pattern in TCGA.

CONCLUSIONS

Our results suggested a six-senescence related signature and established a prognostic nomogram that reliably predicted the overall survival for CC. These findings may be beneficial to personalized treatment and medical decision-making.

The current landscape of m6A modification in urological cancers

N6-methyladenosine (m6A) methylation is a dynamic and reversible procession of epigenetic modifications. It is increasingly recognized that m6A modification has been involved in the tumorigenesis, development, and progression of urological tumors. Emerging research explored the role of m6A modification in urological cancer. In this review, we will summarize the relationship between m6A modification, renal cell carcinoma, bladder cancer, and prostate cancer, and discover the biological function of m6A regulators in tumor cells. We will also discuss the possible mechanism and future application value used as a potential biomarker or therapeutic target to benefit patients with urological cancers.

The emerging roles and mechanism of N6-methyladenosine (m6A) modifications in urologic tumours progression

Prostate cancer (PCa), bladder cancer (BC), and renal cell cancer (RCC) are the most common urologic tumours in males. N6-methyladenosine (m⁶A), adenosine N6 methylation, is the most prevalent RNA modification in mammals. Increasing evidence suggests that m⁶A plays a crucial role in cancer development. In this review, we comprehensively analyzed the influence of m⁶A methylation on Prostate cancer, bladder cancer, and renal cell cancer and the relationship between the expression of relevant regulatory factors and their development and occurrence, which provides new insights and approaches for the early clinical diagnosis and targeted therapy of urologic malignancies.

Multimodal deep learning to predict prognosis in adult and pediatric brain tumors

BACKGROUND

The introduction of deep learning in both imaging and genomics has significantly advanced the analysis of biomedical data. For complex diseases such as cancer, different data modalities may reveal different disease characteristics, and the integration of imaging with genomic data has the potential to unravel additional information than when using these data sources in isolation. Here, we propose a DL framework that combines these two modalities with the aim to predict brain tumor prognosis.

METHODS

Using two separate glioma cohorts of 783 adults and 305 pediatric patients we developed a DL framework that can fuse histopathology images with gene expression profiles. Three strategies for data fusion were implemented and compared: early, late, and joint fusion. Additional validation of the adult glioma models was done on an independent cohort of 97 adult patients.

RESULTS

Here we show that the developed multimodal data models achieve better prediction results compared to the single data models, but also lead to the identification of more relevant biological pathways. When testing our adult models on a third brain tumor dataset, we show our multimodal framework is able to generalize and performs better on new data from different cohorts. Leveraging the concept of transfer learning, we demonstrate how our pediatric multimodal models can be used to predict prognosis for two more rare (less available samples) pediatric brain tumors.

CONCLUSIONS

Our study illustrates that a multimodal data fusion approach can be successfully implemented and customized to model clinical outcome of adult and pediatric brain tumors.

An m6A-Driven Prognostic Marker Panel for Renal Cell Carcinoma Based on the First Transcriptome-Wide m6A-seq

To date, only a single transcriptome-wide m6A sequencing study of clear cell renal cell carcinoma (ccRCC) has been reported, with no validation so far. Herein, by TCGA analysis of the KIRC cohort (n = 530 ccRCC; n = 72 normal), an external expression validation of 35 preidentified m6A targets was performed. Further in-depth expression stratification enabled assessment of m6A-driven key targets. Overall survival (OS) analysis and gene set enrichment analyses (GSEA) were conducted to assess their clinical and functional impact on ccRCC. In the hyper-up cluster significant upregulation was confirmed for NDUFA4L2, NXPH4, SAA1, and PLOD2 (40%) and in the hypo-up cluster for FCHSD1 (10%). Significant downregulation was observed for UMOD, ANK3, and CNTFR (27.3%) in the hypo-down cluster and for CHDH (25%) in the hyper-down cluster. In-depth expression stratification showed consistent dysregulation in ccRCC only for 11.67%: NDUFA4L2, NXPH4, and UMOD (NNU-panel). Patients with strong NNU panel dysregulation had significantly poorer OS (p = 0.0075). GSEA identified 13 associated and significantly upregulated gene sets (all p-values < 0.5; FDR < 0.25). External validation of the only available m6A sequencing in ccRCC consistently reduced dysregulated m6A-driven targets on the NNU panel with highly significant effects on OS. Epitranscriptomics are a promising target for developing novel therapies and for identifying prognostic markers for daily clinical practice.

Non-SMC condensin I complex subunit H participates in anti-programmed cell death-1 resistance of clear cell renal cell carcinomas

Non-SMC condensin I complex subunit H (NCAPH) is reported to play an important role and be a poor prognostic factor in various cancers. However, the function and regulatory mechanism of NCAPH in clear cell renal cell carcinoma (ccRCC) remain unknown. The roles of NCAPH on ccRCC growth were detected in vitro and in vivo assays. The regulatory mechanism of NCAPH was explored by immunoprecipitation assay, ubiquitination assay, ChIP assay, RIP assay, luciferase reporter assay and RNA pull-down assay. The role of NCAPH in immunoregulation also was explored by flow cytometry, T cell-mediated tumour cell killing assay and immune-competent mouse model. In this research, we displayed that NCAPH was upregulated in ccRCC and patients with elevated NCAPH expression had an undesirable prognosis. Functionally, NCAPH depletion restrained ccRCC growth in vitro and in vivo. The elevated NCAPH was attributed to FOXP3-mediated transcription, FUS-mediated transcription splicing and METTL3-mediated m6A modification. Moreover, YTHDC1 promoted NCAPH mRNA nuclear export, and IGF2BP3 enhanced NCAPH mRNA stability in an m6A-dependent manner. NCAPH increased PD-L1 expression by inhibiting the degradation of β-catenin in ccRCC cells, which further facilitated aerobic glycolysis and immune tolerance of ccRCC. Collectively, our findings display the vital function of NCAPH in ccRCC and uncover that NCAPH may be regarded as a potential therapeutic target to reverse the immune tolerance of ccRCC.

A Novel 7-Methylguanosine (m7G)-Related Gene Signature for Overall Survival Prediction in Patient with Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common pathology type of renal cancer that has an abysmal prognosis. Although a crucial role for 7-methylguanosine modification in cancer cell development has been reported, its role in ccRCC remains uncertain. This study was conducted to determine the efficacy of predictive biomarkers based on m7G-related genes in ccRCC. Firstly, we extracted clinical data and gene expression profiles of ccRCC patients from publicly accessible databases. It identified that 22 of the m7G-related 34 genes were related to overall survival, and 5 of the 22 genes were significantly expressed differently in tumor tissues. Based on Lasso regression analysis, five optimal genes (CYFIP2, EIF4A1, NUDT1, NUDT10, and NUDT4) were chosen to build a new predictive risk model in the TCGA cohort. Validation was carried out with the E-MTAB-1980 cohort. Then, a prognostic nomogram was erected, including the m7G-related gene risk score, age, histological grade, and stage status. Further studies and analysis showed that immune cell infiltration might be associated with the m7G-related risk genes. In addition, the relationship between gene expression and drug response was evaluated by the Pearson correlation test. Therefore, the risk signature with five selected m7G-related genes may be a promising prognostic biomarker and contribute to standardized prognostic assessment for ccRCC.

Expression patterns of platinum resistance-related genes in lung adenocarcinoma and related clinical value models

The purpose of this study was to explore platinum resistance-related biomarkers and mechanisms in lung adenocarcinoma. Through the analysis of gene expression data of lung adenocarcinoma patients and normal patients from The Cancer Genome Atlas, Gene Expression Omnibus database, and A database of genes related to platinum resistance, platinum resistance genes in lung adenocarcinoma and platinum resistance-related differentially expressed genes were obtained. After screening by a statistical significance threshold, a total of 252 genes were defined as platinum resistance genes with significant differential expression, of which 161 were up-regulated and 91 were down-regulated. The enrichment results of up-regulated gene Gene Ontology (GO) showed that TOP3 entries related to biological processes (BP) were double-strand break repair, DNA recombination, DNA replication, the down-regulated gene GO enriches the TOP3 items about biological processes (BP) as a response to lipopolysaccharide, muscle cell proliferation, response to molecule of bacterial origin. Gene Set Enrichment Analysis showed that the top three were e2f targets, g2m checkpoint, and rgf beta signaling. A prognostic model based on non-negative matrix factorization classification showed the characteristics of high- and low-risk groups. The prognostic model established by least absolute shrinkage and selection operator regression and risk factor analysis showed that genes such as HOXB7, NT5E, and KRT18 were positively correlated with risk score. By analyzing the differences in m6A regulatory factors between high- and low-risk groups, it was found that FTO, GPM6A, METTL3, and YTHDC2 were higher in the low-risk group, while HNRNPA2B1, HNRNPC, TGF2BP1, IGF2BP2, IGF2BP3, and RBM15B were higher in the high-risk group. Immune infiltration and drug sensitivity analysis also showed the gene characteristics of the platinum-resistant population in lung adenocarcinoma. ceRNA analysis showed that has-miR-374a-5p and RP6-24A23.7 were lower in the tumor expression group, and that the survival of the low expression group was worse than that of the high expression group. In conclusion, the results of this study show that platinum resistance-related differentially expressed genes in lung adenocarcinoma are mainly concentrated in biological processes such as DNA recombination and response to lipopolysaccharide. The validation set proved that the high-risk group of our prognostic model had poor survival. M6A regulatory factor analysis, immune infiltration, and drug sensitivity analysis all showed differences between high and low-risk groups. ceRNA analysis showed that has-miR-374a-5p and RP6-24A23.7 could be protective factors. Further exploration of the potential impact of these genes on the risk and prognosis of drug-resistant patients with lung adenocarcinoma would provide theoretical support for future research.

Identifying Prognostic Biomarkers Related to m6A Modification and Immune Infiltration in Renal Cell Carcinoma

BACKGROUND

Renal cell carcinoma (RCC) is the largest category of kidney tumors and usually does not have a good prognosis. N6-methyladenosine(m6A) and immune infiltration have received increased attention because of their great influence on the clinical outcome and prognosis of cancer patients.

METHODS

We identified hub genes through multi-dimensional screening, including DEGs, PPI analysis, LASSO regression, and random forest. Meanwhile, GO/KEGG enrichment, cMAP analysis, prognostic analysis, m6A prediction, and immune infiltration analysis were performed to understand the potential mechanism and screen therapeutic drugs.

RESULTS

We screened 275 downregulated and 185 upregulated genes using three GEO datasets and the TCGA dataset. In total, 82 candidate hub genes were selected using STRING and Cytoscape. Enrichment analysis illustrated that the top 3 biological process terms and top 1 KEGG term were related to immunity. cMAP analysis showed some antagonistic molecules can be candidate drugs for the treatment of RCC. Then, six hub genes (ERBB2, CASR, P2RY8, CAT, PLAUR, and TIMP1) with strong predictive values for prognosis and clinicopathological features were selected. Meanwhile, P2RY8, ERBB2, CAT, and TIMP1 may obtain m6A modification by binding METTL3 or METTL14. On the other hand, differential expression of CAT, ERBB2, P2RY8, PLAUR, and TIMP1 affects the infiltration of the majority of immune cells.

CONCLUSIONS

We identified six hub genes through multi-dimensional screening. They all possess strong predictive value for prognosis and clinicopathological features. Meanwhile, hub genes may regulate the progression of RCC via an m6A- and immunity-dependent mechanism.

Translational Regulation by eIFs and RNA Modifications in Cancer

Translation is a fundamental process in all living organisms that involves the decoding of genetic information in mRNA by ribosomes and translation factors. The dysregulation of mRNA translation is a common feature of tumorigenesis. Protein expression reflects the total outcome of multiple regulatory mechanisms that change the metabolism of mRNA pathways from synthesis to degradation. Accumulated evidence has clarified the role of an increasing amount of mRNA modifications at each phase of the pathway, resulting in translational output. Translation machinery is directly affected by mRNA modifications, influencing translation initiation, elongation, and termination or altering mRNA abundance and subcellular localization. In this review, we focus on the translation initiation factors associated with cancer as well as several important RNA modifications, for which we describe their association with cancer.

Construction and validation of an m6A RNA methylation regulator prognostic model for early-stage clear cell renal cell carcinoma

N6-methyladenosine (m6A) is the most common type of RNA methylation and is considered to participate in various biological and pathological processes, specifically in the regulation of tumorigenesis and metastasis. However, the exact prognostic role of m6A methylation regulators in early-stage clear cell renal cell carcinoma (ccRCC) is currently unknown. In the present study, a prognostic model consisting of m6A RNA methylation regulators in early stage ccRCC was constructed and the reliability of the signature was assessed by proteomics and immunohistochemistry. Additionally, the relationship between the prognostic model and tumor infiltrating immune cells within the tumor microenvironment was investigated. Gene mutation and RNA sequencing data of 19 m6A methylation regulators for early-stage ccRCC patients were extracted from The Cancer Genome Atlas (TCGA) database with the corresponding clinical information. Univariate and multivariate Cox regression analysis were applied to construct a prognostic model and the proteomic data as well as immunohistochemistry were used to validate the result. The correlations between the prognostic model and tumor infiltrating immune cells were assessed using Spearman's rank correlation analysis. A total of 192 early stage ccRCC gene mutation data as well as 261 RNA sequencing data with relative clinical data were extracted from the TCGA. The overall mutation frequency of the 19 m6A RNA methylation regulators was relatively low with 4.69%. The transcriptome data revealed that 11 genes were differentially expressed between cancer tissues and relatively normal tissues. Survival analysis highlighted four specific genes as having a significant influence on overall survival. An established model with four genes demonstrated the best predictability for early-stage ccRCC. After integrating clinical characteristics into the multivariate analysis, the model remained effective at predicting ccRCC prognosis. Spearman's rank analysis suggested several tumor infiltrating immune cells such as dendric cells, CD4⁺ cells, CD8⁺ T cells and macrophages were significantly correlated with the model. Proteomic data analysis as well as immunohistochemistry from the Human Protein Atlas showed that all the genes used to construct the model were differentially expressed between ccRCC and normal tissues. In conclusion, a novel m6A methylation regulators-based prognostic signature was established and validated with proteomics and immunohistochemistry. In addition, the model was significantly correlated with multiple infiltrating immune cells in tumor microenvironment.

The methyltransferase METTL3 promotes tumorigenesis via mediating HHLA2 mRNA m6A modification in human renal cell carcinoma

Background

As an important N6-methyladenosine (m6A) regulator, abnormal expression of methyltransferase-like protein 3 (METTL3) has been reported in certain human cancers. Although some data have shown that METTL3 plays an essential role in the progression of clear-cell renal cell carcinoma RCC (ccRCC), the detailed mechanism still remains largely undetermined.

Methods

Immunohistochemistry (IHC) assay was used to examine the expression of METTL3 and its clinical implications in human ccRCC by using tissue-microarray (TMA). The cellular models based on ccRCC cell lines such as 786-O and ACHN, were established by operating METTL3 and HHLA2 via knockdown or overexpression, followed by in vitro cellular function studies and in vivo subcutaneous transplantation tumor model.

Results

We found that METTL3 expression in ccRCC tissues was significantly higher compared with adjacent normal tissues. We also found the overall survival (OS) of the patients with low METTL3 expression was significantly better compared with the patients with high METTL3 expression. Furthermore, HHLA2highMETTL3high could serve as a better prognostic predictor for ccRCC patients. Depletion of METTL3 could significantly inhibit the cell viability, migration, and invasion abilities in ccRCC cell lines. Cellular studies further revealed that METTL3 could regulate HHLA2 expression via m6A modification of HHLA2 mRNA. In vitro studies revealed that HHLA2 overexpression could reverse the inhibition of cellular functions mediated by METTL3 depletion. The subcutaneous transplantation tumor model confirmed that HHLA2 overexpression could reverse the inhibition of tumor growth mediated by METTL3 depletion.

Conclusion

Our study indicated that METTL3 served as an important prognostic predictor for ccRCC patients, and we demonstrated a novel regulatory mechanism of HHLA2 by mRNA epigenetic modification via METTL3. Moreover, we found that the METTL3/HHLA2 axis could promote tumorigenesis of ccRCC. Collectively, our current findings provided new insights into the therapeutic strategy against this malignancy targeting METTL3.

Establishment and Validation of a 5 m6A RNA Methylation Regulatory Gene Prognostic Model in Low-Grade Glioma

Background: The prognosis of low-grade glioma (LGG) is different from that of other intracranial tumors. Although many markers of LGG have been established, few are used in clinical practice. M6A methylation significantly affects the biological behavior of LGG tumors. Therefore, establishment of an LGG prognostic model based on m6A methylation regulatory genes is of great interest.

Methods: Data from 495 patients from The Cancer Genome Atlas (TCGA) and 172 patients from the Chinese Glioma Genome Atlas (CGGA) were analyzed. Univariate Cox analysis was used to identify methylation regulatory genes with prognostic significance. LASSO Cox regression was used to identify prognostic genes. Receiver operating characteristic (ROC) and Kaplan–Meier curves were used to verify the accuracy of the model. Gene Set Enrichment Analysis (GSEA) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to identify cellular pathways that were significantly associated with the prognosis of LGG.

Results: A glioma prognostic model based on five methylation regulatory genes was established. Compared with low-risk patients, patients identified as high risk had a poorer prognosis. There was a high degree of consistency between the internal training and internal validation CGGA cohorts and the external validation TCGA cohort. Furthermore, KEGG and GSEA analyses showed that the focal adhesion and cell cycle pathways were significantly upregulated in high-risk patients. This signature could be used to distinguish among patients with different immune checkpoint gene expression levels, which may inform immune checkpoint inhibitor (ICI) immunotherapy.

Conclusion: We comprehensively evaluated m6A methylation regulatory genes in LGG and constructed a prognostic model based on m6A methylation, which may improve prognostic prediction for patients with LGG.

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

Background

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

Methods

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

Results

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

Conclusions

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

Downregulation of Methyltransferase-Like 14 Promotes Ovarian Cancer Cell Proliferation Through Stabilizing TROAP mRNA

Altered expression levels of the proteins that regulate N6-methyladenosine (m⁶A) RNA methylation, including methyltransferase-like 14 (METTL14), are associated with cancer development. Based on our analysis of m⁶A methylation regulators using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, we focused on the regulatory role of METTL14 in ovarian cancer. We performed bioinformatics and survival analyses with these datasets and also used METTL14-overexpressing SKOV-3 ovarian cancer cells for in vitro studies. Trophinin associated protein (TROAP) siRNA and treatment with or without actinomycin D was used in the cells for qRT-PCR, western blot, cDNA microarray, cell viability, colony formation, luciferase gene reporter, methylated RNA immunoprecipitation (MeRIP)-qPCR, total RNA methylation, and RNA stability assays. Additionally, ovarian cancer and normal tissue samples were analyzed by immunohistochemistry, qRT-PCR, and western blot assays. The TCGA and GEO data confirmed copy number variations (CNVs) of these m⁶A RNA methylation regulators in ovarian cancer tissues. Furthermore, reduced METTL14 expression was associated with alterations in CNVs as well as poor patient survival in ovarian cancer. Moreover, the METTL14 and m⁶A RNA methylation levels were both significantly reduced in ovarian cancer tissues than in normal tissues. Restoration of METTL14 expression suppresses ovarian cancer cell proliferation by inhibition of TROAP expression. Further in vivo and in vitro experiments confirmed that METTL14 is a negative regulator of ovarian cancer cell proliferation via TROAP expression and that m⁶A RNA methylation regulates TROAP mRNA stability. In conclusion, METTL14 overexpression decreased ovarian cancer proliferation by inhibition of TROAP expression via an m⁶A RNA methylation-dependent mechanism.

Construction and validation of m6 A RNA methylation regulators associated prognostic model for gastrointestinal cancer

N6-methyladenosine (m⁶ A) RNA methylation is correlated with carcinogenesis and dynamically possessed through the m⁶ A RNA methylation regulators. This paper aimed to explore 13 m⁶ A RNA methylation regulators' role in gastrointestinal cancer (GIC) and determine the risk model and prognosis value of m⁶ A RNA methylation regulators in GIC. We used several bioinformatics methods to identify the differential expression of m⁶ A RNA methylation regulators in GIC, constructed a prognostic model, and carried out functional enrichment analysis. Eleven of 13 m⁶ A RNA methylation regulators were differentially expressed in different clinicopathological characteristics of GIC, and m⁶ A RNA methylation regulators were nearly associated with GIC. We constructed a risk model based on five m⁶ A RNA methylation regulators (METTL3, FTO, YTHDF1, ZC3H13, and WTAP); the risk score is an independent prognosis biomarker. Moreover, the five m⁶ A RNA methylation regulators can also forecast the 1-, 3- and 5-year overall survival through a nomogram. Furthermore, four hallmarks of oxidative phosphorylation, glycolysis, fatty acid metabolism, and cholesterol homoeostasis gene sets were significantly enriched in GIC. m⁶ A RNA methylation regulators were related to the malignant clinicopathological characteristics of GIC and may be used for prognostic stratification and development of therapeutic strategies.

The roles of risk model based on the 3-XRCC genes in lung adenocarcinoma progression

Background

The abnormal expression of deoxyribonucleic acid (DNA) repair genes might be the cause of tumor development and resistance of malignant cells to chemotherapeutic drugs. A risk model based on the X-ray repair of cross-complementary (XRCC) genes was constructed to improve the diagnosis and treatment of lung adenocarcinoma (LUAD) patients.

Methods

The expression levels, diagnostic values, and prognostic values of XRCC genes were identified, and the roles and regulatory mechanisms of the risk model based on the XRCC4/5/6 in LUAD progression was explored via The Cancer Genome Atlas (TCGA) and Oncomine databases.

Results

XRCC1/2/3/4/5/6, XRCC7 (PRKDC), and XRCC9 (FANCG) were overexpressed, and had diagnostic value for LUAD. The XRCC genes were involved in DNA repair, and participated in the regulation of non-homologous end-joining, homologous recombination, etc. The overall survival (OS), tumor (T) stage, and survival status of patients were significantly different between the Cluster1 and Cluster2 groups. XRCC4/5/6 were independent risk factors affecting the prognosis of LUAD patients. The risk score was related to the prognosis, sex, clinical stage, T, lymph node (N), and metastasis (M) stage, as well as the survival status of LUAD patients. The clinical stage and risk score were independent risk factors for poor prognosis in LUAD patients. The risk model was involved in RNA degradation, cell cycle, basal transcription factors, DNA replication etc. The risk scores were significantly correlated with the expression levels of TGFBR1, CD160, TNFSF4, TNFRSF14, IL6R, CXCL16, TNFRSF25, TAPBP, CCL16, and CCL14.

Conclusions

The risk model based on the XRCC4/5/6 genes could predict the progression of LUAD patients.

Construction of Molecular Subtypes and Related Prognostic and Immune Response Models Based on M2 Macrophages in Glioblastoma

OBJECTIVES

To identify the molecular subtypes of glioblastoma multiforme (GBM) related to M2 macrophage-based prognostic genes, then to preliminarily explore their biological functions and construct immunotherapy response gene models.

MATERIAL AND METHODS

We used R language to analyze GBM microarray data, and other tools, including xCell and CIBERSORTx, to identify subtypes of GBM that related to M2 macrophages. The process started with the exploration of biological functions of the two subtypes by pathway analyses and GSEA, and continued with a combined procedure of constructing an M2 macrophage-related prognostic gene model and exploring the immune treatment response for GBM.

RESULTS

A high abundance of M2 macrophages in GBM was associated with poor prognosis. According to M2 macrophage-related prognostic genes, GBM was divided into two subtypes (cluster A and cluster B). The differential gene enrichment analysis of the two clusters showed that cluster A was less enriched in M2 macrophages and had immunopotential. The M2score, which was constructed based on M2 macrophage-related prognostic genes, was not only related to the survival and prognosis of patients with GBM, but also predictive of the effectiveness of immunotherapy in these patients. This result has been effectively verified in an external data set.

CONCLUSION

GBM was successfully divided into two subtypes according to M2-macrophage-related prognostic genes. In GBM, a high M2score may indicate better clinical outcome and enhancement of the immunotherapy response.

The Role of m6A RNA Methylation-Related lncRNAs in the Prognosis and Tumor Immune Microenvironment of Papillary Thyroid Carcinoma

Emerging evidence has indicated that N6-methylandenosine (m6A) RNA methylation plays a critical role in cancer development. However, the function of m6A RNA methylation-related long noncoding RNAs (m6A-lncRNAs) in papillary thyroid carcinoma (PTC) has never been reported. This study aimed to investigate the role of m6A-lncRNAs in the prognosis and tumor microenvironment (TME) of PTC. Three subgroups (clusters 1, 2, and 3) were identified by consensus clustering of 19 prognosis-related m6A-lncRNA regulators, of which cluster 1 is preferentially related to unfavorable prognosis, lower immune scores, and distinct immune infiltrate level. A risk-score model was established based on 8 prognosis-related m6A-lncRNAs. Patients with a high-risk score showed a worse prognosis, and the ROC indicated a reliable prediction performance for patients with PTC (AUC = 0.802). As expected, the immune scores, the infiltration levels of immune cells, and ESTIMATE scores in the low-risk subgroups were notably higher (p < 0.001) when compared with those in high-risk subgroups. Furthermore, GSEA analysis revealed that tumor associated pathways, hallmarks, and biological processes were remarkably enriched in the high-risk subgroup. Further analysis indicated that the risk score and age were independent prognostic factors for PTC. An integrated nomogram was constructed that accurately predicted the survival status (AUC = 0.963). Moreover, a lncRNA-miRNA-mRNA regulated network was established based on seven prognosis-related m6A-lncRNAs. In addition, 30 clinical samples and different PTC cells were validated. This is the first study to reveal that m6A-lncRNAs plays a vital role in the prognosis and TME of PTC. To a certain degree, m6A-lncRNAs can be considered as new, promising prognostic biomarkers and treatment targets.

External Validation of the Prognostic Value of an Immune-Associated Gene Panel for Clear Cell Renal Cell Carcinomas

Clear cell renal cell carcinomas (ccRCCs) are highly immune infiltrates, and many of them respond to immunotherapy with checkpoint inhibitors including anti-PD-L1 or anti-PD1 agents. However, the effect of immune genes on clinical outcomes in ccRCCs has not been fully studied. Here, we show in this study that an immune-associated gene panel has a prognostic value for clear cell renal cell carcinomas. We performed single-sample gene set enrichment analysis (ssGSEA) and cell type identification by estimating subsets of RNA transcripts (CIBERSORT) algorithms on patient-matched normal renal and RCC tissues to characterize two immunophenotypes and immunological characteristic subpopulations. Furthermore, LASSO Cox regression was applied to develop a novel prognosis-associated model for ccRCC patients based on an immune-gene panel. The results were verified by the Gene Expression Omnibus (GEO) dataset and coordinated with the clinicopathological characteristics of ccRCCs, along with genomic signatures. Finally, based on the above perspectives, we generated a nomogram with a high prognostic efficiency for ccRCC patients. Overall, this study offers a unique perspective that can contribute to improving the accuracy of prognosis prediction and treatment with immunotherapy.

Methyltransferase-like 14 suppresses growth and metastasis of renal cell carcinoma by decreasing long noncoding RNA NEAT1

Growing evidence supports that N6‐methyladenosine (m6A) modification acts as a critical regulator involved in tumorigenesis at the mRNA level. However, the role of m6A modification at the noncoding RNA level remains largely unknown. We found that methyltransferase‐like 14 (METTL14) was significantly downregulated in renal cell carcinoma (RCC) tissues (n = 580). Gain‐of‐function and loss‐of‐function experiments revealed that METTL14 attenuated the proliferation and migration ability of RCC cells in vivo and in vitro. The methylated RNA immunoprecipitation experiments identified that METTL14 decreased the expression of long noncoding RNA nuclear enriched abundant transcript 1_1 (NEAT1_1) in an m6A‐dependent manner. Mechanistically, RNA pull‐down assay and RNA immunoprecipitation identified NEAT1_1 directly bound to m6A reader YTH N6‐methyladenosine RNA binding protein 2 (YTHDF2). Notably, YTHDF2 accelerated the degradation of NEAT1_1 by selectively recognizing METTL14‐mediated m6A marks on NEAT1_1. Multivariate analysis suggested that METTL14 downregulation was associated with malignant characteristics and predicted poor prognosis in RCC patients. In conclusion, our results uncover a newly identified METTL14‐YTHDF2‐NEAT1_1 signaling axis, which facilitates RCC growth and metastasis and provides fresh insight into RCC therapy.

Comprehensive Analysis of m5C RNA Methylation Regulator Genes in Clear Cell Renal Cell Carcinoma

Background

Recent research found that N5-methylcytosine (m⁵C) was involved in the development and occurrence of numerous cancers. However, the function and mechanism of m⁵C RNA methylation regulators in clear cell renal cell carcinoma (ccRCC) remains undiscovered. This study is aimed at investigating the predictive and clinical value of these m⁵C-related genes in ccRCC.

Methods

Based on The Cancer Genome Atlas (TCGA) database, the expression patterns of twelve m⁵C regulators and matched clinicopathological characteristics were downloaded and analyzed. To reveal the relationships between the expression levels of m⁵C-related genes and the prognosis value in ccRCC, consensus clustering analysis was carried out. By univariate Cox analysis and last absolute shrinkage and selection operator (LASSO) Cox regression algorithm, a m⁵C-related risk signature was constructed in the training group and further validated in the testing group and the entire cohort. Then, the predictive ability of survival of this m⁵C-related risk signature was analyzed by Cox regression analysis and nomogram. Functional annotation and single-sample Gene Set Enrichment Analysis (ssGSEA) were applied to further explore the biological function and potential signaling pathways. Furthermore, we performed qRT-PCR experiments and measured global m⁵C RNA methylation level to validate this signature in vitro and tissue samples.

Results

In the TCGA-KIRC cohort, we found significant differences in the expression of m⁵C RNA methylation-related genes between ccRCC tissues and normal kidney tissues. Consensus cluster analysis was conducted to separate patients into two m⁵C RNA methylation subtypes. Significantly better outcomes were observed in ccRCC patients in cluster 1 than in cluster 2. m⁵C RNA methylation-related risk score was calculated to evaluate the prognosis of ccRCC patients by seven screened m⁵C RNA methylation regulators (NOP2, NSUN2, NSUN3, NSUN4, NSUN5, TET2, and DNMT3B) in the training cohort. The AUC for the 1-, 2-, and 3-year survival in the training cohort were 0.792, 0.675, and 0.709, respectively, indicating that the risk signature had an excellent prognosis prediction in ccRCC. Additionally, univariate and multivariate Cox regression analyses revealed that the risk signature could be an independent prognostic factor in ccRCC. The results of ssGSEA suggested that the immune cells with different infiltration degrees between the high-risk and low-risk groups were T cells including follicular helper T cells, Th1_cells, Th2_cells, and CD8+_T_cells, and the main differences in immune-related functions between the two groups were the interferon response and T cell costimulation. In addition, qRT-PCR experiments confirmed our results in renal cell lines and tissue samples.

Conclusions

According to the seven selected regulatory factors of m⁵C RNA methylation, a risk signature associated with m⁵C methylation that can independently predict prognosis in patients with ccRCC was developed and further verified the predictive efficiency.

Expression pattern and prognostic value of N6-methyladenosine RNA methylation key regulators in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is still one of the most common malignancies worldwide. The accuracy of biomarkers for predicting the prognosis of HCC and the therapeutic effect is not satisfactory. N6-methyladenosine (m6A) methylation regulators play a crucial role in various tumours. Our research aims further to determine the predictive value of m6A methylation regulators and establish a prognostic model for HCC. In this study, the data of HCC from The Cancer Genome Atlas (TCGA) database was obtained, and the expression level of 15 genes and survival was examined. Then we identified two clusters of HCC with different clinical factors, constructed prognostic markers and analysed gene set enrichment, proteins’ interaction and gene co-expression. Three subgroups by consensus clustering according to the expression of the 13 genes were identified. The risk score generated by five genes divided HCC patients into high-risk and low-risk groups. In addition, we developed a prognostic marker that can identify high-risk HCC. Finally, a novel prognostic nomogram was developed to accurately predict HCC patients’ prognosis. The expression levels of 13 m6A RNA methylation regulators were significantly upregulated in HCC samples. The prognosis of cluster 1 and cluster 3 was worse. Patients in the high-risk group show a poor prognosis. Moreover, the risk score was an independent prognostic factor for HCC patients. In conclusion, we reveal the critical role of m6A RNA methylation modification in HCC and develop a predictive model based on the m6A RNA methylation regulators, which can accurately predict HCC patients’ prognosis and provide meaningful guidance for clinical treatment.

Gene Signatures and Prognostic Values of N6-Methyladenosine Related Genes in Ovarian Cancer

N6-Methyladenosine (m6A) is one of the most prominent modification regulating RNA processing and metabolism. Increasing studies have illuminated the vital role of m6A methylation in carcinogenesis. However, little is known about the interaction between m6A-related genes and survival of ovarian cancer (OC) patients. The purpose of this study was to obtain more reliable m6A-related genes that could be used as prognostic markers of OC using bioinformatics analysis performed on the RNA-seq data of OC. Gene expression datasets of all m6A-related genes as well as corresponding clinical data were obtained from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases. We detected differential expressed m6A-related candidate genes as well as their relationship and interaction. m6A RNA methylation regulator ALKBH5 and 35 m6A-related genes are dysregulated in OC. A gene set that could be used as a potential independent prognostic risk feature was further screened including NEBL, PDGFRA, WDR91, and ZBTB4. The results of mRNA expression analysis by PCR were consistent with those of bioinformatics analysis. We applied consensus clustering analysis on the expression of the four prognostic genes and obtained four OC subgroups TM1-TM4. There were significant differences in age, stage and grade among the subgroups, and the overall survival (OS) as well as Disease-free survival (DFS) of TM2 group were shorter than those of the other three groups. Further GO and KEGG enrichment analysis indicated that these differential genes were closely related to biological processes and key signaling pathways involved in OC. In summary, our study has indicated that m6A-related genes are key factors in the progression of OC and have potential effects on the prognostic stratification of OC and the development of treatment strategies.

N6-methyladenosine methyltransferases: functions, regulation, and clinical potential

N6-methyladenosine (m6A) has emerged as an abundant modification throughout the transcriptome with widespread functions in protein-coding and noncoding RNAs. It affects the fates of modified RNAs, including their stability, splicing, and/or translation, and thus plays important roles in posttranscriptional regulation. To date, m6A methyltransferases have been reported to execute m6A deposition on distinct RNAs by their own or forming different complexes with additional partner proteins. In this review, we summarize the function of these m6A methyltransferases or complexes in regulating the key genes and pathways of cancer biology. We also highlight the progress in the use of m6A methyltransferases in mediating therapy resistance, including chemotherapy, targeted therapy, immunotherapy and radiotherapy. Finally, we discuss the current approaches and clinical potential of m6A methyltransferase-targeting strategies.

m6A Regulator-Mediated Methylation Modification Model Predicts Prognosis, Tumor Microenvironment Characterizations and Response to Immunotherapies of Clear Cell Renal Cell Carcinoma

BACKGROUND

This study aims to establish an N6-methyladenosine (m6A) RNA methylation regulators-mediated methylation model and explore its role in predicting prognostic accuracy of immune contexture and characterizations of clear cell renal cell carcinoma (ccRCC).

METHODS

The m6A modification subclasses (m6AMS) were identified by unsupervised cluster analysis and three clusters were determined by consensus clustering algorithm in a discovering cohort. Testing and real-world validation cohorts were used to identify predictive responses for immune checkpoint therapies (ICTs) of m6AMS.

RESULTS

Prognostic implications landscape of m6A regulators in cancers and its differential expression levels in ccRCC patients were identified. Based on discovering cohort, ccRCC were automatically divided into three m6AMS, and cluster 3 showed significant worse survival than cluster 1/2. Importantly, it was found that the immune checkpoint molecules expression was significantly elevated in cluster 3. Besides, m6A scoreLow group (cluster 1&2) have significantly elevated TIDE score compared with m6A scoreHigh group (cluster 3). There was conspicuous tertiary lymphoid tissue, aggressive phenotype, elevated glycolysis, expression of PD-L1, abundance of CD8+ T cells, CD4+ FOXP3+ Treg cells and TCRn immune cells infiltration in the high m6A score group. Interestingly, there are significantly increased patients with clinical benefit in m6A scoreHigh group in 368 patients receiving ICTs from testing IMvigor210 (n = 292) and validation FUSCC (n = 55) cohorts.

CONCLUSION

Our discovery highlights the relationship between tumor epigenetic heterogeneity and immune contexture. Immune-rejection cluster 3 has pro-tumorigenic immune infiltration, and shows significant clinical benefits for ccRCC patients receiving ICTs, enabling patient selection for future clinical treatment.

Prognostic Implication of the m6A RNA Methylation Regulators in Rectal Cancer

N6-methyladenosine (m⁶A) is a very common and abundant RNA modifications occurring in nearly all types of RNAs. Although the dysregulated expression of m⁶A regulators is implicated in cancer progression, our understanding of the prognostic value of the m⁶A regulators in rectal cancer is still quite limited. In this study, we analyzed the RNA expression levels of the 17 m⁶A regulator genes of 95 rectal cancer and 10 normal rectal samples from the The Cancer Genome Atlas Rectum Adenocarcinoma (TCGA-READ) dataset. Lasso regression analysis was conducted to build a prognostic model and calculate the risk score. The rectal cancer patients were then devided into the high-risk and low-risk groups according to the mean risk score. The prognostic value of the identified model was separately evaluated in the TCGA-READ and GSE87211 datasets. GSEA was conducted to analyze the functional difference of high-risk and low-risk rectal cancer patients. Our analysis revealed that rectal cancer patients with lower expression of YTHDC2 and METTL14 had a remarkable worse overall survival (P < 0.05). The prognostic value of the model was validated in GSE87211 datasets, with AUC = 0.612 for OS and AUC = 0.651 for RFS. Furthermore, the m⁶A modification-based risk score system is associated with activation of distinct signaling pathways, such as DNA repair, epithelial-mesenchymal transition, G₂M checkpoint and the MYC pathway, that may contribute to the progression of rectal cancer. In conclusion, our findings demonstrated that the m⁶A RNA methylation regulators, specifically YTHDC2 and METTL14, were significantly down-regulated and might be potential prognostic biomarkers in rectal cancer.

The Role of RNA Modifications and RNA-modifying Proteins in Cancer Therapy and Drug Resistance

The advent of new genome-wide sequencing technologies has uncovered abnormal RNA modifications and RNA editing in a variety of human cancers. The discovery of reversible RNA N6-methyladenosine (RNA: m⁶A) by fat mass and obesity-associated protein (FTO) demethylase has led to exponential publications on the pathophysiological functions of m⁶A and its corresponding RNA modifying proteins (RMPs) in the past decade. Some excellent reviews have summarized the recent progress in this field. Compared to the extent of research into RNA: m⁶A and DNA 5-methylcytosine (DNA: m⁵C), much less is known about other RNA modifications and their associated RMPs, such as the role of RNA: m⁵C and its RNA cytosine methyltransferases (RCMTs) in cancer therapy and drug resistance. In this review, we will summarize the recent progress surrounding the function, intramolecular distribution and subcellular localization of several major RNA modifications, including 5' cap N7-methylguanosine (m7G) and 2'-O-methylation (Nm), m⁶A, m⁵C, A-to-I editing, and the associated RMPs. We will then discuss dysregulation of those RNA modifications and RMPs in cancer and their role in cancer therapy and drug resistance.

Novel insights into the m6A-RNA methyltransferase METTL3 in cancer

N6-methyladenosine (m⁶A) is a prevalent internal RNA modification in higher eukaryotic cells. As the pivotal m⁶A regulator, RNA methyltransferase-like 3 (METTL3) is responsible for methyl group transfer in the progression of m⁶A modification. This epigenetic regulation contributes to the structure and functional regulation of RNA and further promotes tumorigenesis and tumor progression. Accumulating evidence has illustrated the pivotal roles of METTL3 in a variety of human cancers. Here, we systemically summarize the interaction between METTL3 and RNAs, and illustrate the multiple functions of METTL3 in human cancer. METLL3 is aberrantly expressed in a variety of tumors. Elevation of METTL3 is usually associated with rapid progression and poor prognosis of tumors. On the other hand, METTL3 may also function as a tumor suppressor in several cancers. Based on the tumor-promoting effect of METTL3, the possibility of applying METTL3 inhibitors is further discussed, which is expected to provide novel insights into antitumor therapy.

A five-m6A regulatory gene signature is a prognostic biomarker in lung adenocarcinoma patients

We analyzed the prognostic value of N6-methyladenosine (m6A) regulatory genes in lung adenocarcinoma (LADC) and their association with tumor immunity and immunotherapy response. Seventeen of 20 m6A regulatory genes were differentially expressed in LDAC tissue samples from the TCGA and GEO databases. We developed a five-m6A regulatory gene prognostic signature based on univariate and Lasso Cox regression analysis. Western blot analysis confirmed that the five prognostic m6A regulatory proteins were highly expressed in LADC tissues. We constructed a nomogram with five-m6A regulatory gene prognostic risk signature and AJCC stages. ROC curves and calibration curves showed that the nomogram was well calibrated and accurately distinguished high-risk and low-risk LADC patients. Weighted gene co-expression analysis showed significant correlation between prognostic risk signature genes and the turquoise module enriched with cell cycle genes. The high-risk LADC patients showed significantly higher PD-L1 levels, increased tumor mutational burden, and a lower proportion of CD8+ T cells in the tumor tissues and improved response to immune checkpoint blockade therapy. These findings show that this five-m6A regulatory gene signature is a prognostic biomarker in LADC and that immune checkpoint blockade is a potential therapeutic option for high-risk LADC patients.

N6 -Methyladenosine (m6 A) readers are dysregulated in renal cell carcinoma

N⁶ -Methyladenosine (m⁶ A) is the most common modification of messenger RNA (mRNA) in mammals. It critically influences RNA metabolism and plays an essential role in virtually all types of bioprocesses including gene expression, tissue development, self-renewal and differentiation of stem cells, stress response and circadian clock control. It plays a crucial role in carcinogenesis and could be used as a prognostic and a diagnostic tool and as a target for new anticancer therapies. m⁶ A modification is dynamically and reversibly regulated by three types of proteins. Methyltransferases, so-called "writers" add a methyl group to the adenosine, which can be removed by demethylases, also called "erasers." m⁶ A-specific RNA-binding proteins, from here on referred to as "readers," preferentially bind to the m⁶ A site and mediate biological functions, such as translation, splicing or decay of RNA. In this study, we examined the expression of the six m⁶ A readers HNRNPA2B1, HNRNPC, YTHDC1 and YTHDF1-3 in clear cell renal carcinoma (ccRCC). We show that on mRNA level the expression of all six m⁶ A readers is significantly downregulated compared to normal renal tissue and on protein level five out of six readers are dysregulated. Lower levels of some m⁶ A readers are correlated with advanced stage and grade as well as associated with a shorter overall, progression-free and cancer-specific survival. In summary, we could show that m⁶ A readers are dysregulated in ccRCC and might therefore act as a tumor marker, could give further information on the individual prognosis and be a target of innovative cancer therapy.

RNA Modification of N6-Methyladenosine Predicts Immune Phenotypes and Therapeutic Opportunities in Kidney Renal Clear Cell Carcinoma

RNA modification of N6-methyladenosine (m6A) plays critical roles in various biological processes, such as cancer development, inflammation, and the anticancer immune response. However, the role played by a comprehensive m6A modification pattern in regulating anticancer immunity in kidney renal clear cell carcinoma (KIRC) has not been fully elucidated. In this study, we identified two independent m6A modification patterns with distinct biological functions, immunological characteristics, and prognoses in KIRC. Next, we developed an m6A score algorithm to quantify an individual's m6A modification pattern, which was independently validated in external cohorts. The m6A cluster 1 and low m6A score groups were characterized by a hot tumor microenvironment with an increased infiltration level of cytotoxic immune cells, higher tumor mutation burden, higher immune checkpoint expression, and decreased stroma-associated signature enrichment. In general, the m6A cluster 1 and low m6A score groups reflected an inflammatory phenotype, which may be more sensitive to anticancer immunotherapy. The m6A cluster 2 and high m6A score groups indicated a non-inflammatory phenotype, which may not be sensitive to immunotherapy but rather to targeted therapy. In this study, we first identified m6A clusters and m6A scores to elucidate immune phenotypes and to predict the prognosis and immunotherapy response in KIRC, which can guide urologists for making more precise clinical decisions.

A Ten-N6-Methyladenosine (m6A)-Modified Gene Signature Based on a Risk Score System Predicts Patient Prognosis in Rectum Adenocarcinoma

OBJECTIVES

The study aims to analyze the expression of N6-methyladenosine (m6A)-modified genes in rectum adenocarcinoma (READ) and identify reliable prognostic biomarkers to predict the prognosis of READ.

MATERIALS AND METHODS

RNA sequence data of READ and corresponding clinical survival data were obtained from The Cancer Genome Atlas (TCGA) database. N6-methyladenosine (m6A)-modified genes in READ were downloaded from the "m6Avar" database. Differentially expressed m6A-modified genes in READ stratified by different clinicopathological characteristics were identified using the "limma" package in R. Protein-protein interaction (PPI) network and co-expression analysis of differentially expressed genes (DEGs) were performed using "STRING" and Cytoscape, respectively. Principal component analysis (PCA) was done using R. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used to functionally annotate the differentially expressed genes in different subgroups. Univariate Cox regression analyses were conducted to identify the powerful independent prognostic factors in READ associated with overall survival (OS). A robust likelihood-based survival model was built using the "rbsurv" package to screen for survival-associated signature genes. The Support Vector Machine (SVM) was used to predict the prognosis of READ through the risk score of survival-associated signature genes. Correlation analysis were carried out using GraphPad prism 8.

RESULTS

We screened 974 differentially expressed m6A-modified genes among four types of READ samples. Two READ subgroups (group 1 and group 2) were identified by K means clustering according to the expression of DEGs. The two subgroups were significantly different in overall survival and pathological stages. Next, 118 differentially expressed genes between the two subgroups were screened and the expression of 112 genes was found to be related to the prognosis of READ. Next, a panel of 10 survival-associated signature genes including adamtsl1, csmd2, fam13c, fam184a, klhl4, olfml2b, pdzd4, sec14l5, setbp1, tmem132b was constructed. The signature performed very well for prognosis prediction, time-dependent receiver-operating characteristic (ROC) analysis displaying an area under the curve (AUC) of 0.863, 0.8721, and 0.8752 for 3-year survival rate, prognostic status, and pathological stage prediction, respectively. Correlation analysis showed that the expression levels of the 10 m6A-modified genes were positively correlated with that of m6A demethylase FTO and ALKBH5.

CONCLUSION

This study identified potential m6A-modified genes that may be involved in the pathophysiology of READ and constructed a novel gene expression panel for READ risk stratification and prognosis prediction.

Identification of a Two-m6A RNA Methylation Regulator Risk Signature as an Independent Prognostic Biomarker in Papillary Renal Cell Carcinoma by Bioinformatic Analysis

N6-Methyladenosine (m6A), the most common form of mRNA modification, is dynamically regulated by the m6A RNA methylation regulators, which play an important role in regulating the gene expression and phenotype in both health and disease. However, the role of m6A in papillary renal cell carcinoma (pRCC) is unknown. The purpose of this work is to investigate the prognostic value of m6A RNA methylation regulators in pRCC; thus, we can build a risk score model based on m6A RNA methylation regulators as a risk signature for predicting the prognosis of pRCC. Here, we investigated the expression and corresponding clinical data by bioinformatic analysis based on 289 pRCC tissues and 32 normal kidney tissues obtained from TCGA database. As a result, we identified the landscape of m6A RNA methylation regulators in pRCC. We grouped all pRCC patients into two clusters by consensus clustering to m6A RNA methylation regulators, but we found that the clusters were not correlated to the prognosis and clinicopathological features of pRCC. Therefore, we additionally built a two-m6A RNA methylation regulator risk score model as a risk signature by the univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression. The risk signature was constructed as follows: 0.031HNRNPC + 0.199KIAA1429. It revealed that the risk score was associated with the clinicopathological features such as pT status and pN status of pRCC. More importantly, the risk score was an independent prognostic marker for pRCC patients. Thus, m6A RNA methylation regulators contributed to the malignant progression of pRCC influencing its prognosis.

Effect of N6-Methyladenosine Regulators on Progression and Prognosis of Triple-Negative Breast Cancer

Background: The N6-methyladenosine (m⁶A) modification plays a critical role in cancer development. Little is known about the m⁶A modification in triple-negative breast cancer (TNBC), the most aggressive subtype of breast cancer. Thus, the prognostic value of m⁶A RNA methylation in TNBC deserves exploration.

Methods: The expression levels of the 13 m⁶A methylation regulators were compared between the 98 TNBC tumor samples and normal tissue samples based on the transcriptome profiles from The Cancer Genome Atlas (TCGA). The association between the m⁶A regulators and patients' overall survival was assessed by Kaplan-Meier survival analysis and Cox regression analysis. Lasso regression analysis was conducted to construct a prognostic model based on the m⁶A methylation system. The prognostic performance of the identified model was validated in GSE88847 and GSE135565 datasets. A nomogram combining the TNM stage and the m⁶A prognostic model was further constructed for the survival prediction of TNBC patients.

Results: The m⁶A regulator genes were remarkably dysregulated in TNBC tumor tissues, with ALKBH5, YTHDF2, HNRNPC, KIAA1429, and RBM15 significantly up-regulated and FTO, YTHDC1, YTHDC2, METTL3, METTL14, and ZC3H13 significantly down-regulated (P < 0.01). The expression level of ALKBH5 was an independent unfavorable prognostic factor (HR = 3.327, P = 0.006), while METTL14 (HR = 0.425, P = 0.009) was an independent favorable prognostic factor for TNBC patients. A prognostic model consisting of ALKBH5 and METTL14 was therefore proposed displaying higher accuracy of risk prediction when combined with TNM stage with an AUC of 0.791. The prognostic value of the identified signature remained consistent within the two external validation datasets.

Conclusion: The m⁶A methylation regulators were significantly dysregulated in TNBC tissues and could constitute a novel prognostic signature for the survival prediction of TNBC patients.

The role of m6A, m5C and Ψ RNA modifications in cancer: Novel therapeutic opportunities

RNA modifications have recently emerged as critical posttranscriptional regulators of gene expression programmes. Significant advances have been made in understanding the functional role of RNA modifications in regulating coding and non-coding RNA processing and function, which in turn thoroughly shape distinct gene expression programmes. They affect diverse biological processes, and the correct deposition of many of these modifications is required for normal development. Alterations of their deposition are implicated in several diseases, including cancer. In this Review, we focus on the occurrence of N⁶-methyladenosine (m⁶A), 5-methylcytosine (m⁵C) and pseudouridine (Ψ) in coding and non-coding RNAs and describe their physiopathological role in cancer. We will highlight the latest insights into the mechanisms of how these posttranscriptional modifications influence tumour development, maintenance, and progression. Finally, we will summarize the latest advances on the development of small molecule inhibitors that target specific writers or erasers to rewind the epitranscriptome of a cancer cell and their therapeutic potential.

Identification and Validation of the N6-Methyladenosine RNA Methylation Regulator YTHDF1 as a Novel Prognostic Marker and Potential Target for Hepatocellular Carcinoma

Purpose: N6-methyladenosine (m⁶A) RNA methylation has been implicated in various malignancies. This study aimed to identify the m⁶A methylation regulator-based prognostic signature for hepatocellular carcinoma (HCC) as well as provide candidate targets for HCC treatment.

Methods: The least absolute shrinkage and selection operator (LASSO) analyses were performed to identify a risk signature in The Cancer Genome Atlas (TCGA) datasets. The risk signature was further validated in International Cancer Genome Consortium (ICGC) and Pan-Cancer Analysis of Whole Genomes (PCAWG) datasets. Following transfection of short hairpin RNA (shRNA) targeting YTHDF1, the biological activities of HCC cells were evaluated by Cell Counting Kit-8 (CCK-8), wound-healing, Transwell, flow cytometry, and xenograft tumor assays, respectively. The potential mechanisms mediated by YTHDF1 were predicted by overrepresentation enrichment analysis (ORA)/gene set enrichment analysis (GSEA) and validated by Western blotting.

Results: Overexpression of m⁶A RNA methylation regulators was correlated with malignant clinicopathological characteristics of HCC patients. The Cox regression and LASSO analyses identified a risk signature with five m⁶A methylation regulators (KIAA1429, ZC3H13, YTHDF1, YTHDF2, and METTL3). In accordance with HCC cases in TCGA, the prognostic value of risk signature was also determined in ICGC and PCAWG datasets. Following analyzing the expression and clinical implications in TCGA and Gene Expression Omnibus (GEO), YTHDF1 was chosen for further experimental validation. Knockdown of YTHDF1 significantly inhibited the proliferation, migration, and invasion of HCC cells, as well as enhanced the apoptosis in vitro. Moreover, silencing YTHDF1 repressed the growth of xenograft tumors in vivo. Mechanism investigation indicated that YTHDF1 might promote the aggressive phenotypes by facilitating epithelial–mesenchymal transition (EMT) and activating AKT/glycogen synthase kinase (GSK)-3β/β-catenin signaling.

Conclusion: The current study identified a robust risk signature consisting of m⁶A RNA methylation regulators for HCC prognosis. In addition, YTHDF1 was a potential molecular target for HCC treatment.

The N6-Methyladenosine Features of mRNA and Aberrant Expression of m6A Modified Genes in Gastric Cancer and Their Potential Impact on the Risk and Prognosis

Although N6-methyladenosine (m6A) mRNA methylation is known to be closely related to tumor events, its role in carcinogenesis and the development of gastric cancer (GC) is not yet clear. The aim of this study was to identify common m6A features and novel aberrant expression of m6A modified genes in GC and to further explore their potential impact on risk and prognosis. Three paired GC and paracancerous (PCa) tissues were collected to perform an m6A sequencing by MeRIP-seq and microarray assays. The expression profile of m6A and mRNA were determined. Gene function note and enrichment analysis were performed, and protein–protein interaction networks of differentially m6A methylated genes (DMGs) were generated using the DAVID and STRING databases, respectively. Validation of the m6A related differentially expressed genes by matching TCGA and GTEx data and human tissues. Clinical and pathological correlation and survival analysis were performed by TCGA data. The m6A motif sequence GGACAR (R = U or A) C was the consensus in both GC and PCa tissues. m6A peaks were significantly related to different coordinates, however, for most samples, the end of the coding sequence (CDS) was more prominent than the start of CDS. The genes with higher levels of m6A in their mRNAs were mainly enriched in transcriptional misregulation in carcinogenesis pathways, whereas the genes with decreased methylation mainly regulated digestion and absorption of protein. There are genes with differential m6A modifications in GC and paired PCa tissues, and these genes are mainly enriched in transcriptional misregulation and digestion/absorption pathways. m6A-GC with the down- and up-regulated genes may play an important role in gastric carcinogenesis, which can affect the risk and prognosis in GC.

Prognosis Analysis and Validation of m6A Signature and Tumor Immune Microenvironment in Glioma

Glioma is one of the most typical intracranial tumors, comprising about 80% of all brain malignancies. Several key molecular signatures have emerged as prognostic biomarkers, which indicate room for improvement in the current approach to glioma classification. In order to construct a more veracious prediction model and identify the potential prognosis-biomarker, we explore the differential expressed m⁶A RNA methylation regulators in 665 gliomas from TCGA-GBM and TCGA-LGG. Consensus clustering was applied to the m6A RNA methylation regulators, and two glioma subgroups were identified with a poorer prognosis and a higher grade of WHO classification in cluster 1. The further chi-squared test indicated that the immune infiltration was significantly enriched in cluster 1, indicating a close relation between m⁶A regulators and immune infiltration. In order to explore the potential biomarkers, the weighted gene co-expression network analysis (WGCNA), along with Least absolute shrinkage and selection operator (LASSO), between high/low immune infiltration and m⁶A cluster 1/2 groups were utilized for the hub genes, and four genes (TAGLN2, PDPN, TIMP1, EMP3) were identified as prognostic biomarkers. Besides, a prognostic model was constructed based on the four genes with a good prediction and applicability for the overall survival (OS) of glioma patients (the area under the curve of ROC achieved 0.80 (0.76-0.83) and 0.72 (0.68-0.76) in TCGA and Chinese Glioma Genome Atlas (CGGA), respectively). Moreover, we also found PDPN and TIMP1 were highly expressed in high-grade glioma from The Human Protein Atlas database and both of them were correlated with m6A and immune cell marker in glioma tissue samples. In conclusion, we construct a novel prognostic model which provides new insights into glioma prognosis. The PDPN and TIMP1 may serve as potential biomarkers for prognosis of glioma.

Roles of N6 -methyladenosine (m6 A) RNA modifications in urological cancers

Epigenetics has long been a hot topic in the field of scientific research. The scope of epigenetics usually includes chromatin remodelling, DNA methylation, histone modifications, non-coding RNAs and RNA modifications. In recent years, RNA modifications have emerged as important regulators in a variety of physiological processes and in disease progression, especially in human cancers. Among the various RNA modifications, m⁶ A is the most common. The function of m⁶ A modifications is mainly regulated by 3 types of proteins: m⁶ A methyltransferases (writers), m⁶ A demethylases (erasers) and m⁶ A-binding proteins (readers). In this review, we focus on RNA m⁶ A modification and its relationship with urological cancers, particularly focusing on its roles and potential clinical applications.