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The m6A/m5C/m1A Regulated Gene Signature Predicts the Prognosis and Correlates With the Immune Status of Hepatocellular Carcinoma

ABSTRACT: RNA modification of m6A/m5C/m1A contributes to the occurrence and development of cancer. Consequently, this study aimed to investigate the functions of m6A/m5C/m1A regulated genes in the prognosis and immune microenvironment of hepatocellular carcinoma (HCC). The expression levels of 45 m6A/m5C/m1A regulated genes in HCC tissues were determined. The functional mechanisms and protein–protein interaction network of m6A/m5C/m1A regulated genes were investigated. The Cancer Genome Atlas (TCGA) HCC gene set was categorized based on 45 m6A/m5C/m1A regulated genes, and survival analysis was used to determine the relationship between the overall survival of HCC patients in subgroups. Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were used to construct the risk model and nomogram for m6A/m5C/m1A regulated genes. The relationships between m6A/m5C/m1A regulated gene subsets and risk model and immune cell infiltration were analyzed using CIBERSORT. m6A/m5C/m1A regulated genes were involved in mRNA and RNA modifications, mRNA and RNA methylation, mRNA and RNA stability, and other processes. There was a statistically significant difference between cluster1 and cluster2 groups of genes regulated by m6A/m5C/m1A. The prognosis of cluster1 patients was significantly better than that of cluster2 patients. There were statistically significant differences between the two cluster groups in terms of fustat status, grade, clinical stage, and T stage of HCC patients. The risk model comprised the overexpression of YBX1, ZC3H13, YTHDF1, TRMT10C, YTHDF2, RRP8, TRMT6, LRPPRC, and IGF2BP3, which contributed to the poor prognosis of HCC patients. The high-risk score was associated with prognosis, fustat status, grade, clinical stage, T stage, and M stage and was an independent risk factor for poor prognosis in HCC patients. High-risk score mechanisms included spliceosome, RNA degradation, and DNA replication, among others, and high-risk was closely related to stromal score, CD4 memory resting T cells, M0 macrophages, M1 macrophages, resting mast cells, CD4 memory activated T cells, and follicular helper T cells. In conclusion, the cluster subgroup and risk model of m6A/m5C/m1A regulated genes were associated with the poor prognosis and immune microenvironment in HCC and are expected to be the new tools for assessing the prognosis of HCC patients.

SUBMITTER: Li D

PROVIDER: S-EPMC9272990 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundGastric cancer (GC) is characterized by high morbidity and mortality rates, and the prognosis is not optimistic. Therefore, the search for new biomarkers is crucial. Methylation modifications in RNA modifications play a crucial role in tumors. However, the role of methylation modification of integrated m6A/m5C/m1A/m7G, in GC and its related analysis have not been reported. It still needs to be studied in depth. Our study aims to deepen our understanding of m6A/m5C/m1A/m7G methylation and potentially provide new strategies for GC treatment.MethodsWe used TCGA-STAD (The Cancer Genome Atlas-Stomach Adenocarcinoma) as a training set and GSE84433 as a validation set to analyze and determine potential associations between m6A/m5C/m1A/m7G-related genes and clinical risk of GC. In addition, we explored the prognostic value and potential biological mechanisms of m6A/m5C/m1A/m7G-related genes in GC through consistent clustering, differential expression gene identification, enrichment analysis, and immune infiltration analysis. Finally, we constructed m6A/m5C/m1A/m7G-related risk signature (MRRS) to evaluate the correlation between risk grade and survival prognosis, drug sensitivity, and immune infiltration, and validated the validity by immunohistochemical staining.ResultsWe identified subgroups of C1, C2, and C3 patients by consensus clustering using data from 45 m6A/m5C/m1A/m7G-related genes. The three groups showed significant differences in survival, immune scores, and immune cell infiltration. We then constructed MRRS using least absolute shrinkage and selection operator (LASSO) regression analysis, including SLC5A6, FKBP10, GPC3, and GGH, which could accurately differentiate between high-/low-risk populations. Its accuracy was further validated in the validation set and immunohistochemical staining. These results suggest that m6A/m5C/m1A/m7G are closely related to the GC tumor immune microenvironment, and MRRS has good performance in predicting the survival of GC patients.ConclusionsIn this study, we highlighted the association of m6A/m5C/m1A/m7G subtypes with changes in the GC immunotumor microenvironment. We constructed and validated MRRS, which is valuable in predicting survival, immune infiltration and drug sensitivity in GC patients. This helps to deepen our understanding of m6A/m5C/m1A/m7G methylation and potentially provides new strategies for GC treatment.

Project description:BackgroundIt is widely acknowledged that hypoxia and m6A/m5C/m1A RNA modifications promote the occurrence and development of tumors by regulating the tumor microenvironment. This study aimed to establish a novel liver cancer risk signature based on hypoxia and m6A/m5C/m1A modifications.MethodsWe collected data from The Cancer Genome Atlas (TCGA-LIHC), the National Omics Data Encyclopedia (NODE-HCC), the International Cancer Genome Consortium (ICGC), and the Gene Expression Omnibus (GEO) databases for our study (GSE59729, GSE41666). Using Cox regression and least absolute shrinkage and selection operator (LASSO) method, we developed a risk signature for liver cancer based on differentially expressed genes related to hypoxia and genes regulated by m6A/m5C/m1A modifications. We stratified patients into high- and low-risk groups and assessed differences between these groups in terms of gene mutations, copy number variations, pathway enrichment, stemness scores, immune infiltration, and predictive capabilities of the model for immunotherapy and chemotherapy efficacy.ResultsOur analysis revealed a significantly correlated between hypoxia and methylation as well as m6A/m5C/m1A RNA methylation. The three-gene prognosis signature (CEP55, DPH2, SMS) combining hypoxia and m6A/m5C/m1A regulated genes exhibited strong predictive performance in TCGA-LIHC, NODE-HCC, and ICGC-LIHC-JP cohorts. The low-risk group demonstrated a significantly better overall survival compared to the high-risk group (p < 0.0001 in TCGA, p = 0.0043 in NODE, p = 0.0015 in ICGC). The area under the curve (AUC) values for survival at 1, 2, and 3 years are all greater than 0.65 in the three cohorts. Univariate and Multivariate Cox regression analyses of the three datasets indicated that the signature could serve as an independent prognostic predictor (p < 0.001 in the three cohorts). The high-risk group exhibited more genome changes and higher homologous recombination deficiency scores and stemness scores. Analysis of immune infiltration and immune activation confirmed that the signature was associated with various immune microenvironment characteristics. Finally, patients in the high-risk group experienced a more favorable response to immunotherapy, and various common chemotherapy drugs.ConclusionOur prognostic signature which integrates hypoxia and m6A/m5C/m1A-regulated genes, provides valuable insights for clinical prediction and treatment guidance for liver cancer patients.

Project description:PurposeTo investigate the prognostic value of N6-methyladenosine (m6A)-, 5-methylcytosine (m5C)-, and N1-methyladenosine (m1A)-related genes in cervical cancer (CESC) and predicting immunotherapy response.MethodsWe downloaded cervical cancer mRNA expression profiles, clinical data, and m6A, m5C, m1A-related genes from public databases, and subjected them to serial bioinformatics analysis and clinical sample validation.ResultsDifferential analysis revealed 106 methylation-related differential genes (MEDs), including 44 differentially downregulated and 62 upregulated genes. We then obtained methylation models containing 10 genes by univariate and multifactorial COX analysis. High risk genes with HR > 1 include IQGAP3, PTBP1, STAC3, CUX1, SLC2A1, and CA2, and low risk genes with HR < 1 include IGBP1, DUOX1, CHAF1A, and STAC3. We verified the accuracy of the model from inside TCGA and outside GSE39001 (AUC = 0.729). K-M analysis showed shorter survival times in the High-risk group, and Immunocytic infiltration analysis showed model genes closely associated with six immune cells. The high-risk group may benefit more effectively from immunosuppressive therapy, especially anti-CTLA-4 therapy (p < .05). We also screened nine drugs for potential treatment and verified the expression of three key genes SLC2A1, CUX1, and CA2 using immunohistochemistry and RT-qPCR experiments with clinical samples.ConclusionWe identified a prognostic model using m6A/m5C/m1A-related genes in cervical cancer, which can predict survival time and correlate with immune cell infiltration. Additionally, anti-CTLA-4 may be used as an immunotherapeutic agent for cervical cancer.KEY MESSAGESCervical cancer still has a high mortality rate, we aim to establish a strong prognostic index and new treatment goals for improving patient survival.The role of three types of RNA methylation modifications, m6A, m5C, and m1A, in cervical cancer, remains unknown. Therefore, it is essential to explore the potential molecular mechanisms of m6A, m5C, and m1A methylation regulation in cervical cancer.We also screened nine drugs for potential treatment and anti-CTLA-4 may be used as an immunotherapeutic agent for cervical cancer. We verified the expression of three key genes SLC2A1, CUX1, and CA2.

Project description:RNA modifications implicate pathological and prognosis significance in cancer development and progression, of which, m6A and m5C are representative regulators. These RNA modifications could produce effects on the function of other RNA by regulating gene expression. Thus, in this study, we aimed to explore the correlation between m6A/m5C regulators and early-stage lung adenocarcinoma (LUAD). Only the early-stage LUAD samples were included in this investigation, and the RNA-seq dataset of The Cancer Genome Atlas (TCGA) cohort was utilized to evaluate the expression of 37 m6A/m5C regulated genes. Based on the expression level of these 37 genes, early-stage LUAD patients were divided into 2 clusters, which were performed by consensus clustering, and the m6A/m5C subtypes had significantly different prognostic outcomes (p < 0.001). Cluster1, which has a better prognosis, was characterized by the C3 (inflammatory) immune subtype, low immune infiltration, chemokine expression, major histocompatibility complex (MHC) expression, and immune checkpoint molecule expression. Furthermore, compared with cluster1, cluster2 showed a T cell exhaustion state, characterized by a high expression of immune checkpoint genes, and immune cells, such as T cells, CD8+ T cells, cytotoxic lymphocytes, NK cells, and so on. In addition, patients in cluster2 were with high tumor mutational burden (TMB) and numerous significant mutated oncogene and tumor suppressor genes, such as WNT10B, ERBB4, SMARCA4, TP53, and CDKN2A (p < 0.001). A total of 19 genes were mostly related to the prognosis of LUAD and were upregulated in cluster2 (p < 0.05), showing a positive correlation with the mRNA expression of 37 m6A/m5C regulated genes. The predictive risk model was constructed using Cox and LASSO (least absolute shrinkage and selection operator) regression analysis. Finally, a seven-gene m6A/m5C risk model, comprising of METTL3, NPLOC4, RBM15, YTHDF1, IGF2BP1, NSUN3, and NSUN7, was constructed to stratify the prognosis of early-stage LUAD (p = 0.0049, AUC = 0.791). The high-risk score was associated with a poorer prognosis. This model was also validated using two additional GEO datasets: GSE72094 (p = 0.011, AUC = 0.736) and GSE50081 (p = 0.012, AUC = 0.628). In summary, it was established that the m6A/m5C-regulated genes performed a crosstalk function in the mRNA expression of early-stage LUAD. By interacting with other mRNA genes, m6A/m5C modification disturbs DNA replication and the tumor immune microenvironment (TIME). The seven-gene risk model may be a critical tool for the prognostic assessment of early-stage LUAD.

Project description:IntroductionRNA modifications mediated by the m6A, m1A, and m5C regulatory genes are crucial for the progression of malignancy. This study aimed to explore the expression of regulator genes for m6A/m5C/m1A methylation at the single-cell level and to validate their expression in cancerous and adjacent para-cancerous liver tissues of adult patients with HCC who underwent tumor resection.MethodsThe bulk sequencing from The Cancer Genome Atlas (TCGA) database and the single-cell RNA sequencing (scRNA-seq) data obtained from the Gene Expression Omnibus (GEO) database were used to identify the dysregulated m6A/m5C/m1A genes for hepatocellular carcinoma (HCC). A real-time polymerase chain reaction (real-time PCR) was used to measure the expression of dysregulated m6A/m5C/m1A genes in collected human HCC tissues and compared with adjacent para-cancerous liver tissues. Immune cell infiltration with these significantly expressed methylation-related genes was evaluated using Timer2.0.ResultsA discrepancy in m6A/m5C/m1A gene expression was observed between bulk sequencing and scRNA-seq. The clustered heatmap of the scRNA-seq-identified dysregulated m6A/m5C/m1A genes in TCGA cohort revealed heterogeneous expression of these methylation regulators within the cancer, whereas their expression in the adjacent liver tissues was more homogeneous. The real-time PCR validated the significant overexpression of DNMT1, NSUN5, TRMT6, IGF2BP1, and IGFBP3, which were identified using scRNA-seq, and IGFBP2, which was identified using bulk sequencing. These dysregulated methylation genes are mainly correlated with the infiltration of natural killer cells.DiscussionThis study suggests that cellular diversity inside tumors contributes to the discrepancy in the expression of methylation regulator genes between traditional bulk sequencing and scRNA-seq. This study identified five regulatory genes that will be the focus of further studies regarding the function of m6A/m5C/m1A in HCC.

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The m6A/m5C/m1A Regulated Gene Signature Predicts the Prognosis and Correlates With the Immune Status of Hepatocellular Carcinoma

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