Comprehensive Analyses of the Expression, Genetic Alteration, Prognosis Significance, and Interaction Networks of m6A Regulators Across Human Cancers.
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ABSTRACT:
SUBMITTER: Shi X
PROVIDER: S-EPMC8733627 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundN6-methyladenosine (m6A), the most abundant chemical modification on eukaryotic messenger RNA (mRNA), is modulated by three class of regulators namely "writers," "erasers," and "readers." Increasing studies have shown that aberrant expression of m6A regulators plays broad roles in tumorigenesis and progression. However, it is largely unknown regarding the expression regulation for RNA m6A regulators in human cancers.ResultsHere we characterized the expression profiles of RNA m6A regulators in 13 cancer types with The Cancer Genome Atlas (TCGA) data. We showed that METTL14, FTO, and ALKBH5 were down-regulated in most cancers, whereas YTHDF1 and IGF2BP3 were up-regulated in 12 cancer types except for thyroid carcinoma (THCA). Survival analysis further revealed that low expression of several m6A regulators displayed longer overall survival times. Then, we analyzed microRNA (miRNA)-regulated and DNA methylation-regulated expression changes of m6A regulators in pan-cancer. In total, we identified 158 miRNAs and 58 DNA methylation probes (DMPs) involved in expression regulation for RNA m6A regulators. Furthermore, we assessed the survival significance of those regulatory pairs. Among them, 10 miRNAs and 7 DMPs may promote cancer initiation and progression; conversely, 3 miRNA/mRNA pairs in kidney renal clear cell carcinoma (KIRC) may exert tumor-suppressor function. These findings are indicative of their potential prognostic values. Finally, we validated two of those miRNA/mRNA pairs (hsa-miR-1307-3p/METTL14 and hsa-miR-204-5p/IGF2BP3) that could serve a critical role for potential clinical application in KIRC patients.ConclusionsOur findings highlighted the importance of upstream regulation (miRNA and DNA methylation) governing m6A regulators' expression in pan-cancer. As a result, we identified several informative regulatory pairs for prognostic stratification. Thus, our study provides new insights into molecular mechanisms of m6A modification in human cancers.
| S-EPMC7946859 | biostudies-literature
Project description:Sarcomas are rare malignant tumors that may arise from anywhere of the body, such as bone, adipose, muscle and vascular. However, the conventional pathogenesis of sarcomas has not been found. Therefore, there is an urgent need to identify novel therapeutic strategies and improve prognosis effects for sarcomas. Methylation of N6 adenosine (m6A) regulation is a novel proposed regulatory pattern that works in post-transcription level, which was also the most widely distributed methylation modification in eukaryotic mRNA. Growing evidences have demonstrated that m6A modification played an indispensable role in tumorigenesis. Here, we integrated multi-omics data including genetic alterations, gene expression and epigenomics regulation to systematically analysis the regulatory atlas of 21 m6A regulators in sarcoma. Firstly, we investigated the genetic alterations of m6A regulators and found that ~44% TCGA sarcoma patients have genetic mutations. We also investigated the basic annotation of 21 regulators, such as expression correlation and PPI interactions. Then we identified the upstream and downstream regulatory networks of between transcription factors (TFs)/non-coding RNAs and m6A regulators in sarcoma based on motif analysis and gene expression. These results implied that m6A regulator mediated regulatory axes could be used as prognostic biomarkers in sarcoma. Knockdown experiment results revealed that m6A regulators, YTHDF2 and HNRNPA2B1 participated in the cancer cell invasion and metastasis. Moreover, we also found that the expression levels of m6A regulators were related to immune cell infiltration of sarcoma patients.
| S-EPMC9284210 | biostudies-literature
Project description:The present study explored the prognosis and biological function roles of chromatin regulators (CRs) in patients with lung adenocarcinoma (LUAD). Using transcriptome profile and clinical follow-up data of LUAD dataset, we explored the molecular classification, developed, and validated a CR prognostic model, built an individual risk scoring system in LUAD, and compared the clinical and molecular characteristics between different subtypes and risk stratifications. We investigated the chemotherapy sensitivity and predicted potential immunotherapy response. Lastly, we collected the clinical samples and validated the prognosis and potential function role of NAPS2. Our study indicated that LUAD patients could be classified into two subtypes that had obviously different clinical background and molecular features. We constructed a prognostic model with eight CR genes, which was well validated in several other population cohort. We built high- and low-risk stratifications for LUAD patients. Patients from high-risk group were totally different from low-risk groups in clinical, biological function, gene mutation, microenvironment, and immune infiltration levels. We idented several potential molecular compounds for high-risk group treatment. We predicted that high-risk group may have poor immunotherapy response. We finally found that Neuronal PAS Domain Protein 2 (NPAS2) involved in the progression of LUAD via regulating cell adhesion. Our study indicated that CR involved in the progression of LUAD and affect their prognosis. Different therapeutic strategies should be developed for different molecular subtypes and risk stratifications. Our comprehensive analyses uncover specific determinants of CRs in LUAD and provides implications for investigating disease-associated CRs.
| S-EPMC10449281 | biostudies-literature
Project description:BackgroundMitochondria are the energy factories of cells. The abnormality of mitochondrial energy metabolism pathways is closely related to the occurrence and development of lung cancer. The abnormal genes in mitochondrial energy metabolism pathways might be the novel targets and biomarkers to diagnose and treat lung cancers.MethodGenes in major mitochondrial energy metabolism pathways were obtained from the KEGG database. The transcriptomic, mutation, and clinical data of lung cancers were obtained from The Cancer Genome Atlas (TCGA) database. Genes and clinical biomarkers were mined that affected lung cancer survival. Gene enrichment analysis was performed with ClusterProfiler and the gene set enrichment analysis (GSEA). STRING database and Cytoscape were used for protein-protein interaction (PPI) analysis. The diagnostic biomarker pattern of lung cancer was optimized, and its accuracy was verified with 10-fold cross-validation. The four genes screened by logistic regression model were verified by western blot in 5 pairs of lung cancer specimens collected in hospital.ResultsIn total, 188 mitochondrial energy metabolism pathway-related genes (MMRGs) were included in this study. GSEA analysis found that MMRGs in the lung cancer group were mainly enriched in the metabolic pathway of oxidative phosphorylation and electron respiratory transport chain compared to the control group. Age did not affect the mutation frequency of MMRGs. Comparative analysis of these 188 MMRGs identified 43 differentially expressed MMRGs (24 upregulated and 19 downregulated) in the lung cancer group compared to the control group. The survival analysis of these 43 differentially expressed MMRGs found that the survival time was better in the low-expressed GAPDHS group than that in the high-expressed GAPDHS group of lung cancers. The advanced age, high expression of GAPDHS, low expressions of ACSBG1 and CYP4A11, and ACOX3 mutation were biomarkers of poor prognosis in lung cancers. PPI analysis showed that proteins such as GAPDH and GAPDHS interacted with many proteins in mitochondrial metabolic pathways. A four-MMRG-signature model (y = 0.0069∗ACADL - 0.001∗ALDH18A1 - 0.0405∗CPT1B + 0.0008∗PPARG - 1.625) was established to diagnose lung cancer with the accuracy up to 98.74%, AUC value up to 0.992, and a missed diagnosis rate of only 0.6%. Western blotting showed that ALDH18A1 and CPT1B proteins were significantly overexpressed in the lung cancer group (p < 0.05), and ACADL and PPARG proteins were slightly underexpressed in the lung cancer group (p < 0.05), which were consistent with the results of their corresponding mRNA expressions.ConclusionMitochondrial energy metabolism pathway alterations are the important hallmarks of lung cancer. Age did not increase the risk of MMRG mutation. High expression of GAPDHS, low expression of ACSBG1, low expression of CYP4A11, mutated ACOX3, and old age predict a poor prognosis of lung cancer. Four differentially expressed MMRGs (ACADL, ALDH18A1, CPT1B, and PPARG) established a logistic regression model, which could effectively diagnose lung cancer. At the protein level, ALDH18A1 and CPT1B were significantly upregulated, and ACADL and PPARG were slightly underexpressed, in the lung cancer group compared to the control group, which were consistent with the results of their corresponding mRNA expressions.
| S-EPMC8713050 | biostudies-literature
Project description:The purpose of this study was to investigate the genetic variation, gene expression differences, and clinical significance of SUMOylation regulators in pan-cancers. Based on previous studies, we gained a better understanding of the biological process of SUMOylation and the status of current research. In the present study, we employed a wide range of bioinformatics methods. We used genetic variation and mRNA expression data in the Cancer Genome Atlas (TCGA) to construct a panoramic view of the single nucleotide variants, copy number variants, and gene expression changes in SUMOylation regulators in various tumors. Subsequently, we used the String website and the Cytoscape tool to construct the PPI network between these regulators. We used the GSCALite website to determine the relationship between these regulators and cancer pathways and drug sensitivity. We constructed images of co-expression between these regulators using the R programming language. Using clinical data from TCGA, we performed hazard ratio analysis for these regulators in pan-cancer. Most importantly, we used these regulators to successfully establish risk signatures related to patient prognosis in multiple tumors. Finally, in KIRC, we conducted gene-set enrichment analysis (GSEA) of the five molecules in its risk signatures. We found that these five molecules are involved in multiple cancer pathways. In short, we have comprehensively interpreted the detailed biological process of SUMOylation at the genetic level for the first time, successfully constructed multiple risk signatures, and conducted GSEA in KIRC. We believe that these findings provide credible and valuable information that is relevant for future clinical diagnoses and scientific research.
| S-EPMC7592005 | biostudies-literature
Project description:Recent publications have revealed that N6-methyladenosine (m6A) modification is critically involved in tumorigenesis and metastasis. However, the correlation of m6A modification and immune infiltration in early-stage lung adenocarcinoma (LUAD) is still uncertain. We performed NMF clustering based on 23 m6A regulators and identify three distinct m6A clusters and three m6A related genes clusters (m6A cluster-R) in early-stage LUAD. The immune infiltrating levels were calculated using CIBERSORT, MCPcounter and ssGSEA algorithms. And we established the m6A-predictive score to quantify m6A modified phenotypes and predict immunotherapeutic responses. Based on the TME characteristics, different immune profiles were also identified among three m6A gene-related clusters. And the m6A-R-C2 was related to a favorable overall survival (OS), whereas m6A-R-C3 had unfavorable overall survival. The m6A-predictive score was built according to the expression levels of m6A-related genes, and patients could be stratified into subgroups with low/high scores. Patients with high scores had poor overall survival, enhanced immune infiltration, high tumor mutation burden and increased level of somatic mutation. Besides, patients with high scores had unfavorable overall survival in the anti-PD-1 cohort, whereas the overall survival of high-score patients was better in the adoptive T cell therapy cohort. Our work highlights that m6A modification is closely related to immune infiltration in early-stage LUAD, which also contributes to the development of more effective immunotherapy strategies.
| S-EPMC8505809 | biostudies-literature
Project description:Objective: N6-methyladenosine (m6A) modification is involved in modulating various biological processes in human cancers. But the implication of m6A modification in lung adenocarcinoma (LUAD) is still unclear. Hence, this study conducted a comprehensive analysis of the expression and clinical implication of m6A regulators in LUAD. Methods: Consensus clustering analysis of 502 LUAD samples in the TCGA dataset was presented based on the expression profiles of 20 m6A regulators using ConsensusClusterPlus package. Overall survival (OS), activation of signaling pathways and tumor immunity (immune/stromal score, tumor purity, expression of HLA and immune checkpoints, and immune cell infiltration) were compared between m6A modification patterns. The m6A-related genes between patterns were identified and prognostic m6A-related genes were imported into LASSO-cox regression analysis. The m6A risk score was developed and its prognostic implication was evaluated and externally verified in the GSE30219 and GSE72094 dataset. Furthermore, a nomogram that contained independent prognostic indicators was established, followed by external verification. Results: Two m6A modification patterns were clustered across LUAD based on the expression similarity of the m6A regulators via consensus clustering analysis, with distinct OS, activation of signaling pathways and tumor immunity. Totally, 213 m6A-related genes that were identified by comparing two patterns were significantly related to LUAD prognosis. By LASSO method, we constructed the m6A risk score that was a reliable and independent prognostic factor for LUAD. Patients with low m6A risk score displayed a prominent survival advantage. After incorporating independent clinical features, we developed the prognostic nomogram that exhibited high predictive accuracy and the best clinical net benefit for OS. Conclusion: Collectively, our study may provide a clinically useful tool for precise prognostic management and optimization of immunotherapeutic strategies for LUAD patients.
| S-EPMC8697852 | biostudies-literature
Project description:BACKGROUND: Cancers, a group of multifactorial complex diseases, are generally caused by mutation of multiple genes or dysregulation of pathways. Identifying biomarkers that can characterize cancers would help to understand and diagnose cancers. Traditional computational methods that detect genes differentially expressed between cancer and normal samples fail to work due to small sample size and independent assumption among genes. On the other hand, genes work in concert to perform their functions. Therefore, it is expected that dysregulated pathways will serve as better biomarkers compared with single genes. RESULTS: In this paper, we propose a novel approach to identify dysregulated pathways in cancer based on a pathway interaction network. Our contribution is three-fold. Firstly, we present a new method to construct pathway interaction network based on gene expression, protein-protein interactions and cellular pathways. Secondly, the identification of dysregulated pathways in cancer is treated as a feature selection problem, which is biologically reasonable and easy to interpret. Thirdly, the dysregulated pathways are identified as subnetworks from the pathway interaction networks, where the subnetworks characterize very well the functional dependency or crosstalk between pathways. The benchmarking results on several distinct cancer datasets demonstrate that our method can obtain more reliable and accurate results compared with existing state of the art methods. Further functional analysis and independent literature evidence also confirm that our identified potential pathogenic pathways are biologically reasonable, indicating the effectiveness of our method. CONCLUSIONS: Dysregulated pathways can serve as better biomarkers compared with single genes. In this work, by utilizing pathway interaction networks and gene expression data, we propose a novel approach that effectively identifies dysregulated pathways, which can not only be used as biomarkers to diagnose cancers but also serve as potential drug targets in the future.
| S-EPMC3443452 | biostudies-literature
Project description:Although the associations of p53 dysfunction, p53 interaction networks and oncogenesis have been widely explored, a systematic analysis of TP53 mutations and its related interaction networks in various types of human cancers is lacking. Our study explored the associations of TP53 mutations, gene expression, clinical outcomes, and TP53 interaction networks across 33 cancer types using data from The Cancer Genome Atlas (TCGA). We show that TP53 is the most frequently mutated gene in a number of cancers, and its mutations appear to be early events in cancer initiation. We identified genes potentially repressed by p53, and genes whose expression correlates significantly with TP53 expression. These gene products may be especially important nodes in p53 interaction networks in human cancers. This study shows that while TP53-truncating mutations often result in decreased TP53 expression, other non-truncating TP53 mutations result in increased TP53 expression in some cancers. Survival analyses in a number of cancers show that patients with TP53 mutations are more likely to have worse prognoses than TP53-wildtype patients, and that elevated TP53 expression often leads to poor clinical outcomes. We identified a set of candidate synthetic lethal (SL) genes for TP53, and validated some of these SL interactions using data from the Cancer Cell Line Project. These predicted SL genes are promising candidates for experimental validation and the development of personalized therapeutics for patients with TP53-mutated cancers.
| S-EPMC5352183 | biostudies-literature
Project description:N6-methyladenosine (m6A) plays critical roles in human development and cancer progression. However, our knowledge regarding the dynamic expression of m6A regulators during human tissue development is still lacking. Here, we comprehensively analyzed the dynamic expression alterations of m6A regulators during seven tissue development and eight cancer types. We found that m6A regulators globally exhibited decreased expression during development. In addition, IGF2BP1/2/3 (insulinlike growth factor 2 MRNA-binding protein 1/2/3) exhibited reverse expression pattern in cancer progression, suggesting an oncofetal reprogramming in cancer. The expressions of IGF2BP1/2/3 were regulated by genome alterations, particularly copy number amplification in cancer. Clinical association analysis revealed that higher expressions of IGF2BP1/2/3 were associated with worse survival of cancer patients. Finally, we found that genes significantly correlated with IGF2BP1/2/3 were significantly enriched in cancer hallmark-related pathways. In summary, dynamic expression analysis will guide both mechanistic and therapeutic roles of m6A regulators during tissue development and cancer progression.
| S-EPMC7870680 | biostudies-literature