A new m6A methylation-related gene signature for prognostic value in patient with urothelial carcinoma of the bladder

The identification of a N6-methyladenosin-modifed immune pattern to predict immunotherapy response and survival in urothelial carcinoma

BACKGROUND

Dysregulation of the immune system and N6-methyladenosine (m6A) contribute to immune therapy resistance and cancer progression in urothelial carcinoma (UC). This study aims to identify immune-related molecules, that are m6A-modified, and that are associated with tumor progression, poor prognosis, and immunotherapy response.

METHODS

We identified prognostic immune genes (PIGs) using Cox analysis and random survival forest variable hunting algorithm (RSF-VH) on immune genes retrieved from the Immunology Database and Analysis Portal database (ImmPort). The RM2Target database and MeRIP-seq analysis, combined with a hypergeometric test, assessed m6A methylation in these PIGs. We analyzed the correlation between the immune pattern and prognosis, as well as their association with clinical factors in multiple datasets. Moreover, we explored the interplay between immune patterns, tumor immune cell infiltration, and m6A regulators.

RESULTS

28 PIGs were identified, of which the 10 most significant were termed methylated prognostic immune genes (MPIGs). These MPIGs were used to create an immune pattern score. Kaplan-Meier and Cox analyses indicated this pattern as an independent risk factor for UC. We observed significant associations between the immune pattern, tumor progression, and immune cell infiltration. Differential expression analysis showed correlations with m6A regulators expression. This immune pattern proved effective in predicting immunotherapy response in UC in real-world settings.

CONCLUSION

The study identified a m6A-modified immune pattern in UC, offering prognostic and therapeutic response predictions. This emphasizes that immune genes may influence tumor immune status and progression through m6A modifications.

Multi-omics comprehensive analysis reveals the predictive value of N6-methyladenosine- related genes in prognosis and immune escape of bladder cancer

BACKGROUND

N6-methyladenosine (m6A) is the most frequent RNA modification in mammals, and its role in bladder cancer (BC) remains rarely revealed.

OBJECTIVE

To predict the value of m6A-related genes in prognosis and immunity in BC.

METHODS

We performed multiple omics analysis of 618 TCGA and GEO patients and used principal component analysis (PCA) to calculate the m6A score for BC patients.

RESULTS

We described the multiple omics status of 23 m6A methylation-related genes (MRGs), and four m6A clusters were identified, which showed significant differences in immune infiltration and biological pathways. Next, we intersected the differential genes among m6A clusters, and 11 survival-related genes were identified, which were used to calculate the m6A score for the patients. We found that the high-score (HS) group showed lower tumor mutation burden (TMB) and TP53 mutations and better prognosis than the low-score (LS) group. Lower immune infiltration, higher expression of PD-L1, PD-1, and CTLA4, and higher immune dysfunction and immune exclusion scores were identified in the LS group, suggesting a higher possibility of immune escape. Finally, the experimental verification shows that the m6A related genes, such as IGFBP1, plays an important role in the growth and metastasis of bladder cancer.

CONCLUSIONS

These findings revealed the important roles of m6A MRGs in predicting prognosis, TMB status, TP53 mutation, immune functions and immunotherapeutic response in BC.

The epitranscriptome of high-grade gliomas: a promising therapeutic target with implications from the tumor microenvironment to endogenous retroviruses

Glioblastoma (GBM) comprises 45.6% of all primary malignant brain cancers and is one of the most common and aggressive intracranial tumors in adults. Intratumoral heterogeneity with a wide range of proteomic, genetic, and epigenetic dysregulation contributes to treatment resistance and poor prognosis, thus demanding novel therapeutic approaches. To date, numerous clinical trials have been developed to target the proteome and epigenome of high-grade gliomas with promising results. However, studying RNA modifications, or RNA epitranscriptomics, is a new frontier within neuro-oncology. RNA epitranscriptomics was discovered in the 1970s, but in the last decade, the extent of modification of mRNA and various non-coding RNAs has emerged and been implicated in transposable element activation and many other oncogenic processes within the tumor microenvironment. This review provides background information and discusses the therapeutic potential of agents modulating epitranscriptomics in high-grade gliomas. A particular emphasis will be placed on how combination therapies that include immune agents targeting hERV-mediated viral mimicry could improve the treatment of GBM.

METTL16 in human diseases: What should we do next?

METTL16 is a class-I methyltransferase that is responsible for depositing a vertebrate-conserved S-adenosylmethionine site. Since 2017, there has been a growing body of research focused on METTL16, particularly in the field of structural studies. However, the role of METTL16 in cell biogenesis and human diseases has not been extensively studied, with limited understanding of its function in disease pathology. Recent studies have highlighted the complex and sometimes contradictory role that METTL16 plays in various diseases. In this work, we aim to provide a comprehensive summary of the current research on METTL16 in human diseases.

Reinvestigating the clinical relevance of the m6A writer METTL3 in urothelial carcinoma of the bladder

METTL3 is the major writer of N6-Methyladenosine (m6A) and has been associated with controversial roles in cancer. This is best illustrated in urothelial carcinoma of the bladder (UCB), where METTL3 was described to have both oncogenic and tumor-suppressive functions. Here, we reinvestigated the role of METTL3 in UCB. METTL3 knockout reduced the oncogenic phenotype and m6A levels of UCB cell lines. However, complete depletion of METTL3/m6A was not achieved due to selection of cells expressing alternative METTL3 isoforms. Systematic vulnerability and inhibitor response analyses suggested that uroepithelial cells depend on METTL3 for viability. Furthermore, expression and survival analyses of clinical data revealed a complex role for METTL3 in UCB, with decreased m6A mRNA levels in UCB tumors. Our results suggest that METTL3 expression may be a suitable diagnostic UCB biomarker, as the enzyme promotes UCB formation. However, the suitability of the enzyme as a therapeutic target should be evaluated carefully.

RNA Methyltransferase METTL16's Protein Domains Have Differential Functional Effects on Cell Processes

METTL16, a human m6A RNA methyltransferase, is currently known for its modification of U6 and MAT2A RNAs. Several studies have identified additional RNAs to which METTL16 binds, however whether METTL16 modifies these RNAs is still in question. Moreover, a recent study determined that METTL16 contains more than one RNA-binding domain, leaving the importance of each individual RNA-binding domain unknown. Here we examined the effects of mutating the METTL16 protein in certain domains on overall cell processes. We chose to mutate the N-terminal RNA-binding domain, the methyltransferase domain, and the C-terminal RNA-binding domain. With these mutants, we identified changes in RNA-binding ability, protein and RNA expression, cell cycle phase occupancy, and proliferation. From the resulting changes in RNA and protein expression, we saw effects on cell cycle, metabolism, intracellular transport, and RNA processing pathways, which varied between the METTL16 mutant lines. We also saw significant effects on the G1 and S phase occupancy times and proliferative ability with some but not all the mutants. We have therefore concluded that while METTL16 may or may not m6A-modify all RNAs it binds, its binding (or lack of) has a significant outcome on a variety of cell processes.

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.

Construction of cuproptosis-related gene signature to predict the prognosis and immunotherapy efficacy of patients with bladder cancer through bioinformatics analysis and experimental validation

Background: A new form of cell death, copper-dependent cell death (termed cuproptosis), was illustrated in a recent scientific study. However, the biological function or prognostic value of cuproptosis regulators in bladder cancer (BLCA) remains unknown. Materials and Methods: Sequencing data obtained from BLCA samples in TCGA and GEO databases were preprocessed for analysis. Biological function and immune cell infiltration levels evaluated by gene set variation analysis (GSVA) were employed to calculate enrichment scores. Iteration least absolute shrinkage and selection operator (LASSO) and COX regression model were employed to select feature genes and construct a novel cuproptosis-related (CR) score signature. The genomics of drug sensitivity in cancer (GDSC) and tumor immune dysfunction and exclusion (TIDE) analysis were used to predict the chemotherapy and immunotherapy efficacy for BLCA patients. The relative expression of the genes involved in the signature was also verified by real-time quantitative PCR (qRT-PCR) in cell lines and tissues. Results: Expression abundance and the prognostic value of cuproptosis regulators proved that cuproptosis might play a vital part in the carcinogenesis of BLCA. GSVA revealed that cuproptosis regulators might be associated with metabolism and metastasis-related pathways such as TGF-β, protein secretion, oxidative Phosphorylation, MYC targets, MTORC1, and adipogenesis pathways. CR scores could predict the prognosis and evaluate the chemotherapy and immunotherapy efficacies of BLCA. CR scores were positively correlated with EMT, MYC, MTORC1, HEDGEHOG, and E2F signaling pathways; meanwhile, they were negatively correlated with several immune cell infiltration levels such as CD8+ T cells, γδT cells, and activated dendritic cells. Several GEO datasets were used to validate the power of prognostic prediction, and a nomogram was also established for clinical use. The expressions of DDX10, RBM34, and RPL17 were significantly higher in BLCA cell lines and tissues in comparison with those in the corresponding normal controls. Conclusion: Cuproptosis might play an essential role in the progression of BLCA. CR scores could be helpful in the investigation of prognostic prediction and therapeutic efficacy and could make contributions to further studies in BLCA.

YT521-B homology domain family proteins as N6-methyladenosine readers in tumors

N6-methyladenosine (m6A) is the most abundant internal chemical modification of eukaryotic mRNA and plays diverse roles in gene regulation. The m6A modification plays a significant role in numerous cancer types, including kidney, stomach, lung, bladder tumors, and melanoma, through varied mechanisms. As direct m6A readers, the YT521-B homology domain family proteins (YTHDFs) play a key role in tumor transcription, translation, protein synthesis, tumor stemness, epithelial-mesenchymal transition (EMT), immune escape, and chemotherapy resistance. An in-depth understanding of the molecular mechanism of YTHDFs is expected to provide new strategies for tumor treatment. In this review, we provide a systematic description of YTHDF protein structure and its function in tumor progression.

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

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

An analysis of the role of HnRNP C dysregulation in cancers

Heterogeneous nuclear ribonucleoproteins C (HnRNP C) is part of the hnRNP family of RNA-binding proteins. The relationship between hnRNP C and cancers has been extensively studied, and dysregulation of hnRNP C has been found in many cancers. According to existing public data, hnRNP C could promote the maturation of new heterogeneous nuclear RNAs (hnRNA s, also referred to as pre-mRNAs) into mRNAs and could stabilize mRNAs, controlling their translation. This paper reviews the regulation and dysregulation of hnRNP C in cancers. It interacts with some cancer genes and other biological molecules, such as microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and double-stranded RNAs (dsRNAs). Even directly binds to them. The effects of hnRNP C on biological processes such as alternative cleavage and polyadenylation (APA) and N6-methyladenosine (m6A) modification differ among cancers. Its main function is regulating stability and level of translation of cancer genes, and the hnRNP C is regarded as a candidate biomarker and might be valuable for prognosis evaluation.

Identification and Validation of the Pyroptosis-Related Molecular Subtypes of Lung Adenocarcinoma by Bioinformatics and Machine Learning

Lung cancer remains the leading cause of cancer death globally, with lung adenocarcinoma (LUAD) being its most prevalent subtype. Due to the heterogeneity of LUAD, patients given the same treatment regimen may have different responses and clinical outcomes. Therefore, identifying new subtypes of LUAD is important for predicting prognosis and providing personalized treatment for patients. Pyroptosis-related genes play an essential role in anticancer, but there is limited research investigating pyroptosis in LUAD. In this study, 33 pyroptosis gene expression profiles and clinical information were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. By bioinformatics and machine learning analyses, we identified novel subtypes of LUAD based on 10 pyroptosis-related genes and further validated them in the GEO dataset, with machine learning models performing up to an AUC of 1 for classifying in GEO. A web-based tool was established for clinicians to use our clustering model (http://www.aimedicallab.com/tool/aiml-subphe-luad.html). LUAD patients were clustered into 3 subtypes (A, B, and C), and survival analysis showed that B had the best survival outcome and C had the worst survival outcome. The relationships between pyroptosis gene expression and clinical characteristics were further analyzed in the three molecular subtypes. Immune profiling revealed significant differences in immune cell infiltration among the three molecular subtypes. GO enrichment and KEGG pathway analyses were performed based on the differential genes of the three subtypes, indicating that differentially expressed genes (DEGs) were involved in multiple cellular and biological functions, including RNA catabolic process, mRNA catabolic process, and pathways of neurodegeneration-multiple diseases. Finally, we developed an 8-gene prognostic model that accurately predicted 1-, 3-, and 5-year overall survival. In conclusion, pyroptosis-related genes may play a critical role in LUAD, and provide new insights into the underlying mechanisms of LUAD.

Scoring System Based on RNA Modification Writer-Related Genes to Predict Overall Survival and Therapeutic Response in Bladder Cancer

Introduction

It’s widely reported the “writer” enzymes mediated RNA adenosine modifications which is known as a crucial mechanism of epigenetic regulation in development of tumor and the immunologic response in many kinds of cancers. However, the potential roles of these writer genes in the progression of bladder cancer (BLCA) remain unclear.

Materials and Methods

We comprehensively described the alterations of 26 RNA modification writer genes in BLCA from the genetic and transcriptional fields and identified writer-related genes from four independent datasets. Utilizing least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression, we constructed a ten writer-related gene signature. After that, we confirmed the predictive and prognostic value of this signature on another six independent datasets and established a nomogram to forecast the overall survival (OS) and mortality odds of BLCA patients clinically.

Results

The writer-related genes signature showed good performance in predicting the OS for BLCA patients. Moreover, the writer-related gene signature was related to EMT-related pathways and immune characteristics. Furthermore, the immune cell infiltration levels of CD8 T cells, cytotoxic cells, M1/2 macrophage cells and tumor mutation burden might be able to predict which patients will benefit from immunotherapy. This could also be reflected by the writer-related gene signature.

Conclusions

This signature might play an important role in precision individualized immunotherapy. The present work highlights the crucial clinical implications of RNA modifications and may help developing individualized therapeutic strategies for patients with BLCA.