Dataset Information

RNAMethyPro: a biologically conserved signature of N6-methyladenosine regulators for predicting survival at pan-cancer level.

ABSTRACT: Accumulating evidence indicates the role of N 6-methyladenosine (m6A) regulator-mediated RNA methylation in cancer progression and metastasis; yet its potential clinical significance, if any, remains unclear. In this first-of-its-kind study, we systematically evaluated the role of m6A regulators as potential disease biomarkers based on comprehensive analysis of gene expression profiles of 9770 cancer cell lines and clinical specimens from 25 publicly available datasets, encompassing 13 human cancers. We developed and established RNAMethyPro-a gene expression signature of seven m6A regulators, which robustly predicted patient survival in multiple human cancers. Pan-cancer analysis identified activated epithelial-mesenchymal transition (EMT), as a highly conserved pathway in high-risk patients predicted by RNAMethyPro in 10 of the 13 cancer types. A network-based analysis revealed an intimate functional interplay between m6A regulators and EMT-associated factors via druggable targets such as XPO1 and NTRK1. Finally, the clinical significance of RNAMethyPro was further exemplified in colorectal cancer, where high-risk patients demonstrated strong associations with a mesenchymal subtype, activated stromal infiltration, and poor therapeutic response to targeted anti-EGFR therapy. In summary, RNAMethyPro is a novel, EMT-associated prognostic gene-expression signature in multiple human cancers and may offer an important clinical decision-making tool in the future.

SUBMITTER: Kandimalla R

PROVIDER: S-EPMC6494854 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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RNAMethyPro: a biologically conserved signature of N6-methyladenosine regulators for predicting survival at pan-cancer level.

Kandimalla Raju R Gao Feng F Li Ying Y Huang Hao H Ke Jia J Deng Xin X Zhao Linjie L Zhou Shengtao S Goel Ajay A Wang Xin X

NPJ precision oncology 20190501

Accumulating evidence indicates the role of N 6-methyladenosine (m6A) regulator-mediated RNA methylation in cancer progression and metastasis; yet its potential clinical significance, if any, remains unclear. In this first-of-its-kind study, we systematically evaluated the role of m6A regulators as potential disease biomarkers based on comprehensive analysis of gene expression profiles of 9770 cancer cell lines and clinical specimens from 25 publicly avail ...[more]

PMID: 31069256

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Project description:The N6-methyladenosine (m6A) RNA modification can modify long non-coding RNAs (lncRNAs), thereby affecting the tumorigenesis and progression of tumors. However, the underlying role of m6A-modified lncRNAs in colorectal cancer (CRC) remains largely unknown. Therefore, our aim was to assess the prognostic value of m6A-modified lncRNAs in CRC patients. The gene expression and clinicopathological data of CRC were extracted from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was used to investigate the m6A-modified lncRNAs. Consensus clustering was conducted to identify molecular subtypes of CRC, and the clinical significance of molecular subtypes was identified. The least absolute shrinkage and selection operator analysis (LASSO) was applied to establish a risk signature. Finally, a prognostic nomogram with risk score and clinicopathological variables was established. In total, 29 m6A-modified lncRNAs were identified as prognostic lncRNAs. Two molecular clusters were identified and significant differences were found with respect to clinicopathological features and prognosis. Cluster1 is associated with poor overall survival (OS), down-regulation of Programmed cell death ligand-1 (PD-L1) expression, lower immune score, and less immune cell infiltration. Then, an m6A-modified lncRNA signature for predicting OS was constructed in the TCGA training cohort. The signature demonstrated favorable prediction performance in both training and validation sets. Compared with low-risk patients, patients with high risk showed worse clinical outcomes, lower immune scores, and downregulated PD-L1 expression. Further analysis indicated that the signature was an independent prognostic indicator, and then a prognostic nomogram based on risk score, tumor location, and tumor stage was established. Our study identified a seven m6A-modified lncRNA signature and established a prognostic nomogram that reliably predicts OS in CRC. These findings may improve the understanding of m6A modifications in CRC and provide insights into the prognosis and treatment strategy of CRC.

Project description:An RNA modification known as N6-methyladenosine (m6A) interacts with a range of coding and non-coding RNAs. The majority of the research has focused on identifying m6A regulators that are differentially expressed in endometriosis, but it has ignored their mechanisms that are derived from the alterations of modifications among RNAs, affecting the disease progression primarily. Here, we aimed to investigate the potential roles of m6A regulators in the diagnostic potency, immune microenvironment, and clinicopathological features of endometriosis through interacting genes. A GEO cohort was incorporated into this study. Variance expression profiling was executed via the "limma" R package. Pearson analysis was performed to investigate the correlations among 767 interacting lncRNAs, 374 interacting mRNAs, and 23 m6A regulators. K-means clustering analysis, based on patterns of mRNA modifications, was applied to perform clinical feature analysis. Infiltrating immune cells and stromal cells were calculated using the Cibersort method. An m6A-related risk model was created and supported by an independent risk assay. LASSO regression analysis and Cox analyses were implemented to determine the diagnostic genes. The diagnostic targets of endometriosis were verified using PCR and the WB method. Results: A thorough investigation of the m6A modification patterns in the GEO database was carried out, based on mRNAs and lncRNAs related to these m6A regulators. Two molecular subtypes were identified using unsupervised clustering analysis, resulting in further complex infiltration levels of immune microenvironment cells in diversified endometriosis pathology types. We identified two m6A regulators, namely METTL3 and YTHDF2, as diagnostic targets of endometriosis following the usage of overlapping genes to construct a diagnostic m6A signature of endometriosis through multivariate logistic regression, and we validated it using independent GSE86534 and GSE105764 cohorts. Finally, we found that m6A alterations might be one of the important reasons for the progression of endometriosis, especially with significant downregulation of the expressions of METTL3 and YTHDF2. Finally, m6A modification patterns have significant effects on the diversity and complexity of the progression and immune microenvironment, and might be key diagnostic markers for endometriosis.

Project description:Aortic dissection (AD) develops pathological changes in the separation of the true and false aortic lumen, with high lethality. m6A methylation and oxidative stress have also been shown to be involved in the onset of AD. Through bioinformatics methods, three differentially expressed m6A regulators (YTHDC1, YTHDC2, and RBM15) were excavated from the GSE52093 dataset in the Gene Expression Omnibus (GEO) database, and functional enrichment analysis of the differentially expressed genes (DEGs) regulated by m6A regulators was performed. Then, the genes with oxidative stress-related functions among these genes were found. The protein interaction network of the oxidative stress-related genes and the competing endogenous RNA- (ceRNA-) miRNA-mRNA network were constructed. Among them, DHCR24, P4HB, and PDGFRA, which have m6A differences in AD samples, were selected as key genes. We also performed immune infiltration analysis, as well as cell-gene correlation analysis, on samples from the dataset. The results showed that YTHDC1 was positively correlated with macrophage M1 and negatively correlated with macrophage M2. Finally, we extracted AD and healthy aorta RNA and protein from human tissues that were taken from AD patients and patients who received heart transplants, performed quantitative real-time PCR (qRT-PCR) on YTHDC2 and RBM15, and performed qRT-PCR and western blot (WB) detection on YTHDC1 to verify their differences in AD. The mRNA and protein levels of YTHDC1 were consistent with the results of bioinformatics analysis and were downregulated in AD. Immunofluorescence (IF) was used to colocalize YTHDC1 and endothelial cell marker CD31. After knocking down YTHDC1 in human umbilical vein endothelial cells (HUVECs), reactive oxygen species (ROS) levels had a tendency to increase and the expression of peroxide dismutase SOD2 was decreased. This study provides assistance in discovering the role of m6A regulator YTHDC1 in AD. In particular, m6A modification participates in oxidative stress and jointly affects AD.

Project description:ObjectiveGastric cancer (GC) is one of the most prevalent malignant tumors in Asian countries. Studies have proposed that lncRNAs can be used as diagnostic and prognostic indicators of GC due to the high specificity of lncRNAs expression involvement in GC. Recently, N6-methyladenosine (m6A) has also emerged as an important modulator of the expression of lncRNAs in GC. This study aimed at establishing a novel m6A-related lncRNAs prognostic signature that can be used to construct accurate models for predicting the prognosis of GC in the Asian population.MethodsFirst, the levels of m6A modification and m6A methyltransferases expression in GC samples were determined using dot blot and western blot analyses. Next, we evaluated the lncRNAs expression profiles and the corresponding clinical data of 88 Asian GC patients retrieved from The Cancer Genome Atlas (TCGA) database. Differential expression of m6A-related lncRNAs between GC and normal tissues was investigated. The relationship between these target lncRNAs and potential immunotherapeutic signatures was also analyzed. Gene set enrichment analysis (GSEA) was performed to identify the malignancy-associated pathways. Univariate Cox regression, LASSO regression, and multivariate Cox regression analyses were performed to establish a novel prognostic m6A-related lncRNAs prognostic signature. Moreover, we constructed a predictive nomogram and determined the expression levels of nine m6A-related lncRNAs in 12 pairs of clinical samples.ResultsWe found that m6A methylation levels were significantly increased in GC tumor samples compared to adjacent normal tissues, and the increase was positively correlated with tumor stage. Patients were then divided into two clusters (cluster 1 and cluster 2) based on the differential expression of the m6A-related lncRNAs. Results showed that there was a significant difference in survival probability between the two clusters (p = 0.018). Notably, the low survival rate in cluster 2 may be associated with high expression of immune cells (resting memory CD4+ T cells, p = 0.027; regulatory T cells, p = 0.0018; monocytes, p = 0.00095; and resting dendritic cells, p = 0.015), and low expression of immune cells (resting NK cells, p = 0.033; and macrophages M1, p = 0.045). Enrichment analysis indicated that malignancy-associated biological processes were more common in the cluster 2 subgroup. Finally, the risk model comprising of six m6A-related lncRNAs was identified as an independent predictor of prognoses, which could divide patients into high- or low-risk groups. Time-dependent ROC analysis suggested that the risk score could accurately predict the prognosis of GC patients. Patients in the high-risk group had worse outcomes compared to patients in the low-risk group, and the risk score showed a positive correlation with immune cells (resting memory CD4+ T cells, R = 0.31, P = 0.038; regulatory T cells, R = 0.42, P = 0.0042; monocytes, R = 0.42, P = 0.0043). However, M1 macrophages (R = -0.37, P = 0.012) and resting NK cells (R = -0.31, P = 0.043) had a negative correlation with risk scores. Furthermore, analysis of clinical samples validated the weak positive correlation between the risk score and tumor stage.ConclusionsThe risk model described here, based on the six m6A-related lncRNAs signature, and may predict the clinical prognoses and immunotherapeutic response in Asian GC patients.

Dataset Information

RNAMethyPro: a biologically conserved signature of N6-methyladenosine regulators for predicting survival at pan-cancer level.

Publications

RNAMethyPro: a biologically conserved signature of N6-methyladenosine regulators for predicting survival at pan-cancer level.

Similar Datasets

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