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

m6A regulator-based molecular classification and hub genes associated with immune infiltration characteristics and clinical outcomes in diffuse gliomas

BACKGROUND

m6A methylation modification is a new regulatory mechanism involved in tumorigenesis and tumor-immunity interaction. However, its impact on glioma immune microenvironment and clinical outcomes remains unclear.

METHODS

Comprehensive expression profiles of 18 m6A regulators were used to identify molecular subtypes exhibiting distinct m6A modification patterns in 1673 glioma samples sourced from public datasets. A multi-genes signature was constructed for predicting clinical outcomes and response to immunotherapy in glioma patients. Immunohistochemistry and cellular experiments were performed for validation.

RESULTS

Two m6A subtypes of gliomas were identified. The m6A-low-risk subtype was characterized by paucity of immune infiltrates; While the m6A-high-risk subtype had higher abundances of multiple immune cells including lymphocyte and macrophage as well as increased expression of PD-L1, corresponding to an immunosuppressive phenotype. The m6A-high-risk subtype had poorer survival than the m6A-low-risk subtype in both the glioblastoma and lower grade gliomas cohorts. Eight m6A-related hub genes of high prognostic significances were identified and selected for developing a scoring signature termed as m6Ascore. Elevated m6Ascore indicated worse survival for glioma patients under standard care, but showed enhanced response to immunotherapy. Moreover, we demonstrated that overexpression of FTO, a m6A demethylase, inhibited the expressions of m6A-related hub genes (PTX3, SPAG4), impaired glioma cell viability and reduced macrophage chemotaxis.

CONCLUSION

This work develops an immune- and clinical-relevant m6A subtyping and a scoring model, which enhances our understanding of the role of m6A modification in regulating immune infiltration microenvironment in gliomas and helps to identify patients who are more likely to benefit from immunotherapy.

Epitranscriptomics in the Glioma Context: A Brief Overview

Epitranscriptomics, the study of chemical modifications in RNA, has emerged as a crucial field in cellular regulation, adding another layer to the established landscape of DNA- and histone-based epigenetics. A wide range of RNA modifications, including N6-methyladenosine, pseudouridine, and inosine, have been identified across nearly all RNA species, influencing essential processes such as transcription, splicing, RNA stability, and translation. In the context of brain tumors, particularly gliomas, specific epitranscriptomic signatures have been reported to play a role in tumorigenesis. Despite growing evidence, the biological implications of various RNA modifications remain poorly understood. This review offers an examination of the main RNA modifications, the interplay between modified and unmodified molecules, how they could contribute to glioma-like phenotypes, and the therapeutic impact of targeting these mechanisms.

Prognostic significance and identification of m6A regulator genes and hub genes associated with m6A in breast cancer

This research endeavors to investigate the functions of N6-methyladenosine (m6A) regulatory genes and key genes linked to m6A modifications within the context of breast cancer (BC). The objective is to identify a promising predictive biomarker related to m6A modifications and validate its significance in BC through experimental methodologies. Utilizing data from The Cancer Genome Atlas (TCGA) database, a model for predicting prognosis was developed. Key genes connected to m6A modifications were discerned using weighted gene co-expression network analysis (WGCNA) coupled with LASSO and Cox regression analyses, which were then utilized to construct a predictive model. The influence of ZNF260 within BC was probed experimentally. The predictive model formulated using m6A regulatory genes and key m6A-associated genes demonstrated the capability to categorize BC patients into distinct risk groups effectively (all P < 0.001). Clinical sample analyses revealed notably elevated expression levels of ZNF260 in hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR + /HER2-) BC tissues compared to adjacent non-tumor tissues (all P < 0.001). Reduction in ZNF260 expression was shown to inhibit the proliferation, clonogenicity, migration, and invasiveness of MCF-7 cells while concomitantly enhancing apoptosis (all P < 0.001).This investigation uniquely uncovered ZNF260 as a novel key gene, suggesting its potential utility as a predictive biomarker associated with m6A modifications specifically in HR + /HER2- BC.

Multi-scale brain attributes contribute to the distribution of diffuse glioma subtypes

Gliomas are primary brain tumors and are among the most malignant types. Adult-type diffuse gliomas can be classified based on their histological and molecular signatures as IDH-wildtype glioblastoma, IDH-mutant astrocytoma, and IDH-mutant and 1p/19q-codeleted oligodendroglioma. Recent studies have shown that each subtype of glioma has its own specific distribution pattern. However, the mechanisms underlying the specific distributions of glioma subtypes are not entirely clear despite partial explanations such as cell origin. To investigate the impact of multi-scale brain attributes on glioma distribution, we constructed cumulative frequency maps for diffuse glioma subtypes based on T1w structural images and evaluated the spatial correlation between tumor frequency and diverse brain attributes, including postmortem gene expression, functional connectivity metrics, cerebral perfusion, glucose metabolism, and neurotransmitter signaling. Regression models were constructed to evaluate the contribution of these factors to the anatomic distribution of different glioma subtypes. Our findings revealed that the three different subtypes of gliomas had distinct distribution patterns, showing spatial preferences toward different brain environmental attributes. Glioblastomas were especially likely to occur in regions enriched with synapse-related pathways and diverse neurotransmitter receptors. Astrocytomas and oligodendrogliomas preferentially occurred in areas enriched with genes associated with neutrophil-mediated immune responses. The functional network characteristics and neurotransmitter distribution also contributed to oligodendroglioma distribution. Our results suggest that different brain transcriptomic, neurotransmitter, and connectomic attributes are the factors that determine the specific distributions of glioma subtypes. These findings highlight the importance of bridging diverse scales of biological organization when studying neurological dysfunction.

Identification and Validation of an Invasion-Related Disease-Free Survival Prognostic Model for Tongue Squamous Cell Carcinoma

INTRODUCTION

Tongue squamous cell carcinoma (TSCC) is a common malignant tumour type with aggressive invasion and a poor prognosis. To date, invasion-related gene expression signatures for the prognostic stratification of TSCC patients are unavailable in clinical practice. This study aimed to assess the impact of invasion-related genes on the prognosis of TSCC patients.

METHODS

We obtained mRNA profiles and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases (TCGA-TSCC and GSE41116, respectively). The TSCC samples from the TCGA-TSCC cohort were randomly divided into TCGA training and TCGA test datasets at a 7:3 ratio. Next, a disease-free survival (DFS) prognostic risk model was established on the basis of univariate and stepwise multivariate Cox regression analyses of the TCGA training cohort. Moreover, prognostic genes were screened. The model was subsequently evaluated and validated using the TCGA test and GSE41116 datasets. In addition, the prognostic genes were validated in the human TSCC cell line UM1 and the human oral keratinocyte (HOK) cell line using quantitative real-time polymerase chain reaction (qRT-PCR) analysis.

RESULTS

A total of 70 candidate genes related to invasion were identified in the TCGA-TSCC cohort. DFS data were subsequently constructed, and 6 prognostic genes, HMGN2, MYL12B, ACTB, PPP1CA, PSMB9, and IFITM3, were identified. The TSCC samples were divided into high- and low-risk groups in the TCGA training, TCGA test, and GSE41116 cohorts, respectively. In particular, patients with TSCC in the low-risk group had longer DFS than those in the high-risk group. Furthermore, qRT-PCR analysis confirmed that the expression levels of the 6 prognostic genes were significantly greater in the TSCC cell line UM1 than in the HOK cell line.

CONCLUSION

This study identified new invasion-related target genes related to poor prognosis in TSCC patients, providing new insights into the underlying mechanisms of TSCC invasion.

Inhibitory neuron links the causal relationship from air pollution to psychiatric disorders: a large multi-omics analysis

Psychiatric disorders are severe health challenges that exert a heavy public burden. Air pollution has been widely reported as related to psychiatric disorder risk, but their casual association and pathological mechanism remained unclear. Herein, we systematically investigated the large genome-wide association studies (6 cohorts with 1,357,645 samples), single-cell RNA (26 samples with 157,488 cells), and bulk-RNAseq (1595 samples) datasets to reveal the genetic causality and biological link between four air pollutants and nine psychiatric disorders. As a result, we identified ten positive genetic correlations between air pollution and psychiatric disorders. Besides, PM2.5 and NO2 presented significant causal effects on schizophrenia risk which was robust with adjustment of potential confounders. Besides, transcriptome-wide association studies identified the shared genes between PM2.5/NO2 and schizophrenia. We then discovered a schizophrenia-derived inhibitory neuron subtype with highly expressed shared genes and abnormal synaptic and metabolic pathways by scRNA analyses and confirmed their abnormal level and correlations with the shared genes in schizophrenia patients in a large RNA-seq cohort. Comprehensively, we discovered robust genetic causality between PM2.5, NO2, and schizophrenia and identified an abnormal inhibitory neuron subtype that links schizophrenia pathology and PM2.5/NO2 exposure. These discoveries highlight the schizophrenia risk under air pollutants exposure and provide novel mechanical insights into schizophrenia pathology, contributing to pollutant-related schizophrenia risk control and therapeutic strategies development.

Graphical Abstract

The Role of m6A Methylation in Tumor Immunity and Immune-Associated Disorder

N6-methyladenosine (m6A) represents the most prevalent and significant internal modification in mRNA, with its critical role in gene expression regulation and cell fate determination increasingly recognized in recent research. The immune system, essential for defense against infections and maintaining internal stability through interactions with other bodily systems, is significantly influenced by m6A modification. This modification acts as a key post-transcriptional regulator of immune responses, though its effects on different immune cells vary across diseases. This review delineates the impact of m6A modification across major system-related cancers-including those of the respiratory, digestive, endocrine, nervous, urinary reproductive, musculoskeletal system malignancies, as well as acute myeloid leukemia and autoimmune diseases. We explore the pathogenic roles of m6A RNA modifications within the tumor immune microenvironment and the broader immune system, highlighting how RNA modification regulators interact with immune pathways during disease progression. Furthermore, we discuss how the expression patterns of these regulators can influence disease susceptibility to immunotherapy, facilitating the development of diagnostic and prognostic models and pioneering new therapeutic approaches. Overall, this review emphasizes the challenges and prospective directions of m6A-related immune regulation in various systemic diseases throughout the body.

Biosensor-Enhanced Organ-on-a-Chip Models for Investigating Glioblastoma Tumor Microenvironment Dynamics

Glioblastoma, an aggressive primary brain tumor, poses a significant challenge owing to its dynamic and intricate tumor microenvironment. This review investigates the innovative integration of biosensor-enhanced organ-on-a-chip (OOC) models as a novel strategy for an in-depth exploration of glioblastoma tumor microenvironment dynamics. In recent years, the transformative approach of incorporating biosensors into OOC platforms has enabled real-time monitoring and analysis of cellular behaviors within a controlled microenvironment. Conventional in vitro and in vivo models exhibit inherent limitations in accurately replicating the complex nature of glioblastoma progression. This review addresses the existing research gap by pioneering the integration of biosensor-enhanced OOC models, providing a comprehensive platform for investigating glioblastoma tumor microenvironment dynamics. The applications of this combined approach in studying glioblastoma dynamics are critically scrutinized, emphasizing its potential to bridge the gap between simplistic models and the intricate in vivo conditions. Furthermore, the article discusses the implications of biosensor-enhanced OOC models in elucidating the dynamic features of the tumor microenvironment, encompassing cell migration, proliferation, and interactions. By furnishing real-time insights, these models significantly contribute to unraveling the complex biology of glioblastoma, thereby influencing the development of more accurate diagnostic and therapeutic strategies.

The levels of immunosuppressive checkpoint protein PD-L1 and tumor-infiltrating lymphocytes were integrated to reveal the glioma tumor microenvironment

In spite of significant strides in the realm of cancer biology and therapeutic interventions, the clinical prognosis for patients afflicted with glioblastoma (GBM) remains distressingly dismal. The tumor immune microenvironment (TIME), a crucial player in the progression, treatment response, and prognostic trajectory of glioma, warrants thorough exploration. Within this intricate microcosm, the immunosuppressive checkpoint protein PD-L1 and tumor-infiltrating lymphocytes (TILs) emerge as pivotal constituents, underscoring their potential role in deciphering glioma biology and informing treatment strategies. However, prognostic models based on the association between PD-L1 expression and TIL infiltration in the tumor immune microenvironment have not been established. The aim of this study was to explore TIME genes associated with PD-L1 expression and TIL invasion and to construct a risk score for predicting the overall survival (OS) of GBM patients based on these genes. The samples were separately classified according to the PD-L1 expression level and TIL score and TIME-related genes were identified using differential expression and weighted gene co-expression network analysis. The DEGs were subjected to least absolute contraction and selection operator (LASSO) -Cox regression to construct TIME associated risk score (TIMErisk). A TIMErisk was developed based on STEAP3 and CXCL13 genes. The STLEAP3 was demonstrated to be involved in glioma progression. The results showed that the patients in the high TIMErisk group had poor OS compared with subjects in the low TIMErisk group. The biological phenotypes associated with TIMErisk were analyzed in terms of functional enrichment, tumor immune profile, and tumor mutation profile. The results on tumor immune dysfunction and exclusion dysfunction (TIDE) score and immune surface score (IPS) showed that GBM patients with different TIME risks had different responses to immunotherapy. Tumor purity analysis indicated that PD-L1 and TIL scores were positively correlated with TIMErisk score and negatively correlated with tumor purity. These results show that the TIMErisk-based prognostic model had high predictive value for the prognosis and immune characteristics of GBM patients. Immunohistochemical staining images of patients in the high and low TIMErisk groups were analyzed, showing that the degree of immune cell infiltration was higher in the high TIMErisk group relative to the low TIMErisk group. The present study provides a basis for understanding glioma tumor microenvironment and a foundation for conducting comprehensive immunogenomic analysis.

A bibliometric analysis of m6A methylation in viral infection from 2000 to 2022

BACKGROUND

N6-methyladenosine (m6A) methylation has become an active research area in viral infection, while little bibliometric analysis has been performed. In this study, we aim to visualize hotspots and trends using bibliometric analysis to provide a comprehensive and objective overview of the current research dynamics in this field.

METHODS

The data related to m6A methylation in viral infection were obtained through the Web of Science Core Collection form 2000 to 2022. To reduce bias, the literature search was conducted on December 1, 2022. Bibliometric and visual analyzes were performed using CiteSpace and Bibliometrix package. After screening, 319 qualified records were retrieved.

RESULTS

These publications mainly came from 28 countries led by China and the United States (the US), with the US ranking highest in terms of total link strength.The most common keywords were m6A, COVID-19, epitranscriptomics, METTL3, hepatitis B virus, innate immunity and human immunodeficiency virus 1. The thematic map showed that METTL3, plant viruses, cancer progression and type I interferon (IFN-I) reflected a good development trend and might become a research hotspot in the future, while post-transcriptional modification, as an emerging or declining theme, might not develop well.

CONCLUSIONS

In conclusion, m6A methylation in viral infection is an increasingly important topic in articles. METTL3, plant viruses, cancer progression and IFN-I may still be research hotspots and trends in the future.

Advances in Diagnostic Tools and Therapeutic Approaches for Gliomas: A Comprehensive Review

Gliomas, a prevalent category of primary malignant brain tumors, pose formidable clinical challenges due to their invasive nature and limited treatment options. The current therapeutic landscape for gliomas is constrained by a "one-size-fits-all" paradigm, significantly restricting treatment efficacy. Despite the implementation of multimodal therapeutic strategies, survival rates remain disheartening. The conventional treatment approach, involving surgical resection, radiation, and chemotherapy, grapples with substantial limitations, particularly in addressing the invasive nature of gliomas. Conventional diagnostic tools, including computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), play pivotal roles in outlining tumor characteristics. However, they face limitations, such as poor biological specificity and challenges in distinguishing active tumor regions. The ongoing development of diagnostic tools and therapeutic approaches represents a multifaceted and promising frontier in the battle against this challenging brain tumor. The aim of this comprehensive review is to address recent advances in diagnostic tools and therapeutic approaches for gliomas. These innovations aim to minimize invasiveness while enabling the precise, multimodal targeting of localized gliomas. Researchers are actively developing new diagnostic tools, such as colorimetric techniques, electrochemical biosensors, optical coherence tomography, reflectometric interference spectroscopy, surface-enhanced Raman spectroscopy, and optical biosensors. These tools aim to regulate tumor progression and develop precise treatment methods for gliomas. Recent technological advancements, coupled with bioelectronic sensors, open avenues for new therapeutic modalities, minimizing invasiveness and enabling multimodal targeting with unprecedented precision. The next generation of multimodal therapeutic strategies holds potential for precision medicine, aiding the early detection and effective management of solid brain tumors. These innovations offer promise in adopting precision medicine methodologies, enabling early disease detection, and improving solid brain tumor management. This review comprehensively recognizes the critical role of pioneering therapeutic interventions, holding significant potential to revolutionize brain tumor therapeutics.

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.

Link between m6A modification and infiltration characterization of tumor microenvironment in lung adenocarcinoma

N6-methyladenosine (m6A) RNA methylation plays a pivotal role in immune responses and the onset and advancement of cancer. Nonetheless, the precise impact of m6A modification in lung adenocarcinoma (LUAD) and its associated tumor microenvironment (TME) remains to be fully elucidated. Here, we distinguished distinct m6A modification patterns within two separate LUAD cohorts using a set of 21 m6A regulators. The TME characteristics associated with these two patterns align with the immune-inflamed and immune-excluded phenotypes, respectively. We identified 2064 m6A-related genes, which were used as a basis to divide all LUAD samples into three distinct m6A gene clusters. We applied a scoring system to evaluate the m6A gene signature of the m6A modification pattern in individual patients. To authenticate the categorization significance of m6A modification patterns, we established a correlation between m6A score and TME infiltration profiling, tumor somatic mutations, and responses to immunotherapy. A high level of m6A modification may be associated with the aggressiveness and poor prognosis of LUAD. Further studies should investigate the mechanism of action of m6A regulators and m6A-related genes to improve the diagnosis and treatment of patients with LUAD.

Recent advances in drug delivery systems for targeting brain tumors

Brain tumor accounts for about 1.6% of incidence and 2.5% of mortality of all tumors, and the median survival for brain tumor patients is only about 20 months. The treatment for brain tumor still faces many challenges, such as the blood-brain barrier (BBB), blood-brain tumor barrier (BBTB), the overexpressed efflux pumps, the infiltration, invasion, high heterogeneity of tumor cells, drug resistance and immune escape caused by tumor microenvironment (TME) and cancer stem cells (CSC). This review attempts to clarify the challenges for multi-functional nano drug delivery systems (NDDS) to cross the BBB and target the cancer cells or organelles, and also provides a brief description of the different types of targeted multi-functional NDDS that have shown potential for success in delivering drugs to the brain. Further, this review also summarizes the research progress of multi-functional NDDS in the combination therapy of brain tumors from the following sections, the combination of chemotherapy drugs, chemotherapy-chemodynamic combination therapy, chemotherapy-immunization combination therapy, and chemotherapy-gene combination therapy. We also provide an insight into the recent advances in designing multi-functional NDDS for combination therapy.

Systematic integration of m6A regulators and autophagy-related genes in combination with long non-coding RNAs predicts survival in glioblastoma multiforme

Glioblastoma multiforme (GBM) is probably the only tumor in which a unique epigenetic alteration, namely methylation of the MGMT gene, possesses direct clinical relevance. Now with the emergence of aberrant N6 methyladenosine (m6A) modifications (the most common epigenetic modification of mRNA, closely linked to the autophagy process) in cancer, the epi-transcriptomic landscape of GBM pathobiology has been expanded. Considering this, herein, we systematically analyzed m6A regulators, assessed their correlation with autophagy-related genes (ATG), and established a long non-coding RNAs (lncRNA)-dependent prognostic signature (m6A-autophagy-lncRNAs) for GBM. Our analysis identified a novel signature of five long non-coding RNAs (lncRNAs: ITGA6-AS1, AC124248.1, NFYC-AS1, AC025171.1, and AC005229.3) associated with survival of GBM patients, and four among them clearly showed cancer-associated potential. We further validated and confirmed the altered expression of two lncRNAs (AC124248.1, AC005229.3) in GBM associated clinical samples using RT-PCR. Concerning the prognostic ability, the obtained signature determined high-/low-risk groups in GBM patients and showed sensitivity to anticancer drugs. Collectively, the m6A-autophagy-lncRNAs signature presented in the study is clinically relevant and is the first attempt to systematically predict the potential interaction between the three key determinants (m6A, autophagy, lncRNA) in cancer, particularly in GBM.

A risk prognostic model for patients with esophageal squamous cell carcinoma basing on cuproptosis and ferroptosis

BACKGROUND

Cuproptosis, a form of copper-dependent programmed cell death recently presented by Tsvetkov et al., have been identified as a potential therapeutic target for refractory cancers and ferroptosis, a well-known form describing iron-dependent cell death. However, whether the crossing of cuproptosis-related genes and ferroptosis-related genes can introduce some new idea, thus being used as a novel clinical and therapeutic predictor in esophageal squamous cell carcinoma (ESCC) remains unknown.

METHODS

We collected ESCC patient data from the Gene Expression Omnibus and the Cancer Genome Atlas databases and used Gene Set Variation Analysis to score each sample based on cuproptosis and ferroptosis. We then performed weighted gene co-expression network analysis to identify cuproptosis and ferroptosis-related genes (CFRGs) and construct a ferroptosis and cuproptosis-related risk prognostic model, which we validated using a test group. We also investigated the relationship between the risk score and other molecular features, such as signaling pathways, immune infiltration, and mutation status.

RESULTS

Four CFRGs (MIDN, C15orf65, COMTD1 and RAP2B) were identified to construct our risk prognostic model. Patients were classified into low- and high-risk groups based on our risk prognostic model and the low-risk group showed significantly higher survival possibilities (P < 0.001). We used the "GO", "cibersort" and "ESTIMATE" methods to the above-mentioned genes to estimate the relationship among the risk score, correlated pathways, immune infiltration, and tumor purity.

CONCLUSION

We constructed a prognostic model using four CFRGs and demonstrated its potential clinical and therapeutic guidance value for ESCC patients.

Comprehensive analysis of m6A regulators and relationship with tumor microenvironment, immunotherapy strategies in colorectal adenocarcinoma

BACKGROUND

The N6-methyladenosine (m6A) RNA modification is the most prevalent and abundant type found in eukaryotic cells. It plays a crucial role in the initiation and progression of cancers. In this study, we aimed to comprehensively investigate the landscape of m6A regulators and their association with tumor microenvironment (TME), immunotherapeutic strategies in colon adenocarcinoma (COAD).

RESULTS

The differential expression, mutation, CNV frequency and prognostic value of 27 m6A regulators were systematically analyzed in COAD. Patients were classified into two clusters based on m6A regulators through consistent clustering analysis, with cluster A showing significant survival benefits. Most of the m6A regulators were negatively correlated with immune cells, except for WTAP, IGF2BP3, FTO, ALKBH5, which showed a positive correlation. We developed an m6A scoring system to calculate the m6Ascore for each patient. Patients with a high-m6Ascore had a better outcome, with the AUC of 0.775. An independent cohort of 416 COAD patients acquired from GSE38832 database was used to validate the prognosis prediction ability of m6Ascore. Moreover, the m6Ascore was negatively correlated with infiltration of anti-tumor immune cells. Additionally, patients with a high-m6Ascore responded better to anti-PD1 and anti-CTLA4 therapies, and those with MSI-H had a higher m6Ascore. Finally, we investigated the value of m6Ascore in predicting the response of patients to 15 commonly used drugs.

CONCLUSIONS

We comprehensively analyzed m6A regulators in COAD, including RNA expression, CNV changes, mutations and their correlation with TME. Our results showed that the m6A scoring system had significant predictive power for the prognosis of COAD patients, potentially leading to new personalized immunotherapy strategies.

The roles and implications of RNA m6A modification in cancer

N6-Methyladenosine (m6A), the most prevalent internal modification in eukaryotic mRNA, has been extensively and increasingly studied over the past decade. Dysregulation of RNA m6A modification and its associated machinery, including writers, erasers and readers, is frequently observed in various cancer types, and the dysregulation profiles might serve as diagnostic, prognostic and/or predictive biomarkers. Dysregulated m6A modifiers have been shown to function as oncoproteins or tumour suppressors with essential roles in cancer initiation, progression, metastasis, metabolism, therapy resistance and immune evasion as well as in cancer stem cell self-renewal and the tumour microenvironment, highlighting the therapeutic potential of targeting the dysregulated m6A machinery for cancer treatment. In this Review, we discuss the mechanisms by which m6A modifiers determine the fate of target RNAs and thereby influence protein expression, molecular pathways and cell phenotypes. We also describe the state-of-the-art methodologies for mapping global m6A epitranscriptomes in cancer. We further summarize discoveries regarding the dysregulation of m6A modifiers and modifications in cancer, their pathological roles, and the underlying molecular mechanisms. Finally, we discuss m6A-related prognostic and predictive molecular biomarkers in cancer as well as the development of small-molecule inhibitors targeting oncogenic m6A modifiers and their activity in preclinical models.

Gasdermin D Plays an Oncogenic Role in Glioma and Correlates to an Immunosuppressive Microenvironment

BACKGROUND

Understanding the molecular mechanisms driving oncogenic processes in glioma is important in order to develop efficient treatments. Recent studies have proposed gasdermin D (GSDMD) as a newly discovered pyroptosis executive protein associated with tumorigenesis. However, the precise effect of GSDMD on glioma progression remains unknown.

METHODS

The expression levels of GSDMD in 931 glioma and 1157 normal control tissues were collected. A series of bioinformatic approaches and in vivo and in vitro experiments were used to investigate the roles and mechanisms of GDSMD in glioma.

RESULTS

Significant upregulation of GSDMD was detected in glioma tissues compared to normal brain tissues. Patients with glioma and higher GSDMD levels had shorter overall survival, and the Cox regression analysis revealed that GSDMD was an independent risk factor. In addition, upregulation of GSDMD was associated with higher tumor mutation burden and PD-1/PD-L1 expression. Immune infiltration and single-cell analyses indicated that GSDMD was positively associated with an immunosuppressive microenvironment with more infiltrated macrophages and cancer-associated fibroblasts. Furthermore, the in vitro and in vivo experiments revealed that GSDMD knockdown inhibited glioma proliferation, migration, and growth in vivo.

CONCLUSION

Our analyses revealed a relatively comprehensive understanding of the oncogenic role of GSDMD in glioma. GSDMD is a promising prognostic biomarker and a potential target for glioma treatment.

New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction

Increasing evidence indicates that glioma topographic location is linked to the cellular origin, molecular alterations and genetic profile. This research aims to (a) reveal the underlying mechanisms of tumor location predilection in glioblastoma multiforme (GBM) and lower-grade glioma (LGG) and (b) leverage glioma location features to predict prognosis. MRI images from 396 GBM and 190 LGG (115 astrocytoma and 75 oligodendroglioma) patients were standardized to construct frequency maps and analyzed by voxel-based lesion-symptom mapping. We then investigated the spatial correlation between glioma distribution with gene expression in healthy brains. We also evaluated transcriptomic differences in tumor tissue from predilection and nonpredilection sites. Furthermore, we quantitively characterized tumor anatomical localization and explored whether it was significantly related to overall survival. Finally, we employed a support vector machine to build a survival prediction model for GBM patients. GBMs exhibited a distinct location predilection from LGGs. GBMs were nearer to the subventricular zone and more likely to be localized to regions enriched with synaptic signaling, whereas astrocytoma and oligodendroglioma tended to occur in areas associated with the immune response. Synapse, neurotransmitters and calcium ion channel-related genes were all activated in GBM tissues coming from predilection regions. Furthermore, we characterized tumor location features in terms of a series of tumor-to-predilection distance metrics, which were able to predict GBM 1-year survival status with an accuracy of 0.71. These findings provide new perspectives on our understanding of tumor anatomic localization. The spatial features of glioma are of great value in individual therapy and prognosis prediction.

Understanding the Epitranscriptome for Avant-Garde Brain Tumour Diagnostics

RNA modifications are diverse, dynamic, and reversible transcript alterations rapidly gaining attention due to their newly defined RNA regulatory roles in cellular pathways and pathogenic mechanisms. The exciting emerging field of 'epitranscriptomics' is predominantly centred on studying the most abundant mRNA modification, N6-methyladenine (m⁶A). The m⁶A mark, similar to many other RNA modifications, is strictly regulated by so-called 'writer', 'reader', and 'eraser' protein species. The abundance of genes coding for the expression of these regulator proteins and m⁶A levels shows great potential as diagnostic and predictive tools across several cancer fields. This review explores our current understanding of RNA modifications in glioma biology and the potential of epitranscriptomics to develop new diagnostic and predictive classification tools that can stratify these highly complex and heterogeneous brain tumours.

Application of aptamer functionalized nanomaterials in targeting therapeutics of typical tumors

Cancer is a major cause of human death all over the world. Traditional cancer treatments include surgery, radiotherapy, chemotherapy, immunotherapy, and hormone therapy. Although these conventional treatment methods improve the overall survival rate, there are some problems, such as easy recurrence, poor treatment, and great side effects. Targeted therapy of tumors is a hot research topic at present. Nanomaterials are essential carriers of targeted drug delivery, and nucleic acid aptamers have become one of the most important targets for targeted tumor therapy because of their high stability, high affinity, and high selectivity. At present, aptamer-functionalized nanomaterials (AFNs), which combine the unique selective recognition characteristics of aptamers with the high-loading performance of nanomaterials, have been widely studied in the field of targeted tumor therapy. Based on the reported application of AFNs in the biomedical field, we introduce the characteristics of aptamer and nanomaterials, and the advantages of AFNs first. Then introduce the conventional treatment methods for glioma, oral cancer, lung cancer, breast cancer, liver cancer, colon cancer, pancreatic cancer, ovarian cancer, and prostate cancer, and the application of AFNs in targeted therapy of these tumors. Finally, we discuss the progress and challenges of AFNs in this field.

Characterization of immune microenvironment infiltration and m6A regulator-mediated RNA methylation modification patterns in osteoarthritis

Background

Few studies have been reported the potential role of N6-methyladenosine (m6A) modification in osteoarthritis (OA). We investigated the patterns of m6A modification in the immune microenvironment of OA.

Methods

We evaluated the m6A modification patterns based on 22 m6A regulators in 139 OA samples and systematically associated these modification patterns with immune cell infiltration characteristics. The function of m6A phenotype-related differentially expressed genes (DEGs) was investigated using gene enrichment analysis. An m6A score model was constructed using principal component analysis (PCA), and an OA prediction model was established based on the key m6A regulators. We used real-time PCR analysis to detect the changes of gene expression in the cell model of OA.

Results

Healthy and OA samples showed significant differences in the expression of m6A regulators. Nine key m6A regulators, two m6A modification patterns, m6A-related genes and two gene clusters were identified. Some m6A regulators had a strong correlation with each other. Gene clusters and m6A clusters have high similarity, and cluster A corresponds to a high m6A score. Immunocytes infiltration differed significantly between the two clusters, with the m6A cluster B and gene cluster B having more types of infiltrating immunocytes than cluster A. The predictive model can also predict the progression of OA through m6A regulators expression. The results of real-time PCR analysis showed that the gene expression in the cell model of OA is similar to that of the m6A cluster B.

Conclusions

Our study reveals for the first time the potential regulatory mechanism of m6A modification in the immune microenvironment of OA. This study also sheds new light on the pathogenesis of OA.

Molecular subtypes of cuproptosis regulators and their correlation with clinical prognosis and immune response in glioma

Cuproptosis is a newly described form of cell death. However, nothing is known about the roles of cuproptosis regulators in glioma. First, we explored the characteristics of cuproptosis molecular subtypes and relevant tumor microenvironment (TME) immune cell infiltration patterns in glioma. Using unsupervised clustering analysis, we identified two cuproptosis subtypes and three gene clusters that exhibited different clinical characteristics and TME cell infiltration patterns. Then, we developed and validated a cuproptosis-related prognostic model for predicting the overall survival of glioma patients. We established a risk score tool based on a nomogram to assess the clinical applicability of the cuproptosis model. A high cuproptosis risk score with high immune cell infiltration level, tumor mutation burden, gene alterations, and immunity activation had an unfavorable overall survival. Next, we identified possible competing endogenous ribonucleic acid regulatory networks based on significantly differentially expressed genes between high-risk and low-risk groups and screened several candidate small molecular compounds that may improve chemotherapy. Data from IMvigor and GSE78200 showed that the cuproptosis score affected the prognosis of patients who received immunotherapy. Our study indicated that cuproptosis regulators are involved in TME immune infiltration and impact the clinical prognosis in glioma. It is necessary for clinical practice to develop different therapeutic strategies according to the different phenotypes associated with immune response. The present findings provide new insight for improving immunotherapy strategies and individualized treatment in glioma.

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.

A Risk Signature Consisting of Eight m6A Methylation Regulators Predicts the Prognosis of Glioma

Glioma progression seriously correlates to the epigenetic context. This study aims to identify glioma subtypes by clustering analysis of patients using the multi-omics data of N6-methyladenosine (m6A) methylation regulators and to construct a risk signature for investigating the role of m6A methylation regulators in the prognosis of glioma. Multi-omics data of glioma and normal control tissues were obtained through The Cancer Genome Atlas (TCGA) database. The clustering analysis of multi-omics data of patients was conducted using the R package iClusterPlus software. The risk model was constructed by univariate and multivariate Cox analysis, and the glioma expression data and related clinical data were obtained by Chinese Glioma Genome Atlas (CGGA) datasets to verify the risk model. By analyzing the glioma data in TCGA, we found that the risk signature could be constructed according to the eight genes with m6A methylation modification function, including ALKBH5, HNRNPA2B1, IGF2BP2, IGF2BP3, RBM15, WTAP, YTHDF1, and YTHDF2. Meanwhile, we found that IGF2BP2 and IGF2BP3 were highly expressed in glioma subtypes with high-risk scores and closely related to the prognosis of glioma patients. m6A methylation regulators, especially IGF2BP2 and IGF2BP3, play important roles in the malignant progression of glioma. The risk signature constructed by eight m6A methylation regulators can predict the prognosis of glioma. IGF2BP2 and IGF2BP3 may be the key regulatory factors of m6A methylation regulators involved in the occurrence and development of glioma, and can serve as molecular markers for the prognosis of glioma.

The regulation and potential roles of m6A modifications in early embryonic development and immune tolerance at the maternal-fetal interface

The immune microenvironment at the maternal-fetal interface was determined by the crosstalk between the trophoblast and maternal-derived cells, which dynamically changed during the whole gestation. Trophoblasts act as innate immune cells and dialogue with maternal-derived cells to ensure early embryonic development, depending on the local immune microenvironment. Therefore, dysfunctions in trophoblasts and maternal decidual cells contribute to pregnancy complications, especially recurrent pregnancy loss in early pregnancy. Since many unknown regulatory factors still affect the complex immune status, exploring new potential aspects that could influence early pregnancy is essential. RNA methylation plays an important role in contributing to the transcriptional regulation of various cells. Sufficient studies have shown the crucial roles of N6-methyladenosine (m6A)- and m6A-associated- regulators in embryogenesis during implantation. They are also essential in regulating innate and adaptive immune cells and the immune response and shaping the local and systemic immune microenvironment. However, the function of m6A modifications at the maternal-fetal interface still lacks wide research. This review highlights the critical functions of m6A in early embryonic development, summarizes the reported research on m6A in regulating immune cells and tumor immune microenvironment, and identifies the potential value of m6A modifications in shaping trophoblasts, decidual immune cells, and the microenvironment at the maternal-fetal interface. The m6A modifications are more likely to contribute to embryogenesis, placentation and shape the immune microenvironment at the maternal-fetal interface. Uncovering these crucial regulatory mechanisms could provide novel therapeutic targets for RNA methylation in early pregnancy.

Comprehensive analysis of m6A/m5C/m1A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma

This research aims to develop a prognostic glioma marker based on m⁶A/m⁵C/m¹A genes and investigate the potential role in the tumor immune microenvironment. Data for patients with glioma were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). The expression of genes related to m⁶A/m⁵C/m¹A was compared for normal and glioma groups. Gene Ontology and Kyoto Encyclopedia of Genes and Gene enrichment analysis of differentially expressed genes were conducted. Consistent clustering analysis was performed to obtain glioma subtypes and complete the survival analysis and immune analysis. Based on TCGA, Lasso regression analysis was used to obtain a prognostic model, and the CGGA database was used to validate the model. The model-based risk scores and the hub genes with the immune microenvironment, clinical features, and antitumor drug susceptibility were investigated. The clinical glioma tissues were collected to verify the expression of hub genes via immunohistochemistry. Twenty genes were differentially expressed, Consensus cluster analysis identified two molecular clusters. Overall survival was significantly higher in cluster 2 than in cluster 1. Immunological analysis revealed statistically significant differences in 26 immune cells and 17 immune functions between the two clusters. Enrichment analysis detected multiple meaningful pathways. We constructed a prognostic model that consists of WTAP, TRMT6, DNMT1, and DNMT3B. The high-risk and low-risk groups affected the survival prognosis and immune infiltration, which were related to grade, gender, age, and survival status. The prognostic value of the model was validated using another independent cohort CGGA. Clinical correlation and immune analysis revealed that four hub genes were associated with tumor grade, immune cells, and antitumor drug sensitivity, and WTAP was significantly associated with microsatellite instability(MSI). Immunohistochemistry confirmed the high expression of WTAP, DNMT1, and DNMT3B in tumor tissue, but the low expression of TRMT6. This study established a strong prognostic marker based on m⁶A/m⁵C/m¹A methylation regulators, which can accurately predict the prognosis of patients with gliomas. m⁶A/m⁵C/m¹A modification mode plays an important role in the tumor microenvironment, can provide valuable information for anti-tumor immunotherapy, and have a profound impact on the clinical characteristics.

Multimodal targeting of glioma with functionalized nanoparticles

The most common and aggressive primitive intracranial tumor of the central nervous system is the glioma. The blood–brain barrier (BBB) has proven to be a significant obstacle to the effective treatment of glioma. To effectively treat glioma, different ways have been used to cross the BBB to deliver drugs to the brain. Drug delivery through nanocarriers proves to be an effective and non-invasive technique for the treatment of glioma and has great potential in the treatment of glioma. In this review, we will provide an overview of nanocarrier-mediated drug delivery and related glioma therapy. Nanocarrier-mediated drug delivery techniques to cross the BBB (liposomes, micelles, inorganic systems, polymeric nanoparticles, nanogel system, and biomimetic nanoparticles) are explored. Finally, the use of nanotherapeutic approaches in the treatment of glioblastoma including chemotherapy, radiotherapy, photothermal therapy, gene therapy, glioma genome editing, immunotherapy, chimeric antigen receptor (CAR) T-cells, immune checkpoint modulators, immune photothermal therapy, vaccine-based immunotherapy, and combination therapy is summarized. Furthermore, this article offers various views on the clinical applicability of nanomedicine.

Identification of Prognostic Genes in Gliomas Based on Increased Microenvironment Stiffness

With a median survival time of 15 months, glioblastoma multiforme is one of the most aggressive primary brain cancers. The crucial roles played by the extracellular matrix (ECM) stiffness in glioma progression and treatment resistance have been reported in numerous studies. However, the association between ECM-stiffness-regulated genes and the prognosis of glioma patients remains to be explored. Thus, using bioinformatics analysis, we first identified 180 stiffness-dependent genes from an RNA-Seq dataset, and then evaluated their prognosis in The Cancer Genome Atlas (TCGA) glioma dataset. Our results showed that 11 stiffness-dependent genes common between low- and high-grade gliomas were prognostic. After validation using the Chinese Glioma Genome Atlas (CGGA) database, we further identified four stiffness-dependent prognostic genes: FN1, ITGA5, OSMR, and NGFR. In addition to high-grade glioma, overexpression of the four-gene signature also showed poor prognosis in low-grade glioma patients. Moreover, our analysis confirmed that the expression levels of stiffness-dependent prognostic genes in high-grade glioma were significantly higher than in low-grade glioma, suggesting that these genes were associated with glioma progression. Based on a pathophysiology-inspired approach, our findings illuminate the link between ECM stiffness and the prognosis of glioma patients and suggest a signature of four stiffness-dependent genes as potential therapeutic targets.

Development of a Novel Prognostic Model of Glioblastoma Based on m6A-Associated Immune Genes and Identification of a New Biomarker

Background

Accumulating evidence shows that m6A regulates oncogene and tumor suppressor gene expression, thus playing a dual role in cancer. Likewise, there is a close relationship between the immune system and tumor development and progression. However, for glioblastoma, m6A-associated immunological markers remain to be identified.

Methods

We obtained gene expression, mutation, and clinical data on glioblastoma from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. Next, we performed univariate COX–least absolute shrinkage and selection operator (LASSO)–multivariate COX regression analyses to establish a prognostic gene signature and develop a corresponding dynamic nomogram application. We then carried out a clustering analysis twice to categorize all samples according to their m6A-regulating and m6A-associated immune gene expression levels (high, medium, and low) and calculated their m6A score. Finally, we performed quantitative reverse transcription-polymerase chain reaction, cell counting kit-8, cell stemness detection, cell migration, and apoptosis detection in vitro assays to determine the biological role of CD81 in glioblastoma cells.

Results

Our glioblastoma risk score model had extremely high prediction efficacy, with the area under the receiver operating characteristic curve reaching 0.9. The web version of the dynamic nomogram application allows rapid and accurate calculation of patients’ survival odds. Survival curves and Sankey diagrams indicated that the high-m6A score group corresponded to the groups expressing medium and low m6A-regulating gene levels and high m6A-associated prognostic immune gene levels. Moreover, these groups displayed lower survival rates and higher immune infiltration. Based on the gene set enrichment analysis, the pathophysiological mechanism may be related to the activation of the immunosuppressive function and related signaling pathways. Moreover, the risk score model allowed us to perform immunotherapy benefit assessment. Finally, silencing CD81 in vitro significantly suppressed proliferation, stemness, and migration and facilitated apoptosis in glioblastoma cells.

Conclusion

We developed an accurate and efficient prognostic model. Furthermore, the correlation analysis of different stratification methods with tumor microenvironment provided a basis for further pathophysiological mechanism exploration. Finally, CD81 may serve as a diagnostic and prognostic biomarker in glioblastoma.

A bioinformatic analysis study of m7G regulator-mediated methylation modification patterns and tumor microenvironment infiltration in glioblastoma

BACKGROUND

Glioblastoma is one of the most common brain cancers in adults, and is characterized by recurrence and little curative effect. An effective treatment for glioblastoma patients remains elusive worldwide. 7-methylguanosine (m7G) is a common RNA modification, and its role in tumors has become a research hotspot.

METHODS

By searching for differentially expressed genes related to m7G, we generated a prognostic signature via cluster analysis and established classification criteria of high and low risk scores. The effectiveness of classification was validated using the Non-negative matrix factorization (NMF) algorithm, and repeatedly verified using training and test groups. The dimension reduction method was used to clearly show the difference and clinical significance of the data. All analyses were performed via R (version 4.1.2).

RESULTS

According to the signature that included four genes (TMOD2, CACNG2, PLOD3, and TMSB10), glioblastoma patients were divided into high and low risk score groups. The survival rates between the two groups were significantly different, and the predictive abilities for 1-, 3-, and 5-year survivals were effective. We further established a Nomogram model to further examine the signature,as well as other clinical factors, with remaining significant results. Our signature can act as an independent prognostic factor related to immune-related processes in glioblastoma.

CONCLUSIONS

Our research addresses the gap in knowledge in the m7G and glioblastoma research fields. The establishment of a prognostic signature and the extended analysis of the tumor microenvironment, immune correlation, and tumor mutation burden further suggest the important role of m7G in the development and development of this disease. This work will provide support for future research.

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.

Prognostic Features of the Tumor Immune Microenvironment in Glioma and Their Clinical Applications: Analysis of Multiple Cohorts

Glioma is the most common malignant tumor of the central nervous system. Tumor purity is a source of important prognostic factor for glioma patients, showing the key roles of the microenvironment in glioma prognosis. In this study, we systematically screened functional characterization related to the tumor immune microenvironment and constructed a risk model named Glioma MicroEnvironment Functional Signature (GMEFS) based on eight cohorts. The prognostic value of the GMEFS model was also verified in another two glioma cohorts, glioblastoma (GBM) and low-grade glioma (LGG) cohorts, from The Cancer Genome Atlas (TCGA). Nomograms were established in the training and testing cohorts to validate the clinical use of this model. Furthermore, the relationships between the risk score, intrinsic molecular subtypes, tumor purity, and tumor-infiltrating immune cell abundance were also evaluated. Meanwhile, the performance of the GMEFS model in glioma formation and glioma recurrence was systematically analyzed based on 16 glioma cohorts from the Gene Expression Omnibus (GEO) database. Based on multiple-cohort integrated analysis, risk subpathway signatures were identified, and a drug–subpathway association network was further constructed to explore candidate therapy target regions. Three subpathways derived from Focal adhesion (path: 04510) were identified and contained known targets including platelet derived growth factor receptor alpha (PDGFRA), epidermal growth factor receptor (EGFR), and erb-b2 receptor tyrosine kinase 2 (ERBB2). In conclusion, the novel functional signatures identified in this study could serve as a robust prognostic biomarker, and this study provided a framework to identify candidate therapeutic target regions, which further guide glioma patients’ clinical decision.

Roles of the m6A Modification of RNA in the Glioblastoma Microenvironment as Revealed by Single-Cell Analyses

Purpose

Glioblastoma multiforme (GBM) is a common and aggressive form of brain tumor. The N⁶-methyladenosine (m⁶A) mRNA modification plays multiple roles in many biological processes and disease states. However, the relationship between m⁶A modifications and the tumor microenvironment in GBM remains unclear, especially at the single-cell level.

Experimental Design

Single-cell and bulk RNA-sequencing data were acquired from the GEO and TCGA databases, respectively. We used bioinformatics and statistical tools to analyze associations between m⁶A regulators and multiple factors.

Results

HNRNPA2B1 and HNRNPC were extensively expressed in the GBM microenvironment. m⁶A regulators promoted the stemness state in GBM cancer cells. Immune-related BP terms were enriched in modules of m⁶A-related genes. Cell communication analysis identified genes in the GALECTIN signaling network in GBM samples, and expression of these genes (LGALS9, CD44, CD45, and HAVCR2) correlated with that of m⁶A regulators. Validation experiments revealed that MDK in MK signaling network promoted migration and immunosuppressive polarization of macrophage. Expression of m⁶A regulators correlated with ICPs in GBM cancer cells, M2 macrophages and T/NK cells. Bulk RNA-seq analysis identified two expression patterns (low m⁶A/high ICP and high m⁶A/low ICP) with different predicted immune infiltration and responses to ICP inhibitors. A predictive nomogram model to distinguish these 2 clusters was constructed and validated with excellent performance.

Conclusion

At the single-cell level, m⁶A modification facilitates the stemness state in GBM cancer cells and promotes an immunosuppressive microenvironment through ICPs and the GALECTIN signaling pathway network. And we also identified two m⁶A-ICP expression patterns. These findings could lead to novel treatment strategies for GBM patients.

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

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

A Novel Risk Score Model Based on Eleven Extracellular Matrix-Related Genes for Predicting Overall Survival of Glioma Patients

Gliomas are the most common lethal primary brain tumors with variable survival outcomes for patients. The extracellular matrix (ECM) is linked with clinical prognosis of glioma patients, but it is not commonly used as a clinical indicator. Herein, we investigated changes in ECM-related genes (ECMRGs) via analyzing the transcriptional data of 938 gliomas from TCGA and CGGA datasets. Based on least absolute shrinkage and selection operator (LASSO) Cox regression analysis, a 11-ECMRG signature that is strongly linked with overall survival (OS) in glioma patients was identified. This signature was characterized by high-risk and low-risk score patterns. We found that the patients in the high-risk group are significantly linked with malignant molecular features and worse outcomes. Univariate and multivariate Cox regression analyses suggested that the signature is an independent indicator for glioma prognosis. The prediction accuracy of the signature was verified through time-dependent receiver operating characteristic (ROC) curves and calibration plots. Further bioinformatics analyses implied that the ECMRG signature is strongly associated with the activation of multiple oncogenic and metabolic pathways and immunosuppressive tumor microenvironment in gliomas. In addition, we confirmed that the high-risk score is an indicator for a therapy-resistant phenotype. In addition to bioinformatics analyses, we functionally verified the oncogenic role of bone morphogenetic protein 1 (BMP1) in gliomas in vitro.

Identification of N6-Methyladenosine-Related lncRNAs as a Prognostic Signature in Glioma

N6-methyladenosine (m6A) modification is the most abundant modification in long noncoding RNAs (lncRNAs). Current studies have shown that the abnormal expression of m6A-related genes is closely associated with the tumorigenesis and progression of glioma. However, the role of m6A-related lncRNAs in glioma development is still unclear. Herein, we screened 566 m6A-related lncRNAs in glioma from The Cancer Genome Atlas (TCGA) database. The expression pattern of these lncRNAs could cluster samples into two groups, in which various classical tumor-related functions and the tumor immune microenvironment were significantly different. Subsequently, a nine-factor m6A-related lncRNA prognostic signature (MLPS) was constructed by using a LASSO regression analysis in the training set and was validated in the test set and independent datasets. The AUC values of the MLPS were 0.881, 0.918 and 0.887 for 1-, 3- and 5-year survival in the training set, respectively, and 0.856, 0.916 and 0.909 for 1-, 3-, and 5-year survival in the test set, respectively. Stratification analyses of the MLPS illustrated its prognostic performance in gliomas with different characteristics. Correlation analyses showed that the infiltrations of monocytes and tumor-associated macrophages (TAMs) were significantly relevant to the risk score in the MLPS. Moreover, we detected the expression of four MLPS factors with defined sequences in glioma and normal cells by using RT-PCR. Afterwards, we investigated the functions of LNCTAM34A (one of the MLPS factors) in glioma cells, which have rarely been reported. Via in vitro experiments, LNCTAM34A was demonstrated to promote the proliferation, migration and epithelial-mesenchymal transition (EMT) of glioma cells. Overall, our study revealed the critical role of m6A-related lncRNAs in glioma and elucidated that LNCTAM34A could promote glioma proliferation, migration and EMT.

The hub ten gene-based risk score system using RNA m6A methylation regulator features and tumor immune microenvironment in breast cancer

BACKGROUND

RNA N⁶-methyladenosine (m⁶A) modification is primarily regulated by m⁶A regulators, which play significant epigenetic regulatory roles in tumorigenesis, tumor development, and tumor immune microenvironment. However, the correlation between m⁶A regulators and immune cell infiltration in breast cancer remains unclear.

METHODS

In this study, m⁶A modification patterns were evaluated based on 31 m⁶A modification regulators. m⁶A clusters were determined by consensus clustering. Immune landscape and immune cell infiltration subgroups were characterized by m⁶A clusters. Key module and hub genes related to m⁶A regulators and immune infiltration cells were identified by WGCNA. LASSO algorithm was applied to select prognostic signatures. Multivariate Cox regression analysis was applied to assess the prognostic value of gene signatures.

RESULTS

Two distinct m⁶A clusters were determined based on the expression of 31 m⁶A modification regulators and characterized by two tumor immune microenvironment (TIME) immune cell infiltration subgroups. Further, a total of 1971 differentially expressed genes between breast cancer patients and healthy controls were screened, nine modules associated with clinical characteristics of breast cancer patients were identified. Later, one key module and 13 hub genes correlated with m⁶A regulators and immune infiltration cells were identified. LASSO Cox regression analysis selected and constructed a ten-gene prognostic model to build a risk score system for individual breast cancer patient prognosis. The performance of the ten-gene-based risk score system was further validated in an independent dataset with an AUC of 0.659.

CONCLUSIONS

This study revealed that m⁶A modification regulators played a significant role in the TIME regulation of breast cancer. The hub ten gene-based risk score system is valuable in predicting the prognosis of breast cancer patients, which may provide potential significance for breast cancer diagnosis, prognosis, and immunotherapy in the future.

Recent Progress of RGD Modified Liposomes as Multistage Rocket Against Cancer

Cancer is a life-threatening disease, contributing approximately 9.4 million deaths worldwide. To address this challenge, scientific researchers have investigated molecules that could act as speed-breakers for cancer. As an abiotic drug delivery system, liposomes can hold both hydrophilic and lipophilic drugs, which promote a controlled release, accumulate in the tumor microenvironment, and achieve elongated half-life with an enhanced safety profile. To further improve the safety and impair the off-target effect, the surface of liposomes could be modified in a way that is easily identified by cancer cells, promotes uptake, and facilitates angiogenesis. Integrins are overexpressed on cancer cells, which upon activation promote downstream cell signaling and eventually activate specific pathways, promoting cell growth, proliferation, and migration. RGD peptides are easily recognized by integrin over expressed cells. Just like a multistage rocket, ligand anchored liposomes can be selectively recognized by target cells, accumulate at the specific site, and finally, release the drug in a specific and desired way. This review highlights the role of integrin in cancer development, so gain more insights into the phenomenon of tumor initiation and survival. Since RGD is recognized by the integrin family, the fate of RGD has been demonstrated after its binding with the acceptor’s family. The role of RGD based liposomes in targeting various cancer cells is also highlighted in the paper.

Gene Expression-Based Predication of RNA Pseudouridine Modification in Tumor Microenvironment and Prognosis of Glioma Patients

Aberrant expression of methyltransferases and demethylases may augment tumor initiation, proliferation and metastasis through RNA modification, such as m⁶A and m⁵C. However, activity of pseudouridine (Ψ) modification of RNA remains unknown in glioma, the most common malignant intracranial tumor. In this study, we explored the expression profiles of the Ψ synthase genes in glioma and constructed an efficient prediction model for glioma prognosis based on the CGGA and TCGA datasets. In addition, the risk-score signature was positively associated with malignancy of gliomas and the abundance of tumor-infiltrating immune cells such as macrophages M0 and regulatory T cells (Tregs), but negatively associated with the abundance of monocytes, NK cell activation and T cell CD4⁺ naive. In terms of mechanism, the risk-score signature was positively associated with the expression of inflammatory molecules such as S100A11 and CASP4 in glioma. Overall, this study provided evidence for the activity of RNA Ψ modification in glioma malignancy and local immunity.

m6A regulator-mediated methylation modification patterns and tumor immune microenvironment in sarcoma

Background: Studies have shown that the RNA N⁶-methyladenosine (m⁶A) modification patterns are extensively involved in the development of multiple tumors. However, the association between the m⁶A regulator expression patterns and the sarcoma tumor immune microenvironment (TIME) remains unclear.

Methods: We systematically evaluated the m⁶A regulator expression patterns in patients with sarcoma based on known 23 m⁶A regulators. Different m⁶A regulator expression patterns were analyzed using gene set variation analysis and a single-sample gene set enrichment analysis algorithm. According to the results of consensus clustering, we classified the patients into four different clusters. Next, we subjected the four clusters to differential genetic analysis and established m⁶A-related differentially expressed genes (DEGs). We then calculated the m⁶A-related DEGs score and constructed the m⁶A-related gene signature, named m⁶A score. Finally, the 259 sarcoma samples were divided into high- and low-m⁶A score groups. We further evaluated the TIME landscape between the high- and low-m⁶A score groups.

Results: We identified four different m⁶A modification clusters and found that each cluster had unique metabolic and immunological characteristics. Based on the 19 prognosis-related DEGs, we calculated the principal component analysis scores for each patient with sarcoma and classified them into high- and low-m⁶A score groups.

Conclusions: The m⁶A regulator expression patterns and complexity of the sarcoma TIME landscape are closely related to each other. Systematic evaluation of m⁶A regulator expression patterns and m⁶A scores in patients with sarcoma will enhance our understanding of TIME characteristics.

RNA N1-methyladenosine regulator-mediated methylation modification patterns and heterogeneous signatures in glioma

N1-methyladenosine (m¹A) is ubiquitous in eukaryotic RNA and regulates mRNA translation. However, little is known about its regulatory role in glioma. Here, we identified 4 m¹A modification-related patterns based on m¹A regulators in the TCGA (The Cancer Genome Atlas) and CGGA (Chinese Glioma Genome Atlas) cohorts. The differences in survival prognosis between different clusters were striking. In addition, stemness, genomic heterogeneity, tumor microenvironment (TME), and immune cell infiltration were also significantly different between the poor and best prognostic clusters. To reveal the underlying mechanism, differentially expressed genes (DEGs) between the poor and best prognostic clusters were identified, and then were integrated for weighted correlation network analysis (WGCNA). After Univariate Cox-LASSO-Multivariate Cox analyses, DEGs PLEK2 and ABCC3 were screened as the risk-hub genes and were selected to construct an m¹A-related signature. Moreover, ABCC3 exacerbated glioma proliferation and was associated with temozolomide (TMZ) resistance. Overall, our study provided new insights into the function and potential therapeutic role of m¹A in glioma.

N6-Methyladenosine RNA Modification in the Tumor Immune Microenvironment: Novel Implications for Immunotherapy

N6-methyladenosine (m⁶A) methylation is one of the most common modifications of RNA in eukaryotic cells, and is mainly regulated by m⁶A methyltransferases (writers), m⁶A demethylases (erasers), and m⁶A binding proteins (readers). Recently, accumulating evidence has shown that m⁶A methylation plays crucial roles in the regulation of the tumor immune microenvironment, greatly impacting the initiation, progression, and metastasis processes of various cancers. In this review we first briefly summarizes the m⁶A-related concepts and detection methods, and then describes in detail the associations of m⁶A methylation modification with various tumor immune components especially immune cells (e.g., regulatory T cells, dendritic cells, macrophages, and myeloid-derived suppressor cells) in a variety of cancers. We discuss the relationship between m⁶A methylation and cancer occurrence and development with the involvement of tumor immunity highlighted, suggesting novel markers and potential targets for molecular pathological diagnosis and immunotherapy of various cancers.

Integrating m6A Regulators-Mediated Methylation Modification Models and Tumor Immune Microenvironment Characterization in Caucasian and Chinese Low-Grade Gliomas

Background: As an important epigenetic modification, m6A methylation plays an essential role in post-transcriptional regulation and tumor development. It is urgently needed to comprehensively and rigorously explore the prognostic value of m6A regulators and its association with tumor microenvironment (TME) infiltration characterization of low-grade glioma (LGG).

Methods: Based on the expression of 20 m6A regulatory factors, we comprehensively evaluated the m6A modification patterns of LGG after unsupervised clustering. Subsequent analysis of the differences between these groups was performed to obtain m6A-related genes, then consistent clustering was conducted to generate m6AgeneclusterA and m6AgeneclusterB. A Random Forest and machining learning algorithms were used to reduce dimensionality, identify TME characteristics and predict responses for LGG patients receiving immunotherapies.

Results: Evident differential m6A regulators were found in mutation, CNV and TME characteristics of LGG. Based on TCGA and CGGA databases, we identified that m6A regulators clusterA could significantly predict better prognosis (p = 0.00016) which enriched in mTOR signaling pathway, basal transcription factors, accompanied by elevated immune cells infiltration, and decreased IDH and TP53 mutations. We also investigated the distribution of differential genes in m6A regulators clusters which was closely associated with tumor immune microenvironment through three independent cohort comparisons. Next, we established m6Ascore based on previous m6A model, which accurately predicts outcomes in 1089 LGG patients (p < 0.0001) from discovering cohort and 497 LGG patients from testing cohort. Significant TME characteristics, including genome heterogeneity, abidance of immune cells, and clinicopathologic parameters have been found between m6Ascore groups. Importantly, LGG patients with high m6Ascore are confronted with significantly decreased responses to chemotherapies, but benefit more from immunotherapies.

Conclusion: In conclusion, this study first demonstrates that m6A modification is crucial participant in tumorigenesis and TME infiltration characterization of LGG based on large-scale cohorts. The m6Ascore provides useful and accurately predict of prognosis and clinical responses to chemotherapy, immunotherapy and therapeutic strategy development for LGG patients.

A Pan-Cancer Landscape of HOX-Related lncRNAs and Their Association With Prognosis and Tumor Microenvironment

The highly conserved homology cassette family (HOX) as well as 18 referenced long non-coding antisense transcripts (HOXATs) play vital roles in the development of some cancers. Nevertheless, their expression patterns as well as their association with cancer prognosis and the tumor microenvironment (TME) in pan-cancers are still unclear. Here, based on public databases, the expression levels of HOXATs, their prognostic potentials, and correlation with tumor mutation burden (TMB), immune cell infiltration, immune subtype, immune response-related genes, and stemness scores corresponding to 33 tumor types were analyzed systematically using R language. The results of the analysis indicated that different cancer tissues show different HOXAT expression profiles. Further, HOXAT expression showed association with cancer prognosis and immune and stemness regulation. Gene set enrichment analysis also demonstrated that HOXATs participate in cancer- and immune-related pathways, and based on their expression levels, HOTAIRM1 and HOXB-AS1 showed potential involvement in oncogenesis as well as possible involvement in immune regulation across a variety of cancer types. Further investigation also confirmed a significantly higher expression of HOXB-AS1 in GBM than in lower grade glioma tissues. Importantly, in vitro cell function experiments indicated that HOXB-AS1 supports cancer stem cell and plays a fundamental role in glioma metastasis. In conclusion, our results provide valuable resources that can guide the investigation of the mechanisms related to the role of HOXATs in cancers as well as therapeutic analysis in this regard.

Uncovering the Association Between m5C Regulator-Mediated Methylation Modification Patterns and Tumour Microenvironment Infiltration Characteristics in Hepatocellular Carcinoma

Background: 5-Methylcytosine (m⁵C) plays essential roles in hepatocellular carcinoma (HCC), but the association between m⁵C regulation and immune cell infiltration in HCC has not yet been clarified.

Methods: In this study, we analysed 371 patients with HCC from The Cancer Genome Atlas (TCGA) database, and the expression of 13 m⁵C regulators was investigated. Additionally, gene set variation analysis (GSVA), unsupervised clustering analysis, single-sample gene set enrichment analysis (ssGSEA), correlation analysis, and immunohistochemical (IHC) staining were performed.

Results: Among the 371 patients, 41 had mutations in m⁵C regulators, the frequency of which was 11.26%. Compared with normal hepatic tissues, the expression of m⁵C regulators with copy number variations (CNVs) expansion was significantly higher than that in HCC tissues. Then, we identified three m⁵C modification patterns that had obvious tumour microenvironment (TME) cell infiltration characteristics. The prognostic analysis of the three major m⁵C modification subtypes showed that Cluster-2 had a clear survival advantage over the others. In addition, we found that DNMT1 was highly expressed in tumour tissues compared with normal tissues in a tissue microarray (TMA) and that it was positively correlated with many TME-infiltrating immune cells. High expression of the m⁵C regulator DNMT1 was related to a poor prognosis in patients with HCC. Furthermore, we developed three distinct Immu-clusters. Importantly, mRNAs related to the transcription of growth factor β (TGF-β)/EMT pathway were significantly up-regulated in Immu-cluster 2, indicating that this cluster is considered to be the immune rejection phenotype. Immu-cluster 3 showed elevated expression of mRNAs related to immune checkpoint genes.

Conclusion: Our work revealed the association between m⁵C modification and immune regulators in the TME. These findings also suggest that DNMT1 has great potential as a prognostic biomarker and therapeutic target for HCC.

Identification of an N6-methyladenosine (m6A)-related signature associated with clinical prognosis, immune response, and chemotherapy in primary glioblastomas

Background

N6-methyladenosine (m6A) RNA methylation regulators play crucial role in tumorigenicity and progression. However, their biological significance in primary glioblastomas (GBM) has not been fully elucidated.

Methods

In the present study, we evaluated the 22 m6A RNA regulators using the integrated data of primary GBM samples from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. The different m6A modification patterns and m6A-related gene signature in primary GBM were distinguished by using principal component analysis. Single-sample gene set enrichment analysis was introduced to assess the relative level of immune infiltration. Gene set variation analysis was performed to calculate the enrichment score of the signaling pathways for different clusters. An m6A scoring scheme was established to evaluate the m6A modification pattern in individual tumors in order to predict prognosis and evaluate tumor microenvironment (TME) cell infiltration, immune response, and chemotherapy effect in primary GBM.

Results

Two distinct m6A modification subgroups associated with different clinical features and biological pathways were identified among the 371 primary GBM. Based on 132 prognostic m6A phenotype-related differentially expressed genes (DEGs) between 2 m6A cluster subgroups, an m6A scoring model was constructed to assess the m6A modification pattern in individual tumors. The high-m6A score group was associated with better prognosis and immune response and worse chemotherapy effect.

Conclusions

The findings of the present study indicate the potential role of m6A modification in primary GBM, which will help enhance our understanding of TME characteristics, predict clinical prognosis, and provide important insight into effective immunotherapy and chemotherapy.

Four specific biomarkers associated with the progression of glioblastoma multiforme in older adults identified using weighted gene co-expression network analysis

Glioblastoma multiforme (GBM) is the most common primary intracranial malignancy in adults. Owing to individual tolerance and tumor heterogeneity, the therapy methods for young adults do not apply to older adults. The present study aimed to identify specific biomarkers for GBM in older adults using weighted gene co-expression network analysis (WGCNA). Gene expression profiles of older adults with GBM were downloaded from The Cancer Genome Atlas (TCGA) and set as a discovery cohort to construct WGCNA. Core genes of clinically significant modules were used to perform functional enrichment, protein-protein interaction, and Pearson correlation analyses. Gene expression profiles of young in TCGA and older GBM patients from our research group were set as verification cohorts for hub gene expression and diagnostic value. Four significant gene modules associated clinically with older adults with GBM were identified, whereas 251 genes were core genes with module membership>0.8 and gene significance>0.2. Ermin (ERMN), myelin-associated oligodendrocyte basic protein (MOBP), proteolipid protein 1 (PLP1), and oligodendrocytic myelin paranodal and inner loop protein (OPALIN) genes had significant relationships with the Karnofsky score (KPS) in older GBM patients. ERMN, MOBP, PLP1, and OPALIN had no relationship with KPS in young GBM patients. These genes were upregulated in GBM tissues from older patients with low but not high KPS and had high diagnostic value. In conclusion, ERMN, MOBP, PLP1, and OPALIN may serve as specific biomarkers for the progression of GBM in older adults.

Establishment of an Immune-Related Gene Signature for Risk Stratification for Patients with Glioma

Glioma is a frequently seen primary malignant intracranial tumor, characterized by poor prognosis. The study is aimed at constructing a prognostic model for risk stratification in patients suffering from glioma. Weighted gene coexpression network analysis (WGCNA), integrated transcriptome analysis, and combining immune-related genes (IRGs) were used to identify core differentially expressed IRGs (DE IRGs). Subsequently, univariate and multivariate Cox regression analyses were utilized to establish an immune-related risk score (IRRS) model for risk stratification for glioma patients. Furthermore, a nomogram was developed for predicting glioma patients' overall survival (OS). The turquoise module (cor = 0.67; P < 0.001) and its genes (n = 1092) were significantly pertinent to glioma progression. Ultimately, multivariate Cox regression analysis constructed an IRRS model based on VEGFA, SOCS3, SPP1, and TGFB2 core DE IRGs, with a C-index of 0.811 (95% CI: 0.786-0.836). Then, Kaplan-Meier (KM) survival curves revealed that patients presenting high risk had a dismal outcome (P < 0.0001). Also, this IRRS model was found to be an independent prognostic indicator of gliomas' survival prediction, with HR of 1.89 (95% CI: 1.252-2.85) and 2.17 (95% CI: 1.493-3.14) in the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets, respectively. We established the IRRS prognostic model, capable of effectively stratifying glioma population, convenient for decision-making in clinical practice.