m6A RNA Methylation Regulators Participate in the Malignant Progression and Have Clinical Prognostic Value in Lung Adenocarcinoma

Prognostic value of RNA methylation-related genes in gastric adenocarcinoma based on bioinformatics

Background

Gastric cancer (GC) is a malignant tumor that originates from the epithelium of the gastric mucosa and has a poor prognosis. Stomach adenocarcinoma (STAD) covers 95% of total gastric cancer. This study aimed to identify the prognostic value of RNA methylation-related genes in gastric cancer.

Methods

In this study, The Cancer Genome Atlas (TCGA)-STAD and GSE84426 cohorts were downloaded from public databases. Patients were classified by consistent cluster analysis based on prognosis-related differentially expressed RNA methylation genes Prognostic genes were obtained by differential expression, univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses. The prognostic model was established and validated in the training set, test set and validation set respectively. Independent prognostic analysis was implemented. Finally, the expression of prognostic genes was affirmed by reverse transcription quantitative PCR (RT-qPCR).

Results

In total, four prognostic genes (ACTA2, SAPCD2, PDK4 and APOD) related to RNA methylation were identified and enrolled into the risk signature. The STAD patients were divided into high- and low-risk groups based on the medium value of the risk score, and patients in the high-risk group had a poor prognosis. In addition, the RNA methylation-relevant risk signature was validated in the test and validation sets, and was authenticated as a reliable independent prognostic predictor. The nomogram was constructed based on the independent predictors to predict the 1/3/5-year survival probability of STAD patients. The gene set enrichment analysis (GSEA) result suggested that the poor prognosis in the high-risk subgroup may be related to immune-related pathways. Finally, the experimental results indicated that the expression trends of RNA methylation-relevant prognostic genes in gastric cancer cells were in agreement with the result of bioinformatics.

Conclusion

Our study established a novel RNA methylation-related risk signature for STAD, which was of considerable significance for improving prognosis of STAD patients and offering theoretical support for clinical therapy.

Identification of module genes and functional pathway analysis in septic shock subtypes by integrated bioinformatics analysis

BACKGROUND

The present study aimed to identify the module genes and key gene functions and biological pathways of septic shock (SS) through integrated bioinformatics analysis.

METHODS

In the study, we performed batch correction and principal component analysis on 282 SS samples and 79 normal control samples in three datasets, GSE26440, GSE95233 and GSE57065, to obtain a combined corrected gene expression matrix containing 21,654 transcripts. Patients with SS were then divided into three molecular subtypes according to sample subtyping analysis.

RESULTS

By analyzing the demographic characteristics of the different subtypes, we found no statistically significant differences in gender ratio and age composition among the three groups. Then, three subtypes of differentially expressed genes (DEGs) and specific upregulated DEGs (SDEGs) were identified by differential gene expression analysis. We found 7361 DEGs in the type I group, 5594 DEGs in the type II group, and 7159 DEGs in the type III group. There were 1698 SDEGs in the type I group, 2443 in the type II group, and 1831 in the type III group. In addition, we analyzed the correlation between the expression data of 5972 SDEGs in the three subtypes and the gender and age of 227 patients, constructed a weighted gene co-expression network, and identified 11 gene modules, among which the module with the highest correlation with gender ratio was MEgrey. The modules with the highest correlation with age composition were MEgrey60 and MElightyellow. Then, by analyzing the differences in module genes among different subgroups of SS, we obtained the differential expression of 11 module genes in four groups: type I, type II, type III and the control group. Finally, we analyzed the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment of all module DEGs, and the GO function and KEGG pathway enrichment of different module genes were different.

CONCLUSIONS

Our findings aim to identify the specific genes and intrinsic molecular functional pathways of SS subtypes, as well as further explore the genetic and molecular pathophysiological mechanisms of SS.

The critical roles of m6A RNA methylation in lung cancer: from mechanism to prognosis and therapy

Lung cancer, a highly malignant disease, greatly affects patients' quality of life. N6-methyladenosine (m6A) is one of the most common posttranscriptional modifications of various RNAs, including mRNAs and ncRNAs. Emerging studies have demonstrated that m6A participates in normal physiological processes and that its dysregulation is involved in many diseases, especially pulmonary tumorigenesis and progression. Among these, regulators including m6A writers, readers and erasers mediate m6A modification of lung cancer-related molecular RNAs to regulate their expression. Furthermore, the imbalance of this regulatory effect adversely affects signalling pathways related to lung cancer cell proliferation, invasion, metastasis and other biological behaviours. Based on the close association between m6A and lung cancer, various prognostic risk models have been established and novel drugs have been developed. Overall, this review comprehensively elaborates the mechanism of m6A regulation in the development of lung cancer, suggesting its potential for clinical application in the therapy and prognostic assessment of lung cancer.

A Deep Learning Approach for Prognostic Evaluation of Lung Adenocarcinoma Based on Cuproptosis-Related Genes

Lung adenocarcinoma represents a significant global health challenge. Despite advances in diagnosis and treatment, the prognosis remains poor for many patients. In this study, we aimed to identify cuproptosis-related genes and to develop a deep neural network model to predict the prognosis of lung adenocarcinoma. We screened differentially expressed genes from The Cancer Genome Atlas data through differential analysis of cuproptosis-related genes. We then used this information to establish a prognostic model using a deep neural network, which we validated using data from the Gene Expression Omnibus. Our deep neural network model incorporated nine cuproptosis-related genes and achieved an area under the curve of 0.732 in the training set and 0.646 in the validation set. The model effectively distinguished between distinct risk groups, as evidenced by significant differences in survival curves (p < 0.001), and demonstrated significant independence as a standalone prognostic predictor (p < 0.001). Functional analysis revealed differences in cellular pathways, the immune microenvironment, and tumor mutation burden between the risk groups. Furthermore, our model provided personalized survival probability predictions with a concordance index of 0.795 and identified the drug candidate BMS-754807 as a potentially sensitive treatment option for lung adenocarcinoma. In summary, we presented a deep neural network prognostic model for lung adenocarcinoma, based on nine cuproptosis-related genes, which offers independent prognostic capabilities. This model can be used for personalized predictions of patient survival and the identification of potential therapeutic agents for lung adenocarcinoma, which may ultimately improve patient outcomes.

RBM15 silencing promotes ferroptosis by regulating the TGF-β/Smad2 pathway in lung cancer

OBJECTIVE

We assessed the function and mechanism of RNA binding motif protein 15 (RBM15) silencing in lung cancer development.

METHODS

The effects of RBM15 knockdown on A549 and H1299 cells were evaluated by MTT, EdU, wound healing, and transwell assay. We then detected the functions of RBM15 silencing on lipid peroxidation, labile iron pool (LIP), ferrous iron (Fe²⁺ ), and ferroptosis-related genes. RNA sequencing was performed after RBM15 knockout in lung cancer cells, followed by differentially expressed genes (DEGs), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed. Finally, the expression of RBM15 and pathway-related genes was determined by western blot.

RESULTS

RBM15 was highly expressed in lung cancer cells. RBM15 silencing reduced the viability, inhibited cell proliferation, invasion, and migration, and suppressed tumor growth in the xenograft mouse model. Knockout of RBM15 regulated ferroptosis-related gene expression. LIP, Fe²⁺ , and lipid peroxidation were distinctly increased by the knockout of RBM15. RNA-seq sequencing revealed that there are 367 up-regulated and 368 down-regulated DEGs, which were enriched in molecular functions, biological processes, and cellular components. RBM15 silencing reduced the expression of TGF-β/Smad2, and TGF-β activator (SRI-011381) reversed the inhibitory effect of RBM15 silencing on tumor cell growth.

CONCLUSION

We demonstrated that RBM15 silencing promoted ferroptosis in lung cancer cells by TGF-β/Smad2 pathway, thereby inhibiting lung cancer cell growth, which may provide new light for lung cancer treatment.

Comprehensive analysis of the significance of METTL7A gene in the prognosis of lung adenocarcinoma

Background

The most common subtype of lung cancer, called lung adenocarcinoma (LUAD), is also the largest cause of cancer death in the world. The aim of this study was to determine the importance of the METTL7A gene in the prognosis of patients with LUAD.

Methods

This particular study used a total of four different LUAD datasets, namely TCGA-LUAD, GSE32863, GSE31210 and GSE13213. Using RT-qPCR, we were able to determine METTL7A expression levels in clinical samples. Univariate and multivariate Cox regression analyses were used to identify factors with independent effects on prognosis in patients with LUAD, and nomograms were designed to predict survival in these patients. Using gene set variation analysis (GSVA), we investigated differences in enriched pathways between METTL7A high and low expression groups. Microenvironmental cell population counter (MCP-counter) and single-sample gene set enrichment analysis (ssGSEA) methods were used to study immune infiltration in LUAD samples. Using the ESTIMATE technique, we were able to determine the immune score, stromal score, and estimated score for each LUAD patient. A competing endogenous RNA network, also known as ceRNA, was established with the help of the Cytoscape program.

Results

We detected that METTL7A was down-regulated in pan-cancer, including LUAD. The survival study indicates that METTL7A was a protective factor in the prognosis of LUAD. The univariate and multivariate Cox regression analyses revealed that METTL7A was a robust independent prognostic indicator in survival prediction. Through the use of GSVA, several immune-related pathways were shown to be enriched in both the high-expression and low-expression groups of METTL7A. Analysis of the tumor microenvironment revealed that the immune microenvironment of the group with low expression was suppressed, which may be connected to the poor prognosis. To explore the ceRNA regulatory mechanism of METTL7A, we finally constructed a regulatory network containing 1 mRNA, 2 miRNAs, and 5 long non-coding RNAs (lncRNAs).

Conclusion

In conclusion, we presented METTL7A as a potential and promising prognostic indicator of LUAD. This biomarker has the potential to offer us with a comprehensive perspective of the prediction of prognosis and treatment for LUAD patients.

Comprehensive analysis about prognostic and immunological role of WTAP in pan-cancer

Background: Wilms tumor 1-associated protein (WTAP) plays a critical role in ribonucleic acid (RNA) methylation of N6 adenosine (m⁶A) modification, which is closely related with varieties of biological process. However, the role of WTAP in cancers remains to be determined. This study is designed to demonstrate the prognostic landscape of WTAP in pan-cancer and explore the relationship between WTAP expression and immune infiltration.

Methods: Here, we investigated the expression level and prognostic role of WTAP in pan-cancer using multiple databases, including PrognoScan, GEPIA, and Kaplan-Meier Plotter. Then, applying the GEPIA and TIMER databases, we illustrated the correlations between WTAP expression and immune infiltration in tumors, especially liver hepatocellular carcinoma (LIHC), and esophageal carcinoma (ESCA).

Results: WTAP had significant higher expression levels in tumor tissues of ESCA, LIHC, etc., while lower expression levels in those of bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), etc. And WTAP demonstrated multifaceted prognostic value in cancers. Of our interests, WTAP exerted a harmful effect on LIHC patient for overall survival (OS) and progression free survival (PFS). WTAP expression also significantly associated with the infiltration levels of B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages, neutrophils, and dendritic cells (DC) in LIHC but not ESCA. Furthermore, combined analysis about WTAP expression level and immune cell specific gene markers implied WTAP correlates with regulatory cells (T reg) infiltration in LIHC and ESCA.

Conclusion: The m⁶A regulator WTAP can serve as a prognostic biomarker for certain tumor types in pan-cancer and potentially result from immune cell infiltration.

Identification and construction of a prognostic risk model based on multi-RNA methylation regulators in cervical cancer

AIM

Cervical cancer is one of the most aggressive female cancers. RNA methylation is a necessary epigenetic modification in biological process. This study aimed to construct an RNA methylation regulator-based risk model for predicting the prognosis of cervical cancer patients.

METHODS

The transcriptome profiles of cervical cancer data were obtained from The Cancer Genome Atlas (TCGA) and GSE44001. An RNA methylation-related risk model was constructed and assessed by the Least absolute shrinkage and selection operator (Lasso)-penalized Cox regression model and receiver operating characteristic (ROC). Kaplan-Meier and Cox regression analyses were used to evaluate the prognostic effect of the risk model and calculated scores. The immune infiltration difference was further analyzed between the subgroups with a single-sample gene set enrichment analysis (ssGSEA).

RESULTS

A total of 63 methylation modulators were included in this study, and 618 cervical cancer patients were identified from TCGA and GSE44001. Differential expression genes profiling RNA methylation regulators between normal and tumor samples were distinct. A four-gene signature panel was constructed to predict the prognostic risk. The predictive ability was satisfactory. Cervical cancer patients were classified into high- or low-risk subgroups according to the median risk score. Moreover, the immune infiltration patterns between them differed.

CONCLUSIONS

A risk model including four RNA methylation regulators was constructed, which will provide new perspectives for further investigation of the relationship between RNA methylation and cervical cancer.

Comprehensive Analysis of Gene Signatures of m6ARNA Methylation Regulators in Lung Adenocarcinoma and Development of a Risk Scoring System

The recent application of targeted immunotherapy has greatly improved the clinical outcomes of patients with lung adenocarcinoma (LUAD), but drug resistance continues to emerge, and to evaluate and to improve patient prognosis are arduous. The diagnostic and prognostic value of N6-methyladenosine (M6A) in LUAD has attracted increasing attention. We systematically studied correlations among important M6A methylation regulators, tumor mutational burden (TMB), and immune infiltration in clinical and sequencing data from the LUAD cohort of the cancer genome map (TCGA). The molecular subtype clusters 1 and 2 were identified by the consensus clustering of 16 M6A regulatory factors. Clinical prognosis, M6A regulatory factor expression, TMB, pathway enrichment, and immune cell infiltration significantly differed between clusters 1 and 2. Compared with other clinical traits, a prognostic risk score system constructed using the M6A regulatory factors HNRNPA2B1 and HNRNPC can serve as an independent prognostic method for LUAD, with higher predictive sensitivity and specificity. Risk scores were significantly higher for cluster 2 than 1, which was consistent with the trend towards a better prognosis in cluster 1. Overall, our findings revealed an important role of M6A methylation regulators in LUAD, and our risk scoring system involving these regulators might help to screen groups at high risk for LUAD and provide important theoretical bioinformatic support for evaluating the prognosis of such patients.

Gene amplification-driven RNA methyltransferase KIAA1429 promotes tumorigenesis by regulating BTG2 via m6A-YTHDF2-dependent in lung adenocarcinoma

Background

Epigenetic alterations have been shown to contribute immensely to human carcinogenesis. Dynamic and reversible N6‐methyladenosine (m6A) RNA modification regulates gene expression and cell fate. However, the reasons for activation of KIAA1429 (also known as VIRMA, an RNA methyltransferase) and its underlying mechanism in lung adenocarcinoma (LUAD) remain largely unexplored. In this study, we aimed to clarify the oncogenic role of KIAA1429 in the tumorigenesis of LUAD.

Methods

Whole‐genome sequencing and transcriptome sequencing of LUAD data were used to analyze the gene amplification of RNA methyltransferase. The in vitro and in vivo functions of KIAA1429 were investigated. Transcriptome sequencing, methylated RNA immunoprecipitation sequencing (MeRIP‐seq), m6A dot blot assays and RNA immunoprecipitation (RIP) were performed to confirm the modified gene mediated by KIAA1429. RNA stability assays were used to detect the half‐life of the target gene.

Results

Copy number amplification drove higher expression of KIAA1429 in LUAD, which was correlated with poor overall survival. Manipulating the expression of KIAA1429 could regulate the proliferation and metastasis of LUAD. Mechanistically, the target genes of KIAA1429‐mediated m6A modification were confirmed by transcriptome sequencing and MeRIP‐seq assays. We also revealed that KIAA1429 could regulate BTG2 expression in an m6A‐dependent manner. Knockdown of KIAA1429 significantly decreased the m6A levels of BTG2 mRNA, leading to enhanced YTH m6A RNA binding protein 2 (YTHDF2, the m6A “reader”)‐dependent BTG2 mRNA stability and promoted the expression of BTG2; thus, participating in the tumorigenesis of LUAD.

Conclusions

Our data revealed the activation mechanism and important role of KIAA1429 in LUAD tumorigenesis, which may provide a novel view on the targeted molecular therapy of LUAD.

Construction and validation of a nomogram based on N6-Methylandenosine-related lncRNAs for predicting the prognosis of non-small cell lung cancer patients

BACKGROUND

The N6-methyladenosine (m⁶ A) can modify long non-coding RNAs (lncRNAs), thereby influencing a wide array of biological functions. However, the prognosis of m⁶ A-related lncRNAs (m⁶ ARLncRNAs) in non-small cell lung cancer (NSCLC) remains largely unknown.

METHODS

Pearson correlation analysis was used to identify m⁶ ARLncRNAs in 1835 NSCLC patients and with the condition (|Pearson R| > 0.4 and p < 0.001). Univariant Cox regression analysis was conducted to explore the prognostic m⁶ ARLncRNAs. We filtered prognostic m⁶ ARLncRNAs by LASSO regression and multivariate Cox proportional hazard regression to construct and validate an m⁶ ARLncRNAs signature (m⁶ ARLncSig). We analyzed the correlation between the m⁶ ARLncSig score and clinical features, immune microenvironment, tumor mutation burden, and therapeutic sensitivity and conducted independence and clinical stratification analysis. Finally, we established and validated a nomogram for prognosis prediction in NSCLC patients.

RESULTS

Forty-one m⁶ ARLncRNAs were identified as prognostic lncRNAs, and 12 m⁶ ARLncRNAs were selected to construct m⁶ ARLncSig in the TCGA training dataset. The m⁶ ARLncSig was further validated in the testing dataset, GSE31210, GSE37745, GSE30219, and our NSCLC samples. In terms of m⁶ ARLncSig, NSCLC patients were divided into high- and low-risk groups, with significantly different overall survival (OS), clinical features (age, sex, and tumor stage), tumor-infiltrating immune cells, chemotherapeutic sensitivity, radiotherapeutic response, and biological pathways. Moreover, m⁶ ARLncSig independently predicted the OS of NSCLC patients. Finally, the robustness and clinical practicability for predicting NSCLC patient prognosis was improved by constructing a nomogram containing the m⁶ ARLncSig, age, gender, and tumor stage.

CONCLUSIONS

Our study demonstrated that m⁶ ARLncSig could act as a potential biomarker for evaluating the prognosis and therapeutic efficacy in NSCLC patients.

Roles and mechanisms of the m6A reader YTHDC1 in biological processes and diseases

N6-methyladenosine (m⁶A) is a key area in Epigenetics and has been increasingly focused these years. In the m⁶A process, readers recognize the m⁶A modification on mRNAs or noncoding RNAs and mediate different downstream events. Emerging studies have shown that YTHDC1, an important m⁶A reader, plays a key role in many biological functions and disease progression, especially cancers. Here we summarized the current mechanisms of YTHDC1 in biological functions and diseases and offered guidance for future researches to provide potential strategy for clinical diagnose and therapy.

The Emerging Role of N6-Methyladenosine RNA Methylation as Regulators in Cancer Therapy and Drug Resistance

N6-methyladenosine (m6A) RNA methylation has been considered the most prevalent, abundant, and conserved internal transcriptional modification throughout the eukaryotic mRNAs. Typically, m6A RNA methylation is catalyzed by the RNA methyltransferases (writers), is removed by its demethylases (erasers), and interacts with m6A-binding proteins (readers). Accumulating evidence shows that abnormal changes in the m6A levels of these regulators are increasingly associated with human tumorigenesis and drug resistance. However, the molecular mechanisms underlying m6A RNA methylation in tumor occurrence and development have not been comprehensively clarified. We reviewed the recent findings on biological regulation of m6A RNA methylation and summarized its potential therapeutic strategies in various human cancers.

The molecular mechanism of METTL3 promoting the malignant progression of lung cancer

Lung cancer remains one of the major causes of cancer-related death globally. Recent studies have shown that aberrant m⁶A levels caused by METTL3 are involved in the malignant progression of various tumors, including lung cancer. The m⁶A modification, the most abundant RNA chemical modification, regulates RNA stabilization, splicing, translation, decay, and nuclear export. The methyltransferase complex plays a key role in the occurrence and development of many tumors by installing m⁶A modification. In this complex, METTL3 is the first identified methyltransferase, which is also the major catalytic enzyme. Recent findings have revealed that METTL3 is remarkably associated with different aspects of lung cancer progression, influencing the prognosis of patients. In this review, we will focus on the underlying mechanism of METT3 in lung cancer and predict the future work and potential clinical application of targeting METTL3 for lung cancer therapy.

Methylation Pattern Mediated by m6A Regulator and Tumor Microenvironment Invasion in Lung Adenocarcinoma

BACKGROUND

Recent research has established the existence of epigenetic modulation of the immune response. The possible involvement of RNA-n6-methyladenosine (m⁶A) alteration in tumor microenvironment (TME) cell invasion, on the other hand, is unknown.

METHODS

Based on 23 m⁶A regulators, we examined the alteration patterns of m⁶A in 629 LUAD tissues and comprehensively connected these modification patterns with TME cell invasion characteristics. The m⁶A score was calculated, and the m⁶A modification pattern of a single tumor was quantified using principal component analysis. Then, we further verified the expression of m⁶A related enzymes and the role hub gene (NOL10) closely related to survival in lung cancer cell lines.

RESULTS

Three separate m⁶A alteration modes have been discovered. TME cell invasion characteristics in the three modes were very similar to the three immunological phenotypes of tumors: immunological rejection, immunological inflammation, and immunological desert. We show that assessing the m⁶A modification pattern in a single tumor may help predict tumor inflammatory stage, subtype, TME interstitial activity, and prognosis. TME phenotypic inflammation is indicated by a high m⁶A score, which is characterized by elevated mutation load and immunological activation. The low m⁶A subtype showed matrix activation and ineffective immune infiltration, indicating that the TME phenotype of noninflammation and immunological rejection had a poor survival probability. Increased neoantigen burden was also linked to a high m⁶A score. Patients with a higher m⁶A score saw substantial therapeutic and clinical improvements. And reducing hub gene NOL10 expression substantially inhibited lung cancer cell growth and migration.

CONCLUSIONS

This research shows that m⁶A alteration is critical in the creation of TME variety and complexity. The analysis of a single tumor's m⁶A alteration pattern will aid in improving our knowledge of TME invasion features and guiding more effective immunotherapy tactics.

YTHDF2 Inhibits the Migration and Invasion of Lung Adenocarcinoma by Negatively Regulating the FAM83D-TGFβ1-SMAD2/3 Pathway

OBJECTIVE

YTH domain family 2 (YTHDF2) is an important N6-methyladenosine (m6A) reader, but its role in lung adenocarcinoma remains elusive. This study assessed its function in lung adenocarcinoma.

METHODS

YTHDF2 expression in lung adenocarcinoma was explored using public databases, such as The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumour Analysis Consortium (CPTAC). The effect of YTHDF2 on a lung adenocarcinoma cell line was explored by performing cytological and molecular experiments. Molecules downstream of YTHDF2 were identified using proteomics, and the related pathways were verified through cytological and molecular biology experiments.

RESULTS

YTHDF2 expression was upregulated in lung adenocarcinoma, and patients with high YTHDF2 expression experienced prolonged overall survival. In two lung cancer cell lines, YTHDF2 knockdown inhibited proliferation but promoted migration, invasion, and the epithelial-mesenchymal transition. The proteomic analysis identified 142 molecules downstream of YTHDF2, and 11 were closely related to survival. Further experiments revealed that YTHDF2 inhibited expression of the family with sequence similarity 83D (FAM83D)-TGFβ1-SMAD2/3 pathway components. This study is the first to show that YTHDF2 regulated the downstream TGFβ1-SMAD2/3 pathway through FAM83D in lung adenocarcinoma.

CONCLUSION

YTHDF2 inhibits the migration and invasion of lung adenocarcinoma cells by regulating the FAM83D-TGFβ1-pSMAD2/3 pathway, which may play an important role in lung cancer metastasis.

METTL14-Mediated miR-30c-1-3p Maturation Represses the Progression of Lung Cancer via Regulation of MARCKSL1 Expression

Lung cancer (LC) is a pulmonary malignant tumor with extremely low 5-year survival rate. N6-methyladenosine (m6A) is confirmed to regulate diverse pathophysiological processes including cancers. Methyltransferase-like 14 (METTL14) is an important RNA methyltransferase in m6A modification. However, researches on the regulatory mechanism of METTL14 on LC progression are relatively rare. Tumor xenograft experiment was conducted to investigate the effect of METTL14 on LC in vivo. The relative expression of METTL14, miR-30c-1-3p, and myristoylated alanine-rich C kinase substrate-like protein-1 (MARCKSL1) in LC tissues and/or cell lines was determined using qRT-PCR. Western blot assay was used to measure the protein levels of METTL14 and MARCKSL1 in tumor xenograft model and/or LC cell lines. MTT, wound healing, and transwell assays were performed to detect LC cell viability and metastasis. RNA immunoprecipitation assay and qRT-PCR were used to verify the effects of METTL14 on pri-miR-30c-1-3p. The relationship between miR-30c-1-3p and MARCKSL1 was confirmed by the dual-luciferase reporter assay. METTL14 was remarkably downregulated in LC tissues and cell lines. METTL14 mediated the maturation of miR-30c-1-3p. The overexpressed METTL14 and overexpressed miR-30c-1-3p suppressed the cell viability and metastasis in LC. Meanwhile, the increased METTL14 also repressed the growth of tumor xenograft in vivo. In addition, MARCKSL1 was confirmed to be the target gene of miR-30c-1-3p. High expression of MARCKSL1 and low expression of miR-30c-1-3p reversed the suppressive effects of METTL14 overexpression on cell viability and metastasis. METTL14 promoted the maturation of miR-30c-1-3p and mediated MARCKSL1 expression to inhibit the progression of LC. This study may provide a new insight for the LC clinical therapy.

Risk stratification of lung adenocarcinoma using a nomogram combined with ferroptosis-related LncRNAs and subgroup analysis with immune and N6-methyladenosine modification

Background

Determining the prognosis of lung adenocarcinoma (LUAD) is challenging. The present study aimed to identify prognostic ferroptosis-related long noncoding RNAs (FRLs) and construct a prognostic model. Moreover, differential analysis of immune and N6-methyladenosine (m6A)-related genes was systematically conducted.

Methods

A total of 504 patients selected from a dataset from The Cancer Genome Atlas were included. The patients with LUAD were randomly divided into a training group and a test group at a ratio of 1:1. Pearson correlation analysis and univariate Cox regression analysis were used to identify the prognostic FRLs. Then, a prognostic model was constructed from the optimized subset of prognostic FRLs based on the least absolute shrinkage and selection operator (LASSO) algorithm. Subsequently, the receiver operating characteristic (ROC) curve and survival analysis were used to evaluate the performance of the model. The risk score based on the prognostic model was analyzed using Cox regression analysis. Moreover, gene set enrichment analysis and differential analysis of immune- and m6A-related genes were conducted.

Results

After univariate Cox regression analysis and LASSO algorithm analysis, a total of 19 prognostic FRLs were selected to construct the final model to obtain the risk score. The area under the ROC curve of the prognostic model for 1-year, 3-year, and 5-year overall survival (OS) was 0.763, 0.745, and 0.778 in the training set and 0.716, 0.724, and 0.736 in the validation set, respectively. Moreover, the OS of the high-risk group was significantly worse than that of the low-risk group in the training group (P < 0.001) and in the test group (P < 0.001). After univariate and multivariate Cox regression analysis, the risk score [hazard ratio (HR) = 1.734; P < 0.001] and stage (HR = 1.557; P < 0.001) were both considered significant prognostic factors for LUAD. A nomogram was constructed based on clinical features and risk score. The expression of 34 checkpoint genes and 13 m6A-related genes varied significantly between the two risk groups.

Conclusion

This study constructed a prognostic model to effectively predict the OS of patients with LUAD, and these OS-related FRLs might serve as potential therapeutic targets of LUAD.

The Prognostic Role of m6A-Related Genes in Paediatric Neuroblastoma Patients

Methods

The gene expression data were extracted from the “Therapeutically Applicable Research to Generate Effective Treatments” (TARGET) database. The differentially expressed genes (DEGs) were identified, and the relationships between DEGs and m6A genes were explored. Then, the correlations among the m6A genes in neuroblastoma were investigated. Finally, the prognostic role of the m6A genes was studied, and the risk model was constructed.

Results

81 NB patients were extracted from the TARGET database. After comparing the gene expression between unfavorable and favorable outcome groups, 73 DEGs were identified, including 54 downregulated genes and 19 upregulated genes. In NB patients, we found that IGF2BP3, METTL14, and METTL16 are prognostic factors for disease-free survival (DFS) while IGF2BP3, METTL14, and METTL16 are prognostic factors for overall survival (OS). Besides, after the risk model construction, the OS between the two risk groups was drawn (log-rank p = 1.64e − 08, HR = 3.438, 95% CI 2.24-5.278). The 1-, 3-, and 5-year time-dependent receiving operating characteristic (ROC) curves were also illustrated, and the areas under the receiver operating characteristic curves (AUCs) attained 0.75, 0.798, and 0.768, respectively.

Conclusions

IGF2BP3, METTL14, and METTL16 were identified as the significant factors for DFS and OS in NB patients.

An N6-methyladenosine and target genes-based study on subtypes and prognosis of lung adenocarcinoma

Purpose: Lung adenocarcinoma (LUAD) is a highly lethal subtype of primary lung cancer with a poor prognosis. N6-methyladenosine (m⁶A), the most predominant form of RNA modification, regulates biological processes and has critical prognostic implications for LUAD. Our study aimed to mine potential target genes of m⁶A regulators to explore their biological significance in subtyping LUAD and predicting survival. Methods: Using gene expression data from TCGA database, candidate target genes of m⁶A were predicted from differentially expressed genes (DEGs) in tumor based on M⁶A2 Target database. The survival-related target DEGs identified by Cox-regression analysis was used for consensus clustering analysis to subtype LUAD. Uni-and multi-variable Cox regression analysis and LASSO Cox-PH regression analysis were used to select the optimal prognostic genes for constructing prognostic score (PS) model. Nomogram encompassing PS score and independent prognostic factors was built to predict 3-year and 5-year survival probability. Results: We obtained 2429 DEGs in tumor tissue, within which, 1267 were predicted to m⁶A target genes. A prognostic m⁶A-DEGs network of 224 survival-related target DEGs was established. We classified LUAD into 2 subtypes, which were significantly different in OS time, clinicopathological characteristics, and fractions of 12 immune cell types. A PS model of five genes (C1QTNF6, THSD1, GRIK2, E2F7 and SLCO1B3) successfully split the training set or an independent GEO dataset into two subgroups with significantly different OS time (p < 0.001, AUC = 0.723; p = 0.017, AUC = 0.705).A nomogram model combining PS status, pathologic stage, and recurrence was built, showing good performance in predicting 3-year and 5-year survival probability (C-index = 0.708, 0.723, p-value = 0). Conclusion: Using candidate m⁶A target genes, we obtained two molecular subtypes and designed a reliable five-gene PS score model for survival prediction in LUAD.

Genomics and Prognosis Analysis of N6-Methyladenosine Regulators in Lung Adenocarcinoma

Objective: N⁶-methyladenosine (m⁶A) modification is involved in modulating various biological processes in human cancers. But the implication of m⁶A modification in lung adenocarcinoma (LUAD) is still unclear. Hence, this study conducted a comprehensive analysis of the expression and clinical implication of m⁶A regulators in LUAD.

Methods: Consensus clustering analysis of 502 LUAD samples in the TCGA dataset was presented based on the expression profiles of 20 m⁶A regulators using ConsensusClusterPlus package. Overall survival (OS), activation of signaling pathways and tumor immunity (immune/stromal score, tumor purity, expression of HLA and immune checkpoints, and immune cell infiltration) were compared between m⁶A modification patterns. The m⁶A-related genes between patterns were identified and prognostic m⁶A-related genes were imported into LASSO-cox regression analysis. The m⁶A risk score was developed and its prognostic implication was evaluated and externally verified in the GSE30219 and GSE72094 dataset. Furthermore, a nomogram that contained independent prognostic indicators was established, followed by external verification.

Results: Two m⁶A modification patterns were clustered across LUAD based on the expression similarity of the m⁶A regulators via consensus clustering analysis, with distinct OS, activation of signaling pathways and tumor immunity. Totally, 213 m⁶A-related genes that were identified by comparing two patterns were significantly related to LUAD prognosis. By LASSO method, we constructed the m⁶A risk score that was a reliable and independent prognostic factor for LUAD. Patients with low m⁶A risk score displayed a prominent survival advantage. After incorporating independent clinical features, we developed the prognostic nomogram that exhibited high predictive accuracy and the best clinical net benefit for OS.

Conclusion: Collectively, our study may provide a clinically useful tool for precise prognostic management and optimization of immunotherapeutic strategies for LUAD patients.

Analysis of the expression patterns and clinical relevance of m6A regulators in 33 cancer types

Background: The role of N6-methyladenine (m6A) RNA methylation in a variety of biological processes is gradually being revealed. Methods: Here, we systematically describe the correlation between the expression pattern of m6A RNA methylation regulatory factors and clinical phenotype, immunity, drug sensitivity, stem cells and prognosis in more than 10,000 samples of 33 types of cancer. Results: The results show that there are significant differences in the expression of 20 m6A RNA methylation regulatory factors in different cancers, and there was a significant correlation with the analysis indicators. Conclusion: In this study, the m6A RNA methylation regulatory factor was found not only to potentially assist in stratifying the prognosis but also to predict or improve the sensitivity of clinical drug therapy.

Development and Validation of a Prognostic N6-Methyladenosine-Related Immune Gene Signature for Lung Adenocarcinoma

Purpose

The prognostic value of an N6-methyladenosine (m6A) methylation-related immune gene signature for lung adenocarcinoma (LUAD) was investigated.

Patients and Methods

Gene expression and clinical phenotype data of LUAD patients were downloaded from The Cancer Genome Atlas database. A list of immune-related genes was retrieved from the InnateDB database. Correlation analysis, survival analysis, and univariate and multivariate Cox regression analyses were performed. After allocating patients into a high-risk or a low-risk group, the corresponding survival rates, immune microenvironment, expression of immune checkpoint genes, and modulation of Kyoto Encyclopedia of Genes and Genomes pathways were examined. Finally, the expression levels of prognostic biomarkers were assessed in the GSE126044 dataset.

Results

Seven m6A-related immune prognostic genes were identified. High expression of PSMD10P1, DIDO1, ABCA5, and CIITA was associated with high survival rates, while that of PRC1, ZWILCH, and ANLN was associated with low survival rates. The high- and low-risk groups showed significant differences in terms of the abundance of six tumor-infiltrating immune cell types and expression of 12 immune checkpoint genes. The risk group acted as an independent prognostic factor (hazard ratio = 0.398, 95% confidence interval = 0.217–0.729, P = 0.003). Finally, the developed nomogram could predict most efficiently the 1-, 2-, and 3-year survival probability of LUAD patients with a C-index of 0.833.

Conclusion

A seven-gene risk signature, associated with the immune microenvironment in LUAD, showed independent prognostic value.

The roles and mechanisms of the m6A reader protein YTHDF1 in tumor biology and human diseases

YTHDF1 is the most versatile and powerful reader protein of N⁶-methyladenosine (m6A)-modified RNA, and it can recognize both G(m6A)C and A(m6A)C RNAs as ligands without sequence selectivity. YTHDF1 regulates target gene expression by different mechanisms, such as promoting translation or regulating the stability of mRNA. Numerous studies have shown that YTHDF1 plays an important role in tumor biology and nontumor lesions by mediating the protein translation of important genes or by affecting the expression of key factors involved in many important cell signaling pathways. Therefore, in this review we focus on some of the roles of YTHDF1 in tumor biology and diseases.

LncRNA HCG11 mediated by METTL14 inhibits the growth of lung adenocarcinoma via IGF2BP2/LATS1

Lung adenocarcinoma (LUAD) is a common malignancy the pathogenesis of which is terribly complicated and remains largely unclear. Long non-coding RNAs (lncRNAs) are a group of endogenous RNA molecules that are involved in various malignant processes. In this study, we explored the roles of lncRNA Human leukocyte antigen complex group 11 (HCG11) in LUAD. Our data revealed that lncRNA HCG11 expression was downregulated in LUAD, which was modulated by the hypermethylation of HCG11 promoter and Methyltransferase Like 14 (METTL14) mediated N6-methyladenosine (m6A) modification. The m6A modification of HCG11 promoted its nuclear exportation and binding by Insulin Like Growth Factor 2 MRNA Binding Protein 2 (IGF2BP2), resulting in increased stability. HCG11 could recruit IGF2BP2 to target Large Tumor Suppressor Kinase 1 (LATS1) mRNA to enhance the stability and promote the expression of LATS1. HCG11 served as a tumor suppressor to restrain tumor growth in LUAD by regulating LATS1. In summary, this study demonstrated that HCG11 mediated by METTL14 inhibited the growth of lung adenocarcinoma via IGF2BP2/LATS1.

An integrated model of FTO and METTL3 expression that predicts prognosis in lung squamous cell carcinoma patients

Background

Lung squamous cell carcinoma (LUSC) approximately accounts for a third of lung cancers. However, the role of N6-methyladenosine (m6A) in LUSC remains largely unknown according to previous studies.

Methods

In this study, we investigated the mutations, copy number variants (CNVs), expression of 20 m6A RNA methylation regulators, and clinical data from The Cancer Genome Atlas-LUSC (TCGA-LUSC). These data were used for the training cohort of screening potential biomarkers. The prognostic model of m6A RNA methylation regulators was constructed. A receiver operating characteristic (ROC) analysis was undertaken to determine the area under the curves (AUCs) (for 3- and 5-year survival) for the model. Additionally, the accuracy of the two-gene model was confirmed with external data verifications. Combined two-gene model and clinincal information were performed to construct a nomogram to predict patient’s prognostic risk assessment.

Results

Fat mass- and obesity-associated protein (FTO) and methyltransferase-like 3 (METTL3) were identified as potential prognostic biomarkers to evaluate benign and malignant tumors and prognosticate. The following prognostic model of m6A RNA methylation regulators was constructed: risk score = 0.162 × FTO − 0.069 × METTL3. Patients in low-risk group [median overall survival (mOS), 43.4 months] had longer survival than those with high-risk (mOS, 67.3 months) with P=0.0023. The smoking grade and risk score could be independent prognostic factors (P=0.00098 and P=0.0014, respectively). Ultimately, a nomogram was developed to assist clinicians to predict clinical outcomes.

Conclusions

FTO and METTL3 are potential prognostic biomarkers of LUSC. The two-gene model’s use of prognostic risk scores may provide guidance in the selection of therapeutic strategies.

Relationships of N6-Methyladenosine-Related Long Non-Coding RNAs With Tumor Immune Microenvironment and Clinical Prognosis in Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is the major subtype of lung cancer and is associated with very high mortality. Emerging studies have shown that N6-methyladenosine (m6A)-related long non-coding (lnc) RNAs play crucial roles in tumor prognosis and the tumor immune microenvironment (TME). We aimed to explore the expression patterns of different m6A-related lncRNAs concerning patient prognosis and construct an m6A-related lncRNA prognostic model for LUAD. Methods: The prognostic value of m6A-related lncRNAs was investigated in LUAD samples from The Cancer Genome Atlas (TCGA). Potential prognostic m6A-related lncRNAs were selected by Pearson's correlation and univariate Cox regression analysis. Patients were divided into clusters using principal component analysis and the m6A-related lncRNA prognostic signature was calculated using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Results: Based on 91 prognostic m6A-related lncRNAs, we identified two m6A-related-lncRNA pattern clusters with different overall survival (OS) and different TMEs. We subsequently verified our findings multidimensionally by constructing a 13 m6A-related lncRNA prognostic signature (m6A-LPS) to calculate the risk score, which was robust in different subgroups. The receiver operating characteristic (ROC) curves and concordance index demonstrated that m6A-LPS harbored a promising ability to predict OS in TCGA data set and independent GSE11969 cohort. The risk score was also related to OS, TME, and clinical stage, and the risk score calculated by our model was also identified as independent prognostic predictive factors for LUAD patients after adjustment for age, smoking, gender, and stage. Enrichment analysis indicated that malignancy and drug resistance-associated pathways were more common in cluster2 (LUAD-unfavorable m6A-LPS). Furthermore, the results indicated that the signaling pathway enriched by the target gene of 13 m6A-related lncRNAs may be associated with metastasis and progression of cancer according to current studies. Conclusion: The current results indicated that different m6A-related-lncRNA patterns could affect OS and TME in patients with LUAD, and the prognostic signature based on 13 m6A-related lncRNAs may help to predict the prognosis in LUAD patients.

Knockdown of METTL14 suppresses the malignant progression of non-small cell lung cancer by reducing Twist expression

Non-small cell lung cancer (NSCLC) is one of the most malignant cancer types. N6-methyladenosine (m6A), an abundant eukaryotic mRNA modification, has been observed in multiple diseases, particularly cancer. Methyltransferase-like 14 (METTL14) is a central component of the m6A methyltransferase complex and has been reported to promote tumor development in several cancer types. The present study aimed to investigate the role of METTL14 in NSCLC. Relevant clinical and mRNA sequencing data for m6A-related genes were downloaded from The Cancer Genome Atlas database. R software was used to evaluate the expression of m6A regulators in NSCLC. The biological functions of METTL14 were evaluated using Cell Counting Kit-8, colony formation, Transwell migration and western blot analyses. The results demonstrated that METTL14 expression was upregulated in NSCLC tissues and cell lines, and its expression was high in cancer tissues from patients with NSCLC with all four stages (I, II, III and IV) of disease. METTL14 downregulation inhibited cell proliferation and migration in A549 and SK-MES-1 lung cancer cell lines. Knockdown of METTL14 in lung cancer cell lines increased E-cadherin expression and suppressed N-cadherin expression. Furthermore, METTL14 downregulation reduced the expression levels of the transcription factor Twist and the p-AKT/AKT ratio. In conclusion, the present findings revealed that silencing of METTL14 suppressed NSCLC malignancy by inhibiting Twist-mediated activation of AKT signaling. These data suggest that METTL14 may be a potential therapeutic target for NSCLC.

RNA Modifications and Epigenetics in Modulation of Lung Cancer and Pulmonary Diseases

Lung cancer is the leading cause of cancer-related mortality worldwide, and its tumorigenesis involves the accumulation of genetic and epigenetic events in the respiratory epithelium. Epigenetic modifications, such as DNA methylation, RNA modification, and histone modifications, have been widely reported to play an important role in lung cancer development and in other pulmonary diseases. Whereas the functionality of DNA and chromatin modifications referred to as epigenetics is widely characterized, various modifications of RNA nucleotides have recently come into prominence as functionally important. N6-methyladosine (m6A) is the most prevalent internal modification in mRNAs, and its machinery of writers, erasers, and readers is well-characterized. However, several other nucleotide modifications of mRNAs and various noncoding RNAs have also been shown to play an important role in the regulation of biological processes and pathology. Such epitranscriptomic modifications play an important role in regulating various aspects of RNA metabolism, including transcription, translation, splicing, and stability. The dysregulation of epitranscriptomic machinery has been implicated in the pathological processes associated with carcinogenesis including uncontrolled cell proliferation, migration, invasion, and epithelial-mesenchymal transition. In recent years, with the advancement of RNA sequencing technology, high-resolution maps of different modifications in various tissues, organs, or disease models are being constantly reported at a dramatic speed. This facilitates further understanding of the relationship between disease development and epitranscriptomics, shedding light on new therapeutic possibilities. In this review, we summarize the basic information on RNA modifications, including m6A, m1A, m5C, m7G, pseudouridine, and A-to-I editing. We then demonstrate their relation to different kinds of lung diseases, especially lung cancer. By comparing the different roles RNA modifications play in the development processes of different diseases, this review may provide some new insights and offer a better understanding of RNA epigenetics and its involvement in pulmonary diseases.

The bioinformatics and experimental analysis of AlkB family for prognosis and immune cell infiltration in hepatocellular carcinoma

Background

Serving as N6-methyladenosine demethylases, the AlkB family is involved in the tumorigenesis of hepatocellular carcinoma (HCC). However, the molecular profiles and clinical values of the AlkB family in HCC are not well known.

Methods

Several bioinformatics tools and in vitro experiments were used to identify the immune-related profiles and prognostic values of AlkB family in HCC.

Results

In this study expression levels of ALKBH1/2/3/4/7 were all remarkably increased in HCC tissues when compared with normal tissues. Quantitative PCR (qPCR) and immunohistochemistry were used to validate the expression of AlkB family members in HCC tissues and normal liver tissues. In addition, high expression levels of ALKBH4 were negatively correlated with overall survival (OS) and disease-free survival (DFS) in patients with HCC. Increased ALKBH4 was also associated with pathological stage in HCC patients. The molecular profiles of AlkB family in HCC were mainly associated with peptidyl-serine modification, peptidyl-tyrosine modification, regulation of metal ion transport, etc. Furthermore, tumor-infiltrating immune cell analysis indicated that ALKBH1/2/3/4/5/6/7/8 and FTO were related to the infiltration of different immune cell, such as CD8+ T cells, macrophages, neutrophils, dendritic cells and CD4+ T cells. We also discovered that the methylation levels of ALKBH1/2/4/5/6/8 and FTO were remarkably reduced in HCC tissues.

Conclusions

Collectively, our findings may deepen the understanding of specific molecular profiles of the AlkB family in HCC pathology. In particular, ALKBH4 could serve as a promising prognostic candidate for treating HCC, and these results might potentiate the development of more reliable therapeutic strategies for patients with HCC.

RNA Methylations in Cardiovascular Diseases, Molecular Structure, Biological Functions and Regulatory Roles in Cardiovascular Diseases

Cardiovascular diseases (CVDs) are the leading cause of morbidity and mortality in the world. Despite considerable progress in the diagnosis, treatment and prognosis of CVDs, new diagnostic biomarkers and new therapeutic measures are urgently needed to reduce the mortality of CVDs and improve the therapeutic effect. RNA methylations regulate almost all aspects of RNA processing, such as RNA nuclear export, translation, splicing and non-coding RNA processing. In view of the importance of RNA methylations in the pathogenesis of diseases, this work reviews the molecular structures, biological functions of five kinds of RNA methylations (m6A, m5C, m1a, m6am and m7G) and their effects on CVDs, including pulmonary hypertension, hypertension, vascular calcification, cardiac hypertrophy, heart failure. In CVDs, m6A “writers” catalyze the installation of m6A on RNAs, while “erasers” remove these modifications. Finally, the “readers” of m6A further influence the mRNA splicing, nuclear export, translation and degradation. M5C, m1A, m6Am and m7G are new types of RNA methylations, their roles in CVDs need to be further explored. RNA methylations have become a new research hotspot and the roles in CVDs is gradually emerging, the review of the molecular characteristics, biological functions and effects of RNA methylation on CVDs will contribute to the elucidation of the pathological mechanisms of CVDs and the discovery of new diagnostic markers and therapeutic targets of CVDs.

N6-methyladenosine-modified circIGF2BP3 inhibits CD8+ T-cell responses to facilitate tumor immune evasion by promoting the deubiquitination of PD-L1 in non-small cell lung cancer

Background

An in-depth understanding of immune evasion mechanisms in tumors is crucial to overcome resistance and enable innovative advances in immunotherapy. Circular RNAs (circRNAs) have been implicated in cancer progression. However, much remains unknown regarding whether circRNAs impact immune escape in non-small-cell lung carcinoma (NSCLC).

Methods

We performed bioinformatics analysis to profile and identify the circRNAs mediating immune evasion in NSCLC. A luciferase reporter assay, RNA immunoprecipitation (RIP), RNA pulldown assays and fluorescence in situ hybridization were performed to identify the interactions among circIGF2BP3, miR-328-3p, miR-3173-5p and plakophilin 3 (PKP3). In vitro T cell-mediated killing assays and in vivo syngeneic mouse models were used to investigate the functional roles of circIGF2BP3 and its downstream target PKP3 in antitumor immunity in NSCLC. The molecular mechanism of PKP3-induced PD-L1 upregulation was explored by immunoprecipitation, RIP, and ubiquitination assays.

Results

We demonstrated that circIGF2BP3 (hsa_circ_0079587) expression was increased in NSCLC and negatively correlated with CD8⁺ T cell infiltration. Functionally, elevated circIGF2BP3 inactivated cocultured T cells in vitro and compromised antitumor immunity in an immunocompetent mouse model, and this effect was dependent on CD8⁺ T cells. Mechanistically, METTL3 mediates the N⁶-methyladenosine (m⁶A) modification of circIGF2BP3 and promotes its circularization in a manner dependent on the m⁶A reader protein YTHDC1. circIGF2BP3 competitively upregulates PKP3 expression by sponging miR-328-3p and miR-3173-5p to compromise the cancer immune response. Furthermore, PKP3 engages with the RNA-binding protein FXR1 to stabilize OTUB1 mRNA, and OTUB1 elevates PD-L1 abundance by facilitating its deubiquitination. Tumor PD-L1 deletion completely blocked the impact of the circIGF2BP3/PKP3 axis on the CD8⁺ T cell response. The inhibition of circIGF2BP3/PKP3 enhanced the treatment efficacy of anti-PD-1 therapy in a Lewis lung carcinoma mouse model. Collectively, the PKP3/PD-L1 signature and the infiltrating CD8⁺ T cell status stratified NSCLC patients into different risk groups.

Conclusion

Our results reveal the function of circIGF2BP3 in causing immune escape from CD8⁺ T cell-mediated killing through a decrease in PD-L1 ubiquitination and subsequent proteasomal degradation by stabilizing OTUB1 mRNA in a PKP3-dependent manner. This work sheds light on a novel mechanism of PD-L1 regulation in NSCLC and provides a rationale to enhance the efficacy of anti-PD-1 treatment in NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12943-021-01398-4.

Importance of N6-methyladenosine RNA modification in lung cancer (Review)

The N6-methyladenosine (m6A) modification is the most common mRNA modification in eukaryotes and exerts biological functions by affecting RNA metabolism. The m6A modification is installed by m6A methyltransferases, removed by demethylases and recognized by m6A-binding proteins. The interaction between these three elements maintains the dynamic equilibrium of m6A in cells. Accumulating evidence indicates that m6A RNA methylation has a significant impact on RNA metabolism and is involved in the pathogenesis of cancer. Lung cancer is the leading cause of cancer-related deaths worldwide. The treatment options for lung cancer have developed considerably over the past few years; however, the survival rate of patients with lung cancer still remains very low. Although diagnostic methods and targeted therapies have been rapidly developed in recent years, the underlying mechanism and importance of m6A RNA methylation in the pathogenesis of lung cancer remains ambiguous. The current review summarized the biological functions of m6A modification and considers the potential roles of m6A regulators in the occurrence and development of lung cancer.

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.

Comprehensive Analysis of the Prognostic Role and Mutational Characteristics of m6A-Related Genes in Lung Squamous Cell Carcinoma

BACKGROUND

There have been limited treatment therapies for lung squamous cell carcinoma (LUSC). M6A-related genes may be the next therapeutic targets for LUSC. In this study, we explored the prognostic role and mutational characteristics of m6A-related genes in LUSC.

METHODS

LUSC gene expression data, mutational data, and corresponding clinical information were extracted from The Cancer Genome Atlas database. Differentially expressed genes (DEGs) were identified, and the mutation characteristics of LUSC patients were explored. Then, m6A-related genes were extracted and the correlations among the genes were detected. Finally, the prognostic roles of the genes were investigated and the nomogram model was developed. Besides, the protein-protein interaction (PPI) network was used to explore the potential interactions among the genes.

RESULTS

In total, there are 551 LUSC samples enrolled in our study, containing 502 LUSC tumor samples and 49 adjacent normal LUSC samples, respectively. There were 2970 upregulated DEGs and 1806 downregulated DEGs were further explored. IGF2BP1 and RBM15 had significant co-occurrence frequency (p < 0.05). Besides, METTL14 and ZC3H13 or YTHDF3 also had significant co-occurrence frequency (p < 0.05). All the m6A-related genes represent the positive correlation. WTAP was identified as a prognostic gene in the TCGA database while YTHDC1 and YTHDF1 were identified as prognostic genes. In multivariate Cox analysis, YTHDF1, age, pN stage, pTNM stage, and smoking were all identified as significant prognostic factors for OS.

CONCLUSION

We investigated the expression patterns and mutational characteristics of LUSC patients and identified three potential independent prognostic m6A-related genes (WTAP, YTHDC1, and YTHDF1) for OS in LUSC patients.

m6A RNA Methylation in Systemic Autoimmune Diseases-A New Target for Epigenetic-Based Therapy?

The general background of autoimmune diseases is a combination of genetic, epigenetic and environmental factors, that lead to defective immune reactions. This erroneous immune cell activation results in an excessive production of autoantibodies and prolonged inflammation. During recent years epigenetic mechanisms have been extensively studied as potential culprits of autoreactivity. Alike DNA and proteins, also RNA molecules are subjected to an extensive repertoire of chemical modifications. N6-methyladenosine is the most prevalent form of internal mRNA modification in eukaryotic cells and attracts increasing attention due to its contribution to human health and disease. Even though m6A is confirmed as an essential player in immune response, little is known about its role in autoimmunity. Only few data have been published up to date in the field of RNA methylome. Moreover, only selected autoimmune diseases have been studied in respect of m6A role in their pathogenesis. In this review, I attempt to present all available research data regarding m6A alterations in autoimmune disorders and appraise its role as a potential target for epigenetic-based therapies.

YTH Domain Proteins: A Family of m6A Readers in Cancer Progression

N⁶-methyladenosine (m⁶A) is the most abundant internal modification in eukaryotic messenger RNAs (mRNAs). m⁶A RNA methylation is involved in all stages of RNA life cycle, from RNA processing, nuclear output, translation regulation to RNA degradation, indicating that m⁶A has various functions affecting RNA metabolism positively or negatively. Reading proteins are vital in regulating the translation and stability of m⁶A mRNAs positively or negatively. Recent studies have enhanced the understanding of the molecular mechanism of the YT521-B homology (YTH) domain family and the modification of m⁶A. This study aimed to review the specific mechanisms, functions, and interactions of the YTH domain protein family. It also discussed future research directions, thus providing new ideas for the clinical diagnosis and targeted therapy of cancer.

N6-Methyladenosine RNA Methylation Regulator-Related Alternative Splicing (AS) Gene Signature Predicts Non-Small Cell Lung Cancer Prognosis

Aberrant N6-methyladenosine (m6A) RNA methylation regulatory genes and related gene alternative splicing (AS) could be used to predict the prognosis of non-small cell lung carcinoma. This study focused on 13 m6A regulatory genes (METTL3, METTL14, WTAP, KIAA1429, RBM15, ZC3H13, YTHDC1, YTHDC2, YTHDF1, YTHDF2, HNRNPC, FTO, and ALKBH5) and expression profiles in TCGA-LUAD (n = 504) and TCGA-LUSC (n = 479) datasets from the Cancer Genome Atlas database. The data were downloaded and bioinformatically and statistically analyzed, including the gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. There were 43,948 mRNA splicing events in lung adenocarcinoma (LUAD) and 46,020 in lung squamous cell carcinoma (LUSC), and the data suggested that m6A regulators could regulate mRNA splicing. Differential HNRNPC and RBM15 expression was associated with overall survival (OS) of LUAD and HNRNPC and METTL3 expression with the OS of LUSC patients. Furthermore, the non-small cell lung cancer prognosis-related AS events signature was constructed and divided patients into high- vs. low-risk groups using seven and 14 AS genes in LUAD and LUSC, respectively. The LUAD risk signature was associated with gender and T, N, and TNM stages, but the LUSC risk signature was not associated with any clinical features. In addition, the risk signature and TNM stage were independent prognostic predictors in LUAD and the risk signature and T stage were independent prognostic predictors in LUSC after the multivariate Cox regression and receiver operating characteristic analyses. In conclusion, this study revealed the AS prognostic signature in the prediction of LUAD and LUSC prognosis.