RNA m6A Modification in Cancers: Molecular Mechanisms and Potential Clinical Applications

Gu, Chang; Shi, Xin; Dai, Chenyang; Shen, Feng; Rocco, Gaetano; Chen, Jiafei; Huang, Zhiyong; Chen, Chunji; He, Chuan; Huang, Tao; Chen, Chang

doi:10.1016/j.xinn.2020.100066

Cited by 89 publications

(89 citation statements)

References 189 publications

(339 reference statements)

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“…Differences in immune cell infiltration showed that innate immune response was more associated with osteoporosis. Methylation markers have been acted as biological markers recently [22,23]. In this study, we also similarly found methylation markers involved in the process of osteoporosis [24].…”

Section: Discussionsupporting

confidence: 79%

Identification of Potential Therapeutic Targets and Molecular Regulatory Mechanisms for Osteoporosis by Bioinformatics Methods

Zhang

Yang

Geng

et al. 2021

BioMed Research International

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Background. Osteoporosis is characterized by low bone mass, deterioration of bone tissue structure, and susceptibility to fracture. New and more suitable therapeutic targets need to be discovered. Methods. We collected osteoporosis-related datasets (GSE56815, GSE99624, and GSE63446). The methylation markers were obtained by differential analysis. Degree, DMNC, MCC, and MNC plug-ins were used to screen the important methylation markers in PPI network, then enrichment analysis was performed. ROC curve was used to evaluate the diagnostic effect of osteoporosis. In addition, we evaluated the difference in immune cell infiltration between osteoporotic patients and control by ssGSEA. Finally, differential miRNAs in osteoporosis were used to predict the regulators of key methylation markers. Results. A total of 2351 differentially expressed genes and 5246 differentially methylated positions were obtained between osteoporotic patients and controls. We identified 19 methylation markers by PPI network. They were mainly involved in biological functions and signaling pathways such as apoptosis and immune inflammation. HIST1H3G, MAP3K5, NOP2, OXA1L, and ZFPM2 with higher AUC values were considered key methylation markers. There were significant differences in immune cell infiltration between osteoporotic patients and controls, especially dendritic cells and natural killer cells. The correlation between MAP3K5 and immune cells was high, and its differential expression was also validated by other two datasets. In addition, NOP2 was predicted to be regulated by differentially expressed hsa-miR-3130-5p. Conclusion. Our efforts aim to provide new methylation markers as therapeutic targets for osteoporosis to better treat osteoporosis in the future.

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Section: Discussionsupporting

confidence: 79%

Identification of Potential Therapeutic Targets and Molecular Regulatory Mechanisms for Osteoporosis by Bioinformatics Methods

Zhang

Yang

Geng

et al. 2021

BioMed Research International

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“…m6A modification in RNA is a dynamic and reversible process, which is related to many diseases, such as cancer ( Yue et al, 2015 ; He et al, 2017 ; Fan et al, 2019 ; Gu et al, 2020b ). Recently, several progresses had been made in RNA splicing, stability and Translation regulation through the post-transcriptional modification of m6A ( Zhang et al, 2019a ).…”

Section: Introductionmentioning

confidence: 99%

m6A Regulators Is Differently Expressed and Correlated With Immune Response of Esophageal Cancer

Zhao

Xie

et al. 2021

Front. Cell Dev. Biol.

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N6 methyladenosine (m6A) RNA methylation regulators play an important role in the development of tumors. However, their function in esophageal cancer (EC) has not been fully elucidated. Here, we analyzed the gene expression data of 24 major m6A RNA methylation regulators from 775 patients with EC from TCGA dataset. The present study showed the aberrations of m6A regulators in genome were correlated to prognosis in human ECs. Meanwhile, 17 m6A regulators showed increased expression in EC samples, including YTHDC1, IGF2BP2, FTO, METTL14, YTHDF3, RBM15, WTAP, HNRNPA2B1, HNRNPC, ALKBH5, YTHDF2, METTL16, IGF2BP3, VIRMA, RBM15B, YTHDF1, KIAA1429, HAKAI, and ZC3H13. Among them, we found HNRNPC, YTHDC2, WTAP, VIRMA, IGF2BP3, and HNRNPA2B1 were significantly correlated to worse outcomes and advanced stage in EC. Furthermore, we showed levels of m6A regulators is correlated with the expression of Immuno-regulators (Immunoinhibitors, Immunostimulators, and MHC molecules) and immune infiltration levels in EC. Bioinformatics further confirm m6A regulators were involved in regulating RNA splicing, RNA stability, and cell proliferation. Our study showed m6A regulators are promising targets and biomarkers for cancer immunotherapy in EC.

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“…As for tumor invasion and metastasis, carcinoma-associated fibroblasts are able to enhance tumor cells migration and invasion via activating the process of specific pathways. For example, as lung cancer maintains the leading cause of cancer-related deaths, IPF has been demonstrated that it increases the risk of lung cancer development by 7–20%, and there are multiple common molecular processes that associated IPF with lung cancer, such as epithelial–mesenchymal transition (EMT), endoplasmic reticulum stress, and abnormal expression of growth factors ( Gu et al, 2018 , 2020a , b ; Ballester et al, 2019 ; Jiao and Yang, 2020 ). In the tissue of myopathies, there is prominent endomysial fibrosis, but little or no inflammation.…”

Section: Introductionmentioning

confidence: 99%

Identification of Common Genes and Pathways in Eight Fibrosis Diseases

Shi

Dang

et al. 2021

Front. Genet.

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Acute and chronic inflammation often leads to fibrosis, which is also the common and final pathological outcome of chronic inflammatory diseases. To explore the common genes and pathogenic pathways among different fibrotic diseases, we collected all the reported genes of the eight fibrotic diseases: eye fibrosis, heart fibrosis, hepatic fibrosis, intestinal fibrosis, lung fibrosis, pancreas fibrosis, renal fibrosis, and skin fibrosis. We calculated the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment scores of all fibrotic disease genes. Each gene was encoded using KEGG and GO enrichment scores, which reflected how much a gene can affect this function. For each fibrotic disease, by comparing the KEGG and GO enrichment scores between reported disease genes and other genes using the Monte Carlo feature selection (MCFS) method, the key KEGG and GO features were identified. We compared the gene overlaps among eight fibrotic diseases and connective tissue growth factor (CTGF) was finally identified as the common key molecule. The key KEGG and GO features of the eight fibrotic diseases were all screened by MCFS method. Moreover, we interestingly found overlaps of pathways between renal fibrosis and skin fibrosis, such as GO:1901890-positive regulation of cell junction assembly, as well as common regulatory genes, such as CTGF, which is the key molecule regulating fibrogenesis. We hope to offer a new insight into the cellular and molecular mechanisms underlying fibrosis and therefore help leading to the development of new drugs, which specifically delay or even improve the symptoms of fibrosis.

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RNA m6A Modification in Cancers: Molecular Mechanisms and Potential Clinical Applications

Cited by 89 publications

References 189 publications

Identification of Potential Therapeutic Targets and Molecular Regulatory Mechanisms for Osteoporosis by Bioinformatics Methods

Identification of Potential Therapeutic Targets and Molecular Regulatory Mechanisms for Osteoporosis by Bioinformatics Methods

m6A Regulators Is Differently Expressed and Correlated With Immune Response of Esophageal Cancer

Identification of Common Genes and Pathways in Eight Fibrosis Diseases

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