The Impact of m1A Methylation Modification Patterns on Tumor Immune Microenvironment and Prognosis in Oral Squamous Cell Carcinoma.
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ABSTRACT:
SUBMITTER: Gao L
PROVIDER: S-EPMC8508946 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe dysregulation of RNA methylation has been demonstrated to contribute to tumorigenicity and progression in recent years. However, the alteration of N1-methyladenosine (m1A) methylation and its role in hepatocellular carcinoma (HCC) remain unclear.MethodsWe systematically investigated the modification patterns of 10 m1A regulators in HCC samples and evaluated the metabolic characteristics of each pattern. A scoring system named the m1Ascore was developed using principal component analysis. The clinical value of the m1Ascore in risk stratification and drug screening was further explored.ResultsThree m1A modification patterns with distinct metabolic characteristics were identified, corresponding to the metabolism-high, metabolism-intermediate and metabolism-excluded phenotypes. Patients were divided into high- or low-m1Ascore groups, and a significant survival difference was observed. External validation confirmed the prognostic value of the m1Ascore. A nomogram incorporating the m1Ascore and other clinicopathological factors was constructed and had good performance for predicting survival. Two agents, mitoxantrone and doxorubicin, were determined to be potential therapeutic drugs for the high-risk group.ConclusionThis study provided novel insights into m1A modification and metabolic heterogeneity in cancer, promoted risk stratification in the clinic from the perspective of m1A modification, and further guided individual treatment strategies.
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Project description:Glioma is a common intracranial tumor and is generally associated with poor prognosis. Recently, numerous studies illustrated the importance of 5-methylcytosine (m5C) RNA modification to tumorigenesis. However, the prognostic value and immune correlation of m5C in glioma remain unclear. We obtained RNA expression and clinical information from The Cancer Genome Atlas (TCGA) and The Chinese Glioma Genome Atlas (CGGA) datasets to analyze. Nonnegative matrix factorization (NMF) was used to classify patients into two subgroups and compare these patients in survival and clinicopathological characteristics. CIBERSORT and single-sample gene-set algorithm (ssGSEA) methods were used to investigate the relationship between m5C and the immune environment. The Weighted correlation network analysis (WGCNA) and univariate Cox proportional hazard model (CoxPH) were used to construct a m5C-related signature. Most of m5C RNA methylation regulators presented differential expression and prognostic values. There were obvious relationships between immune infiltration cells and m5C regulators, especially NSUN7. In the m5C-related module from WGCNA, we found SEPT3, CHI3L1, PLBD1, PHYHIPL, SAMD8, RAP1B, B3GNT5, RER1, PTPN7, SLC39A1, and MXI1 were prognostic factors for glioma, and they were used to construct the signature. The great significance of m5C-related signature in predicting the survival of patients with glioma was confirmed in the validation sets and CGGA cohort.
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Project description:ObjectiveThis study aims to identify an immune-related signature to predict clinical outcomes of oral squamous cell carcinoma (OSCC) patients.MethodsGene transcriptome data of both tumor and normal tissues from OSCC and the corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA). Tumor Immune Estimation Resource algorithm (ESTIMATE) was used to calculate the immune/stromal-related scores. The immune/stromal scores and associated clinical characteristics of OSCC patients were evaluated. Univariate Cox proportional hazards regression analyses, least absolute shrinkage, and selection operator (LASSO) and receiver operating characteristic (ROC) curve analyses were performed to assess the prognostic prediction capacity. Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO) function annotation were used to analysis the functions of TME-related genes.ResultsEleven predictor genes were identified in the immune-related signature and overall survival (OS) in the high-risk group was significantly shorter than in the low-risk group. An ROC analysis showed the TME-related signature could predict the total OS of OSCC patients. Moreover, GSEA and GO function annotation proved that immunity and immune-related pathways were mainly enriched in the high-risk group.ConclusionsWe identified an immune-related signature that was closely correlated with the prognosis and immune response of OSCC patients. This signature may have important implications for improving the clinical survival rate of OSCC patients and provide a potential strategy for cancer immunotherapy.
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Project description:RNA methylation is a novel epigenetic modification that can be used to evaluate tumor prognosis. However, the underlying mechanisms are unclear. This study aimed to investigate the genetic characteristics of 5-methylcytosine (m5C) and N1-methyladenosine (m1A) regulators in lung squamous cell carcinoma (LUSC) and the prognostic value and immune-related effects of m5C regulators. To this end, we selected the public LUSC dataset from the Cancer Genome Atlas and Gene Expression Omnibus. The least absolute shrinkage and selection operator regression model was used to identify prognostic risk signatures. We used the UALCAN and Human Protein Atlas databases to study the expression of target gene mRNA/protein expression. Furthermore, the Tumor Immune Single Cell Hub and the Tumor Immune Estimation Resource were used to evaluate the degree of immune cell infiltration. Most of the m5C and m1A regulators showed significantly different expression between LUSC and normal samples. The m5C regulators were associated with poor prognosis. In addition, a prognostic risk signature was developed based on two m5C regulators, NOP2/Sun RNA methyltransferase 3 (NSUN3), and NOP2/Sun RNA methyltransferase 4 (NSUN4). Compared with normal lung tissues, the expression of NSUN3 and NSUN4 in the LUSC TCGA dataset was increased, which was related to clinicopathological characteristics and survival. NSUN3 and NSUN4 were related to the infiltration of six major immune cells; especially NSUN3, which was closely related to CD8+ T cells, while NSUN4 was closely related to neutrophils. Our findings suggest that m5C regulators can predict the clinical prognosis risk and regulate the tumor immune microenvironment in LUSC.
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Project description:N6-methyladenosine (m6A) is a form of posttranscriptional modification that plays important roles in cancer including oral squamous cell carcinoma (OSCC). Most studies to date have focused on a limited number of regulators and oncogenic pathways, thus failing to provide comprehensive insight into the dynamic effects of m6A modification. In addition, the role of m6A modification in shaping immune cell infiltration in OSCC has yet to be clarified. This study was designed to assess m6A modification dynamics in OSCC and to understand how such modifications influence clinical immunotherapeutic treatment outcomes. m6A modification patterns linked with 23 m6A regulators were analyzed in 437 OSCC patients from TCGA and GEO cohorts. These patterns were then quantified through m6A score based on algorithms derived from a principal component analysis (PCA) approach. The m6A modification patterns of OSCC samples were grouped into two clusters based on the m6A regulators expression, and immune cell infiltration was linked with the 5-year survival outcomes of patients in these clusters. 1575 genes associated with OSCC patient prognosis were identified and used to re-cluster these samples into two groups. Patients in clusters exhibiting higher levels of m6A regulator expression exhibited poorer overall survival (OS), whereas patients with high m6A scores survived for longer (p < 0.001). The overall mortality rates in the groups of patients with low and high m6A scores were 55% and 40%, respectively, and the m6A score distributions in clusters of patients grouped by m6A modification patterns and gene expression further supported the link between a high m6A score and better prognostic outcomes. Immunophenoscore (IPS) values for patients in different m6A score groups suggested that the use of PD-1-specific antibodies or CTLA-4 inhibitors alone or in combination would yield superior treatment outcomes in patients in the high-m6A score group relative to the low-m6A score group. m6A modification patterns are relevant to heterogeneity in OSCC. Detailed analyses of m6A modification patterns may thus offer novel insight regarding immune cell infiltration within the OSCC tumor microenvironment, guiding novel efforts to provide patients with more effective immunotherapeutic interventions.
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Project description:N1-methyladenosine (m1A) modification is a crucial post-transcriptional regulatory mechanism of messenger RNA (mRNA) in living organisms. Few studies have focused on analysis of m1A regulators in lower-grade gliomas (LGG). We employed the Nonnegative Matrix Factorization (NMF) technique on The Cancer Genome Atlas (TCGA) dataset to categorize LGG patients into 2 groups. These groups exhibited substantial disparities in terms of both overall survival (OS) and levels of infiltrating immune cells. We collected the significantly differentially expressed immune-related genes between the 2 clusters, and performed LASSO regression analysis to obtain m1AScores, and established an m1A-related immune-related gene signature (m1A-RIGS). Next, we categorized all patients with LGG into high- and low-risk subgroups, predictive significance of m1AScore was confirmed by conducting univariate/multivariate Cox regression analyses. Additionally, we confirmed variations in immune-related cells and ssGSEA and among the high-/low-risk subcategories in the TCGA dataset. Finally, our study characterized the effects of MSR1 and BIRC5 on LGG cells utilizing Edu assay and flow cytometry to explore the effects of modulation of these genes on glioma. The results of this study suggested that m1A-RIGS may be an excellent prognostic indicator for patients with LGG, and could also promote development of novel immune-based treatment strategies for LGG. Additionally, BIRC5 and MSR1 may be potential therapeutic targets for LGG.
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Project description:Background: Oral tongue squamous cell carcinoma (OTSCC) causes over 350,000 cases annually and particularly impacts populations in developing countries. Smoking and alcohol consumption are major risk factors. Determining the role of the tumor immune microenvironment (TIME) in OTSCC outcomes can elucidate immune mechanisms behind disease progression, and can potentially identify prognostic biomarkers. Methods: We performed a retrospective study of 48 OTSCC surgical specimens from patients with tobacco and alcohol exposures. A panel of immunoregulatory cell subpopulations including T (CD3, CD4, CD8) and B (CD20) lymphocytes, dendritic cells (CD1a, CD83), macrophages (CD68), and immune checkpoint molecules programmed cell death protein 1 (PD-1) and ligand 1 (PD-L1) were analyzed using immunohistochemistry. The levels of immune effector cell subpopulations and markers were analyzed in relation to overall survival. Results: Pathological characteristics of the tumor microenvironment included inflammatory infiltrates (83.3%), desmoplasia (41.6%), and perineural invasion (50.0%). The TIME contained high levels of T cells (CD3+, CD4+, and CD8+) and B cells (CD20+), as well as immature (CD1a) and mature (CD83) dendritic cells, PD-1, and PD-L1. Higher numbers of TIME infiltrating CD3+ T cells and CD20+ B cells were predictive of better survival, while higher levels of CD83+ mature dendritic cells predicted better survival. CD3+ T cells were identified as an independent prognostic marker for OTSCC. Lastly, CD3+ T cells were strongly correlated with the number of CD8+ cells and PD-L1 expression. Conclusion: Our findings provide evidence that the TIME profile of OTSSC impacted prognosis. The high expression of CD3+ T cells and B cells are predictive of better overall survival and indicative of an immunologically active, inflammatory TIME in patients with better survival. The number of CD3+ T cells was an independent prognostic marker.
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Project description:Disorders pertaining to 5-methylcytosine (m5C) modifications are involved in the pathological process of many diseases. However, the effect of m5C on the tumorigenesis and progression of oral squamous cell carcinoma (OSCC) remains unclear. In this study, we integrated the genomic and clinical data of 558 OSCC samples to comprehensively evaluate m5C modification patterns. Based on 16 m5C methylation regulators, two m5C modification clusters were identified with distinct tumor immune microenvironment (TIME) characteristics and prognosis in OSCC. We then performed weighted gene co-expression network analysis (WGCNA) to identify m5C modification cluster-related modules. Genes in the selected module were chosen to construct the m5Cscore scoring system for evaluating m5C modification pattern in individual OSCC patients. Patients with a high m5Cscore had higher immune, stromal, and ESTIMATE scores; lower tumor purity score; lower immune activity; and higher tumor mutational burden. The overall survival rate and progression-free survival rate were markedly worse and the tumor recurrence rate was higher in OSCC patients with a high m5Cscore. Furthermore, patients with oral leukoplakia who also had a high m5Cscore had a higher risk of deterioration to OSCC. This study demonstrated that m5C modification patterns might affect the TIME in OSCC. m5Cscore may provide a new approach for predicting the prognosis and progression of OSCC.
| S-EPMC8696036 | biostudies-literature
Project description:Epigenetic regulation, particularly RNA n6 methyl adenosine (m6A) modification, plays an important role in the immune response. However, the regulatory role of m6A in the immune microenvironment in osteoarthritis (OA) remains unclear. Accordingly, we systematically studied RNA modification patterns mediated by 23 m6A regulators in 38 samples and discussed the characteristics of the immune microenvironment modified by m6A. Next, we constructed a novel OA m6A nomogram, an m6A-transcription factor-miRNA network, and a drug network. Healthy and OA samples showed distinct m6A regulatory factor expression patterns. YTHDF3 expression was upregulated in OA samples and positively correlated with type II helper cells and TGFb family member receptors. Furthermore, three different RNA modification patterns were mediated by 23 m6A regulatory factors; in Mode 3, the expression levels of YTHDF3, type II T helper cells, and TGFb family member receptors were upregulated. Pathways related to endoplasmic reticulum oxidative stress and mitochondrial autophagy showed a strong correlation with the regulatory factors associated with Mode 3 and 23 m6A regulatory factors. Through RT-qPCR we validated that SREBF2 and EGR1 as transcription factors of YTHDF3 and IGF2BP3 are closely associated with the development of OA, hsa-miR-340 as a miRNA for YTHDF3 and IGF2BP3 was involved in the development of OA, we also detected the protein expression levels of IGF2BP3, YTHDF3, EGR1 and SREBF2 by western blotting, and the results were consistent with PCR. Overall, the constructed nomogram can facilitate the prediction of OA risk.
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Project description:Osteoarthritis (OA) is a common disease in orthopedics. RNA N6-methyladenosine (m6A) exerts an essential effect in a variety of biological processes in the eukaryotes. In this study, we determined the effect of m6A regulators in the OA along with performing the subtype classification. Differential analysis of OA and normal samples in the database of Gene Expression Omnibus identified 9 significantly differentially expressed m6A regulators. These regulators were monitored by a random forest algorithm so as to evaluate the risk of developing OA disease. On the basis of these 9 moderators, a nomogram was established. The results of decision curve analysis suggested that the patients could benefit from a nomogram model. The OA sample was classified as 2 m6A models through a consensus clustering algorithm in accordance with these 9 regulators. These 2 m6A patterns were then assessed with principal component analysis. We also determined the m6A scores for the 2 m6A patterns and their correlation with immune infiltration. The results indicated that type A had a higher m6A score than type B. Thus, we suggest that the m6A pattern may provide a new approach for diagnose and provide novel ideas for molecular targeted therapy of OA.
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