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Yang L, Tang L, Min Q, Tian H, Li L, Zhao Y, Wu X, Li M, Du F, Chen Y, Li W, Li X, Chen M, Gu L, Sun Y, Xiao Z, Shen J. Emerging role of RNA modification and long noncoding RNA interaction in cancer. Cancer Gene Ther 2024; 31:816-830. [PMID: 38351139 PMCID: PMC11192634 DOI: 10.1038/s41417-024-00734-2] [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: 07/11/2023] [Revised: 01/11/2024] [Accepted: 01/12/2024] [Indexed: 02/16/2024]
Abstract
RNA modification, especially N6-methyladenosine, 5-methylcytosine, and N7-methylguanosine methylation, participates in the occurrence and progression of cancer through multiple pathways. The function and expression of these epigenetic regulators have gradually become a hot topic in cancer research. Mutation and regulation of noncoding RNA, especially lncRNA, play a major role in cancer. Generally, lncRNAs exert tumor-suppressive or oncogenic functions and its dysregulation can promote tumor occurrence and metastasis. In this review, we summarize N6-methyladenosine, 5-methylcytosine, and N7-methylguanosine modifications in lncRNAs. Furthermore, we discuss the relationship between epigenetic RNA modification and lncRNA interaction and cancer progression in various cancers. Therefore, this review gives a comprehensive understanding of the mechanisms by which RNA modification affects the progression of various cancers by regulating lncRNAs, which may shed new light on cancer research and provide new insights into cancer therapy.
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Affiliation(s)
- Liqiong Yang
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Lu Tang
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Qi Min
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Hua Tian
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Linwei Li
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China
| | - Yueshui Zhao
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Xu Wu
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Mingxing Li
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Fukuan Du
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Yu Chen
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Wanping Li
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Xiaobing Li
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Meijuan Chen
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Li Gu
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Yuhong Sun
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China
| | - Zhangang Xiao
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China.
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China.
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China.
| | - Jing Shen
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China.
- Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, 646000, China.
- South Sichuan Institute of Translational Medicine, Luzhou, 646000, China.
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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: 6] [Impact Index Per Article: 6.0] [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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Zhong S, Chen S, Lin H, Luo Y, He J. Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their putative diagnostic and prognostic role. BMC Urol 2023; 23:186. [PMID: 37968670 PMCID: PMC10652602 DOI: 10.1186/s12894-023-01357-9] [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: 06/20/2023] [Accepted: 11/01/2023] [Indexed: 11/17/2023] Open
Abstract
BACKGROUND Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. This study aims to develop new biomarkers for KIRC and explore the impact of biomarkers on the immunotherapeutic efficacy for KIRC, providing a theoretical basis for the treatment of KIRC patients. METHODS Transcriptome data for KIRC was obtained from the The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Weighted gene co-expression network analysis identified KIRC-related modules of long noncoding RNAs (lncRNAs). Intersection analysis was performed differentially expressed lncRNAs between KIRC and normal control samples, and lncRNAs associated with N(7)-methylguanosine (m7G), resulting in differentially expressed m7G-associated lncRNAs in KIRC patients (DE-m7G-lncRNAs). Machine Learning was employed to select biomarkers for KIRC. The prognostic value of biomarkers and clinical features was evaluated using Kaplan-Meier (K-M) survival analysis, univariate and multivariate Cox regression analysis. A nomogram was constructed based on biomarkers and clinical features, and its efficacy was evaluated using calibration curves and decision curves. Functional enrichment analysis was performed to investigate the functional enrichment of biomarkers. Correlation analysis was conducted to explore the relationship between biomarkers and immune cell infiltration levels and common immune checkpoint in KIRC samples. RESULTS By intersecting 575 KIRC-related module lncRNAs, 1773 differentially expressed lncRNAs, and 62 m7G-related lncRNAs, we identified 42 DE-m7G-lncRNAs. Using XGBoost and Boruta algorithms, 8 biomarkers for KIRC were selected. Kaplan-Meier survival analysis showed significant survival differences in KIRC patients with high and low expression of the PTCSC3 and RP11-321G12.1. Univariate and multivariate Cox regression analyses showed that AP000696.2, PTCSC3 and clinical characteristics were independent prognostic factors for patients with KIRC. A nomogram based on these prognostic factors accurately predicted the prognosis of KIRC patients. The biomarkers showed associations with clinical features of KIRC patients, mainly localized in the cytoplasm and related to cytokine-mediated immune response. Furthermore, immune feature analysis demonstrated a significant decrease in immune cell infiltration levels in KIRC samples compared to normal samples, with a negative correlation observed between the biomarkers and most differentially infiltrating immune cells and common immune checkpoints. CONCLUSION In summary, this study discovered eight prognostic biomarkers associated with KIRC patients. These biomarkers showed significant correlations with clinical features, immune cell infiltration, and immune checkpoint expression in KIRC patients, laying a theoretical foundation for the diagnosis and treatment of KIRC.
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Affiliation(s)
- Shuangze Zhong
- Guangdong Medical University, Zhanjiang City, 524023, Guangdong Province, China
| | - Shangjin Chen
- Guangdong Medical University, Zhanjiang City, 524023, Guangdong Province, China
| | - Hansheng Lin
- Guangdong Medical University, Zhanjiang City, 524023, Guangdong Province, China
- Department of Urology, Yangjiang People's Hospital affiliated to Guangdong Medical University, Yangjiang, 42 Dongshan Road, Jiangcheng District, Guangdong Province, 529500, China
| | - Yuancheng Luo
- Guangdong Medical University, Zhanjiang City, 524023, Guangdong Province, China
| | - Jingwei He
- Department of Urology, Yangjiang People's Hospital affiliated to Guangdong Medical University, Yangjiang, 42 Dongshan Road, Jiangcheng District, Guangdong Province, 529500, China.
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Zhang Y, Wang X, Zhang C, Yi H. The dysregulation of lncRNAs by epigenetic factors in human pathologies. Drug Discov Today 2023; 28:103664. [PMID: 37348827 DOI: 10.1016/j.drudis.2023.103664] [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: 12/23/2022] [Revised: 06/05/2023] [Accepted: 06/06/2023] [Indexed: 06/24/2023]
Abstract
Dysregulation of long noncoding RNAs (lncRNAs) contributes to numerous human diseases, including cancers and autoimmune diseases (ADs). Given the importance of lncRNAs in disease initiation and progression, a deeper understanding of their complex regulatory network is required to facilitate their use as therapeutic targets for ADs. In this review, we summarize how lncRNAs are dysregulated in pathological states by epigenetic factors, including RNA-binding proteins, chemical modifications (N6-methyladenosine, 5-methylcytosine, 7-methylguanosine, adenosine-to-inosine editing, microRNA, alternative splicing, DNA methylation, and histone modification). Moreover, the roles of lncRNA epigenetic regulators in immune response and ADs are discussed, providing new insights into the complicated epigenetic factor-lncRNA network, thus, laying a theoretical foundation for future research and clinical application of lncRNAs.
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Affiliation(s)
- Yanli Zhang
- Central Laboratory, The First Hospital of Jilin University, Changchun, Jilin, China; Key Laboratory of Organ Regeneration and Transplantation, Ministry of Education, Changchun, Jilin 130021, China; Department of Echocardiography, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Xiaocong Wang
- Department of Echocardiography, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Chen Zhang
- Colorectal and Anal Surgery, General Surgery Center, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Huanfa Yi
- Central Laboratory, The First Hospital of Jilin University, Changchun, Jilin, China; Key Laboratory of Organ Regeneration and Transplantation, Ministry of Education, Changchun, Jilin 130021, China.
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5
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Qiu L, Jing Q, Li Y, Han J. RNA modification: mechanisms and therapeutic targets. MOLECULAR BIOMEDICINE 2023; 4:25. [PMID: 37612540 PMCID: PMC10447785 DOI: 10.1186/s43556-023-00139-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Accepted: 07/28/2023] [Indexed: 08/25/2023] Open
Abstract
RNA modifications are dynamic and reversible chemical modifications on substrate RNA that are regulated by specific modifying enzymes. They play important roles in the regulation of many biological processes in various diseases, such as the development of cancer and other diseases. With the help of advanced sequencing technologies, the role of RNA modifications has caught increasing attention in human diseases in scientific research. In this review, we briefly summarized the basic mechanisms of several common RNA modifications, including m6A, m5C, m1A, m7G, Ψ, A-to-I editing and ac4C. Importantly, we discussed their potential functions in human diseases, including cancer, neurological disorders, cardiovascular diseases, metabolic diseases, genetic and developmental diseases, as well as immune disorders. Through the "writing-erasing-reading" mechanisms, RNA modifications regulate the stability, translation, and localization of pivotal disease-related mRNAs to manipulate disease development. Moreover, we also highlighted in this review all currently available RNA-modifier-targeting small molecular inhibitors or activators, most of which are designed against m6A-related enzymes, such as METTL3, FTO and ALKBH5. This review provides clues for potential clinical therapy as well as future study directions in the RNA modification field. More in-depth studies on RNA modifications, their roles in human diseases and further development of their inhibitors or activators are needed for a thorough understanding of epitranscriptomics as well as diagnosis, treatment, and prognosis of human diseases.
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Affiliation(s)
- Lei Qiu
- State Key Laboratory of Biotherapy and Cancer Center, Research Laboratory of Tumor Epigenetics and Genomics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, P.R. China
| | - Qian Jing
- State Key Laboratory of Biotherapy and Cancer Center, Research Laboratory of Tumor Epigenetics and Genomics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, P.R. China
| | - Yanbo Li
- State Key Laboratory of Biotherapy and Cancer Center, Research Laboratory of Tumor Epigenetics and Genomics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, P.R. China
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Junhong Han
- State Key Laboratory of Biotherapy and Cancer Center, Research Laboratory of Tumor Epigenetics and Genomics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, P.R. China.
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Kapinova A, Mazurakova A, Halasova E, Dankova Z, Büsselberg D, Costigliola V, Golubnitschaja O, Kubatka P. Underexplored reciprocity between genome-wide methylation status and long non-coding RNA expression reflected in breast cancer research: potential impacts for the disease management in the framework of 3P medicine. EPMA J 2023; 14:249-273. [PMID: 37275549 PMCID: PMC10236066 DOI: 10.1007/s13167-023-00323-7] [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: 04/21/2023] [Accepted: 05/04/2023] [Indexed: 06/07/2023]
Abstract
Breast cancer (BC) is the most common female malignancy reaching a pandemic scale worldwide. A comprehensive interplay between genetic alterations and shifted epigenetic regions synergistically leads to disease development and progression into metastatic BC. DNA and histones methylations, as the most studied epigenetic modifications, represent frequent and early events in the process of carcinogenesis. To this end, long non-coding RNAs (lncRNAs) are recognized as potent epigenetic modulators in pathomechanisms of BC by contributing to the regulation of DNA, RNA, and histones' methylation. In turn, the methylation status of DNA, RNA, and histones can affect the level of lncRNAs expression demonstrating the reciprocity of mechanisms involved. Furthermore, lncRNAs might undergo methylation in response to actual medical conditions such as tumor development and treated malignancies. The reciprocity between genome-wide methylation status and long non-coding RNA expression levels in BC remains largely unexplored. Since the bio/medical research in the area is, per evidence, strongly fragmented, the relevance of this reciprocity for BC development and progression has not yet been systematically analyzed. Contextually, the article aims at:consolidating the accumulated knowledge on both-the genome-wide methylation status and corresponding lncRNA expression patterns in BC andhighlighting the potential benefits of this consolidated multi-professional approach for advanced BC management. Based on a big data analysis and machine learning for individualized data interpretation, the proposed approach demonstrates a great potential to promote predictive diagnostics and targeted prevention in the cost-effective primary healthcare (sub-optimal health conditions and protection against the health-to-disease transition) as well as advanced treatment algorithms tailored to the individualized patient profiles in secondary BC care (effective protection against metastatic disease). Clinically relevant examples are provided, including mitochondrial health control and epigenetic regulatory mechanisms involved.
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Affiliation(s)
- Andrea Kapinova
- Biomedical Center Martin, Jessenius Faculty of Medicine, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Alena Mazurakova
- Department of Anatomy, Jessenius Faculty of Medicine, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Erika Halasova
- Biomedical Center Martin, Jessenius Faculty of Medicine, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Zuzana Dankova
- Biomedical Center Martin, Jessenius Faculty of Medicine, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Dietrich Büsselberg
- Weill Cornell Medicine-Qatar, Education City, Qatar Foundation, 24144 Doha, Qatar
| | | | - Olga Golubnitschaja
- Predictive, Preventive, and Personalised (3P) Medicine, Department of Radiation Oncology, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, 53127 Bonn, Germany
| | - Peter Kubatka
- Department of Medical Biology, Jessenius Faculty of Medicine, Comenius University in Bratislava, 036 01 Martin, Slovakia
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Ren L, Yang X, Liu J, Wang W, Liu Z, Lin Q, Huang B, Pan J, Mao X. An innovative model based on N7-methylguanosine-related lncRNAs for forecasting prognosis and tumor immune landscape in bladder cancer. Cancer Cell Int 2023; 23:85. [PMID: 37158958 PMCID: PMC10165842 DOI: 10.1186/s12935-023-02933-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 04/21/2023] [Indexed: 05/10/2023] Open
Abstract
BACKGROUND As a novel type of the prevalent post-transcriptional modifications, N7-methylguanosine (m7G) modification is essential in the tumorigenesis, progression, and invasion of many cancers, including bladder cancer (BCa). However, the integrated roles of m7G-related lncRNAs in BCa remain undiscovered. This study aims to develop a prognostic model based on the m7G-related lncRNAs and explore its predictive value of the prognosis and anti-cancer treatment sensitivity. METHODS We obtained RNA-seq data and corresponding clinicopathological information from the TCGA database and collected m7G-related genes from previous studies and GSEA. Based on LASSO and Cox regression analysis, we developed a m7G prognostic model. The Kaplan-Meier (K-M) survival analysis and ROC curves were performed to evaluate the predictive power of the model. Gene set enrichment analysis (GSEA) was conducted to explore the molecular mechanisms behind apparent discrepancies between the low- and high-risk groups. We also investigated immune cell infiltration, TIDE score, TMB, the sensitivity of common chemotherapy drugs, and the response to immunotherapy between the two risk groups. Finally, we validated the expression levels of these ten m7G-related lncRNAs in BCa cell lines by qRT-PCR. RESULTS We developed a m7G prognostic model (risk score) composed of 10 m7G-related lncRNAs that are significantly associated with the OS of BCa patients. The K-M survival curves revealed that the high-risk group patients had significantly worse OS than those in the low-risk group. The Cox regression analysis confirmed that the risk score was a significant independent prognostic factor for BCa patients. We found that the high-risk group had higher the immune scores and immune cell infiltration. Furthermore, the results of the sensitivity of common anti-BCa drugs showed that the high-risk group was more sensitive to neoadjuvant cisplatin-based chemotherapy and anti-PD1 immunotherapy. Finally, qRT-PCR revealed that AC006058.1, AC073133.2, LINC00677, and LINC01338 were significantly downregulated in BCa cell lines, while the expression levels of AC124312.2 and AL158209.1 were significantly upregulated in BCa cell lines compared with normal cell lines. CONCLUSION The m7G prognostic model can be applied to accurately predict the prognosis and provide robust directions for clinicians to develop better individual-based and precise treatment strategies for BCa patients.
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Affiliation(s)
- Lei Ren
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, No.58 Zhongshan 2nd Road, Guangzhou, 510080, Guangdong, China
| | - Xu Yang
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, No.58 Zhongshan 2nd Road, Guangzhou, 510080, Guangdong, China
| | - Jinwen Liu
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, No.58 Zhongshan 2nd Road, Guangzhou, 510080, Guangdong, China
| | - Weifeng Wang
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, No.58 Zhongshan 2nd Road, Guangzhou, 510080, Guangdong, China
| | - Zixiong Liu
- Department of Urology, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, China
| | - Qingyuan Lin
- Department of Urology, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, China
| | - Bin Huang
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, No.58 Zhongshan 2nd Road, Guangzhou, 510080, Guangdong, China.
| | - Jincheng Pan
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, No.58 Zhongshan 2nd Road, Guangzhou, 510080, Guangdong, China.
| | - Xiaopeng Mao
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, No.58 Zhongshan 2nd Road, Guangzhou, 510080, Guangdong, China.
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8
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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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Wei W, Liu C, Wang C, Wang M, Jiang W, Zhou Y, Zhang S. Comprehensive pan-cancer analysis of N7-methylguanosine regulators: Expression features and potential implications in prognosis and immunotherapy. Front Genet 2022; 13:1016797. [PMID: 36339001 PMCID: PMC9633684 DOI: 10.3389/fgene.2022.1016797] [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: 08/11/2022] [Accepted: 10/11/2022] [Indexed: 11/27/2022] Open
Abstract
Although immunotherapy has made great strides in cancer therapy, its effectiveness varies widely among individual patients as well as tumor types, and there is an urgent need to develop biomarkers for effectively assessing immunotherapy response. In recent years, RNA methylation regulators have demonstrated to be novel potential biomarkers for prognosis as well as immunotherapy of cancers, such as N6-methyladenine (m6A) and 5-methylcytosine (m5C). N7-methylguanosine (m7G) is a prevalent RNA modification in eukaryotes, but the relationship between m7G regulators and prognosis as well as tumor immune microenvironment is still unclear. In this study, a pan-cancer analysis of 26 m7G regulators across 17 cancer types was conducted based on the bioinformatics approach. On the one hand, a comprehensive analysis of expression features, genetic variations and epigenetic regulation of m7G regulators was carried out, and we found that the expression tendency of m7G regulators were different among tumors and their aberrant expression in cancers could be affected by single nucleotide variation (SNV), copy number variation (CNV), DNA methylation and microRNA (miRNA) separately or simultaneously. On the other hand, the m7Gscore was modeled based on single sample gene set enrichment analysis (ssGSEA) for evaluating the relationships between m7G regulators and cancer clinical features, hallmark pathways, tumor immune microenvironment, immunotherapy response as well as pharmacotherapy sensitivity, and we illustrated that the m7Gscore exhibited tight correlations with prognosis, several immune features, immunotherapy response and drug sensitivity in most cancers. In conclusion, our pan-cancer analysis revealed that m7G regulators may exert critical roles in the tumor progression and immune microenvironment, and have the potential as biomarkers for predicting prognosis, immunotherapy response as well as candidate drug compounds for cancer patients.
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Affiliation(s)
- Wei Wei
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Chao Liu
- Department of Vascular Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Caihong Wang
- Department of Pathology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Meng Wang
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Wei Jiang
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yaqian Zhou
- College of Chemistry and Materials Science, Northwest University, Xi’an, Shaanxi, China
- *Correspondence: Shuqun Zhang, ; Yaqian Zhou,
| | - Shuqun Zhang
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- *Correspondence: Shuqun Zhang, ; Yaqian Zhou,
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RNA modifications in aging-associated cardiovascular diseases. Aging (Albany NY) 2022; 14:8110-8136. [PMID: 36178367 PMCID: PMC9596201 DOI: 10.18632/aging.204311] [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: 05/07/2022] [Accepted: 09/17/2022] [Indexed: 11/25/2022]
Abstract
Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide that bears an enormous healthcare burden and aging is a major contributing factor to CVDs. Functional gene expression network during aging is regulated by mRNAs transcriptionally and by non-coding RNAs epi-transcriptionally. RNA modifications alter the stability and function of both mRNAs and non-coding RNAs and are involved in differentiation, development, and diseases. Here we review major chemical RNA modifications on mRNAs and non-coding RNAs, including N6-adenosine methylation, N1-adenosine methylation, 5-methylcytidine, pseudouridylation, 2′ -O-ribose-methylation, and N7-methylguanosine, in the aging process with an emphasis on cardiovascular aging. We also summarize the currently available methods to detect RNA modifications and the bioinformatic tools to study RNA modifications. More importantly, we discussed the specific implication of the RNA modifications on mRNAs and non-coding RNAs in the pathogenesis of aging-associated CVDs, including atherosclerosis, hypertension, coronary heart diseases, congestive heart failure, atrial fibrillation, peripheral artery disease, venous insufficiency, and stroke.
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Wang T, Zhou Z, Wang X, You L, Li W, Zheng C, Zhang J, Wang L, Kong X, Gao Y, Sun X. Comprehensive analysis of nine m7G-related lncRNAs as prognosis factors in tumor immune microenvironment of hepatocellular carcinoma and experimental validation. Front Genet 2022; 13:929035. [PMID: 36081998 PMCID: PMC9445240 DOI: 10.3389/fgene.2022.929035] [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: 04/26/2022] [Accepted: 07/18/2022] [Indexed: 12/24/2022] Open
Abstract
Background: Hepatocellular carcinoma (HCC) remains the most prevalent gastrointestinal malignancy worldwide, with robust drug resistance to therapy. N7-methylguanosine (m7G) mRNA modification has been significantly related to massive human diseases. Considering the effect of m7G-modified long non-coding RNAs (lncRNAs) in HCC progression is unknown, the study aims at investigating a prognostic signature to improve clinical outcomes for patients with HCC.Methods: Two independent databases (TCGA and ICGC) were used to analyze RNAseq data of HCC patients. First, co-expression analysis was applied to obtain the m7G-related lncRNAs. Moreover, consensus clustering analysis was employed to divide HCC patients into clusters. Then, using least absolute shrinkage and selection operator-Cox regression analysis, the m7G-related lncRNA prognostic signature (m7G-LPS) was first tested in the training set and then confirmed in both the testing and ICGC sets. The expression levels of the nine lncRNAs were further confirmed via real-time PCR in cell lines, principal component analysis, and receiver operating characteristic curve. The m7G-LPS could divide HCC patients into two different risk groups with the optimal risk score. Then, Kaplan–Meier curves, tumor mutation burden (TMB), therapeutic effects of chemotherapy agents, and expressions of immune checkpoints were performed to further enhance the availability of immunotherapeutic treatments for HCC patients.Results: A total of 1465 lncRNAs associated with the m7G genes were finally selected from the TCGA database, and through the univariate Cox regression, the expression levels of 22 m7G-related lncRNAs were concerning HCC patients’ overall survival (OS). Then, the whole patients were grouped into two subgroups, and the OS in Cluster 1 was longer than that of patients in Cluster 2. Furthermore, nine prognostic m7G-related lncRNAs were identified to conduct the m7G-LPS, which were further verified. A prognostic nomogram combined age, gender, HCC grade, stage, and m7G-LPS showed strong reliability and accuracy in predicting OS in HCC patients. Finally, immune checkpoint expression, TMB, and several chemotherapy agents were remarkably associated with risk scores. More importantly, the OS of the TMB-high patients was the worst among the four groups.Conclusion: The prognostic model we established was validated by abundant algorithms, which provided a new perspective on HCC tumorigenesis and thus improved individualized treatments for patients.
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Affiliation(s)
- Tao Wang
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhijia Zhou
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xuan Wang
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Liping You
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Wenxuan Li
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Chao Zheng
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jinghao Zhang
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Lingtai Wang
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xiaoni Kong
- Central Laboratory, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- *Correspondence: Xiaoni Kong, ; Yueqiu Gao, ; Xuehua Sun,
| | - Yueqiu Gao
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- *Correspondence: Xiaoni Kong, ; Yueqiu Gao, ; Xuehua Sun,
| | - Xuehua Sun
- Department of Hepatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- *Correspondence: Xiaoni Kong, ; Yueqiu Gao, ; Xuehua Sun,
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Wei W, Liu C, Wang M, Jiang W, Wang C, Zhang S. Prognostic Signature and Tumor Immune Landscape of N7-Methylguanosine-Related lncRNAs in Hepatocellular Carcinoma. Front Genet 2022; 13:906496. [PMID: 35938009 PMCID: PMC9354608 DOI: 10.3389/fgene.2022.906496] [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: 04/24/2022] [Accepted: 06/20/2022] [Indexed: 01/15/2023] Open
Abstract
Despite great advances in the treatment of liver hepatocellular carcinoma (LIHC), such as immunotherapy, the prognosis remains extremely poor, and there is an urgent need to develop novel diagnostic and prognostic markers. Recently, RNA methylation-related long non-coding RNAs (lncRNAs) have been demonstrated to be novel potential biomarkers for tumor diagnosis and prognosis as well as immunotherapy response, such as N6-methyladenine (m6A) and 5-methylcytosine (m5C). N7-Methylguanosine (m7G) is a widespread RNA modification in eukaryotes, but the relationship between m7G-related lncRNAs and prognosis of LIHC patients as well as tumor immunotherapy response is still unknown. In this study, based on the LIHC patients’ clinical and transcriptomic data from TCGA database, a total of 992 m7G-related lncRNAs that co-expressed with 22 m7G regulatory genes were identified using Pearson correlation analysis. Univariate regression analysis was used to screen prognostic m7G-related lncRNAs, and the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were applied to construct a 9-m7G-related-lncRNA risk model. The m7G-related lncRNA risk model was validated to exhibit good prognostic performance through Kaplan–Meier analysis and ROC analysis. Together with the clinicopathological features, the m7G-related lncRNA risk score was found to be an independent prognostic factor for LIHC. Furthermore, the high-risk group of LIHC patients was unveiled to have a higher tumor mutation burden (TMB), and their tumor microenvironment was more prone to the immunosuppressive state and exhibited a lower response rate to immunotherapy. In addition, 47 anti-cancer drugs were identified to exhibit a difference in drug sensitivity between the high-risk and low-risk groups. Taken together, the m7G-related lncRNA risk model might display potential value in predicting prognosis, immunotherapy response, and drug sensitivity in LIHC patients.
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Affiliation(s)
- Wei Wei
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Chao Liu
- Department of Vascular Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Meng Wang
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Wei Jiang
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Caihong Wang
- Department of Pathology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Shuqun Zhang
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- *Correspondence: Shuqun Zhang,
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