M5C regulator-mediated methylation modification patterns and tumor microenvironment infiltration characterization in lung adenocarcinoma

The E3 ubiquitin ligase RNF135 modulates chemotherapy resistance to oxaliplatin for colorectal cancer by modulating autophagy

BACKGROUND

RING finger protein 135 plays an important role in tumorigenesis and is associated with drug resistance.

METHODS

Bioinformatics analysis showed that RNF135 was significantly differentially expressed in colorectal cancer. RT-qPCR and western blot were used to detect the expression of RNF135. Immunohistochemical analysis were used to measure the expression of RNF135 and Ki-67.

RESULTS

The expression of RNF135 was up-regulated in human tissue samples and colorectal cancer and was positively correlated with Ki-67. Compared with oxaliplatin sensitive patients, RNF135 expression levels were higher in the tissue of resistant patients. The regulatory effect of RNF135 on colorectal cancer cells was further investigated in vitro. Therefore, inhibition of autophagy by down-regulating RNF135 can partially increase its susceptibility to oxaliplatin.

TICRR serves as a prognostic biomarker in lung adenocarcinoma with implications in RNA epigenetic modification, DDR pathway, and RNA metabolism

Purpose

TOPBP1 interacting checkpoint and replication regulator (TICRR), a hub gene of the Cdk2-mediated initiation step of DNA replication, has been shown an essential role in tumorigenesis by accelerating the DNA replication of tumor cells.

Methods

RT-qPCR was used to detect the mRNA expression of TICRR in LUAD tumors and adjacent normal tissues. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database of LUAD were acquired to analyze the critical role of TICRR expression in survival prognosis and clinicopathology characters in LUAD. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were performed using the R package. The correlation of TICRR expression with immune cell infiltration, RNA epigenetic modification, DNA damage repair (DDR) pathway, and cell metabolism of LUAD was further explored to verify significant conclusions.

Results

TICRR was significantly upregulated in most cancer types, including LUAD, lung squamous cell carcinoma (LUSC), and others. Cox regression analysis indicated the overexpression of TICRR was associated with poor survival in several cancers. In LUAD, TICRR expression was positively correlated with tumor stage and was increased in smoking, male, and high tumor mutational burden (TMB) patients. Enrichment analysis revealed that TICRR could influence tumor proliferation and prognosis via activating pathways involving cell cycle, DNA repair, DNA replication, cysteine metabolism, oxidative phosphorylation, and ubiquitin-mediated proteolysis pathways. Interestingly, high TICRR expression correlated with DDR pathway signature (34 genes), 37 m6A/m5C regulated genes, and some metabolism-regulated genes. Silencing the TICRR gene affects cysteine metabolism and modifies cancer-related pathways, with decreased cell cycle and increased B/T cell receptor signaling. Our TICRR risk model accurately predicts LUAD patient prognosis, validated across GEO datasets, and is integrated with clinical characteristics via a nomogram, facilitating personalized treatment strategies and enhancing patient management.

Conclusions

Taken together, TICRR has emerged as a promising prognostic biomarker in lung adenocarcinoma (LUAD), with implications in immune activation, cell cycle regulation, RNA modification, and tumor energy metabolism. These findings suggest that TICRR could serve as a viable therapeutic target and a reliable prognostic indicator for LUAD.

RNA m5C methylation orchestrates BLCA progression via macrophage reprogramming

Recently, epigenetics showed essential roles in tumour microenvironment (TME) and immunotherapy response, however, the functions of RNA 5-methylcytosine (m5C) modification in TME remains unknown. According to 13 m5C regulators, we evaluated 412 BLCA patients from The Cancer Genome Atlas (TCGA) database. The m5C score was constructed by unsupervised clustering analysis and principal component analysis (PCA) algorithms. Gene set variation analysis (GSVA), ESTIMATE algorithm, and immunohistochemical (IHC) staining were performed. Macrophage chemotaxis assay was used to assess the M2 macrophages. Among the 412 patients, the frequency of mutation was 13%. m5C regulators was expressed significantly in BLCA tissue compared with normal tissue. Then, two m5C methylation modification patterns were identified with dissimilar TME cell infiltration patterns. The C1 alteration pattern in the m5C cluster was connected with better survival. In addition, we found that NSUN6 was highly correlated with recruitment of macrophages via bioinformatics and IHC. Further experiment validated that NSUN6 promoted HDAC10 expression by mediating m5C methylation, inhibited the transcription of macrophage-associated chemokines and thus inhibited the recruitment of M2 macrophages. The m5C score constructed by m5C modification pattern showed that high m5C score group had a better prognosis. This study uncovered the significant roles of m5C modifications in modulating the TME and indicated that NSUN6 could inhibit the recruitment of M2 macrophages via m5C methylation, which provided novel insight into epigenetic regulation of TME and clinical suggestions for immunotherapeutic strategies.

Diagnostic value of aberrant decreased 5-Methylcytosine RNA modification in leukocytes for non-small cell lung cancer

Background: Non-small cell lung cancer (NSCLC) was a disease with poor outcomes, partly because there were no high-efficiency non-invasive diagnostic biomarkers. The RNA modification status of 5-Methylcytosine (m5C) has been shown to be a biomarker for various diseases, but its potentiality to be a diagnostic biomarker for NSCLC remained inconclusive. Methods: In this research, we collected peripheral leukocyte samples from 141 patients with NSCLC and 90 normal people as controls to evaluate the extent of m5C RNA modification. Results: We found that the m5C modification levels in leukocytes of NSCLC patients were decreased dramatically, which were compared to the normal controls, and levels of m5C modification decreased progressively with tumor stage. Importantly, m5C modification exhibited superior diagnostic value compared to carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCC), cytokeratin 19 fragment (Cyfra21-1), and carbohydrate antigen 125 (CA125), which demonstrated area under the curves (AUCs) of 0.912, 0.773, 0.669, 0.754, and 0.732, respectively. The combination of m5C modification with these serum tumor biomarkers further improved the AUC to 0.960. A nomogram model incorporating m5C modification also provided an effectively diagnostic tool for NSCLC. Conclusion: Collectively, our findings suggested that m5C modification in leukocytes held promise as a prospective biomarker for NSCLC diagnosis.

Construction of a serum diagnostic signature based on m5C-related miRNAs for cancer detection

Currently, no clinically relevant non-invasive biomarkers are available for screening of multiple cancer types. In this study, we developed a serum diagnostic signature based on 5-methylcytosine (m5C)-related miRNAs (m5C-miRNAs) for multiple-cancer detection. Serum miRNA expression data and the corresponding clinical information of patients were collected from the Gene Expression Omnibus database. Serum samples were then randomly assigned to the training or validation cohort at a 1:1 ratio. Using the identified m5C-miRNAs, an m5C-miRNA signature for cancer detection was established using a support vector machine algorithm. The constructed m5C-miRNA signature displayed excellent accuracy, and its areas under the curve were 0.977, 0.934, and 0.965 in the training cohort, validation cohort, and combined training and validation cohort, respectively. Moreover, the diagnostic capability of the m5C-miRNA signature was unaffected by patient age or sex or the presence of noncancerous disease. The m5C-miRNA signature also displayed satisfactory performance for distinguishing tumor types. Importantly, in the detection of early-stage cancers, the diagnostic performance of the m5C-miRNA signature was obviously superior to that of conventional tumor biomarkers. In summary, this work revealed the value of serum m5C-miRNAs in cancer detection and provided a new strategy for developing non-invasive and cost effective tools for large-scale cancer screening.

Analysis of m7G methylation modification patterns and pulmonary vascular immune microenvironment in pulmonary arterial hypertension

Background

M⁷G methylation modification plays an important role in cardiovascular disease development. Dysregulation of the immune microenvironment is closely related to the pathogenesis of PAH. However, it is unclear whether m⁷G methylation is involved in the progress of PAH by affecting the immune microenvironment.

Methods

The gene expression profile of PAH was obtained from the GEO database, and the m⁷G regulatory factors were analyzed for differences. Machine learning algorithms were used to screen characteristic genes, including the least absolute shrinkage and selection operator, random forest, and support vector machine recursive feature elimination analysis. Constructed a nomogram model, and receiver operating characteristic was used to evaluate the diagnosis of disease characteristic genes value. Next, we used an unsupervised clustering method to perform consistent clustering analysis on m⁷G differential genes. Used the ssGSEA algorithm to estimate the relationship between the m⁷G regulator in PAH and immune cell infiltration and analyze the correlation with disease-characteristic genes. Finally, the listed drugs were evaluated through the screened signature genes.

Results

We identified 15 kinds of m⁷G differential genes. CYFIP1, EIF4E, and IFIT5 were identified as signature genes by the machine learning algorithm. Meanwhile, two m⁷G molecular subtypes were identified by consensus clustering (cluster A/B). In addition, immune cell infiltration analysis showed that activated CD4 T cells, regulatory T cells, and type 2 T helper cells were upregulated in m⁷G cluster B, CD56 dim natural killer cells, MDSC, and monocyte were upregulated in the m⁷G cluster A. It might be helpful to select Calpain inhibitor I and Everolimus for the treatment of PAH.

Conclusion

Our study identified CYFIP1, EIF4E, and IFIT5 as novel diagnostic biomarkers in PAH. Furthermore, their association with immune cell infiltration may facilitate the development of immune therapy in PAH.

Identification of a novel m5C/m6A-related gene signature for predicting prognosis and immunotherapy efficacy in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most prevalent subtype of non-small cell lung cancer (NSCLC) and is associated with high mortality rates. However, effective methods to guide clinical therapeutic strategies for LUAD are still lacking. The goals of this study were to analyze the relationship between an m5C/m6A-related signature and LUAD and construct a novel model for evaluating prognosis and predicting drug resistance and immunotherapy efficacy. We obtained data from LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Based on the differentially expressed m5C/m6A-related genes, we identified distinct m5C/m6A-related modification subtypes in LUAD by unsupervised clustering and compared the differences in functions and pathways between different clusters. In addition, a risk model was constructed using multivariate Cox regression analysis based on prognostic m5C/m6A-related genes to predict prognosis and immunotherapy response. We showed the landscape of 36 m5C/m6A regulators in TCGA-LUAD samples and identified 29 differentially expressed m5C/m6A regulators between the normal and LUAD groups. Two m5C/m6A-related subtypes were identified in 29 genes. Compared to cluster 2, cluster 1 had lower m5C/m6A regulator expression, higher OS (overall survival), higher immune activity, and an abundance of infiltrating immune cells. Four m5C/m6A-related gene signatures consisting of HNRNPA2B1, IGF2BP2, NSUN4, and ALYREF were used to construct a prognostic risk model, and the high-risk group had a worse prognosis, higher immune checkpoint expression, and tumor mutational burden (TMB). In patients treated with immunotherapy, samples with high-risk scores had higher expression of immune checkpoint genes and better immunotherapeutic efficacy than those with low-risk scores. We concluded that the m5C/m6A regulator-related risk model could serve as an effective prognostic biomarker and predict the therapeutic sensitivity of chemotherapy and immunotherapy.

Crosstalk of Eight Types of RNA Modification Regulators Defines Tumor Microenvironments, Cancer Hallmarks, and Prognosis of Lung Adenocarcinoma

RNA modification has become an exciting underexplored field in recent years. In lung adenocarcinoma (LUAD), m⁶A was the best characterized and most studied RNA modification, while knowledge about other kinds of RNA modifications in LUAD is limited. In our study, we included a total of 100 RNA modification regulators of eight types of cancer-related RNA modifications (m⁶A, m¹A, m⁵C, Nm, m⁷G, Ψ, A-to-I, and mcm⁵s²U) to systematically profile their specific roles in LUAD. By gene mutation and expression analysis, we identified extensive dysregulations and complicated interactions of 100 RNA modification regulators in LUAD. Based on unsupervised clustering analysis, gene set variation analysis (GSVA), and single-sample gene-set enrichment analysis (ssGSEA), two RNA modification patterns in LUAD were defined to show distinct biological characteristics. The favorable prognostic pattern was enriched with infiltrated immune cells, including activated B cells, CD8 T cells, eosinophil cells, dendritic cells, and natural killer cells, while the unfavorable prognostic pattern was enriched with cancer hallmarks, including hypoxia, epithelial-mesenchymal transition (EMT), angiogenesis, PI3K-AKT-mTOR pathway, MYC pathway, and glycolysis pathway. We also constructed an RNA modification score (RMScore) based on five critical genes (CYP17A1, NTSR1, PITX3, KRT6A, and ANLN) to evaluate the RNA modification status of individual LUAD patients. RMScore was revealed to be related to the infiltrated immune cells and cancer hallmarks and was an independent prognostic factor in the TCGA-LUAD cohort and two external GEO-LUAD cohorts. Our study was the first to comprehensively investigate the dysregulations, crosstalk, and potential prognostic value of eight types of RNA modifications in LUAD. Our results highlighted the significance of eight types of RNA modifications in tumor microenvironments and cancer hallmarks and provided novel prognostic biomarkers and potential therapeutic targets in the management of LUAD patients in the future.

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.

Roles of m5C RNA Modification Patterns in Biochemical Recurrence and Tumor Microenvironment Characterization of Prostate Adenocarcinoma

Background

Prostate cancer is the second most common cancer with a high risk of biochemical recurrence (BCR) among men. Recently, 5-methylcytosine (m5C) modification has attracted more attention as a new layer of RNA post-transcriptional regulation. Hence, we aimed at investigating the potential roles of m5C modification regulators in the BCR of prostate adenocarcinoma (PRAD).

Methods

CNV data, mutation annotation data, mRNA expression profiles, and clinical data were downloaded from TCGA and GEO databases. Kaplan-Meier curves analysis, log-rank test, univariate and multivariate Cox regression, and time-dependent ROC curves analysis were performed to evaluate the prognostic factors. Principal components analysis (PCA) was applied to validate the distinction between subgroups. Gene set variation analysis (GSVA) was used to investigate the underlying pathways associated with m5C modification patterns. Single sample gene set enrichment analysis (ssGSEA) was utilized to assess the infiltration of distinct immune cells. Tumor Immune Dysfunction and Exclusion (TIDE) prediction was carried out to assess the potential response to immune checkpoint blockade (ICB) therapy. The m5C modification signature was constructed via LASSO Cox's proportional hazards regression method.

Results

After comprehensively analyzing various types of data from TCGA dataset, and exploring the differential expression and prognostic value of each m5C regulator, we identified m5C modification patterns based on 17 m5C regulators. Two patterns presented a significant difference in the risk of BCR, the tumor microenvironment (TME), and immunotherapy response in PRAD. We found that TET2, which was highly expressed in adjacent normal tissues compared to tumor tissues, was closely associated with many infiltrating immune cells. The m5C modification signature was constructed for the clinical application. Risk score calculated by m5C signature was associated with T stage, N stage, Gleason score, and the possibility of BCR (HR, 4.197; 95% CI, 3.016-5.842; p < 0.001). A higher risk score also represented the possibility of immunotherapy response. Finally, the potential roles of m5C modification signature were validated in the testing dataset.

Conclusions

Our study revealed the potential roles of m5C modification in the PRAD BCR and TME diversity, which may provide new insight into the field of prostate cancer in future research.

Role of main RNA modifications in cancer: N6-methyladenosine, 5-methylcytosine, and pseudouridine

Cancer is one of the major diseases threatening human life and health worldwide. Epigenetic modification refers to heritable changes in the genetic material without any changes in the nucleic acid sequence and results in heritable phenotypic changes. Epigenetic modifications regulate many biological processes, such as growth, aging, and various diseases, including cancer. With the advancement of next-generation sequencing technology, the role of RNA modifications in cancer progression has become increasingly prominent and is a hot spot in scientific research. This review studied several common RNA modifications, such as N⁶-methyladenosine, 5-methylcytosine, and pseudouridine. The deposition and roles of these modifications in coding and noncoding RNAs are summarized in detail. Based on the RNA modification background, this review summarized the expression, function, and underlying molecular mechanism of these modifications and their regulators in cancer and further discussed the role of some existing small-molecule inhibitors. More in-depth studies on RNA modification and cancer are needed to broaden the understanding of epigenetics and cancer diagnosis, treatment, and prognosis.

Comprehensive Analysis of 5-Methylcytosine (m5C) Regulators and the Immune Microenvironment in Pancreatic Adenocarcinoma to Aid Immunotherapy

Background

Pancreatic adenocarcinoma (PAAD) is one of the most malignant cancers and has a poor prognosis. As a critical RNA modification, 5-methylcytosine (m⁵C) has been reported to regulate tumor progression, including PAAD progression. However, a comprehensive analysis of m⁵C regulators in PAAD is lacking.

Methods

In the present study, PAAD datasets were obtained from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and ArrayExpress databases. The expression pattern of m⁵C regulators were analyzed and patients were divided into different m⁵C clusters according to consensus clustering based on m⁵C regulators. Additionally, m⁵C differentially expressed genes (DEGs) were determined using Limma package. Based on m⁵C DEGs, patients were divided into m⁵C gene clusters. Moreover, m⁵C gene signatures were derived from m⁵C DEGs and a quantitative indicator, the m⁵C score, was developed from the m⁵C gene signatures.

Results

Our study showed that m⁵C regulators were differentially expressed in patients with PAAD. The m⁵C clusters and gene clusters based on m⁵C regulators and m⁵C DEGs were related to immune cell infiltration, immune-related genes and patient survival status, indicating that m⁵C modification play a central role in regulating PAAD development partly by modulating immune microenvironment. Additionally, a quantitative indicator, the m⁵C score, was also developed and was related to a series of immune-related indicators. Moreover, the m⁵C score precisely predicted the immunotherapy response and prognosis of patients with PAAD.

Conclusion

In summary, we confirmed that m⁵C regulators regulate PAAD development by modulating the immune microenvironment. In addition, a quantitative indicator, the m⁵C score, was developed to predict immunotherapy response and prognosis and assisted in identifying PAAD patients suitable for tailored immunotherapy strategies.

Biological roles of RNA m5C modification and its implications in Cancer immunotherapy

Epigenetics including DNA and RNA modifications have always been the hotspot field of life sciences in the post-genome era. Since the first mapping of N6-methyladenosine (m⁶A) and the discovery of its widespread presence in mRNA, there are at least 160-170 RNA modifications have been discovered. These methylations occur in different RNA types, and their distribution is species-specific. 5-methylcytosine (m⁵C) has been found in mRNA, rRNA and tRNA of representative organisms from all kinds of species. As reversible epigenetic modifications, m⁵C modifications of RNA affect the fate of the modified RNA molecules and play important roles in various biological processes including RNA stability control, protein synthesis, and transcriptional regulation. Furthermore, accumulative evidence also implicates the role of RNA m⁵C in tumorigenesis. Here, we review the latest progresses in the biological roles of m⁵C modifications and how it is regulated by corresponding “writers”, “readers” and “erasers” proteins, as well as the potential molecular mechanism in tumorigenesis and cancer immunotherapy.

Immune Infiltrates of m5C RNA Methylation-Related LncRNAs in Uterine Corpus Endometrial Carcinoma

Aberrant 5-methylcytidine (m5C) modification plays an essential role in the progression of different cancers. More and more researchers are focusing on developing a lncRNA-based risk model to assess the clinical prognosis of cancer patients. However, the impact of m5C-related lncRNAs on the prognosis of patients with uterine corpus endometrial carcinoma (UCEC), as well as the immune microenvironment of UCEC, remains unclear. Here, we comprehensively analyzed the predictive value of m5C-associated lncRNAs in UCEC and their association with the tumor immune microenvironment, according to the information extracted from the TCGA-UCEC dataset. We identified a total of 32 m5C-associated lncRNAs that were significantly correlated with the prognosis of UCEC patients. Two molecular subtypes were determined by consensus clustering analysis of these 32 m5C-associated prognostic lncRNAs. Further data showed that cluster 1 was associated with poor clinical prognosis, advanced tumor grade, higher PD-L1 expression levels, higher ESTIMATEScore, and higher immuneScore, as well as the immune cell infiltration. Then, 17 m5C-associated lncRNAs with prognostic values were obtained using LASSO regression analysis. And a risk model was constructed based on these 17 lncRNAs. It was revealed that the risk model could be used as an independent factor for UCEC prognosis. In addition, patients with UCEC in the high-risk group had higher tumor grades and immune scores. The risk model based on m5C-related lncRNAs was also closely associated with infiltrating immune cells. In conclusion, our study elucidated the crucial roles of the identified m5C-related lncRNAs in the UCEC patients' prognoses, as well as in the immune microenvironment in UCEC. The results suggest that the components of risk models based on the m5C-related lncRNAs may serve as important mediators of the immune microenvironment in UCEC.

Identification of the Expression Patterns and Potential Prognostic Role of 5-Methylcytosine Regulators in Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is the most common primary liver cancer with a poor prognosis. 5-methylcytosine (m5C) modification plays a nonnegligible role in tumor pathogenesis and progression. However, little is known about the role of m5C regulators in HCC.

Methods: Based on 9 m5C regulators, the m5C modification patterns of HCC samples extracted from public databases were systematically evaluated and correlated with tumor immune and prognosis characteristics. An integrated model called the “m5Cscore” was constructed using principal component analysis, and its prognostic value was evaluated.

Results: Almost all m5C regulators were differentially expressed between HCC and normal tissues. Through unsupervised clustering, three different m5Cclusters were ultimately uncovered; these clusters were characterized by differences in prognosis, immune cell infiltration, and pathway signatures. The m5Cscore was constructed to quantify the m5C modifications of individual patients. Subsequent analysis revealed that the m5Cscore was an independent prognostic factor of HCC and could be a novel indicator to predict the prognosis of HCC.

Conclusion: This study comprehensively explored and systematically profiled the features of m5C modification in HCC. m5C modification patterns play a crucial role in the tumor immune microenvironment (TIME) and prognosis of HCC. The m5Cscore provides a more holistic understanding of m5C modification in HCC and provides a practical tool for predicting the prognosis of HCC. This study will help clinicians identify effective indicators of HCC to improve the poor prognosis of this disease.

5-Methylcytosine Related LncRNAs Reveal Immune Characteristics, Predict Prognosis and Oncology Treatment Outcome in Lower-Grade Gliomas

5-Methylcytosine (m5C) methylation is an important RNA modification pattern that can participate in oncogenesis and progression of cancers by affecting RNA stability, expression of oncogenes, and the activity of cancer signaling pathways. Alterations in the expression pattern of long non-coding RNAs (lncRNAs) are potentially correlated with abnormalities in the m5C regulation features of cancers. Our aim was to reveal the mechanisms by which lncRNAs regulated the m5C process, to explore the impact of aberrant regulation of m5C on the biological properties of lower-grade gliomas (LGG), and to optimize current therapeutic. By searching 1017 LGG samples from the Cancer Genome Atlas and Chinese Glioma Genome Atlas, we first clarified the potential impact of m5C regulators on LGG prognosis in this study and used univariate Cox analysis and least absolute shrinkage and selection operator regression to explore clinically meaningful lncRNAs. Consequently, we identified four lncRNAs, including LINC00265, CIRBP-AS1, GDNF-AS1, and ZBTB20-AS4, and established a novel m5C-related lncRNAs signature (m5CrLS) that was effective in predicting prognosis. Notably, mutation rate, WHO class II, IDH mutation, 1p/19q co-deletion and MGMT promoter methylation were increased in the low m5CrLS score group. Patients with increased m5CrLS scores mostly showed activation of tumor malignancy-related pathways, increased immune infiltrating cells, and decreased anti-tumor immune function. Besides, the relatively high expression of immune checkpoints also revealed the immunosuppressed state of patients with high m5CrLS scores. In particular, m5CrLS stratification was sensitive to assess the efficacy of LGG to temozolomide and the responsiveness of immune checkpoint blockade. In conclusion, our results revealed the molecular basis of LGG, provided valuable clues for our understanding of m5C-related lncRNAs, and filled a gap between epigenetics and tumor microenvironment.