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Wang X, Zhi M, Zhao W, Deng J. HNRNPA2B1 promotes oral squamous cell carcinogenesis via m 6A-dependent stabilization of FOXQ1 mRNA stability. IUBMB Life 2024; 76:437-450. [PMID: 38265150 DOI: 10.1002/iub.2808] [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: 11/18/2023] [Accepted: 12/20/2023] [Indexed: 01/25/2024]
Abstract
Oral squamous cell carcinoma (OSCC), as a common type of oral malignancy, has an unclear pathogenesis. N6 methyladenosine (m6A) is a reversible and dynamic process that participates in the modulation of cancer pathogenesis and development. As an m6A recognition protein (reader), heterogeneous nuclear ribonucleoproteins A2/B1 (HNRNPA2B1) show abnormally high expression in cancers. Forkhead box Q1 (FOXQ1), an oncogenic transcription factor, controls multiple biological processes (e.g., embryonic development, cell differentiation, and apoptosis, impacting the initiation and progression of cancers by mediating signaling pathways together with epithelial-mesenchymal transition). Through the Cancer Genome Atlas database screening along with clinical and laboratory experiments, in head and neck squamous cell carcinoma, we found a correlation between HNRNPA2B1 and FOXQ1 gene expression, with shared m6A motifs between HNRNPA2B1 and FOXQ1 mRNA sequences. Silencing or overexpression of HNRNPA2B1 in OSCC cells affected the malignant phenotypes of OSCC cells in vitro, and depletion of HNRNPA2B1 retarded tumor growth in vivo. HNRNPA2B1 could bind to m6A-modified FOXQ1 mRNA to enhance its mRNA stability, resulting in up-regulation of FOXQ1 protein expression. To conclude, HNRNPA2B1 was upregulated in OSCC and enhanced OSCC cell malignant phenotypes by stabilizing m6A-modified FOXQ1 mRNA, eventually aggravating the malignancy and tumorigenicity of OSCC. This study accelerates the recognition of the potency of m6A modification in OSCC and paves the path for OSCC's targeted diagnosis and therapy.
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Affiliation(s)
- Xi Wang
- The School and Hospital of Stomatology, Tianjin Medical University, Tianjin, PR China
| | - Min Zhi
- The School and Hospital of Stomatology, Tianjin Medical University, Tianjin, PR China
| | - Wei Zhao
- The School and Hospital of Stomatology, Tianjin Medical University, Tianjin, PR China
| | - Jiayin Deng
- The School and Hospital of Stomatology, Tianjin Medical University, Tianjin, PR China
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Song M, Zhao J, Zhang C, Jia C, Yang J, Zhao H, Zhai J, Lei B, Tao S, Chen S, Su R, Ma C. PEA-m6A: an ensemble learning framework for accurately predicting N6-methyladenosine modifications in plants. PLANT PHYSIOLOGY 2024; 195:1200-1213. [PMID: 38428981 DOI: 10.1093/plphys/kiae120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 01/11/2024] [Accepted: 02/01/2024] [Indexed: 03/03/2024]
Abstract
N 6-methyladenosine (m6A), which is the mostly prevalent modification in eukaryotic mRNAs, is involved in gene expression regulation and many RNA metabolism processes. Accurate prediction of m6A modification is important for understanding its molecular mechanisms in different biological contexts. However, most existing models have limited range of application and are species-centric. Here we present PEA-m6A, a unified, modularized and parameterized framework that can streamline m6A-Seq data analysis for predicting m6A-modified regions in plant genomes. The PEA-m6A framework builds ensemble learning-based m6A prediction models with statistic-based and deep learning-driven features, achieving superior performance with an improvement of 6.7% to 23.3% in the area under precision-recall curve compared with state-of-the-art regional-scale m6A predictor WeakRM in 12 plant species. Especially, PEA-m6A is capable of leveraging knowledge from pretrained models via transfer learning, representing an innovation in that it can improve prediction accuracy of m6A modifications under small-sample training tasks. PEA-m6A also has a strong capability for generalization, making it suitable for application in within- and cross-species m6A prediction. Overall, this study presents a promising m6A prediction tool, PEA-m6A, with outstanding performance in terms of its accuracy, flexibility, transferability, and generalization ability. PEA-m6A has been packaged using Galaxy and Docker technologies for ease of use and is publicly available at https://github.com/cma2015/PEA-m6A.
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Affiliation(s)
- Minggui Song
- State Key Laboratory of Crop Stress Resistance and High-Efficiency Production, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Jiawen Zhao
- State Key Laboratory of Crop Stress Resistance and High-Efficiency Production, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Chujun Zhang
- State Key Laboratory of Crop Stress Resistance and High-Efficiency Production, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Chengchao Jia
- State Key Laboratory of Crop Stress Resistance and High-Efficiency Production, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Jing Yang
- State Key Laboratory of Crop Stress Resistance and High-Efficiency Production, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Haonan Zhao
- State Key Laboratory of Crop Stress Resistance and High-Efficiency Production, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Jingjing Zhai
- State Key Laboratory of Crop Stress Resistance and High-Efficiency Production, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853, USA
| | - Beilei Lei
- State Key Laboratory of Crop Stress Resistance and High-Efficiency Production, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Shiheng Tao
- State Key Laboratory of Crop Stress Resistance and High-Efficiency Production, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Siqi Chen
- School of Computer Software, College of Intelligence and Computing, Tianjin University, Tianjin 300072, China
| | - Ran Su
- School of Computer Software, College of Intelligence and Computing, Tianjin University, Tianjin 300072, China
| | - Chuang Ma
- State Key Laboratory of Crop Stress Resistance and High-Efficiency Production, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
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Wang J, Zhao G, Zhao Y, Zhao Z, Yang S, Zhou A, Li P, Zhang S. N 6-methylation in the development, diagnosis, and treatment of gastric cancer. J Transl Int Med 2024; 12:5-21. [PMID: 38525439 PMCID: PMC10956730 DOI: 10.2478/jtim-2023-0103] [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] [Indexed: 03/26/2024] Open
Abstract
Gastric cancer (GC) ranks third among cancers in terms of mortality rate worldwide. A clear understanding of the mechanisms underlying the genesis and progression of GC will contribute to clinical decision making. N6-methyladenosine (m6A) is the most abundant among diverse mRNA modification types and regulates multiple facets of RNA metabolism. In recent years, emerging studies have shown that m6A modifications are involved in gastric carcinoma tumorigenesis and progression and can potentially be valuable new prospects for diagnosis and prognosis. This article reviews the recent progress regarding m6A in GC.
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Affiliation(s)
- Jiaxin Wang
- Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Guiping Zhao
- Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Yan Zhao
- Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Zheng Zhao
- Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Shuyue Yang
- Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Anni Zhou
- Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Peng Li
- Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Shutian Zhang
- Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
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Mao Z, Wang B, Zhang T, Cui B. The roles of m6A methylation in cervical cancer: functions, molecular mechanisms, and clinical applications. Cell Death Dis 2023; 14:734. [PMID: 37951987 PMCID: PMC10640579 DOI: 10.1038/s41419-023-06265-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 10/24/2023] [Accepted: 10/31/2023] [Indexed: 11/14/2023]
Abstract
Cervical cancer (CC) is a gynecological neoplasm with the highest incidence rate, primarily attributed to the persistent infection of high-risk Human papillomavirus (HPV). Despite extensive research, the pathogenesis of CC remains unclear. N6-methyladenosine (m6A) methylation, the most prevalent form of epigenetic modification in RNA, is intricately linked to cell proliferation, metastasis, metabolism, and therapeutic resistance within the tumor microenvironment (TME) of CC. The involvement of the writer, reader, and eraser in m6A modification impacts the advancement of tumors through the regulation of RNA stability, nuclear export, translation efficiency, and RNA degradation. Here, we discuss the biogenesis of m6A, the atypical expressions of m6A regulators, the mechanisms of molecular interactions, and their functions in CC. Furthermore, we elucidate m6A modification of non-coding RNA. In the context of precision medicine, and with the advancements of genomics, proteomics, and high-throughput sequencing technologies, we summarize the application of m6A in the clinical diagnosis and treatment of CC. Additionally, new perspectives on detection methods, immune regulation, and nano-drug development are presented, which lay the foundation for further research of m6A and provide new ideas for the clinical treatment of CC.
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Affiliation(s)
- Zhonghao Mao
- Cheeloo College of Medicine, Shandong University, No. 44 Wenhua West Road, Jinan City, 250012, Shandong Province, China
| | - Bingyu Wang
- Cheeloo College of Medicine, Shandong University, No. 44 Wenhua West Road, Jinan City, 250012, Shandong Province, China
| | - Teng Zhang
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, No. 107 Wenhua West Road, Jinan City, 250012, Shandong Province, China
| | - Baoxia Cui
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, No. 107 Wenhua West Road, Jinan City, 250012, Shandong Province, China.
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An Updated Review of Contribution of Long Noncoding RNA-NEAT1 to the Progression of Human Cancers. Pathol Res Pract 2023; 245:154380. [PMID: 37043964 DOI: 10.1016/j.prp.2023.154380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 02/12/2023] [Accepted: 02/16/2023] [Indexed: 02/26/2023]
Abstract
Long non-coding RNAs (lncRNAs) present pivotal roles in cancer tumorigenesis and progression. Recently, nuclear paraspeckle assembly transcript 1 (NEAT1) as a lncRNA has been shown to mediate cell proliferation, migration, and EMT in tumor cells. NEAT1 by targeting several miRNAs/mRNA axes could regulate cancer cell behavior. Therefore, NEAT1 may function as a potent biomarker for the prediction and treatment of some human cancers. In this review, we summarized various NEAT1-related signaling pathways that are critical in cancer initiation and progression.
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