The Impact of m1A Methylation Modification Patterns on Tumor Immune Microenvironment and Prognosis in Oral Squamous Cell Carcinoma

Development of m6A/m5C/m1A regulated lncRNA signature for prognostic prediction, personalized immune intervention and drug selection in LUAD

Research indicates that there are links between m6A, m5C and m1A modifications and the development of different types of tumours. However, it is not yet clear if these modifications are involved in the prognosis of LUAD. The TCGA-LUAD dataset was used as for signature training, while the validation cohort was created by amalgamating publicly accessible GEO datasets including GSE29013, GSE30219, GSE31210, GSE37745 and GSE50081. The study focused on 33 genes that are regulated by m6A, m5C or m1A (mRG), which were used to form mRGs clusters and clusters of mRG differentially expressed genes clusters (mRG-DEG clusters). Our subsequent LASSO regression analysis trained the signature of m6A/m5C/m1A-related lncRNA (mRLncSig) using lncRNAs that exhibited differential expression among mRG-DEG clusters and had prognostic value. The model's accuracy underwent validation via Kaplan-Meier analysis, Cox regression, ROC analysis, tAUC evaluation, PCA examination and nomogram predictor validation. In evaluating the immunotherapeutic potential of the signature, we employed multiple bioinformatics algorithms and concepts through various analyses. These included seven newly developed immunoinformatic algorithms, as well as evaluations of TMB, TIDE and immune checkpoints. Additionally, we identified and validated promising agents that target the high-risk mRLncSig in LUAD. To validate the real-world expression pattern of mRLncSig, real-time PCR was carried out on human LUAD tissues. The signature's ability to perform in pan-cancer settings was also evaluated. The study created a 10-lncRNA signature, mRLncSig, which was validated to have prognostic power in the validation cohort. Real-time PCR was applied to verify the actual manifestation of each gene in the signature in the real world. Our immunotherapy analysis revealed an association between mRLncSig and immune status. mRLncSig was found to be closely linked to several checkpoints, such as IL10, IL2, CD40LG, SELP, BTLA and CD28, which could be appropriate immunotherapy targets for LUAD. Among the high-risk patients, our study identified 12 candidate drugs and verified gemcitabine as the most significant one that could target our signature and be effective in treating LUAD. Additionally, we discovered that some of the lncRNAs in mRLncSig could play a crucial role in certain cancer types, and thus, may require further attention in future studies. According to the findings of this study, the use of mRLncSig has the potential to aid in forecasting the prognosis of LUAD and could serve as a potential target for immunotherapy. Moreover, our signature may assist in identifying targets and therapeutic agents more effectively.

Histone lactylation-boosted ALKBH3 potentiates tumor progression and diminished promyelocytic leukemia protein nuclear condensates by m1A demethylation of SP100A

Albeit N1-Methyladenosine (m1A) RNA modification represents an important regulator of RNA metabolism, the role of m1A modification in carcinogenesis remains enigmatic. Herein, we found that histone lactylation enhances ALKBH3 expression and simultaneously attenuates the formation of tumor-suppressive promyelocytic leukemia protein (PML) condensates by removing the m1A methylation of SP100A, promoting the malignant transformation of cancers. First, ALKBH3 is specifically upregulated in high-risk ocular melanoma due to excessive histone lactylation levels, referring to m1A hypomethylation status. Moreover, the multiomics analysis subsequently identified that SP100A, a core component for PML bodies, serves as a downstream candidate target for ALKBH3. Therapeutically, the silencing of ALKBH3 exhibits efficient therapeutic efficacy in melanoma both in vitro and in vivo, which could be reversed by the depletion of SP100A. Mechanistically, we found that YTHDF1 is responsible for recognition of the m1A methylated SP100A transcript, which increases its RNA stability and translational efficacy. Conclusively, we initially demonstrated that m1A modification is necessary for tumor suppressor gene expression, expanding the current understandings of dynamic m1A function during tumor progression. In addition, our results indicate that lactylation-driven ALKBH3 is essential for the formation of PML nuclear condensates, which bridges our knowledge of m1A modification, metabolic reprogramming, and phase-separation events.

Oral squamous cell carcinoma gene patterns connected with RNA methylation for prognostic prediction

OBJECTIVES

To determine whether m6A/m1A/m5C/m7G/m6Am/Ψ-related genes influence the prognosis of a patient with oral squamous cell carcinoma.

MATERIALS AND METHODS

We investigated the changes in regulatory genes using publicly available data from The Cancer Genome Atlas. Consensus clustering by RNA methylation-related regulators was used to describe oral squamous cell carcinomas (OSCCs). Then, we developed the prediction model. The tumor microenvironment was investigated using ESTIMATE. Gene set enrichment analysis was used to determine whether pathways or cell types were enriched in different groups. The association between the model and immune-related risk scores was investigated using correlation analysis.

RESULTS

We found 22 gene signatures in this analysis and then developed a predictive model that reveals the genes that are highly connected to the overall survival of OSCC patients. The survival and death rates were substantially different in the two groups (high and low risk) classified by the risk scores. The validation cohort verified the phenotypic diversity and prognostic effects of these genes.

CONCLUSION

Our data reveal that immune cell infiltration, genetic mutation, and survival potential in OSCC patients are linked to m6A/m1A/m5C/m7G/m6Am/Ψ-related genes, and we constructed a dependable prognostic model for OSCC patients.

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

Background

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

Methods

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

Results

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

Conclusion

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

m1A Regulatory gene signatures are associated with certain immune cell compositions of the tumor microenvironment and predict survival in kidney renal clear cell carcinoma

Adenosine N1 methylation (m1A) of RNA, a type of post-transcriptional modification, has been shown to play a significant role in the progression of cancer. The objective of the current research was to analyze the genetic alteration and prognostic significance of m1A regulators in kidney renal clear cell carcinoma (KIRC). Genomic and clinicopathological characteristics were obtained from 558 KIRC patients in the Cancer Genome Atlas (TCGA) and Gene Omnibus Expression (GEO) databases. Alterations in the gene expression of ten m1A-regulators were analyzed and survival analysis was performed using the Cox regression method. We also identified three clusters of patients based on their distinct m1A alteration patterns, using integrated analysis of the ten m1A-related regulators, which were significantly related to overall survival (OS), disease-free survival (DFS) and tumor microenvironment (TME) immune cell infiltration cells in KIRC. Our findings showed that m1A alteration patterns have critical roles in determining TME complexity and its immune cell composition. Furthermore, different m1A expression patterns were significantly associated with DFS and OS rates in KIRC patients. In conclusion, the identified m1A RNA modification patterns offer a potentially effective way to classify KIRC patients based on their TME immune cell infiltration, enabling the development of more personalized and successful treatment strategies for these patients.

Predicting response of immunotherapy and targeted therapy and prognosis characteristics for renal clear cell carcinoma based on m1A methylation regulators

In recent years, RNA methylation modification has been found to be related to a variety of tumor mechanisms, such as rectal cancer. Clear cell renal cell carcinoma (ccRCC) is most common in renal cell carcinoma. In this study, we get the RNA profiles of ccRCC patients from ArrayExpress and TCGA databases. The prognosis model of ccRCC was developed by the least absolute shrinkage and selection operator (LASSO) regression analysis, and the samples were stratified into low-high risk groups. In addition, our prognostic model was validated through the receiver operating characteristic curve (ROC). "pRRophetic" package screened five potential small molecule drugs. Protein interaction networks explore tumor driving factors and drug targeting factors. Finally, polymerase chain reaction (PCR) was used to verify the expression of the model in the ccRCC cell line. The mRNA matrix in ArrayExpress and TCGA databases was used to establish a prognostic model for ccRCC through LASSO regression analysis. Kaplan Meier analysis showed that the overall survival rate (OS) of the high-risk group was poor. ROC verifies the reliability of our model. Functional enrichment analysis showed that there was a obviously difference in immune status between the high-low risk groups. "pRRophetic" package screened five potential small molecule drugs (A.443654, A.770041, ABT.888, AG.014699, AMG.706). Protein interaction network shows that epidermal growth factor receptor [EGRF] and estrogen receptor 1 [ESR1] are tumor drivers and drug targeting factors. To further analyze the differential expression and pathway correlation of the prognosis risk model species. Finally, polymerase chain reaction (PCR) showed the expression of YTHN6-Methyladenosine RNA Binding Protein 1[YTHDF1], TRNA Methyltransferase 61B [TRMT61B], TRNA Methyltransferase 10C [TRMT10C] and AlkB Homolog 1[ALKBH1] in ccRCC cell lines. To sum up, the prognosis risk model we created not only has good predictive value, but also can provide guidance for accurately predicting the prognosis of ccRCC.

RNA modifications in cancer

Currently, more than 170 modifications have been identified on RNA. Among these RNA modifications, various methylations account for two-thirds of total cases and exist on almost all RNAs. Roles of RNA modifications in cancer are garnering increasing interest. The research on m6A RNA methylation in cancer is in full swing at present. However, there are still many other popular RNA modifications involved in the regulation of gene expression post-transcriptionally besides m6A RNA methylation. In this review, we focus on several important RNA modifications including m1A, m5C, m7G, 2'-O-Me, Ψ and A-to-I editing in cancer, which will provide a new perspective on tumourigenesis by peeking into the complex regulatory network of epigenetic RNA modifications, transcript processing, and protein translation.

Novel insight into RNA modifications in tumor immunity: Promising targets to prevent tumor immune escape

An immunosuppressive state is a typical feature of the tumor microenvironment. Despite the dramatic success of immune checkpoint inhibitor (ICI) therapy in preventing tumor cell escape from immune surveillance, primary and acquired resistance have limited its clinical use. Notably, recent clinical trials have shown that epigenetic drugs can significantly improve the outcome of ICI therapy in various cancers, indicating the importance of epigenetic modifications in immune regulation of tumors. Recently, RNA modifications (N⁶-methyladenosine [m⁶A], N¹-methyladenosine [m¹A], 5-methylcytosine [m⁵C], etc.), novel hotspot areas of epigenetic research, have been shown to play crucial roles in protumor and antitumor immunity. In this review, we provide a comprehensive understanding of how m⁶A, m¹A, and m⁵C function in tumor immunity by directly regulating different immune cells as well as indirectly regulating tumor cells through different mechanisms, including modulating the expression of immune checkpoints, inducing metabolic reprogramming, and affecting the secretion of immune-related factors. Finally, we discuss the current status of strategies targeting RNA modifications to prevent tumor immune escape, highlighting their potential.

Epigenetic regulation in the tumor microenvironment: molecular mechanisms and therapeutic targets

Over decades, researchers have focused on the epigenetic control of DNA-templated processes. Histone modification, DNA methylation, chromatin remodeling, RNA modification, and noncoding RNAs modulate many biological processes that are crucial to the development of cancers. Dysregulation of the epigenome drives aberrant transcriptional programs. A growing body of evidence suggests that the mechanisms of epigenetic modification are dysregulated in human cancers and might be excellent targets for tumor treatment. Epigenetics has also been shown to influence tumor immunogenicity and immune cells involved in antitumor responses. Thus, the development and application of epigenetic therapy and cancer immunotherapy and their combinations may have important implications for cancer treatment. Here, we present an up-to-date and thorough description of how epigenetic modifications in tumor cells influence immune cell responses in the tumor microenvironment (TME) and how epigenetics influence immune cells internally to modify the TME. Additionally, we highlight the therapeutic potential of targeting epigenetic regulators for cancer immunotherapy. Harnessing the complex interplay between epigenetics and cancer immunology to develop therapeutics that combine thereof is challenging but could yield significant benefits. The purpose of this review is to assist researchers in understanding how epigenetics impact immune responses in the TME, so that better cancer immunotherapies can be developed.

The m6A/m5C/m1A regulator genes signature reveals the prognosis and is related with immune microenvironment for hepatocellular carcinoma

BACKGROUND

RNA methylation is a crucial in many biological functions, and its aberrant regulation is associated with cancer progression. N6-Methyladenosine (m6A), 5-Methylcytosine (m5C), N1-methyladenosine (m1A) are common modifications of RNA methylation. However, the effect of methylation of m6A/m5C/m1A in hepatocellular carcinoma (HCC) remains unclear.

METHOD

The transcriptome datasets, clinic information, and mutational data of 48 m6A/m5C/m1A regulator genes were acquired from the TCGA database, and the prognostic hazard model was established by univariate and Least absolute shrinkage and selection operator (Lasso) regression. The multivariate regression was performed to determine whether the risk score was an independent prognostic indicator. Kaplan-Meier survival analysis and ROC curve analysis were used to evaluate the predictive ability of the risk model. Decision curve analysis（DCA）analysis was conducted to estimate the clinical utility of the risk model. We further analyzed the association between risk score and functional enrichment, tumor immune microenvironment, and somatic mutation.

RESULT

The four-gene (YTHDF1, YBX1, TRMT10C, TRMT61A) risk signature was constructed. The high-risk group had shorter overall survival (OS) than the low-risk group. Univariate and multivariate regression analysis indicated that risk score was an independent prognostic indicator. Risk scores in male group, T3 + T4 group and Stage III + IV group were higher in female group, T1 + T2 group and stage I + II group. The AUC values for 1-, 2-, and 3-year OS in the TCGA dataset were 0.764, 0.693, and 0.689, respectively. DCA analysis showed that the risk score had a higher clinical net benefit in 1- and 2-year OS than other clinical features.The risk score was positively related to some immune cell infiltration and most immune checkpoints.

CONCLUSION

We developed a novel m6A/m5C/m1A regulator genes' prognostic model, which could be applied as a latent prognostic tool for HCC and might guide the choice of immunotherapies.

Genetic and epigenetic defects of the RNA modification machinery in cancer

Cancer was initially considered to be an exclusively genetic disease, but an interplay of dysregulated genetic and epigenetic mechanisms is now known to contribute to the cancer phenotype. More recently, chemical modifications of RNA molecules - the so-called epitranscriptome - have been found to regulate various aspects of RNA function and homeostasis. Specific enzymes, known as RNA-modifying proteins (RMPs), are responsible for depositing, removing, and reading chemical modifications in RNA. Intensive investigations in the epitranscriptomic field in recent years, in conjunction with great technological advances, have revealed the critical role of RNA modifications in regulating numerous cellular pathways. Furthermore, growing evidence has revealed that RNA modification machinery is often altered in human cancers, highlighting the enormous potential of RMPs as pharmacological targets or diagnostic markers.

N1-methyladenosine modification in cancer biology: current status and future perspectives

Post-transcriptional modifications in RNAs regulate their biological behaviors and functions. N¹-methyladenosine (m¹A), which is dynamically regulated by writers, erasers and readers, has been found as a reversible modification in tRNA, mRNA, rRNA and long non-coding RNA (lncRNA). m¹A modification has impacts on the RNA processing, structure and functions of targets. Increasing studies reveal the critical roles of m¹A modification and its regulators in tumorigenesis. Due to the positive relevance between m¹A and cancer development, targeting m¹A modification and m¹A-related regulators has been of attention. In this review, we summarized the current understanding of m¹A in RNAs, covering the modulation of m¹A modification in cancer biology, as well as the possibility of targeting m¹A modification as a potential target for cancer diagnosis and therapy.

Regulation of epigenetic modifications in the head and neck tumour microenvironment

Head and neck tumours are common malignancies that are associated with high mortality. The low rate of early diagnosis and the high rates of local recurrence and distant metastasis are the main reasons for treatment failure. Recent studies have established that the tumour microenvironment (TME) can affect the proliferation and metastasis of head and neck tumours via several mechanisms, including altered expressions of certain genes and cytokines. Increasing evidence has shown that epigenetic modifications, such as DNA methylation, histone modification, RNA modification, and non-coding RNAs, can regulate the head and neck TME and thereby influence tumour development. Epigenetic modifications can regulate the expression of different genes and subsequently alter the TME to affect the progression of head and neck tumours. In addition, the cell components in the TME are regulated by epigenetic modifications, which, in turn, affect the behaviour of head and neck tumour cells. In this review, we have discussed the functions of epigenetic modifications in the head and neck TME. We have further examined the roles of such modifications in the malignancy and metastasis of head and neck tumours.

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures

Increasing evidence has implicated the modification of 7-methylguanosine (m7G), a type of RNA modification, in tumor progression. However, no comprehensive analysis to date has summarized the predicted role of m7G-related gene signatures in lung adenocarcinoma (LUAD). Herein, we aimed to develop a novel prognostic model in LUAD based on m7G-related gene signatures. The LUAD transcriptome profiling data and corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) and two Gene Expression Omnibus datasets. After screening, we first obtained 29 m7G-related genes, most of which were upregulated in tumor tissues and negatively associated with overall survival (OS). According to the expression similarity of m7G-related genes, the combined samples from the TCGA-LUAD and GSE68465 datasets were further classified as two clusters that exhibit distinct OS rates and genetic heterogeneity. Then, we constructed a novel prognostic model involving four genes by using 130 differentially expressed genes among the two clusters. The combined samples were randomly divided into a training cohort and an internal validation cohort in a 1:1 ratio, and the GSE72094 dataset was used as an external validation cohort. The samples were divided into high- and low-risk groups. We demonstrated that a higher risk score was an independent negative prognostic factor and predicted poor OS. A nomogram was further constructed to better predict the survival of LUAD patients. Functional enrichment analyses indicated that cell cycle and DNA replication-related biological processes and pathways were enriched in the high-risk group. More importantly, the low-risk group had greater infiltration and enrichment of most immune cells, as well as higher ESTIMATE, immune, and stromal scores. In addition, the high-risk group had a lower TIDE score and higher expressions of most immune checkpoint-related genes. We finally noticed that patients in the high-risk group were more sensitive to chemotherapeutic agents commonly used in LUAD. In conclusion, we herein summarized for the first time the alterations and prognostic role of m7G-related genes in LUAD and then constructed a prognostic model based on m7G-related gene signatures that could accurately and stably predict survival and guide individualized treatment decision-making in LUAD patients.

N1-Methyladenosine (m1A) Regulation Associated With the Pathogenesis of Abdominal Aortic Aneurysm Through YTHDF3 Modulating Macrophage Polarization

Objectives

This study aimed to identify key AAA-related m1A RNA methylation regulators and their association with immune infiltration in AAA. Furthermore, we aimed to explore the mechanism that m1A regulators modulate the functions of certain immune cells as well as the downstream target genes, participating in the progression of AAA.

Methods

Based on the gene expression profiles of the GSE47472 and GSE98278 datasets, differential expression analysis focusing on m1A regulators was performed on the combined dataset to identify differentially expressed m1A regulatory genes (DEMRGs). Additionally, CIBERSORT tool was utilized in the analysis of the immune infiltration landscape and its correlation with DEMRGs. Moreover, we validated the expression levels of DEMRGs in human AAA tissues by real-time quantitative PCR (RT-qPCR). Immunofluorescence (IF) staining was also applied in the validation of cellular localization of YTHDF3 in AAA tissues. Furthermore, we established LPS/IFN-γ induced M1 macrophages and ythdf3 knockdown macrophages in vitro, to explore the relationship between YTHDF3 and macrophage polarization. At last, RNA immunoprecipitation-sequencing (RIP-Seq) combined with PPI network analysis was used to predict the target genes of YTHDF3 in AAA progression.

Results

Eight DEMRGs were identified in our study, including YTHDC1, YTHDF1-3, RRP8, TRMT61A as up-regulated genes and FTO, ALKBH1 as down-regulated genes. The immune infiltration analysis showed these DEMRGs were positively correlated with activated mast cells, plasma cells and M1 macrophages in AAA. RT-qPCR analysis also verified the up-regulated expression levels of YTHDC1, YTHDF1, and YTHDF3 in human AAA tissues. Besides, IF staining result in AAA adventitia indicated the localization of YTHDF3 in macrophages. Moreover, our in-vitro experiments found that the knockdown of ythdf3 in M0 macrophages inhibits macrophage M1 polarization but promotes macrophage M2 polarization. Eventually, 30 key AAA-related target genes of YTHDF3 were predicted, including CD44, mTOR, ITGB1, STAT3, etc.

Conclusion

Our study reveals that m1A regulation is significantly associated with the pathogenesis of human AAA. The m1A “reader,” YTHDF3, may participate in the modulating of macrophage polarization that promotes aortic inflammation, and influence AAA progression by regulating the expression of its target genes.

Prognostic value of tumor-stroma ratio in oral carcinoma: role of cancer associated fibroblasts

OBJECTIVE

Tumor-stroma Ratio(TSR) is a promising parameter representing the abundance of the stroma which has been validated in many solid tumors. However, it is still not clear which part of stroma mainly contribute to the prognostic value of TSR. The aim of this study is to confirm the prognostic value of TSR in a large cohort of oral squamous cell carcinoma (OSCC) and further demonstrated that cancer associated fibroblasts (CAFs)-stroma ratio (CSR) contributed to the prognostic value of TSR.

MATERIALS AND METHODS

TSR was evaluated on hematoxylin and eosin-stained tissue samples from 581 patients with OSCC, which divides patients into high (>50%) and low (<50%) stroma. Then, CSR was estimated on immunohistochemical staining slides of 100 patients selected from 581patients.

RESULTS

In multivariate analysis, TSR was identified as an independent prognostic factor for disease-free survival (DFS) (P < 0.001) and oral cancer-specific survival (OCSS) (P < 0.001). The interaction term reached statistical significance for histological grade for DFS and OCSS separately. Furthermore, the high-stroma group had a higher CSR than the low-stroma group.

CONCLUSION

The prognostic value of TSR is validated in OSCC particularly in moderate and high differentiation. And CSR palys its part in the prognosis of TSR.

The RNA Methylation Modification 5-Methylcytosine Impacts Immunity Characteristics, Prognosis and Progression of Oral Squamous Cell Carcinoma by Bioinformatics Analysis

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.