Dataset Information

Expression and Prognostic Characteristics of m⁶ A RNA Methylation Regulators in Breast Cancer.

ABSTRACT:

Purpose

N6-methyladenosine (m⁶A) is the most prevalent modification in mRNA methylation which has a wide effect on biological functions. This study aims to figure out the efficacy of m⁶A RNA methylation regulator-based biomarkers with prognostic significance in breast cancer.

Patients and methods

The 23 RNA methylation regulators were firstly analyzed through ONCOMINE, then relative RNA-seq transcriptome and clinical data of 1,096 breast cancer samples and 112 normal tissue samples were acquired from The Cancer Gene Atlas (TCGA) database. The expressive distinction was also showed by the Gene Expression Omnibus (GEO) database. The gene expression data of m⁶A RNA regulators in human tissues were acquired from the Genotype-Tissue Expression (GTEx) database. The R v3.5.1 and other online tools such as STRING, bc-GeneExminer v4.5, Kaplan-Meier Plotter were applied for bioinformatics analysis.

Results

Results from ONCOMINE, TCGA, and GEO databases showed distinctive expression and clinical correlations of m⁶A RNA methylation regulators in breast cancer patients. The high expression of YTHDF3, ZC3H13, LRPPRC, and METTL16 indicated poor survival rate in patients with breast cancer, while high expression of RBM15B pointed to a better survival rate. Both univariate and multivariate Cox regression analyses revealed that age and risk scores were related to overall survival (OS). Univariate analysis also delineated that stage, tumor (T) status, lymph node (N) status, and metastasis (M) status were associated with OS. From another perspective, Kaplan-Meier Plotter platform showed that the relatively high expression of YTHDF3 and LRPPRC and the relatively low expression of RBM15B, ZC3H13, and METTL16 in breast cancer patients had worse Relapse-Free Survival (RFS). Breast Cancer Gene-Expression Miner v4.5 showed that LRPPRC level was negatively associated with ER and PR expression, while METTL16, RBM15B, ZC3H13 level was positively linked with ER and PR expression. In HER-2 (+) breast cancer patients, the expression of LRPPRC, METTL16, RBM15B, and ZC3H13 were all lower than the HER-2 (-) group.

Conclusion

The significant difference in expression levels and prognostic value of m⁶A RNA methylation regulators were analyzed and validated in this study. This signature revealed the potential therapeutic value of m⁶A RNA methylation regulators in breast cancer.

SUBMITTER: Zhang B

PROVIDER: S-EPMC7758326 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Expression and Prognostic Characteristics of m<sup>6</sup> A RNA Methylation Regulators in Breast Cancer.

Zhang Bo B Gu Yanlin Y Jiang Guoqin G

Frontiers in genetics 20201210

<h4>Purpose</h4>N6-methyladenosine (m<sup>6</sup>A) is the most prevalent modification in mRNA methylation which has a wide effect on biological functions. This study aims to figure out the efficacy of m<sup>6</sup>A RNA methylation regulator-based biomarkers with prognostic significance in breast cancer.<h4>Patients and methods</h4>The 23 RNA methylation regulators were firstly analyzed through ONCOMINE, then relative RNA-seq transcriptome and clinical data of 1,096 breast cancer samples and 11 ...[more]

PMID: 33362863

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Project description:The significance of N6-methyladenosine (m6A) RNA modifications in the progression of breast cancer (BC) has been recognised. However, their potential role and mechanism of action in the tumour microenvironment (TME) and immune response has not been demonstrated. Thus, the role of m6A regulators and their downstream target gene components in BC remain to be explored. In this study, we used a series of bioinformatics methods and experiments to conduct exploratory research on the possible role of m6A regulators in BC. First, two regulatory modes of immune activation and inactivation were determined by tumour classification. The TME, immune cell infiltration, and gene set variation analysis results confirmed the reliability of this pattern. The prognostic model of the m6A regulator was established by the least absolute shrinkage and selection operator and univariate and multivariate Cox analyses, with the two regulators most closely related to survival verified by real-time quantitative reverse transcription polymerase chain reaction. Next, the prognostic m6A regulator identified in the model was crossed with the differential copy number of variant genes in invasive BC (IBC), and it was determined that YTHDF1 was a hub regulator. Subsequently, single-cell analysis revealed the expression patterns of m6A regulators in different IBC cell populations and found that YTHDF1 had significantly higher expression in immune-related IBC cells. Therefore, we selected the intersection of the BC differential expression gene set and the differential expression gene set of a cell line with knocked-down YTHDF1 in literature to identify downstream target genes of YTHDF1, in which we found IFI6, EIR, and SPTBN1. A polymerase chain reaction was conducted to verify the results. Finally, we confirmed the role of YTHDF1 as a potential prognostic biomarker through pan-cancer analysis. Furthermore, our findings revealed that YTHDF1 can serve as a new molecular marker for BC immunotherapy.

Project description:N7-methylguanosine (m7G) modification on internal RNA positions plays a vital role in several biological processes. Recent research shows m7G modification is associated with multiple cancers. However, in hepatocellular carcinoma (HCC), its implications remain to be determined. In this place, we need to interrogate the mRNA patterns for 29 key regulators of m7G RNA modification and assess their prognostic value in HCC. Initial, the details from The Cancer Genome Atlas (TCGA) database concerning transcribed gene data and clinical information of HCC patients were inspected systematically. Second, according to the mRNA profiles of 29 m7G RNA methylation regulators, two clusters (named 1 and 2, respectively) were identified by consensus clustering. Furthermore, robust risk signature for seven m7G RNA modification regulators was constructed. Last, we used the Gene Expression Omnibus (GEO) dataset to validate the prognostic associations of the seven-gene risk signature. We figured out that 24/29 key regulators of m7G RNA modification varied remarkably in their grades of expression between the HCC and the adjacent tumor control tissues. Cluster one compared with cluster two had a substandard prognosis and was also positively correlated with T classification (T), pathological stage, and vital status (fustat) significantly. Consensus clustering results suggested the expression pattern of m7G RNA modification regulators was correlated with the malignancy of HCC strongly. In addition, cluster one was extensively enriched in metabolic-related pathways. Seven optimal genes (METTL1, WDR4, NSUN2, EIF4E, EIF4E2, NCBP1, and NCBP2) were selected to establish the risk model for HCC. Indicating by further analyses and validation, the prognostic model has fine anticipating command and this probability signature might be a self supporting presage factor for HCC. Finally, a new prognostic nomogram based on age, gender, pathological stage, histological grade, and prospects were established to forecast the prognosis of HCC patients accurately. In essence, we detected association of HCC severity and expression levels of m7G RNA modification regulators, and developed a risk score model for predicting prognosis of HCC patients' progression.

Project description:PurposeThe m5C RNA methylation regulators are closely related to tumor proliferation, occurrence, and metastasis. This study aimed to investigate the gene expression, clinicopathological characteristics, and prognostic value of m5C regulators in triple-negative breast cancer (TNBC) and their correlation with the tumor immune microenvironment (TIM).MethodsThe TNBC data, Luminal BC data and HER2 positive BC data set were obtained from The Cancer Genome Atlas and Gene Expression Omnibus, and 11 m5C RNA methylation regulators were analyzed. Univariate Cox regression and the least absolute shrinkage and selection operator regression models were used to develop a prognostic risk signature. The UALCAN and cBioportal databases were used to analyze the gene characteristics and gene alteration frequency of prognosis-related m5C RNA methylation regulators. Gene set enrichment analysis was used to analyze cellular pathways enriched by prognostic factors. The Tumor Immune Single Cell Hub (TISCH) and Timer online databases were used to explore the relationship between prognosis-related genes and the TIM.ResultsMost of the 11 m5C RNA methylation regulators were differentially expressed in TNBC and normal samples. The prognostic risk signature showed good reliability and an independent prognostic value. Prognosis-related gene mutations were mainly amplified. Concurrently, the NOP2/Sun domain family member 2 (NSUN2) upregulation was closely related to spliceosome, RNA degradation, cell cycle signaling pathways, and RNA polymerase. Meanwhile, NSUN6 downregulation was related to extracellular matrix receptor interaction, metabolism, and cell adhesion. Analysis of the TISCH and Timer databases showed that prognosis-related genes affected the TIM, and the subtypes of immune-infiltrating cells differed between NSUN2 and NSUN6.ConclusionRegulatory factors of m5C RNA methylation can predict the clinical prognostic risk of TNBC patients and affect tumor development and the TIM. Thus, they have the potential to be a novel prognostic marker of TNBC, providing clues for understanding the RNA epigenetic modification of TNBC.

Project description:Background: N6-methyladenosine (m6A) RNA methylation is dynamically and reversibly regulated by methyl-transferases ("writers"), binding proteins ("readers"), and demethylases ("erasers"). The m6A is restored to adenosine and thus to achieve demethylation modification. The abnormality of m6A epigenetic modification in cancer has been increasingly attended. However, we are rarely aware of its diagnostic, progressive and prognostic performance in lung adenocarcinoma (LUAD). Methods and Results: The expression of 13 widely reported m6A RNA regulators in LUAD and normal samples were systematically analyzed. There were 12 m6A RNA methylation genes displaying aberrant expressions, and an 11-gene diagnostic score model was finally built (Diagnostic score =0.033*KIAA1429+0.116*HNRNPC+0.115*RBM15-0.067* METTL3-0.048*ZC3H13-0.221*WTAP+0.213*YTHDF1-0.132*YTHDC1-0.135* FTO+0.078*YTHDF2+0.014*ALKBH5). Receiver operating characteristic (ROC) analysis was performed to demonstrate superiority of the diagnostic score model (Area under the curve (AUC) was 0.996 of training cohort, P<0.0001; AUC was 0.971 of one validation cohort-GSE75037, P<0.0001; AUC was 0.878 of another validation cohort-GSE63459, P<0.0001). In both training and validation cohorts, YTHDC2 was associated with tumor stage (P<0.01), while HNRNPC was up expressed in progressed tumor (P<0.05). Besides, WTAP, RBM15, KIAA1429, YTHDF1, and YTHDF2 were all up expressed for TP53 mutation. Furthermore, using least absolute shrinkage and selection operator (lasso) regression analysis, a ten-gene risk score model was built. Risk score=0.169*ALKBH5-0.159*FTO+0.581*HNRNPC-0.348* YTHDF2-0.265*YTHDF1-0.123*YTHDC2+0.434*RBM15+0.143*KIAA1429-0.200*WTAP-0.310*METTL3. There existed correlation between the risk score and TNM stage (P<0.01), lymph node stage (P<0.05), gender (P<0.05), living status (P<0.001). Univariate and multivariate Cox regression analyses of relevant clinicopathological characters and the risk score revealed risk score was an independent risk factor of lung adenocarcinoma (HR: 2.181, 95%CI (1.594-2.984), P<0.001). Finally, a nomogram was built to facilitate clinicians to predict outcome. Conclusions: m6A epigenetic modification took part in the progression, and provided auxiliary diagnosis and prognosis of LUAD.

Dataset Information

Expression and Prognostic Characteristics of m⁶ A RNA Methylation Regulators in Breast Cancer.

Purpose

Patients and methods

Results

Conclusion

Publications

Expression and Prognostic Characteristics of m<sup>6</sup> A RNA Methylation Regulators in Breast Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Expression and Prognostic Characteristics of m6 A RNA Methylation Regulators in Breast Cancer.

Purpose

Patients and methods

Results

Conclusion

Publications

Expression and Prognostic Characteristics of m<sup>6</sup> A RNA Methylation Regulators in Breast Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Expression and Prognostic Characteristics of m⁶ A RNA Methylation Regulators in Breast Cancer.