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Zhang H, Fan K, Chen Y, Xu P, Zhang Z, Mo X, Guo Y. Genome-Wide Identification of Cell Type-Specific Susceptibility Genes for SLE Through the Analysis of RNA Modification-Associated SNPs. Immunol Invest 2024:1-15. [PMID: 39230170 DOI: 10.1080/08820139.2024.2399577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
INTRODUCTION This study aimed to elucidate the functional genes associated with systemic lupus erythematosus (SLE) in various cell types through the utilization of RNAm-SNPs. METHODS Utilizing large-scale genetic data, we identified associations between RNAm-SNPs and SLE. The association between RNAm-SNPs and bulk and single-cell mRNA expression (eQTL) and protein levels (pQTL) were examined. Mendelian randomization and differential expression analyses were conducted to explore the links between gene expression, protein levels, and SLE. RESULTS We identified 41 RNAm-SNPs that were significantly associated with SLE. The GWAS signals exhibited notable enrichment in m6A-SNPs and m7G-SNPs. These RNAm-SNPs showed both eQTL and pQTL effects. In our single-cell analysis, 16 RNAm-SNPs exhibited associations with gene expression levels across 13 distinct cell types, including HLA-A, HLA-B, HLA-C, HLA-DQA1, HLA-DQB1, HLA-DRB1 and IRF7. We identified 58 noteworthy associations between the expression levels of 20 genes and SLE across 12 distinct immune cell types. Notably, HLA-DQB1, HLA-DRB1 and IRF7 exhibited abnormalities in CD8+ T cells, IRF7 displayed abnormal expression in CD4+ T cells, while HLA-DRB1 and IRF7 were also distinctly perturbed in natural killer cells. DISCUSSION This study advances our understanding of the genetic basis of SLE by highlighting the significance of RNAm-SNPs and immune cell gene expression in SLE.
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Affiliation(s)
- Huan Zhang
- Department of Epidemiology, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China
| | - Kedi Fan
- Department of Epidemiology, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China
- Center for Genetic Epidemiology and Genomics, MOE Key Laboratory of Geriatric Diseases and Immunology, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China
| | - Yuxi Chen
- Department of Epidemiology, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China
| | - Peng Xu
- Department of Epidemiology, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China
| | - Zhentao Zhang
- Department of Epidemiology, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China
- Center for Genetic Epidemiology and Genomics, MOE Key Laboratory of Geriatric Diseases and Immunology, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China
| | - Xingbo Mo
- Department of Epidemiology, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China
- Center for Genetic Epidemiology and Genomics, MOE Key Laboratory of Geriatric Diseases and Immunology, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China
| | - Yufan Guo
- Department of Rheumatology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China
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Zheng Y, Li H, Lin S. m7GRegpred: substrate prediction of N7-methylguanosine (m7G) writers and readers based on sequencing features. Front Genet 2024; 15:1469011. [PMID: 39262420 PMCID: PMC11387174 DOI: 10.3389/fgene.2024.1469011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2024] [Accepted: 08/19/2024] [Indexed: 09/13/2024] Open
Abstract
N7-Methylguanosine (m7G) is important RNA modification at internal and the cap structure of five terminal end of message RNA. It is essential for RNA stability of RNA, the efficiency of translation, and various intracellular RNA processing pathways. Given the significance of the m7G modification, numerous studies have been conducted to predict m7G sites. To further elucidate the regulatory mechanisms surrounding m7G, we introduce a novel bioinformatics framework, m7GRegpred, designed to forecast the targets of the m7G methyltransferases METTL1 and WDR4, and m7G readers QKI5, QKI6, and QKI7 for the first time. We integrated different features to build predictors, with AUROC scores of 0.856, 0.857, 0.780, 0.776, 0.818 for METTL1, WDR4, QKI5, QKI6, and QKI7, respectively. In addition, the effect of window lengths and algorism were systemically evaluated in this work. The finial model was summarized in a user-friendly webserver: http://modinfor.com/m7GRegpred/. Our research indicates that the substrates of m7G regulators can be identified and may potentially advance the study of m7G regulators under unique conditions.
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Affiliation(s)
- Yu Zheng
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian, China
- School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
| | - Haipeng Li
- Graduate School of Fujian Medical University, Fuzhou, Fujian, China
- Department of Operating Room, Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Shaofeng Lin
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian, China
- School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
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3
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Poltronieri P. Regulatory RNAs: role as scaffolds assembling protein complexes and their epigenetic deregulation. EXPLORATION OF TARGETED ANTI-TUMOR THERAPY 2024; 5:841-876. [PMID: 39280246 PMCID: PMC11390297 DOI: 10.37349/etat.2024.00252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 04/26/2024] [Indexed: 09/18/2024] Open
Abstract
Recently, new data have been added to the interaction between non-coding RNAs (ncRNAs) and epigenetic machinery. Epigenetics includes enzymes involved in DNA methylation, histone modifications, and RNA modifications, and mechanisms underlying chromatin structure, repressive states, and active states operating in transcription. The main focus is on long ncRNAs (lncRNAs) acting as scaffolds to assemble protein complexes. This review does not cover RNA's role in sponging microRNAs, or decoy functions. Several lncRNAs were shown to regulate chromatin activation and repression by interacting with Polycomb repressive complexes and mixed-lineage leukemia (MLL) activating complexes. Various groups reported on enhancer of zeste homolog 2 (EZH2) interactions with regulatory RNAs. Knowledge of the function of these complexes opens the perspective to develop new therapeutics for cancer treatment. Lastly, the interplay between lncRNAs and epitranscriptomic modifications in cancers paves the way for new targets in cancer therapy. The approach to inhibit lncRNAs interaction with protein complexes and perspective to regulate epitrascriptomics-regulated RNAs may bring new compounds as therapeuticals in various types of cancer.
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Affiliation(s)
- Palmiro Poltronieri
- Agrofood Department, National Research Council, CNR-ISPA, 73100 Lecce, Italy
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Su X, Li Y, Ren Y, Cao M, Yang G, Luo J, Hu Z, Deng H, Deng M, Liu B, Yao Z. A new strategy for overcoming drug resistance in liver cancer: Epigenetic regulation. Biomed Pharmacother 2024; 176:116902. [PMID: 38870626 DOI: 10.1016/j.biopha.2024.116902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Revised: 05/30/2024] [Accepted: 06/06/2024] [Indexed: 06/15/2024] Open
Abstract
Drug resistance in hepatocellular carcinoma has posed significant obstacles to effective treatment. Recent evidence indicates that, in addition to traditional gene mutations, epigenetic recoding plays a crucial role in HCC drug resistance. Unlike irreversible gene mutations, epigenetic changes are reversible, offering a promising avenue for preventing and overcoming drug resistance in liver cancer. This review focuses on various epigenetic modifications relevant to drug resistance in HCC and their underlying mechanisms. Additionally, we introduce current clinical epigenetic drugs and clinical trials of these drugs as regulators of drug resistance in other solid tumors. Although there is no clinical study to prevent the occurrence of drug resistance in liver cancer, the development of liquid biopsy and other technologies has provided a bridge to achieve this goal.
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Affiliation(s)
- Xiaorui Su
- Department of Hepatobiliary-Pancreatic-Splenic Surgery, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Yuxuan Li
- Department of Hepatobiliary Surgery, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Yupeng Ren
- Department of Hepatobiliary Surgery, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Mingbo Cao
- Department of Hepatobiliary Surgery, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Gaoyuan Yang
- Department of Hepatobiliary Surgery, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Jing Luo
- Department of Infectious Diseases, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Ziyi Hu
- Department of Hepatobiliary-Pancreatic-Splenic Surgery, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Haixia Deng
- Department of Hepatobiliary Surgery, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Meihai Deng
- Department of Hepatobiliary Surgery, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Bo Liu
- Department of Hepatobiliary-Pancreatic-Splenic Surgery, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Zhicheng Yao
- Department of Hepatobiliary-Pancreatic-Splenic Surgery, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China.
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Lin X, Zhang J, Wu Z, Shi Y, Chen M, Li M, Hu H, Tian K, Lv X, Li C, Liu Y, Gao X, Yang Q, Chen K, Zhu A. Involvement of autophagy in mesaconitine-induced neurotoxicity in HT22 cells revealed through integrated transcriptomic, proteomic, and m6A epitranscriptomic profiling. Front Pharmacol 2024; 15:1393717. [PMID: 38939838 PMCID: PMC11208636 DOI: 10.3389/fphar.2024.1393717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 05/20/2024] [Indexed: 06/29/2024] Open
Abstract
Background: Mesaconitine (MA), a diester-diterpenoid alkaloid extracted from the medicinal herb Aconitum carmichaelii, is commonly used to treat various diseases. Previous studies have indicated the potent toxicity of aconitum despite its pharmacological activities, with limited understanding of its effects on the nervous system and the underlying mechanisms. Methods: HT22 cells and zebrafish were used to investigate the neurotoxic effects of MA both in vitro and in vivo, employing multi-omics techniques to explore the potential mechanisms of toxicity. Results: Our results demonstrated that treatment with MA induces neurotoxicity in zebrafish and HT22 cells. Subsequent analysis revealed that MA induced oxidative stress, as well as structural and functional damage to mitochondria in HT22 cells, accompanied by an upregulation of mRNA and protein expression related to autophagic and lysosomal pathways. Furthermore, methylated RNA immunoprecipitation sequencing (MeRIP-seq) showed a correlation between the expression of autophagy-related genes and N6-methyladenosine (m6A) modification following MA treatment. In addition, we identified METTL14 as a potential regulator of m6A methylation in HT22 cells after exposure to MA. Conclusion: Our study has contributed to a thorough mechanistic elucidation of the neurotoxic effects caused by MA, and has provided valuable insights for optimizing the rational utilization of traditional Chinese medicine formulations containing aconitum in clinical practice.
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Affiliation(s)
- Xiaohuang Lin
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Jian Zhang
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Zekai Wu
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Yuan Shi
- State Key Laboratory of Mariculture Breeding, College of Marine Sciences, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Mengting Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Maodong Li
- Shenzhen Bay Laboratory, Institute of Systems and Physical Biology, Shenzhen, China
| | - Hong Hu
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Kun Tian
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Xiaoqi Lv
- Key Laboratory of Cell Proliferation and Differentiation of the Ministry of Education, Peking University Genome Editing Research Center, College of Life Sciences, Peking University, Beijing, China
| | - Chutao Li
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Yang Liu
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Xinyue Gao
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Qiaomei Yang
- Department of Gynecology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou, China
| | - Kunqi Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - An Zhu
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
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Qian W, Yang L, Li T, Li W, Zhou J, Xie S. RNA modifications in pulmonary diseases. MedComm (Beijing) 2024; 5:e546. [PMID: 38706740 PMCID: PMC11068158 DOI: 10.1002/mco2.546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 02/26/2024] [Accepted: 03/14/2024] [Indexed: 05/07/2024] Open
Abstract
Threatening public health, pulmonary disease (PD) encompasses diverse lung injuries like chronic obstructive PD, pulmonary fibrosis, asthma, pulmonary infections due to pathogen invasion, and fatal lung cancer. The crucial involvement of RNA epigenetic modifications in PD pathogenesis is underscored by robust evidence. These modifications not only shape cell fates but also finely modulate the expression of genes linked to disease progression, suggesting their utility as biomarkers and targets for therapeutic strategies. The critical RNA modifications implicated in PDs are summarized in this review, including N6-methylation of adenosine, N1-methylation of adenosine, 5-methylcytosine, pseudouridine (5-ribosyl uracil), 7-methylguanosine, and adenosine to inosine editing, along with relevant regulatory mechanisms. By shedding light on the pathology of PDs, these summaries could spur the identification of new biomarkers and therapeutic strategies, ultimately paving the way for early PD diagnosis and treatment innovation.
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Affiliation(s)
- Weiwei Qian
- Emergency Department of Emergency MedicineLaboratory of Emergency Medicine, West China Hospital, And Disaster Medical, Sichuan UniversityChengduSichuanChina
- Emergency DepartmentShangjinnanfu Hospital, West China Hospital, Sichuan UniversityChengduSichuanChina
| | - Lvying Yang
- The Department of Respiratory and Critical Care MedicineThe First Veterans Hospital of Sichuan ProvinceChengduSichuanChina
| | - Tianlong Li
- Department of Critical Care Medicine Sichuan Provincial People's HospitalUniversity of Electronic Science and Technology of ChinaChengduSichuanChina
| | - Wanlin Li
- National Clinical Research Center for Infectious Disease, Shenzhen Third People's HospitalShenzhenGuangdongChina
| | - Jian Zhou
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National‐Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University Medical SchoolShenzhenChina
- Department of ImmunologyInternational Cancer Center, Shenzhen University Health Science CenterShenzhenGuangdongChina
| | - Shenglong Xie
- Department of Thoracic SurgerySichuan Provincial People's Hospital, University of Electronic Science and Technology of ChinaChengduSichuanChina
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Chang H, Chen H, Ma T, Ma K, Li Y, Suo L, Liang X, Jia K, Ma J, Li J, Sun D. Multi-omics pan-cancer study of SPTBN2 and its value as a potential therapeutic target in pancreatic cancer. Sci Rep 2024; 14:9764. [PMID: 38684762 PMCID: PMC11059406 DOI: 10.1038/s41598-024-60780-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 04/26/2024] [Indexed: 05/02/2024] Open
Abstract
SPTBN2 is a protein-coding gene that is closely related to the development of malignant tumors. However, its prognostic value and biological function in pan-cancer, especially pancreatic cancer (PAAD), have not been reported. In the present study, a novel exploration of the value and potential mechanism of SPTBN2 in PAAD was conducted using multi-omics in the background of pan-cancer. Via various database analysis, up-regulated expression of SPTBN2 was detected in most of the tumor tissues examined. Overexpression of SPTBN2 in PAAD and kidney renal clear cell cancer patients potentially affected overall survival, disease-specific survival, and progression-free interval. In PAAD, SPTBN2 can be used as an independent factor affecting prognosis. Mutations and amplification of SPTBN2 were detected, with abnormal methylation of SPTBN2 affecting its expression and the survival outcome of PAAD patients. Immunoassay results demonstrate that SPTBN2 was a potential biomarker for predicting therapeutic response in PAAD, and may influence the immunotherapy efficacy of PAAD by regulating levels of CD8 + T cells and neutrophil infiltration. Results from an enrichment analysis indicated that SPTBN2 may regulate the development of PAAD via immune pathways. Thus, SPTBN2 is a potential prognostic biomarker and immunotherapy target based on its crucial role in the development of PAAD.
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Affiliation(s)
- Hongliang Chang
- Division of Cholelithiasis Minimally Invasive Surgery, Department of General Surgery, Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, China
| | - Hong Chen
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgery, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Dalian, 116021, China
| | - Taiheng Ma
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgery, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Dalian, 116021, China
| | - Kexin Ma
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgery, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Dalian, 116021, China
| | - Yi Li
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgery, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Dalian, 116021, China
| | - Lida Suo
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgery, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Dalian, 116021, China
| | - Xiangnan Liang
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgery, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Dalian, 116021, China
| | - Kunyu Jia
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgery, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Dalian, 116021, China
| | - Jiahong Ma
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgery, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Dalian, 116021, China
| | - Jing Li
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgery, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Dalian, 116021, China
| | - Deguang Sun
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgery, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Dalian, 116021, China.
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Liang Z, Ye H, Ma J, Wei Z, Wang Y, Zhang Y, Huang D, Song B, Meng J, Rigden DJ, Chen K. m6A-Atlas v2.0: updated resources for unraveling the N6-methyladenosine (m6A) epitranscriptome among multiple species. Nucleic Acids Res 2024; 52:D194-D202. [PMID: 37587690 PMCID: PMC10768109 DOI: 10.1093/nar/gkad691] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 08/02/2023] [Accepted: 08/10/2023] [Indexed: 08/18/2023] Open
Abstract
N 6-Methyladenosine (m6A) is one of the most abundant internal chemical modifications on eukaryote mRNA and is involved in numerous essential molecular functions and biological processes. To facilitate the study of this important post-transcriptional modification, we present here m6A-Atlas v2.0, an updated version of m6A-Atlas. It was expanded to include a total of 797 091 reliable m6A sites from 13 high-resolution technologies and two single-cell m6A profiles. Additionally, three methods (exomePeaks2, MACS2 and TRESS) were used to identify >16 million m6A enrichment peaks from 2712 MeRIP-seq experiments covering 651 conditions in 42 species. Quality control results of MeRIP-seq samples were also provided to help users to select reliable peaks. We also estimated the condition-specific quantitative m6A profiles (i.e. differential methylation) under 172 experimental conditions for 19 species. Further, to provide insights into potential functional circuitry, the m6A epitranscriptomics were annotated with various genomic features, interactions with RNA-binding proteins and microRNA, potentially linked splicing events and single nucleotide polymorphisms. The collected m6A sites and their functional annotations can be freely queried and downloaded via a user-friendly graphical interface at: http://rnamd.org/m6a.
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Affiliation(s)
- Zhanmin Liang
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350004, China
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
| | - Haokai Ye
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Jiongming Ma
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350004, China
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Zhen Wei
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L69 7ZB, UK
| | - Yue Wang
- Department of Mathematical Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Department of Computer Science, University of Liverpool, Liverpool L69 7ZB, UK
| | - Yuxin Zhang
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350004, China
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Daiyun Huang
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Department of Computer Science, University of Liverpool, Liverpool L69 7ZB, UK
| | - Bowen Song
- Department of Public Health, School of Medicine & Holistic Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Jia Meng
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- AI University Research Centre, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Daniel J Rigden
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Kunqi Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350004, China
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9
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Wang X, Zhang Y, Chen K, Liang Z, Ma J, Xia R, de Magalhães JP, Rigden DJ, Meng J, Song B. m7GHub V2.0: an updated database for decoding the N7-methylguanosine (m7G) epitranscriptome. Nucleic Acids Res 2024; 52:D203-D212. [PMID: 37811871 PMCID: PMC10767970 DOI: 10.1093/nar/gkad789] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 08/18/2023] [Accepted: 09/18/2023] [Indexed: 10/10/2023] Open
Abstract
With recent progress in mapping N7-methylguanosine (m7G) RNA methylation sites, tens of thousands of experimentally validated m7G sites have been discovered in various species, shedding light on the significant role of m7G modification in regulating numerous biological processes including disease pathogenesis. An integrated resource that enables the sharing, annotation and customized analysis of m7G data will greatly facilitate m7G studies under various physiological contexts. We previously developed the m7GHub database to host mRNA m7G sites identified in the human transcriptome. Here, we present m7GHub v.2.0, an updated resource for a comprehensive collection of m7G modifications in various types of RNA across multiple species: an m7GDB database containing 430 898 putative m7G sites identified in 23 species, collected from both widely applied next-generation sequencing (NGS) and the emerging Oxford Nanopore direct RNA sequencing (ONT) techniques; an m7GDiseaseDB hosting 156 206 m7G-associated variants (involving addition or removal of an m7G site), including 3238 disease-relevant m7G-SNPs that may function through epitranscriptome disturbance; and two enhanced analysis modules to perform interactive analyses on the collections of m7G sites (m7GFinder) and functional variants (m7GSNPer). We expect that m7Ghub v.2.0 should serve as a valuable centralized resource for studying m7G modification. It is freely accessible at: www.rnamd.org/m7GHub2.
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Affiliation(s)
- Xuan Wang
- Department of Public Health, School of Medicine & Holistic Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
| | - Yuxin Zhang
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L7 8TX, Liverpool, UK
| | - Kunqi Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350004, China
| | - Zhanmin Liang
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
| | - Jiongming Ma
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L7 8TX, Liverpool, UK
| | - Rong Xia
- Department of Financial and Actuarial Mathematics, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
| | | | - Daniel J Rigden
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L7 8TX, Liverpool, UK
| | - Jia Meng
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L7 8TX, Liverpool, UK
- AI University Research Centre, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China
| | - Bowen Song
- Department of Public Health, School of Medicine & Holistic Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China
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10
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Chen Y, Jiang Z, Yang Y, Zhang C, Liu H, Wan J. The functions and mechanisms of post-translational modification in protein regulators of RNA methylation: Current status and future perspectives. Int J Biol Macromol 2023; 253:126773. [PMID: 37690652 DOI: 10.1016/j.ijbiomac.2023.126773] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 08/31/2023] [Accepted: 09/05/2023] [Indexed: 09/12/2023]
Abstract
RNA methylation, an epigenetic modification that does not alter gene sequence, may be important to diverse biological processes. Protein regulators of RNA methylation include "writers," "erasers," and "readers," which respectively deposit, remove, and recognize methylated RNA. RNA methylation, particularly N6-methyladenosine (m6A), 5-methylcytosine (m5C), N3-methylcytosine (m3C), N1-methyladenosine (m1A) and N7-methylguanosine (m7G), has been suggested as disease therapeutic targets. Despite advances in the structure and pharmacology of RNA methylation regulators that have improved drug discovery, regulating these proteins by various post-translational modifications (PTMs) has received little attention. PTM modifies protein structure and function, affecting all aspects of normal biology and pathogenesis, including immunology, cell differentiation, DNA damage repair, and tumors. It is becoming evident that RNA methylation regulators are also regulated by diverse PTMs. PTM of RNA methylation regulators induces their covalent linkage to new functional groups, hence modifying their activity and function. Mass spectrometry has identified many PTMs on protein regulators of RNA methylation. In this review, we describe the functions and PTM of protein regulators of RNA methylation and summarize the recent advances in the regulatory mode of human disease and its underlying mechanisms.
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Affiliation(s)
- Youming Chen
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Zuli Jiang
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Ying Yang
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Chenxing Zhang
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Hongyang Liu
- Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
| | - Junhu Wan
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
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11
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Ren J, Chen X, Zhang Z, Shi H, Wu S. DPred_3S: identifying dihydrouridine (D) modification on three species epitranscriptome based on multiple sequence-derived features. Front Genet 2023; 14:1334132. [PMID: 38169665 PMCID: PMC10758487 DOI: 10.3389/fgene.2023.1334132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 11/29/2023] [Indexed: 01/05/2024] Open
Abstract
Introduction: Dihydrouridine (D) is a conserved modification of tRNA among all three life domains. D modification enhances the flexibility of a single nucleotide base in the spatial structure and is disease- and evolution-associated. Recent studies have also suggested the presence of dihydrouridine on mRNA. Methods: To identify D in epitranscriptome, we provided a prediction framework named "DPred_3S" based on the machine learning approach for three species D epitranscriptome, which used epitranscriptome sequencing data as training data for the first time. Results: The optimal features were evaluated by the F-score and integration of different features; our model achieved area under the receiver operating characteristic curve (AUROC) scores 0.955, 0.946, and 0.905 for Saccharomyces cerevisiae, Escherichia coli, and Schizosaccharomyces pombe, respectively. The performances of different machine learning algorithms were also compared in this study. Discussion: The high performances of our model suggest the D sites can be distinguished based on their surrounding sequence, but the lower performance of cross-species prediction may be limited by technique preferences.
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Affiliation(s)
- Jinjin Ren
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian, China
- Fujian Key Laboratory of Tumor Microbiology, Department of Medical Microbiology, Fujian Medical University, Fuzhou, Fujian, China
| | - Xiaozhen Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian, China
| | - Zhengqian Zhang
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian, China
| | - Haoran Shi
- Institute of Applied Microbiology, Research Center for BioSystems, Land Use, and Nutrition (IFZ), Justus-Liebig-University Giessen, Giessen, Germany
| | - Shuxiang Wu
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian, China
- Fujian Key Laboratory of Tumor Microbiology, Department of Medical Microbiology, Fujian Medical University, Fuzhou, Fujian, China
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12
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Jin Z, Sheng J, Hu Y, Zhang Y, Wang X, Huang Y. Shining a spotlight on m6A and the vital role of RNA modification in endometrial cancer: a review. Front Genet 2023; 14:1247309. [PMID: 37886684 PMCID: PMC10598767 DOI: 10.3389/fgene.2023.1247309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 09/19/2023] [Indexed: 10/28/2023] Open
Abstract
RNA modifications are mostly dynamically reversible post-transcriptional modifications, of which m6A is the most prevalent in eukaryotic mRNAs. A growing number of studies indicate that RNA modification can finely tune gene expression and modulate RNA metabolic homeostasis, which in turn affects the self-renewal, proliferation, apoptosis, migration, and invasion of tumor cells. Endometrial carcinoma (EC) is the most common gynecologic tumor in developed countries. Although it can be diagnosed early in the onset and have a preferable prognosis, some cases might develop and become metastatic or recurrent, with a worse prognosis. Fortunately, immunotherapy and targeted therapy are promising methods of treating endometrial cancer patients. Gene modifications may also contribute to these treatments, as is especially the case with recent developments of new targeted therapeutic genes and diagnostic biomarkers for EC, even though current findings on the relationship between RNA modification and EC are still very limited, especially m6A. For example, what is the elaborate mechanism by which RNA modification affects EC progression? Taking m6A modification as an example, what is the conversion mode of methylation and demethylation for RNAs, and how to achieve selective recognition of specific RNA? Understanding how they cope with various stimuli as part of in vivo and in vitro biological development, disease or tumor occurrence and development, and other processes is valuable and RNA modifications provide a distinctive insight into genetic information. The roles of these processes in coping with various stimuli, biological development, disease, or tumor development in vivo and in vitro are self-evident and may become a new direction for cancer in the future. In this review, we summarize the category, characteristics, and therapeutic precis of RNA modification, m6A in particular, with the purpose of seeking the systematic regulation axis related to RNA modification to provide a better solution for the treatment of EC.
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Affiliation(s)
- Zujian Jin
- Department of Gynecology and Obstetrics, The Fourth Affiliated Hospital, Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
| | - Jingjing Sheng
- Department of Gynecology and Obstetrics, The Fourth Affiliated Hospital, Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
| | - Yingying Hu
- Department of Gynecology and Obstetrics, The Fourth Affiliated Hospital, Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
| | - Yu Zhang
- Department of Gynecology and Obstetrics, The Fourth Affiliated Hospital, Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
| | - Xiaoxia Wang
- Reproductive Medicine Center, School of Medicine, The Fourth Affiliated Hospital, Zhejiang University, Yiwu, Zhejiang, China
| | - Yiping Huang
- Department of Gynecology and Obstetrics, The Fourth Affiliated Hospital, Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
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13
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Li T, Chen Z, Wang Z, Lu J, Chen D. Combined signature of N7-methylguanosine regulators with their related genes and the tumor microenvironment: a prognostic and therapeutic biomarker for breast cancer. Front Immunol 2023; 14:1260195. [PMID: 37868988 PMCID: PMC10585266 DOI: 10.3389/fimmu.2023.1260195] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 09/19/2023] [Indexed: 10/24/2023] Open
Abstract
Background Identifying predictive markers for breast cancer (BC) prognosis and immunotherapeutic responses remains challenging. Recent findings indicate that N7-methylguanosine (m7G) modification and the tumor microenvironment (TME) are critical for BC tumorigenesis and metastasis, suggesting that integrating m7G modifications and TME cell characteristics could improve the predictive accuracy for prognosis and immunotherapeutic responses. Methods We utilized bulk RNA-sequencing data from The Cancer Genome Atlas Breast Cancer Cohort and the GSE42568 and GSE146558 datasets to identify BC-specific m7G-modification regulators and associated genes. We used multiple m7G databases and RNA interference to validate the relationships between BC-specific m7G-modification regulators (METTL1 and WDR4) and related genes. Single-cell RNA-sequencing data from GSE176078 confirmed the association between m7G modifications and TME cells. We constructed an m7G-TME classifier, validated the results using an independent BC cohort (GSE20685; n = 327), investigated the clinical significance of BC-specific m7G-modifying regulators by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis, and performed tissue-microarray assays on 192 BC samples. Results Immunohistochemistry and RT-qPCR results indicated that METTL1 and WDR4 overexpression in BC correlated with poor patient prognosis. Moreover, single-cell analysis revealed relationships between m7G modification and TME cells, indicating their potential as indicators of BC prognosis and treatment responses. The m7G-TME classifier enabled patient subgrouping and revealed significantly better survival and treatment responses in the m7Glow+TMEhigh group. Significant differences in tumor biological functions and immunophenotypes occurred among the different subgroups. Conclusions The m7G-TME classifier offers a promising tool for predicting prognosis and immunotherapeutic responses in BC, which could support personalized therapeutic strategies.
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Affiliation(s)
- Tingjun Li
- The School of Clinical Medicine, Fujian Medical University, Fuzhou, China
- Department of Breast Surgery, Quanzhou First Hospital of Fujian Medical University, Quanzhou, China
| | - Zhishan Chen
- Department of Breast and Thyroid Surgery, Nan’an Hospital, Quanzhou, China
| | - Zhitang Wang
- The School of Clinical Medicine, Fujian Medical University, Fuzhou, China
- Department of Breast Surgery, Quanzhou First Hospital of Fujian Medical University, Quanzhou, China
| | - Jingyu Lu
- The School of Clinical Medicine, Fujian Medical University, Fuzhou, China
- Department of Breast Surgery, The Affiliated Hospital of Putian University, Putian, China
| | - Debo Chen
- The School of Clinical Medicine, Fujian Medical University, Fuzhou, China
- Department of Breast Surgery, Quanzhou First Hospital of Fujian Medical University, Quanzhou, China
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14
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Zhang X, Zhu WY, Shen SY, Shen JH, Chen XD. Biological roles of RNA m7G modification and its implications in cancer. Biol Direct 2023; 18:58. [PMID: 37710294 PMCID: PMC10500781 DOI: 10.1186/s13062-023-00414-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 09/07/2023] [Indexed: 09/16/2023] Open
Abstract
M7G modification, known as one of the common post-transcriptional modifications of RNA, is present in many different types of RNAs. With the accurate identification of m7G modifications within RNAs, their functional roles in the regulation of gene expression and different physiological functions have been revealed. In addition, there is growing evidence that m7G modifications are crucial in the emergence of cancer. Here, we review the most recent findings regarding the detection techniques, distribution, biological functions and Regulators of m7G. We also summarize the connections between m7G modifications and cancer development, drug resistance, and tumor microenvironment as well as we discuss the research's future directions and trends.
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Affiliation(s)
- Xin Zhang
- Department of Dermatology, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China
| | - Wen-Yan Zhu
- Department of Dermatology, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China
| | - Shu-Yi Shen
- Department of Dermatology, the First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Jia-Hao Shen
- Department of Dermatology, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China
| | - Xiao-Dong Chen
- Department of Dermatology, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China.
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15
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Huang Y, Wu Z, Lan W, Zhong C. Predicting Disease-Associated N7-Methylguanosine (m 7G) Sites via Random Walk on Heterogeneous Network. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2023; 20:3173-3181. [PMID: 37294648 DOI: 10.1109/tcbb.2023.3284505] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Recent studies revealed that the modification of N7-methylguanosine (m7G) has associations with many human diseases. Effectively identifying disease-associated m7G methylation sites would provide crucial clues for disease diagnosis and treatment. Previous studies have developed computational methods to predict disease-associated m7G sites based on similarities among m7G sites and diseases. However, few have focused on the influence of the known m7G-disease association information on calculating similarity measures of m7G site and disease, which potentially promotes the identification of the disease-associated m7G sites. In this work, we propose а computational method called m7GDP-RW to predict m7G-disease associations by random walk algorithm. m7GDP-RW first incorporates the feature information of m7G site and disease with the known m7G-disease associations to compute m7G site similarity and disease similarity. Then m7GDP-RW combines the known m7G-disease associations with the computed similarity of m7G site and disease to construct a m7G-disease heterogeneous network. Finally, m7GDP-RW utilizes a two-pass random walk with restart algorithm to find novel m7G-disease associations on the heterogeneous network. The experimental results show that our method achieves higher prediction accuracy compared to the existing methods. The study case also demonstrates the effectiveness of m7GDP-RW in discovering potential m7G-disease associations.
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16
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Zhang Y, Ge F, Li F, Yang X, Song J, Yu DJ. Prediction of Multiple Types of RNA Modifications via Biological Language Model. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2023; 20:3205-3214. [PMID: 37289599 DOI: 10.1109/tcbb.2023.3283985] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
It has been demonstrated that RNA modifications play essential roles in multiple biological processes. Accurate identification of RNA modifications in the transcriptome is critical for providing insights into the biological functions and mechanisms. Many tools have been developed for predicting RNA modifications at single-base resolution, which employ conventional feature engineering methods that focus on feature design and feature selection processes that require extensive biological expertise and may introduce redundant information. With the rapid development of artificial intelligence technologies, end-to-end methods are favorably received by researchers. Nevertheless, each well-trained model is only suitable for a specific RNA methylation modification type for nearly all of these approaches. In this study, we present MRM-BERT by feeding task-specific sequences into the powerful BERT (Bidirectional Encoder Representations from Transformers) model and implementing fine-tuning, which exhibits competitive performance to the state-of-the-art methods. MRM-BERT avoids repeated de novo training of the model and can predict multiple RNA modifications such as pseudouridine, m6A, m5C, and m1A in Mus musculus, Arabidopsis thaliana, and Saccharomyces cerevisiae. In addition, we analyse the attention heads to provide high attention regions for the prediction, and conduct saturated in silico mutagenesis of the input sequences to discover potential changes of RNA modifications, which can better assist researchers in their follow-up research.
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17
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Wang Y, Wei Z, Su J, Coenen F, Meng J. RgnTX: Colocalization analysis of transcriptome elements in the presence of isoform heterogeneity and ambiguity. Comput Struct Biotechnol J 2023; 21:4110-4117. [PMID: 37671241 PMCID: PMC10475473 DOI: 10.1016/j.csbj.2023.08.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 08/13/2023] [Accepted: 08/23/2023] [Indexed: 09/07/2023] Open
Abstract
Colocalization analysis of genomic region sets has been widely adopted to unveil potential functional interactions between corresponding biological attributes, which often serves as the basis for further investigation. A number of methods have been developed for colocalization analysis of genomic elements. However, none of them explicitly considered the transcriptome heterogeneity and isoform ambiguity, making them less appropriate for analyzing transcriptome elements. Here, we developed RgnTX, an R/Bioconductor tool for the colocalization analysis of transcriptome elements with permutation tests. Different from existing approaches, RgnTX directly takes advantage of transcriptome annotation, and offers high flexibility in the null model to simulate realistic transcriptome-wide background, such as the complex alternative splicing patterns. Importantly, it supports the testing of transcriptome elements without clear isoform association, which is often the real scenario due to technical limitations. Proposed package offers a wide selection of pre-defined functions, easy to be utilized by users for visualizing permutation results, calculating shifted z-scores and conducting multiple hypothesis testing under Benjamini-Hochberg correction. Moreover, with synthetic and real datasets, we show that RgnTX novel testing modes return distinct and more significant results compared to existing genome-based methods. We believe RgnTX should make a useful tool to characterize the randomness of the transcriptome, and for conducting statistical association analysis for genomic region sets within the heterogeneous transcriptome. The package now has been accepted by Bioconductor and is freely available at: https://bioconductor.org/packages/RgnTX.
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Affiliation(s)
- Yue Wang
- Department of Mathematical Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Department of Computer Science, University of Liverpool, L69 7ZB Liverpool, United Kingdom
| | - Zhen Wei
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L69 7ZB Liverpool, United Kingdom
| | - Jionglong Su
- School of AI and Advanced Computing, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
| | - Frans Coenen
- Department of Computer Science, University of Liverpool, L69 7ZB Liverpool, United Kingdom
| | - Jia Meng
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- AI University Research Centre, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L69 7ZB Liverpool, United Kingdom
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18
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Lin Z, Wu Z, Yuan Y, Zhong W, Luo W. m7G-related genes predict prognosis and affect the immune microenvironment and drug sensitivity in osteosarcoma. Front Pharmacol 2023; 14:1158775. [PMID: 37654606 PMCID: PMC10466804 DOI: 10.3389/fphar.2023.1158775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Accepted: 08/01/2023] [Indexed: 09/02/2023] Open
Abstract
Background: Osteosarcoma (OS), a primary malignant bone tumor, confronts therapeutic challenges rooted in multidrug resistance. Comprehensive understanding of disease occurrence and progression is imperative for advancing treatment strategies. m7G modification, an emerging post-transcriptional modification implicated in various diseases, may provide new insights to explore OS pathogenesis and progression. Methods: The m7G-related molecular landscape in OS was probed using diverse bioinformatics analyses, encompassing LASSO Cox regression, immune infiltration assessment, and drug sensitivity analysis. Furthermore, the therapeutic potential of AZD2014 for OS was investigated through cell apoptosis and cycle assays. Eventually, multivariate Cox analysis and experimental validations, were conducted to investigate the independent prognostic m7G-related genes. Results: A comprehensive m7G-related risk model incorporating eight signatures was established, with corresponding risk scores correlated with immune infiltration and drug sensitivity. Drug sensitivity analysis spotlighted AZD2014 as a potential therapeutic candidate for OS. Subsequent experiments corroborated AZD2014's capability to induce G1-phase cell cycle arrest and apoptosis in OS cells. Ultimately, multivariate Cox regression analysis unveiled the independent prognostic importance of CYFIP1 and EIF4A1, differential expressions of which were validated at histological and cytological levels. Conclusion: This study furnishes a profound understanding of the contribution of m7G-related genes to the pathogenesis of OS. The discerned therapeutic potential of AZD2014, in conjunction with the identification of CYFIP1 and EIF4A1 as independent risk factors, opens novel vistas for the treatment of OS.
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Affiliation(s)
- Zili Lin
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, China
| | - Ziyi Wu
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yuhao Yuan
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, China
| | - Wei Zhong
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, China
| | - Wei Luo
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, China
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19
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Song B, Huang D, Zhang Y, Wei Z, Su J, Pedro de Magalhães J, Rigden DJ, Meng J, Chen K. m6A-TSHub: Unveiling the Context-specific m 6A Methylation and m 6A-affecting Mutations in 23 Human Tissues. GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:678-694. [PMID: 36096444 PMCID: PMC10787194 DOI: 10.1016/j.gpb.2022.09.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 08/19/2022] [Accepted: 09/02/2022] [Indexed: 06/15/2023]
Abstract
As the most pervasive epigenetic marker present on mRNAs and long non-coding RNAs (lncRNAs), N6-methyladenosine (m6A) RNA methylation has been shown to participate in essential biological processes. Recent studies have revealed the distinct patterns of m6A methylome across human tissues, and a major challenge remains in elucidating the tissue-specific presence and circuitry of m6A methylation. We present here a comprehensive online platform, m6A-TSHub, for unveiling the context-specific m6A methylation and genetic mutations that potentially regulate m6A epigenetic mark. m6A-TSHub consists of four core components, including (1) m6A-TSDB, a comprehensive database of 184,554 functionally annotated m6A sites derived from 23 human tissues and 499,369 m6A sites from 25 tumor conditions, respectively; (2) m6A-TSFinder, a web server for high-accuracy prediction of m6A methylation sites within a specific tissue from RNA sequences, which was constructed using multi-instance deep neural networks with gated attention; (3) m6A-TSVar, a web server for assessing the impact of genetic variants on tissue-specific m6A RNA modifications; and (4) m6A-CAVar, a database of 587,983 The Cancer Genome Atlas (TCGA) cancer mutations (derived from 27 cancer types) that were predicted to affect m6A modifications in the primary tissue of cancers. The database should make a useful resource for studying the m6A methylome and the genetic factors of epitranscriptome disturbance in a specific tissue (or cancer type). m6A-TSHub is accessible at www.xjtlu.edu.cn/biologicalsciences/m6ats.
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Affiliation(s)
- Bowen Song
- Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350004, China; Department of Mathematical Sciences, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China; Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Daiyun Huang
- Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China; Department of Computer Science, University of Liverpool, Liverpool L69 7ZB, United Kingdom.
| | - Yuxin Zhang
- Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China
| | - Zhen Wei
- Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China; Institute of Ageing & Chronic Disease, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Jionglong Su
- School of AI and Advanced Computing, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China
| | - João Pedro de Magalhães
- Institute of Ageing & Chronic Disease, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Daniel J Rigden
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Jia Meng
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom; Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China; AI University Research Centre, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China
| | - Kunqi Chen
- Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350004, China.
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20
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Zhang Y, Yu L, Jing R, Han B, Luo J. Fast and Efficient Design of Deep Neural Networks for Predicting N 7-Methylguanosine Sites Using autoBioSeqpy. ACS OMEGA 2023; 8:19728-19740. [PMID: 37305295 PMCID: PMC10249100 DOI: 10.1021/acsomega.3c01371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 05/10/2023] [Indexed: 06/13/2023]
Abstract
N7-Methylguanosine (m7G) is a crucial post-transcriptional RNA modification that plays a pivotal role in regulating gene expression. Accurately identifying m7G sites is a fundamental step in understanding the biological functions and regulatory mechanisms associated with this modification. While whole-genome sequencing is the gold standard for RNA modification site detection, it is a time-consuming, expensive, and intricate process. Recently, computational approaches, especially deep learning (DL) techniques, have gained popularity in achieving this objective. Convolutional neural networks and recurrent neural networks are examples of DL algorithms that have emerged as versatile tools for modeling biological sequence data. However, developing an efficient network architecture with superior performance remains a challenging task, requiring significant expertise, time, and effort. To address this, we previously introduced a tool called autoBioSeqpy, which streamlines the design and implementation of DL networks for biological sequence classification. In this study, we utilized autoBioSeqpy to develop, train, evaluate, and fine-tune sequence-level DL models for predicting m7G sites. We provided detailed descriptions of these models, along with a step-by-step guide on their execution. The same methodology can be applied to other systems dealing with similar biological questions. The benchmark data and code utilized in this study can be accessed for free at http://github.com/jingry/autoBioSeeqpy/tree/2.0/examples/m7G.
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Affiliation(s)
- Yonglin Zhang
- Department
of Pharmacy, Affiliated Hospital of North
Sichuan Medical College, Nanchong 637000, China
| | - Lezheng Yu
- School
of Chemistry and Materials Science, Guizhou
Education University, Guiyang 550024, China
| | - Runyu Jing
- School
of Cyber Science and Engineering, Sichuan
University, Chengdu 610017, China
| | - Bin Han
- GCP
Center/Institute of Drug Clinical Trials, Affiliated Hospital of North Sichuan Medical College, Nanchong 637503, China
| | - Jiesi Luo
- Basic
Medical College, Southwest Medical University, Luzhou 646099, Sichuan, China
- Key
Medical
Laboratory of New Drug Discovery and Druggability Evaluation, Luzhou
Key Laboratory of Activity Screening and Druggability Evaluation for
Chinese Materia Medica, Southwest Medical
University, Luzhou 646099, China
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21
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Yu L, Zhang Y, Xue L, Liu F, Jing R, Luo J. Evaluation and development of deep neural networks for RNA 5-Methyluridine classifications using autoBioSeqpy. Front Microbiol 2023; 14:1175925. [PMID: 37275146 PMCID: PMC10232852 DOI: 10.3389/fmicb.2023.1175925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/27/2023] [Indexed: 06/07/2023] Open
Abstract
Post-transcriptionally RNA modifications, also known as the epitranscriptome, play crucial roles in the regulation of gene expression during development. Recently, deep learning (DL) has been employed for RNA modification site prediction and has shown promising results. However, due to the lack of relevant studies, it is unclear which DL architecture is best suited for some pyrimidine modifications, such as 5-methyluridine (m5U). To fill this knowledge gap, we first performed a comparative evaluation of various commonly used DL models for epigenetic studies with the help of autoBioSeqpy. We identified optimal architectural variations for m5U site classification, optimizing the layer depth and neuron width. Second, we used this knowledge to develop Deepm5U, an improved convolutional-recurrent neural network that accurately predicts m5U sites from RNA sequences. We successfully applied Deepm5U to transcriptomewide m5U profiling data across different sequencing technologies and cell types. Third, we showed that the techniques for interpreting deep neural networks, including LayerUMAP and DeepSHAP, can provide important insights into the internal operation and behavior of models. Overall, we offered practical guidance for the development, benchmark, and analysis of deep learning models when designing new algorithms for RNA modifications.
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Affiliation(s)
- Lezheng Yu
- School of Chemistry and Materials Science, Guizhou Education University, Guiyang, China
| | - Yonglin Zhang
- Department of Pharmacy, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Li Xue
- School of Public Health, Southwest Medical University, Luzhou, China
| | - Fengjuan Liu
- School of Geography and Resources, Guizhou Education University, Guiyang, China
| | - Runyu Jing
- School of Cyber Science and Engineering, Sichuan University, Chengdu, China
| | - Jiesi Luo
- Basic Medical College, Southwest Medical University, Luzhou, China
- Sichuan Key Medical Laboratory of New Drug Discovery and Druggability Evaluation, Luzhou Key Laboratory of Activity Screening and Druggability Evaluation for Chinese Materia Medica, Southwest Medical University, Luzhou, China
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22
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Abstract
The epitranscriptome, defined as RNA modifications that do not involve alterations in the nucleotide sequence, is a popular topic in the genomic sciences. Because we need massive computational techniques to identify epitranscriptomes within individual transcripts, many tools have been developed to infer epitranscriptomic sites as well as to process datasets using high-throughput sequencing. In this review, we summarize recent developments in epitranscriptome spatial detection and data analysis and discuss their progression.
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Affiliation(s)
- Y-H Taguchi
- Department of Physics, Chuo University, Tokyo, Japan
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23
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Xia X, Wang Y, Zheng JC. Internal m7G methylation: A novel epitranscriptomic contributor in brain development and diseases. MOLECULAR THERAPY. NUCLEIC ACIDS 2023; 31:295-308. [PMID: 36726408 PMCID: PMC9883147 DOI: 10.1016/j.omtn.2023.01.003] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
In recent years, N7-methylguanosine (m7G) methylation, originally considered as messenger RNA (mRNA) 5' caps modifications, has been identified at defined internal positions within multiple types of RNAs, including transfer RNAs, ribosomal RNAs, miRNA, and mRNAs. Scientists have put substantial efforts to discover m7G methyltransferases and methylated sites in RNAs to unveil the essential roles of m7G modifications in the regulation of gene expression and determine the association of m7G dysregulation in various diseases, including neurological disorders. Here, we review recent findings regarding the distribution, abundance, biogenesis, modifiers, and functions of m7G modifications. We also provide an up-to-date summary of m7G detection and profile mapping techniques, databases for validated and predicted m7G RNA sites, and web servers for m7G methylation prediction. Furthermore, we discuss the pathological roles of METTL1/WDR-driven m7G methylation in neurological disorders. Last, we outline a roadmap for future directions and trends of m7G modification research, particularly in the central nervous system.
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Affiliation(s)
- Xiaohuan Xia
- Center for Translational Neurodegeneration and Regenerative Therapy, Tongji Hospital affiliated to Tongji University School of Medicine, Shanghai 200072, China,Shanghai Frontiers Science Center of Nanocatalytic Medicine, Shanghai 200331, China,Corresponding author: Xiaohuan Xia, Center for Translational Neurodegeneration and Regenerative Therapy, Tongji Hospital affiliated to Tongji University School of Medicine, Shanghai 200065, China.
| | - Yi Wang
- Shanghai Frontiers Science Center of Nanocatalytic Medicine, Shanghai 200331, China,Translational Research Center, Shanghai Yangzhi Rehabilitation Hospital affiliated to Tongji University School of Medicine, Shanghai 201613, China
| | - Jialin C. Zheng
- Center for Translational Neurodegeneration and Regenerative Therapy, Tongji Hospital affiliated to Tongji University School of Medicine, Shanghai 200072, China,Shanghai Frontiers Science Center of Nanocatalytic Medicine, Shanghai 200331, China,Corresponding author: Jialin C. Zheng, Center for Translational Neurodegeneration and Regenerative Therapy, Tongji Hospital affiliated to Tongji University School of Medicine, Shanghai 200065, China.
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24
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Song B, Wang X, Liang Z, Ma J, Huang D, Wang Y, de Magalhães JP, Rigden DJ, Meng J, Liu G, Chen K, Wei Z. RMDisease V2.0: an updated database of genetic variants that affect RNA modifications with disease and trait implication. Nucleic Acids Res 2023; 51:D1388-D1396. [PMID: 36062570 PMCID: PMC9825452 DOI: 10.1093/nar/gkac750] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/02/2022] [Accepted: 08/24/2022] [Indexed: 01/30/2023] Open
Abstract
Recent advances in epitranscriptomics have unveiled functional associations between RNA modifications (RMs) and multiple human diseases, but distinguishing the functional or disease-related single nucleotide variants (SNVs) from the majority of 'silent' variants remains a major challenge. We previously developed the RMDisease database for unveiling the association between genetic variants and RMs concerning human disease pathogenesis. In this work, we present RMDisease v2.0, an updated database with expanded coverage. Using deep learning models and from 873 819 experimentally validated RM sites, we identified a total of 1 366 252 RM-associated variants that may affect (add or remove an RM site) 16 different types of RNA modifications (m6A, m5C, m1A, m5U, Ψ, m6Am, m7G, A-to-I, ac4C, Am, Cm, Um, Gm, hm5C, D and f5C) in 20 organisms (human, mouse, rat, zebrafish, maize, fruit fly, yeast, fission yeast, Arabidopsis, rice, chicken, goat, sheep, pig, cow, rhesus monkey, tomato, chimpanzee, green monkey and SARS-CoV-2). Among them, 14 749 disease- and 2441 trait-associated genetic variants may function via the perturbation of epitranscriptomic markers. RMDisease v2.0 should serve as a useful resource for studying the genetic drivers of phenotypes that lie within the epitranscriptome layer circuitry, and is freely accessible at: www.rnamd.org/rmdisease2.
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Affiliation(s)
- Bowen Song
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
- Department of Mathematical Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L7 8TX, UK
| | - Xuan Wang
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
| | - Zhanmin Liang
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
| | - Jiongming Ma
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L7 8TX, UK
| | - Daiyun Huang
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
- Department of Computer Science, University of Liverpool, Liverpool L7 8TX, UK
| | - Yue Wang
- Department of Mathematical Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
- Department of Computer Science, University of Liverpool, Liverpool L7 8TX, UK
| | - João Pedro de Magalhães
- Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
| | - Daniel J Rigden
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L7 8TX, UK
| | - Jia Meng
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L7 8TX, UK
- AI University Research Centre, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
| | - Gang Liu
- Department of Mathematical Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
| | - Kunqi Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350004, China
| | - Zhen Wei
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China
- Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
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25
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Li Y, Ren J, Zhang Z, Weng Y, Zhang J, Zou X, Wu S, Hu H. Modification and Expression of mRNA m6A in the Lateral Habenular of Rats after Long-Term Exposure to Blue Light during the Sleep Period. Genes (Basel) 2023; 14:143. [PMID: 36672884 PMCID: PMC9859551 DOI: 10.3390/genes14010143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 12/26/2022] [Accepted: 12/30/2022] [Indexed: 01/06/2023] Open
Abstract
Artificial lighting, especially blue light, is becoming a public-health risk. Excessive exposure to blue light at night has been reported to be associated with brain diseases. However, the mechanisms underlying neuropathy induced by blue light remain unclear. An early anatomical tracing study described the projection of the retina to the lateral habenula (LHb), whereas more mechanistic reports are available on multiple brain functions and neuropsychiatric disorders in the LHb, which are rarely seen in epigenetic studies, particularly N6-methyladenosine (m6A). The purpose of our study was to first expose Sprague-Dawley rats to blue light (6.11 ± 0.05 mW/cm2, the same irradiance as 200 lx of white light in the control group) for 4 h, and simultaneously provide white light to the control group for the same time to enter a sleep period. The experiment was conducted over 12 weeks. RNA m6A modifications and different mRNA transcriptome profiles were observed in the LHb. We refer to this experimental group as BLS. High-throughput MeRIP-seq and mRNA-seq were performed, and we used bioinformatics to analyze the data. There were 188 genes in the LHb that overlapped between differentially m6A-modified mRNA and differentially expressed mRNA. The Kyoto Encyclopedia of Genes and Genomes and gene ontology analysis were used to enrich neuroactive ligand-receptor interaction, long-term depression, the cyclic guanosine monophosphate-dependent protein kinase G (cGMP-PKG) signaling pathway, and circadian entrainment. The m6A methylation level of the target genes in the BLS group was disordered. In conclusion, this study suggests that the mRNA expression and their m6A of the LHb were abnormal after blue light exposure during the sleep period, and the methylation levels of target genes related to synaptic plasticity were disturbed. This study offers a theoretical basis for the scientific use of light.
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Affiliation(s)
- Yinhan Li
- Fujian Key Laboratory of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou 350108, China
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou 350108, China
- Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou 350108, China
| | - Jinjin Ren
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Zhaoting Zhang
- School of Public Health, Fujian Medical University, Fuzhou 350108, China
| | - Yali Weng
- School of Public Health, Fujian Medical University, Fuzhou 350108, China
| | - Jian Zhang
- School of Public Health, Fujian Medical University, Fuzhou 350108, China
| | - Xinhui Zou
- School of Public Health, Fujian Medical University, Fuzhou 350108, China
| | - Siying Wu
- Fujian Key Laboratory of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou 350108, China
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou 350108, China
- Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou 350108, China
| | - Hong Hu
- Fujian Key Laboratory of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou 350108, China
- Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou 350108, China
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou 350108, China
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Yang C, Zhang L, Hao X, Tang M, Zhou B, Hou J. Identification of a Novel N7-Methylguanosine-Related LncRNA Signature Predicts the Prognosis of Hepatocellular Carcinoma and Experiment Verification. Curr Oncol 2022; 30:430-448. [PMID: 36661684 PMCID: PMC9857529 DOI: 10.3390/curroncol30010035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/24/2022] [Accepted: 12/26/2022] [Indexed: 12/30/2022] Open
Abstract
(1) Background: It is well-known that long non-coding RNAs (lncRNAs) and N7-methylguanosine (m7G) contribute to hepatocellular carcinoma (HCC) progression. However, it remains unclear whether lncRNAs regulating m7G modification could predict HCC prognosis. Thus, we sought to explore the prognostic implications of m7G-related lncRNAs in HCC patients. (2) Methods: Prognostic M7G-related lncRNAs obtained from The Cancer Genome Atlas (TCGA) database were screened by co-expression analysis and univariate Cox regression analysis. Next, the m7G-related lncRNA signature (m7GRLSig) was conducted by Least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression analysis. Kaplan-Meier analysis and time-dependent receiver operating characteristics (ROC) assessed the prognostic abilities of our signature. Univariate and multivariate Cox regression, nomogram, and principal component analysis (PCA) were conducted to evaluate our signature. Subsequently, we investigated the role of m7GRLSig on the immune landscape and sensitivity to drugs in HCC patients. The potential function of lncRNAs obtained from the prognostic signature was explored by in vitro experiments. (3) Results: A novel m7GRLSig was identified using seven meaningful lncRNA (ZFPM2-AS1, AC092171.2, PIK3CD-AS2, NRAV, CASC19, HPN-AS1, AC022613.1). The m7GLPSig exhibited worse survival in the high-risk group and served as an independent prognostic factor. The m7GRLSig stratification was sensitive in assessing the immune landscape and sensitivity to drugs between the high-risk and low-risk groups. Finally, in vitro experiments confirmed that the knockdown of NRAV was accompanied by the downregulation of METTL1 during HCC progression. (4) Conclusions: The m7G-related signature is a potential predictor of HCC prognosis and contributes to individualize the effective drug treatment of HCC.
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Affiliation(s)
| | | | | | | | - Bin Zhou
- State Key Laboratory of Organ Failure Research, Guangdong Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Jinlin Hou
- State Key Laboratory of Organ Failure Research, Guangdong Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
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Integrated Profiles of Transcriptome and mRNA m6A Modification Reveal the Intestinal Cytotoxicity of Aflatoxin B1 on HCT116 Cells. Genes (Basel) 2022; 14:genes14010079. [PMID: 36672820 PMCID: PMC9858580 DOI: 10.3390/genes14010079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 12/11/2022] [Accepted: 12/19/2022] [Indexed: 12/28/2022] Open
Abstract
Aflatoxin B1 (AFB1) is widely prevalent in foods and animal feeds and is one of the most toxic and carcinogenic aflatoxin subtypes. Existing studies have proved that the intestine is targeted by AFB1, and adverse organic effects have been observed. This study aimed to investigate the relationship between AFB1-induced intestinal toxicity and N6-methyladenosine (m6A) RNA methylation, which involves the post-transcriptional regulation of mRNA expression. The transcriptome-wide m6A methylome and transcriptome profiles in human intestinal cells treated with AFB1 are presented. Methylated RNA immunoprecipitation sequencing and mRNA sequencing were carried out to determine the distinctions in m6A methylation and different genes expressed in AFB1-induced intestinal toxicity. The results showed that there were 2289 overlapping genes of the differentially expressed mRNAs and differentially m6A-methylation-modified mRNAs. After enrichment of the signaling pathways and biological processes, these genes participated in the terms of the cell cycle, endoplasmic reticulum, tight junction, and mitophagy. In conclusion, the study demonstrated that AFB1-induced HCT116 injury was related to the disruptions to the levels of m6A methylation modifications of target genes and the abnormal expression of m6A regulators.
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28
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Wang X, Guo Z, Yan F. RNA Epigenetics in Chronic Lung Diseases. Genes (Basel) 2022; 13:genes13122381. [PMID: 36553648 PMCID: PMC9777603 DOI: 10.3390/genes13122381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 11/29/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022] Open
Abstract
Chronic lung diseases are highly prevalent worldwide and cause significant mortality. Lung cancer is the end stage of many chronic lung diseases. RNA epigenetics can dynamically modulate gene expression and decide cell fate. Recently, studies have confirmed that RNA epigenetics plays a crucial role in the developing of chronic lung diseases. Further exploration of the underlying mechanisms of RNA epigenetics in chronic lung diseases, including lung cancer, may lead to a better understanding of the diseases and promote the development of new biomarkers and therapeutic strategies. This article reviews basic information on RNA modifications, including N6 methylation of adenosine (m6A), N1 methylation of adenosine (m1A), N7-methylguanosine (m7G), 5-methylcytosine (m5C), 2'O-methylation (2'-O-Me or Nm), pseudouridine (5-ribosyl uracil or Ψ), and adenosine to inosine RNA editing (A-to-I editing). We then show how they relate to different types of lung disease. This paper hopes to summarize the mechanisms of RNA modification in chronic lung disease and finds a new way to develop early diagnosis and treatment of chronic lung disease.
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Affiliation(s)
- Xiaorui Wang
- Department of Ophthalmology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362002, China
| | - Zhihou Guo
- Center for Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362002, China
| | - Furong Yan
- Center for Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362002, China
- Correspondence:
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The prognostic index of m 7G-related genes in CRC correlates with immune infiltration. Sci Rep 2022; 12:21282. [PMID: 36482181 PMCID: PMC9732290 DOI: 10.1038/s41598-022-25823-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 12/05/2022] [Indexed: 12/13/2022] Open
Abstract
N7-methyladenosine (m7G) modifications have been the subject of growing research interest with respect to their relationship with the progression and treatment of various cancers. This analysis was designed to examine the association between m7G-related gene expression and colorectal cancer (CRC) patient outcomes. Initial training analyses were performed using the TCGA dataset, with the GSE28722 dataset then being used to validate these results. Univariate Cox analyses were initially conducted to screen out prognostic m7G-related genes, after which a LASSO approach was used to construct an m7G risk score (MRS) model. Kaplan-Meier curves, ROC curves, and Cox analyses were subsequently used to validate the prognostic utility of this model in CRC patients. The R maftools package was further employed to assess mutational characteristics in CRC patients in different MRS subgroups, while the ESTIMATE, CIBERSORT, and ssGSEA tools were used to conduct immune infiltration analyses. A WGCNA was then performed to identify key immune-associated hub genes. The EIF4E3, GEMIN5, and NCBP2 genes were used to establish the MRS model. Patients with high MRS scores exhibited worse overall survival than patients with low scores. In Cox analyses, MRS scores were independently associated with CRC patient prognosis. Patients with low MRS scores exhibited a higher tumor mutational burden and higher levels of microsatellite instability. In immune infiltration analyses, higher immune checkpoint expression and greater immune cell infiltration were also observed in patients with low MRS scores. WGCNA analyses further identified 25 CD8+ T cell infiltration-associated genes. These findings suggest that MRS values represent a useful biomarker capable of differentiating among CRC patients with different immunological features and prognostic outcomes, offering an opportunity to better determine which patients are likely to benefit from immune checkpoint inhibitor treatment.
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Wang D, Mo Y, Zhang D, Bai Y. Analysis of m 7G methylation modification patterns and pulmonary vascular immune microenvironment in pulmonary arterial hypertension. Front Immunol 2022; 13:1014509. [PMID: 36544768 PMCID: PMC9762157 DOI: 10.3389/fimmu.2022.1014509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 11/09/2022] [Indexed: 12/12/2022] Open
Abstract
Background M7G methylation modification plays an important role in cardiovascular disease development. Dysregulation of the immune microenvironment is closely related to the pathogenesis of PAH. However, it is unclear whether m7G methylation is involved in the progress of PAH by affecting the immune microenvironment. Methods The gene expression profile of PAH was obtained from the GEO database, and the m7G regulatory factors were analyzed for differences. Machine learning algorithms were used to screen characteristic genes, including the least absolute shrinkage and selection operator, random forest, and support vector machine recursive feature elimination analysis. Constructed a nomogram model, and receiver operating characteristic was used to evaluate the diagnosis of disease characteristic genes value. Next, we used an unsupervised clustering method to perform consistent clustering analysis on m7G differential genes. Used the ssGSEA algorithm to estimate the relationship between the m7G regulator in PAH and immune cell infiltration and analyze the correlation with disease-characteristic genes. Finally, the listed drugs were evaluated through the screened signature genes. Results We identified 15 kinds of m7G differential genes. CYFIP1, EIF4E, and IFIT5 were identified as signature genes by the machine learning algorithm. Meanwhile, two m7G molecular subtypes were identified by consensus clustering (cluster A/B). In addition, immune cell infiltration analysis showed that activated CD4 T cells, regulatory T cells, and type 2 T helper cells were upregulated in m7G cluster B, CD56 dim natural killer cells, MDSC, and monocyte were upregulated in the m7G cluster A. It might be helpful to select Calpain inhibitor I and Everolimus for the treatment of PAH. Conclusion Our study identified CYFIP1, EIF4E, and IFIT5 as novel diagnostic biomarkers in PAH. Furthermore, their association with immune cell infiltration may facilitate the development of immune therapy in PAH.
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Affiliation(s)
- Desheng Wang
- Department of Clinical Pharmacology, School of Pharmacy, China Medical University, Shenyang, Liaoning, China
| | - Yanfei Mo
- Department of Clinical Pharmacology, School of Pharmacy, China Medical University, Shenyang, Liaoning, China
| | - Dongfang Zhang
- Department of Pharmacognosy, School of Pharmacy, China Medical University, Shenyang, Liaoning, China,*Correspondence: Yang Bai, ; Dongfang Zhang,
| | - Yang Bai
- Department of Clinical Pharmacology, School of Pharmacy, China Medical University, Shenyang, Liaoning, China,*Correspondence: Yang Bai, ; Dongfang Zhang,
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Wu S, Ballah AK, Che W, Wang X. M7G-related LncRNAs: A comprehensive analysis of the prognosis and immunity in glioma. Front Genet 2022; 13:961278. [DOI: 10.3389/fgene.2022.961278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Accepted: 11/02/2022] [Indexed: 11/17/2022] Open
Abstract
Today, numerous international researchers have demonstrated that N7-methylguanosine (m7G) related long non-coding RNAs (m7G-related lncRNAs) are closely linked to the happenings and developments of various human beings’ cancers. However, the connection between m7G-related lncRNAs and glioma prognosis has not been investigated. We did this study to look for new potential biomarkers and construct an m7G-related lncRNA prognostic signature for glioma. We identified those lncRNAs associated with DEGs from glioma tissue sequences as m7G-related lncRNAs. First, we used Pearson’s correlation analysis to identify 28 DEGs by glioma and normal brain tissue gene sequences and predicated 657 m7G-related lncRNAs. Then, eight lncRNAs associated with prognosis were obtained and used to construct the m7G risk score model by lasso and Cox regression analysis methods. Furthermore, we used Kaplan-Meier analysis, time-dependent ROC, principal component analysis, clinical variables, independent prognostic analysis, nomograms, calibration curves, and expression levels of lncRNAs to determine the model’s accuracy. Importantly, we validated the model with external and internal validation methods and found it has strong predictive power. Finally, we performed functional enrichment analysis (GSEA, aaGSEA enrichment analyses) and analyzed immune checkpoints, associated pathways, and drug sensitivity based on predictors. In conclusion, we successfully constructed the formula of m7G-related lncRNAs with powerful predictive functions. Our study provides instructional value for analyzing glioma pathogenesis and offers potential research targets for glioma treatment and scientific research.
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32
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Ma J, Zhang L, Li S, Liu H. BRPCA: Bounded Robust Principal Component Analysis to Incorporate Similarity Network for N7-Methylguanosine(m 7G) Site-Disease Association Prediction. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2022; 19:3295-3306. [PMID: 34469307 DOI: 10.1109/tcbb.2021.3109055] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Recent studies have revealed that N7-methylguanosine(m7G) plays a pivotal role in various biological processes and disease pathogenesis. To date, transcriptome-wide m7G modification sites have been identified by high-throughput sequencing approaches, and some related information has been recorded in a few biological databases. However, the mechanism of site action in disease remains uncharted. Wet experiments can help identify true m7G sites with high confidence, but it is time-consuming to find the true ones in such a large number of sites, which will also cost too much. Thus, computational methods are emergently needed to predict the associations between m7G sites and various diseases, thus help to uncover potential active sites for specific diseases. In this article, we proposed a bounded robust principal component analysis (BRPCA) method to predict unknown m7G-disease association based on similarity information. Importantly, BRPCA tolerates the noise and redundancy existing in association and similarity information. Moreover, a suitable bounded constraint is incorporated into BRPCA to ensure that the predicted association scores locate in a meaningful interval. The extensive experiments demonstrate the superiority and robustness of the BRPCA.
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Lai G, Zhong X, Liu H, Deng J, Li K, Xie B. A Novel m7G-Related Genes-Based Signature with Prognostic Value and Predictive Ability to Select Patients Responsive to Personalized Treatment Strategies in Bladder Cancer. Cancers (Basel) 2022; 14:5346. [PMID: 36358764 PMCID: PMC9656096 DOI: 10.3390/cancers14215346] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/27/2022] [Accepted: 10/27/2022] [Indexed: 09/08/2023] Open
Abstract
Although N7-methylguanosine (m7G) modification serves as a tumor promoter in bladder cancer (BLCA), the comprehensive role of m7G-related characterization in BLCA remains unclear. In this study, we systematically evaluated the m7G-related clusters of 760 BLCA patients through consensus unsupervised clustering analysis. Next, we investigated the underlying m7G-related genes among these m7G-related clusters. Univariate Cox and LASSO regressions were used for screening out prognostic genes and for reducing the dimension, respectively. Finally, we developed a novel m7G-related scoring system via the GSVA algorithm. The correlation between tumor microenvironment, prediction of personalized therapies and this m7G-related signature was gradually revealed. We first identified three m7G-related clusters and 1108 differentially expressed genes relevant to the three clusters. Based on the profile of 1108 genes, we divided BLCA patients into two clusters, which were quantified by our established m7G-related scoring system. Patients with higher m7G-related scores tended to have a better OS and more chances to benefit from immunotherapy. A significantly negative connection between sensitivity to classic chemotherapeutic drugs and m7G-related signature was uncovered. In summary, our data show that m7G-related characterization of BLCA patients can be of value for prognostic stratification and for patient-oriented therapeutic options, designing personalized treatment strategies in the preclinical setting.
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Affiliation(s)
| | - Xiaoni Zhong
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Yixue Road, Chongqing 400016, China
| | | | | | | | - Biao Xie
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Yixue Road, Chongqing 400016, China
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Wang L, Hu X, Liu X, Feng Y, Zhang Y, Han J, Liu X, Meng F. m7G regulator-mediated methylation modification patterns define immune cell infiltration and patient survival. Front Immunol 2022; 13:1022720. [DOI: 10.3389/fimmu.2022.1022720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 10/18/2022] [Indexed: 11/13/2022] Open
Abstract
Numerous studies have demonstrated the important roles of epigenetic modifications in tumorigenesis, progression and prognosis. However, in hepatocellular carcinoma, the potential link between N7-methylguanosine (m7G) modification and molecular heterogeneity and tumor microenvironment (TME) remains unclear.MethodWe performed a comprehensive evaluation of m7G modification patterns in 816 hepatocellular carcinoma samples based on 24 m7G regulatory factors, identified different m7G modification patterns, and made a systematic correlation of these modification patterns with the infiltration characteristics of immunocytes. Then, we built and validated a scoring tool called m7G score.ResultsIn this study, we revealed the presence of three distinct m7G modification patterns in liver cancer, with remarkable differences in the immunocyte infiltration characteristics of these three subtypes. The m7G scoring system of this study could assess m7G modification patterns in individual hepatocellular carcinoma patients, could predict TME infiltration characteristics, genetic variants and patient prognosis. We also found that the m7G scoring system may be useful in guiding patients’ clinical use of medications.ConclusionsThis study revealed that m7G methylation modifications exerted a significant role in formation of TME in hepatocellular carcinoma. Assessing the m7G modification patterns of single patients would help enhance our perception of TME infiltration characteristics and give significant insights into immunotherapy efficacy.
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Lu L, Zheng J, Liu B, Wu H, Huang J, Wu L, Li D. The m7G Modification Level and Immune Infiltration Characteristics in Patients with COVID-19. J Multidiscip Healthc 2022; 15:2461-2472. [PMID: 36320552 PMCID: PMC9618243 DOI: 10.2147/jmdh.s385050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 10/14/2022] [Indexed: 11/10/2022] Open
Abstract
Purpose The 7-methylguanosine (m7G)-related genes were used to identify the clinical severity and prognosis of patients with coronavirus disease 2019 (COVID-19) and to identify possible therapeutic targets. Patients and Methods The GSE157103 dataset provides the transcriptional spectrum and clinical information required to analyze the expression of m7G-related genes and the disease subtypes. R language was applied for immune infiltration analysis, functional enrichment analysis, and nomogram model construction. Results Most m7G-related genes were up-regulated in COVID-19 and were closely related to immune cell infiltration. Disease subtypes were grouped using a clustering algorithm. It was found that the m7G-cluster B was associated with higher immune infiltration, lower mechanical ventilation, lower intensive care unit (ICU) status, higher ventilator-free days, and lower m7G scores. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that differentially expressed genes (DEGs) between m7G-cluster A and B were enriched in viral infection and immune-related aspects, including COVID-19 infection; Th17, Th1, and Th2 cell differentiation, and human T-cell leukemia virus 1 infection. Finally, through machine learning, six disease characteristic genes, NUDT4B, IFIT5, LARP1, EIF4E, LSM1, and NUDT4, were screened and used to develop a nomogram model to estimate disease risk. Conclusion The expression of most m7G genes was higher in COVID-19 patients compared with that in non-COVID-19 patients. The m7G-cluster B showed higher immune infiltration and milder symptoms. The predictive nomogram based on the six m7G genes can be used to accurately assess risk.
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Affiliation(s)
- Lingling Lu
- Fuzong Clinical Medical College of Fujian Medical University, The 900th Hospital, Fuzhou, People’s Republic of China
| | - Jiaolong Zheng
- Fuzong Clinical Medical College of Fujian Medical University, The 900th Hospital, Fuzhou, People’s Republic of China,Department of Hepatobiliary Disease, The 900th Hospital of Joint Logistics Support Force, Fuzhou, People’s Republic of China
| | - Bang Liu
- Fuzong Clinical Medical College of Fujian Medical University, The 900th Hospital, Fuzhou, People’s Republic of China
| | - Haicong Wu
- Fuzong Clinical Medical College of Fujian Medical University, The 900th Hospital, Fuzhou, People’s Republic of China,Department of Hepatobiliary Disease, The 900th Hospital of Joint Logistics Support Force, Fuzhou, People’s Republic of China
| | - Jiaofeng Huang
- Fuzong Clinical Medical College of Fujian Medical University, The 900th Hospital, Fuzhou, People’s Republic of China
| | - Liqing Wu
- Department of Hepatobiliary Disease, The 900th Hospital of Joint Logistics Support Force, Fuzhou, People’s Republic of China
| | - Dongliang Li
- Fuzong Clinical Medical College of Fujian Medical University, The 900th Hospital, Fuzhou, People’s Republic of China,Department of Hepatobiliary Disease, The 900th Hospital of Joint Logistics Support Force, Fuzhou, People’s Republic of China,Correspondence: Dongliang Li, Fuzong Clinical Medical College of Fujian Medical University, The 900th Hospital of the People’s Liberation Army Joint Logistics Support Force, No. 156 Xierhuan Road, Fuzhou, Fujian, 350025, People’s Republic of China, Tel/Fax +86 591 22859128, Email
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Li M, Zhang T, Chen W. Development of necroptosis-related gene signature to predict the prognosis of colon adenocarcinoma. Front Genet 2022; 13:1051800. [DOI: 10.3389/fgene.2022.1051800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 10/10/2022] [Indexed: 12/24/2022] Open
Abstract
Colon adenocarcinoma (COAD) is a common malignancy and has a high mortality rate. However, the current tumor node metastasis (TNM) staging system is inadequate for prognostic assessment of COAD patients. Therefore, there is an urgent need to identify reliable biomarkers for the prognosis COAD patients. The aberrant expression of necroptosis-related genes (NRGs) is reported to be associated with tumorigenesis and metastasis. In the present work, we compared the expression profiles of NRGs between COAD patients and normal individuals. Based on seven differentially expressed NRGs, a risk score was defined to predict the prognosis of COAD patients. The validation results from both training and independent external cohorts demonstrated that the risk score is able to distinguish the high and low risk COAD patients with higher accuracies, and is independent of the other clinical factors. To facilitate its clinical use, by integrating the proposed risk score, a nomogram was built to predict the risk of individual COAD patients. The C-index of the nomogram is 0.75, indicating the reliability of the nomogram in predicting survival rates. Furthermore, two candidate drugs, namely dapsone and xanthohumol, were screed out and validated by molecular docking, which hold the potential for the treatment of COAD. These results will provide novel clues for the diagnosis and treatment of COAD.
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Cao J, Liang Y, Gu JJ, Huang Y, Wang B. Construction of prognostic signature of breast cancer based on N7-Methylguanosine-Related LncRNAs and prediction of immune response. Front Genet 2022; 13:991162. [PMID: 36353118 PMCID: PMC9639662 DOI: 10.3389/fgene.2022.991162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 10/12/2022] [Indexed: 11/17/2022] Open
Abstract
Background: Long non-coding RNA (LncRNA) is a prognostic factor for malignancies, and N7-Methylguanosine (m7G) is crucial in the occurrence and progression of tumors. However, it has not been documented how well m7G-related LncRNAs predict the development of breast cancer (BC). This study aims to develop a predictive signature based on long non-coding RNAs (LncRNAs) associated with m7G to predict the prognosis of breast cancer patients. Methods: The Cancer Genome Atlas (TCGA) database provided us with the RNA-seq data and matching clinical information of individuals with breast cancer. To identify the signature of N7-Methylguanosine-Related LncRNAs and create a prognostic model, we employed co-expression network analysis, least absolute shrinkage selection operator (LASSO) regression analysis, univariate Cox regression analysis, and multivariate Cox regression analysis. The signature was assessed using the Kaplan-Meier analysis and Receiver Operating Characteristic (ROC) curve. A nomogram and principal component analysis (PCA) were employed to confirm the predictive signature’s usefulness. Then, we examined the drug sensitivity between the two risk groups and utilized single-sample gene set enrichment analysis (ssGSEA) to investigate the association between predictive factors and the tumor immune microenvironment in high-risk and low-risk groups. Results: Nine m7G-related LncRNAs (LINC01871, AP003469.4, Z68871.1, AC245297.3, EGOT, TFAP2A-AS1, AL136531.1, SEMA3B-AS1, AL606834.2) that are independently associated with the overall survival time (OS) of BC patients make up the signature we developed. For predicting 1-, 3-, and 5-year survival rates, the areas under the ROC curve (AUC) were 0.715, 0.724, and 0.726, respectively. The Kaplan-Meier analysis revealed that the prognosis of BC patients in the high-risk group was worse than that of those in the low-risk group. When compared to clinicopathological variables, multiple regression analysis demonstrated that risk score was a significant independent predictive factor for BC patients. The results of the ssGSEA study revealed a substantial correlation between the predictive traits and the BC patients’ immunological status, low-risk BC patients had more active immune systems, and they responded better to PD1/L1 immunotherapy. Conclusion: The prognostic signature, which is based on m7G-related LncRNAs, can be utilized to inform patients’ customized treatment plans by independently predicting their prognosis and how well they would respond to immunotherapy.
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Affiliation(s)
- Jin Cao
- Medical College, Yangzhou University, Yangzhou, Jiangsu, China
| | - Yichen Liang
- Institute of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, China
- Department of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, China
| | - J. Juan Gu
- Medical College, Yangzhou University, Yangzhou, Jiangsu, China
- Institute of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, China
- Department of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, China
| | - Yuxiang Huang
- Institute of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, China
- Department of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, China
| | - Buhai Wang
- Medical College, Yangzhou University, Yangzhou, Jiangsu, China
- Institute of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, China
- Department of Oncology, Northern Jiangsu People’s Hospital, Yangzhou, Jiangsu, China
- *Correspondence: Buhai Wang,
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Huang Z, Lou K, Liu H. A novel prognostic signature based on N7-methylguanosine-related long non-coding RNAs in breast cancer. Front Genet 2022; 13:1030275. [PMID: 36313442 PMCID: PMC9608183 DOI: 10.3389/fgene.2022.1030275] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Accepted: 10/03/2022] [Indexed: 12/24/2022] Open
Abstract
Long non-coding RNA (lncRNA) are closely associated with the occurrence and progression of tumors. However, research on N7-methylguanosine (m7G)-related lncRNA in breast cancer is lacking. Therefore, the present study explored the prognostic value, gene expression characteristics, and effects of m7G-related lncRNA on tumor immune cell infiltration and tumor mutational burden (TMB) in breast cancer. lncRNA expression matrices and clinical follow-up data of patients with breast cancer were obtained from The Cancer Genome Atlas, revealing eight significantly differentially expressed and prognostically relevant m7G-related lncRNAs in breast cancer tissues: BAIAP2-DT, COL4A2-AS1, FARP1-AS1, RERE-AS1, NDUFA6-DT, TFAP2A-AS1, LINC00115, and MIR302CHG. A breast cancer prognostic signature was created based on these m7G-related lncRNAs according to least absolute shrinkage and selection operator Cox regression. The prognostic signature combined with potential prognostic factors showed independent prognostic value, reliability, and specificity. Meanwhile, we constructed a risk score-based nomogram to assist clinical decision-making. Gene set enrichment analysis revealed that low- and high-risk group were associated with metabolism-related pathways. Our study demonstrated the association between tumor immune cell infiltration based on analyses with the CIBERSORT algorithm and prognostic signature. We also assessed the correlation between prognostic signature and TMB. Lastly, quantitative real-time polymerase chain reaction analysis was performed to validate differentially expressed lncRNAs. The effective prognostic signature based on m7G-related lncRNAs has the potential to predict the survival prognosis of patients with breast cancer. The eight m7G-related lncRNAs identified in this study might represent potential biomarkers and therapeutic targets of breast cancer.
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Chen M, Nie Z, Gao Y, Cao H, Zheng L, Guo N, Peng Y, Zhang S. m7G regulator-mediated molecular subtypes and tumor microenvironment in kidney renal clear cell carcinoma. Front Pharmacol 2022; 13:900006. [PMID: 36147333 PMCID: PMC9486008 DOI: 10.3389/fphar.2022.900006] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Accepted: 08/15/2022] [Indexed: 11/13/2022] Open
Abstract
Background: RNA methylation modification plays an important role in immune regulation. m7G RNA methylation is an emerging research hotspot in the RNA methylation field. However, its role in the tumor immune microenvironment of kidney renal clear cell carcinoma (KIRC) is still unclear. Methods: We analyzed the expression profiles of 29 m7G regulators in KIRC, integrated multiple datasets to identify a novel m7G regulator-mediated molecular subtype, and developed the m7G score. We evaluated the immune tumor microenvironments in m7G clusters and analyzed the correlation of the m7G score with immune cells and drug sensitivity. We tested the predictive power of the m7G score for prognosis of patients with KIRC and verified the predictive accuracy of the m7G score by using the GSE40912 and E-MTAB-1980 datasets. The genes used to develop the m7G score were verified by qRT-PCR. Finally, we experimentally analyzed the effects of WDR4 knockdown on KIRC proliferation, migration, invasion, and drug sensitivity. Results: We identified three m7G clusters. The expression of m7G regulators was higher in cluster C than in other clusters. m7G cluster C was related to immune activation, low tumor purity, good prognosis, and low m7G score. Cluster B was related to drug metabolism, high tumor purity, poor survival, and high m7G score. Cluster A was related to purine metabolism. The m7G score can well-predict the prognosis of patients with KIRC, and its prediction accuracy based on the m7G score nomogram was very high. Patients with high m7G scores were more sensitive to rapamycin, gefitinib, sunitinib, and vinblastine than other patients. Knocking down WDR4 can inhibit the proliferation, migration, and invasion of 786-0 and Caki-1 cells and increase sensitivity to sorafenib and sunitinib. Conclusion: We proposed a novel molecular subtype related to m7G modification and revealed the immune cell infiltration characteristics of different subtypes. The developed m7G score can well-predict the prognosis of patients with KIRC, and our research provides a basis for personalized treatment of patients with KIRC.
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Feng Q, Wang D, Xue T, Lin C, Gao Y, Sun L, Jin Y, Liu D. The role of RNA modification in hepatocellular carcinoma. Front Pharmacol 2022; 13:984453. [PMID: 36120301 PMCID: PMC9479111 DOI: 10.3389/fphar.2022.984453] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 08/11/2022] [Indexed: 12/25/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is a highly mortal type of primary liver cancer. Abnormal epigenetic modifications are present in HCC, and RNA modification is dynamic and reversible and is a key post-transcriptional regulator. With the in-depth study of post-transcriptional modifications, RNA modifications are aberrantly expressed in human cancers. Moreover, the regulators of RNA modifications can be used as potential targets for cancer therapy. In RNA modifications, N6-methyladenosine (m6A), N7-methylguanosine (m7G), and 5-methylcytosine (m5C) and their regulators have important regulatory roles in HCC progression and represent potential novel biomarkers for the confirmation of diagnosis and treatment of HCC. This review focuses on RNA modifications in HCC and the roles and mechanisms of m6A, m7G, m5C, N1-methyladenosine (m1A), N3-methylcytosine (m3C), and pseudouridine (ψ) on its development and maintenance. The potential therapeutic strategies of RNA modifications are elaborated for HCC.
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Affiliation(s)
- Qiang Feng
- Laboratory Animal Center, College of Animal Science, Jilin University, Changchun, China
| | - Dongxu Wang
- Laboratory Animal Center, College of Animal Science, Jilin University, Changchun, China
| | - Tianyi Xue
- Laboratory Animal Center, College of Animal Science, Jilin University, Changchun, China
| | - Chao Lin
- School of Grain Science and Technology, Jilin Business and Technology College, Changchun, China
| | - Yongjian Gao
- Department of Gastrointestinal Colorectal and Anal Surgery, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Liqun Sun
- Department of Pediatrics, First Hospital of Jilin University, Changchun, China
| | - Ye Jin
- School of Pharmacy, Changchun University of Chinese Medicine, Changchun, China
| | - Dianfeng Liu
- Laboratory Animal Center, College of Animal Science, Jilin University, Changchun, China
- *Correspondence: Dianfeng Liu,
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Zhao K, Mao Y, Li Y, Yang C, Wang K, Zhang J. The roles and mechanisms of epigenetic regulation in pathological myocardial remodeling. Front Cardiovasc Med 2022; 9:952949. [PMID: 36093141 PMCID: PMC9458904 DOI: 10.3389/fcvm.2022.952949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 08/10/2022] [Indexed: 11/22/2022] Open
Abstract
Pathological myocardial remodeling was still one of the leading causes of death worldwide with an unmet therapeutic need. A growing number of researchers have addressed the role of epigenome changes in cardiovascular diseases, paving the way for the clinical application of novel cardiovascular-related epigenetic targets in the future. In this review, we summarized the emerged advances of epigenetic regulation, including DNA methylation, Histone posttranslational modification, Adenosine disodium triphosphate (ATP)-dependent chromatin remodeling, Non-coding RNA, and RNA modification, in pathological myocardial remodeling. Also, we provided an overview of the mechanisms that potentially involve the participation of these epigenetic regulation.
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Affiliation(s)
- Kun Zhao
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yukang Mao
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yansong Li
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Chuanxi Yang
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Department of Cardiology, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Kai Wang
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Kai Wang
| | - Jing Zhang
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- *Correspondence: Jing Zhang
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Yang H, Messina-Pacheco J, Corredor ALG, Gregorieff A, Liu JL, Nehme A, Najafabadi HS, Riazalhosseini Y, Gao B, Gao ZH. An integrated model of acinar to ductal metaplasia-related N7-methyladenosine regulators predicts prognosis and immunotherapy in pancreatic carcinoma based on digital spatial profiling. Front Immunol 2022; 13:961457. [PMID: 35979350 PMCID: PMC9377277 DOI: 10.3389/fimmu.2022.961457] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Accepted: 06/24/2022] [Indexed: 12/14/2022] Open
Abstract
Acinar-to-ductal metaplasia (ADM) is a recently recognized, yet less well-studied, precursor lesion of pancreatic ductal adenocarcinoma (PDAC) developed in the setting of chronic pancreatitis. Through digital spatial mRNA profiling, we compared ADM and adjacent PDAC tissues from patient samples to unveil the bridging genes during the malignant transformation of pancreatitis. By comparing the bridging genes with the 7-methylguanosine (m7G)-seq dataset, we screened 19 m7G methylation genes for a subsequent large sample analysis. We constructed the “m7G score” model based on the RNA-seq data for pancreatic cancer in The Cancer Genome Atlas (TCGA) database and The Gene Expression Omnibus (GEO) database. Tumors with a high m7G score were characterized by increased immune cell infiltration, increased genomic instability, higher response rate to combined immune checkpoint inhibitors (ICIs), and overall poor survival. These findings indicate that the m7G score is associated with tumor invasiveness, immune cell infiltration, ICI treatment response, and overall patients’ survival. We also identified FN1 and ITGB1 as core genes in the m7Gscore model, which affect immune cell infiltration and genomic instability not only in pancreatic cancer but also in pan-cancer. FN1 and ITGB1 can inhibit immune T cell activition by upregulation of macrophages and neutrophils, thereby leading to immune escape of pancreatic cancer cells and reducing the response rate of ICI treatment.
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Affiliation(s)
- Hao Yang
- Department of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Julia Messina-Pacheco
- Department of Pathology, McGill University and the Research Institute of McGill University Health Centre, Montreal, QC, Canada
| | - Andrea Liliam Gomez Corredor
- Department of Pathology, McGill University and the Research Institute of McGill University Health Centre, Montreal, QC, Canada
| | - Alex Gregorieff
- Department of Pathology, McGill University and the Research Institute of McGill University Health Centre, Montreal, QC, Canada
| | - Jun-li Liu
- MeDic Program, The Research Institute of McGill University Health Centre, & Division of Endocrinology and Metabolism, Department of Medicine, McGill University, Montreal, QC, Canada
| | - Ali Nehme
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- McGill University Genome Centre, Montreal, QC, Canada
| | - Hamed S. Najafabadi
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- McGill University Genome Centre, Montreal, QC, Canada
| | - Yasser Riazalhosseini
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- McGill University Genome Centre, Montreal, QC, Canada
| | - Bo Gao
- Department of General Surgery, Peking University People’s Hospital, Beijing, China
- *Correspondence: Zu-hua Gao, ; Bo Gao,
| | - Zu-hua Gao
- Department of Pathology and Laboratory Medicine, British Columbia (BC) Cancer Research Center, University of British Columbia, Vancouver, BC, Canada
- *Correspondence: Zu-hua Gao, ; Bo Gao,
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Chen HM, Li H, Lin MX, Fan WJ, Zhang Y, Lin YT, Wu SX. Research Progress for RNA Modifications in Physiological and Pathological Angiogenesis. Front Genet 2022; 13:952667. [PMID: 35937999 PMCID: PMC9354963 DOI: 10.3389/fgene.2022.952667] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 06/20/2022] [Indexed: 12/04/2022] Open
Abstract
As a critical layer of epigenetics, RNA modifications demonstrate various molecular functions and participate in numerous biological processes. RNA modifications have been shown to be essential for embryogenesis and stem cell fate. As high-throughput sequencing and antibody technologies advanced by leaps and bounds, the association of RNA modifications with multiple human diseases sparked research enthusiasm; in addition, aberrant RNA modification leads to tumor angiogenesis by regulating angiogenesis-related factors. This review collected recent cutting-edge studies focused on RNA modifications (N6-methyladenosine (m6A), N5-methylcytosine (m5C), N7-methylguanosine (m7G), N1-methyladenosine (m1A), and pseudopuridine (Ψ)), and their related regulators in tumor angiogenesis to emphasize the role and impact of RNA modifications.
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Affiliation(s)
- Hui-Ming Chen
- Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
- Fujian Key Laboratory of Tumor Microbiology, Department of Medical Microbiology, Fujian Medical University, Fuzhou, China
| | - Hang Li
- Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Meng-Xian Lin
- Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Wei-Jie Fan
- Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Yi Zhang
- Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Yan-Ting Lin
- Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
- Fujian Key Laboratory of Tumor Microbiology, Department of Medical Microbiology, Fujian Medical University, Fuzhou, China
- *Correspondence: Shu-Xiang Wu, ; Yan-Ting Lin,
| | - Shu-Xiang Wu
- Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
- Fujian Key Laboratory of Tumor Microbiology, Department of Medical Microbiology, Fujian Medical University, Fuzhou, China
- *Correspondence: Shu-Xiang Wu, ; Yan-Ting Lin,
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Wu JY, Song QY, Huang CZ, Shao Y, Wang ZL, Zhang HQ, Fu Z. N7-methylguanosine-related lncRNAs: Predicting the prognosis and diagnosis of colorectal cancer in the cold and hot tumors. Front Genet 2022; 13:952836. [PMID: 35937987 PMCID: PMC9352958 DOI: 10.3389/fgene.2022.952836] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 06/27/2022] [Indexed: 11/13/2022] Open
Abstract
Background: 7-Methylguanosine(m7G) contributes greatly to its pathogenesis and progression in colorectal cancer. We proposed building a prognostic model of m7G-related LncRNAs. Our prognostic model was used to identify differences between hot and cold tumors.Methods: The study included 647 colorectal cancer patients (51 cancer-free patients and 647 cancer patients) from The Cancer Genome Atlas (TCGA). We identified m7G-related prognostic lncRNAs by employing the univariate Cox regression method. Assessments were conducted using univariate Cox regression, multivariate Cox regression, receiver operating characteristics (ROC), nomogram, calibration curves, and Kaplan-Meier analysis. All of these procedures were used with the aim of confirming the validity and stability of the model. Besides these two analyses, we also conducted half-maximal inhibitory concentration (IC50), immune analysis, principal component analysis (PCA), and gene set enrichment analysis (GSEA). The entire set of m7G-related (lncRNAs) with respect to cold and hot tumors has been divided into two clusters for further discussion of immunotherapy.Results: The risk model was constructed with 17 m7G-related lncRNAs. A good correlation was found between the calibration plots and the prognosis prediction in the model. By assessing IC50 in a significant way across risk groups, systemic treatment can be guided. By using clusters, it may be possible to distinguish hot and cold tumors effectively and to aid in specific therapeutic interventions. Cluster 1 was identified as having the highest response to immunotherapy drugs and thus was identified as the hot tumor.Conclusion: This study shows that 17 m7G-related lncRNA can be used in clinical settings to predict prognosis and use them to determine whether a tumor is cold or hot in colorectal cancer and improve the individualization of treatment.
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Affiliation(s)
- Jing-Yu Wu
- The General Surgery Laboratory, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qing-Yu Song
- The General Surgery Laboratory, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Chang-Zhi Huang
- The General Surgery Laboratory, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yu Shao
- The General Surgery Laboratory, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zhen-Ling Wang
- The General Surgery Laboratory, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hong-Qiang Zhang
- The General Surgery Laboratory, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zan Fu
- The General Surgery Laboratory, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- *Correspondence: Zan Fu,
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45
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Zhang B, Li D, Wang R. Transcriptome Profiling of N7-Methylguanosine Modification of Messenger RNA in Drug-Resistant Acute Myeloid Leukemia. Front Oncol 2022; 12:926296. [PMID: 35865472 PMCID: PMC9294171 DOI: 10.3389/fonc.2022.926296] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 06/09/2022] [Indexed: 11/13/2022] Open
Abstract
Acute myeloid leukemia (AML) is an aggressive hematological tumor caused by the malignant transformation of myeloid progenitor cells. Although intensive chemotherapy leads to an initial therapeutic response, relapse due to drug resistance remains a significant challenge. In recent years, accumulating evidence has suggested that post-transcriptional methylation modifications are strongly associated with tumorigenesis. However, the mRNA profile of m7G modification in AML and its role in drug-resistant AML are unknown. In this study, we used MeRIP-seq technology to establish the first transcriptome-wide m7G methylome profile for AML and drug-resistant AML cells, and differences in m7G between the two groups were analyzed. In addition, bioinformatics analysis was conducted to explore the function of m7G-specific methylated transcripts. We found significant differences in m7G mRNA modification between AML and drug-resistant AML cells. Furthermore, bioinformatics analysis revealed that differential m7G-modified mRNAs were associated with a wide range of cellular functions. Importantly, down-methylated m7G modification was significantly enriched in ABC transporter-related mRNAs, which are widely recognized to play a key role in multidrug resistance. Our results provide new insights into a novel function of m7G methylation in drug resistance progression of AML.
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Affiliation(s)
- Bing Zhang
- Department of Pediatrics, Qilu Hospital of Shandong University, Shandong, China
| | - Dong Li
- Department of Pediatrics, Qilu Hospital of Shandong University, Shandong, China
| | - Ran Wang
- Department of Hematology, Qilu Hospital of Shandong University, Shandong, China
- *Correspondence: Ran Wang,
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Rong J, Wang H, Yao Y, Wu Z, Chen L, Jin C, Shi Z, Wu C, Hu X. Identification of m7G-associated lncRNA prognostic signature for predicting the immune status in cutaneous melanoma. Aging (Albany NY) 2022; 14:5233-5249. [PMID: 35771136 PMCID: PMC9271298 DOI: 10.18632/aging.204151] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 06/14/2022] [Indexed: 12/24/2022]
Abstract
RNA modifications, including RNA methylation, are widely existed in cutaneous melanoma (CM). Among epigenetic modifications, N7-methylguanosine (m7G) is a kind of modification at 5' cap of RNA which participate in maintaining the stability of mRNA and various cell biological processes. However, there is still no study concerning the relationship between CM and m7G methylation complexes, METTL1 and WDR4. Here, long non-coding RNA (lncRNAs) and gene expression data of CM from the Cancer Genome Atlas (TCGA) database were retrieved to identify differentially expressed m7G-related lncRNAs connected with overall survival of CM. Then, Cox regression analyses was applied to construct a lncRNA risk signature, the prognostic value of identified signature was further evaluated. As a result, 6 m7G-associated lncRNAs that were significantly related to CM prognosis were incorporated into our prognostic signature. The functional analyses indicated that the prognostic model was correlated with patient survival, cancer metastasis, and growth. Meanwhile, its diagnostic accuracy was better than conventional clinicopathological characteristics. The pathway enrichment analysis showed that the risk model was enriched in several immunity-associated pathways. Moreover, the signature model was significantly connected with the immune subtypes, infiltration of immune cells, immune microenvironment, as well as several m6A-related genes and tumor stem cells. Finally, a nomogram based on the calculated risk score was established. Overall, a risk signature based on 6 m7G-associated lncRNAs was generated which presented predictive value for the prognosis of CM patients and can be further used in the development of novel therapeutic strategies for CM.
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Affiliation(s)
- Jielin Rong
- Department of Hand Plastic Surgery, The First People's Hospital of Linping District, Hangzhou 311199, China
| | - Hui Wang
- Department of Plastic Surgery, The Second Affiliated Hospital of Zhejiang University, Hangzhou 311199, China
| | - Yi Yao
- Department of Hand Plastic Surgery, The First People's Hospital of Linping District, Hangzhou 311199, China
| | - Zhengyuan Wu
- Department of Hand Plastic Surgery, The First People's Hospital of Linping District, Hangzhou 311199, China
| | - Leilei Chen
- Department of Hand Plastic Surgery, The First People's Hospital of Linping District, Hangzhou 311199, China
| | - Chaojie Jin
- Department of Hand Plastic Surgery, The First People's Hospital of Linping District, Hangzhou 311199, China
| | - Zhaoyang Shi
- Department of Hand Plastic Surgery, The First People's Hospital of Linping District, Hangzhou 311199, China
| | - Cheng Wu
- Department of Hand Plastic Surgery, The First People's Hospital of Linping District, Hangzhou 311199, China
| | - Xueqing Hu
- Department of Plastic Surgery, The Second Affiliated Hospital of Zhejiang University, Hangzhou 311199, China
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Zou H. iRNA5hmC-HOC: High-order correlation information for identifying RNA 5-hydroxymethylcytosine modification. J Bioinform Comput Biol 2022; 20:2250017. [DOI: 10.1142/s0219720022500172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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48
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Pharmacoepitranscriptomic landscape revealing m6A modification could be a drug-effect biomarker for cancer treatment. MOLECULAR THERAPY. NUCLEIC ACIDS 2022; 28:464-476. [PMID: 35505958 PMCID: PMC9044172 DOI: 10.1016/j.omtn.2022.04.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 04/01/2022] [Indexed: 01/02/2023]
Abstract
RNA chemical modifications are a new but rapidly developing field. They can directly affect RNA splicing, transport, stability, and translation. Consequently, they are involved in the occurrence and development of diseases that have been studied extensively in recent years. However, few studies have focused on the correlation between chemical modifications and drug effects. Here, we provide a landscape of six RNA modifications in pharmacogene RNA (pharmacoepitranscriptomics) to fully clarify the correlation between chemical modifications and drugs. We performed systematic and comprehensive analyses on pharmacoepitranscriptomics, including basic characteristics of RNA modification and modification-associated mutations and drugs affected by them. Our results show that chemical modifications are common in pharmacogenes, especially N6-methyladenosine (m6A) modification. In addition, we found a very close relationship between chemical modifications and anti-tumor drugs. More interestingly, the results demonstrate the importance of m6A modification for anti-tumor drugs, especially for drugs in triple-negative breast cancer (TNBC), ovarian cancer, and acute myelocytic leukemia (AML). These results indicate that pharmacoepitranscriptomics could be a new source of drug-effect biomarkers, especially for m6A and anti-tumor drugs.
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Regmi P, He ZQ, Lia T, Paudyal A, Li FY. N7-Methylguanosine Genes Related Prognostic Biomarker in Hepatocellular Carcinoma. Front Genet 2022; 13:918983. [PMID: 35734429 PMCID: PMC9207530 DOI: 10.3389/fgene.2022.918983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 05/24/2022] [Indexed: 12/24/2022] Open
Abstract
Background: About 90% of liver cancer-related deaths are caused by hepatocellular carcinoma (HCC). N7-methylguanosine (m7G) modification is associated with the biological process and regulation of various diseases. To the best of our knowledge, its role in the pathogenesis and prognosis of HCC has not been thoroughly investigated. Aim: To identify N7-methylguanosine (m7G) related prognostic biomarkers in HCC. Furthermore, we also studied the association of m7G–related prognostic gene signature with immune infiltration in HCC. Methods: The TCGA datasets were used as a training and GEO dataset “GSE76427” for validation of the results. Statistical analyses were performed using the R statistical software version 4.1.2. Results: Functional enrichment analysis identified some pathogenesis related to HCC. We identified 3 m7G-related genes (CDK1, ANO1, and PDGFRA) as prognostic biomarkers for HCC. A risk score was calculated from these 3 prognostic m7G-related genes which showed the high-risk group had a significantly poorer prognosis than the low-risk group in both training and validation datasets. The 3- and 5-years overall survival was predicted better with the risk score than the ideal model in the entire cohort in the predictive nomogram. Furthermore, immune checkpoint genes like CTLA4, HAVCR2, LAG3, and TIGT were expressed significantly higher in the high-risk group and the chemotherapy sensitivity analysis showed that the high-risk groups were responsive to sorafenib treatment. Conclusion: These 3 m7G genes related signature model can be used as prognostic biomarkers in HCC and a guide for immunotherapy and chemotherapy response. Future clinical study on this biomarker model is required to verify its clinical implications.
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Affiliation(s)
- Parbatraj Regmi
- Department of Biliary Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Zhi-Qiang He
- Department of Biliary Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Thongher Lia
- Department of Uro Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Aliza Paudyal
- Department of Dermatology, West China Hospital, Sichuan University, Chengdu, China
| | - Fu-Yu Li
- Department of Biliary Surgery, West China Hospital, Sichuan University, Chengdu, China
- *Correspondence: Fu-Yu Li,
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50
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Chen Z, Zhang Z, Ding W, Zhang JH, Tan ZL, Mei YR, He W, Wang XJ. Expression and Potential Biomarkers of Regulators for M7G RNA Modification in Gliomas. Front Neurol 2022; 13:886246. [PMID: 35614925 PMCID: PMC9124973 DOI: 10.3389/fneur.2022.886246] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 04/11/2022] [Indexed: 12/15/2022] Open
Abstract
Gliomas are the most frequent primary malignant brain tumors of the central nervous system, causing significant impairment and death. There is mounting evidence that N7 methylguanosine (m7G) RNA dysmethylation plays a significant role in the development and progression of cancer. However, the expression patterns and function of the m7G RNA methylation regulator in gliomas are yet unknown. The goal of this study was to examine the expression patterns of 31 critical regulators linked with m7G RNA methylation and their prognostic significance in gliomas. To begin, we systematically analyzed patient clinical and prognostic data and mRNA gene expression data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. We found that 17 key regulators of m7G RNA methylation showed significantly higher expression levels in gliomas. We then divided the sample into two subgroups by consensus clustering. Cluster 2 had a poorer prognosis than cluster 1 and was associated with a higher histological grade. In addition, cluster 2 was significantly enriched for cancer-related pathways. Based on this discovery, we developed a risk model involving three m7G methylation regulators. Patients were divided into high-risk and low-risk groups based on risk scores. Overall survival (OS) was significantly lower in the high-risk group than in the low-risk group. Further analysis showed that the risk score was an independent prognostic factor for gliomas.
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Affiliation(s)
- Zhen Chen
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Zhe Zhang
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Wei Ding
- Yifeng County People's Hospital, Yichun City, China
| | | | - Zi-long Tan
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yu-ran Mei
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Wei He
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
- Wei He
| | - Xiao-jing Wang
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- *Correspondence: Xiao-jing Wang
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