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Yang K, Zhao J, Liu S, Man S. RELA promotes the progression of oral squamous cell carcinoma via TFAP2A-Wnt/β-catenin signaling. Mol Carcinog 2023; 62:641-651. [PMID: 36789977 DOI: 10.1002/mc.23512] [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: 01/11/2023] [Accepted: 01/26/2023] [Indexed: 02/16/2023]
Abstract
Oral squamous cell carcinoma (OSCC) has emerged as the most prevailing oral malignancy worldwide, characterized by cervical solid lymph node metastasis and strong local invasiveness. Overexpression of Transcription Factor AP-2 alpha (TFAP2A) is observed in a significant proportion of OSCC cases. In this study, we aimed to elucidate the function of TFAP2A in the progression of OSCC and the related molecular signaling pathways. The role of RELA was predicted using bioinformatics analysis. The mRNA abundances of RELA, TFAP2A, and β-catenin were assessed by Western blot and quantitative real-timePCR. The relationship between RELA, TFAP2A, and β-catenin and their correlation with clinicopathological characteristics of OSCC was evaluated. The target of RELA and TFAP2A was identified by the chromatin immunoprecipitation as well as luciferase reporter assay. The colony formation assay and MTS assay were performed to determine the proliferative level of OSCC cells. OSCC cell motility was determined by Transwell assay and wound-healing assay. The protein expressions of epithelial-mesenchymal transition-associated factors were evaluated by Western blot. The expressions of RELA and TFAP2A were elevated in OSCC, and their expressions displayed a positive correlation. The expression levels of RELA and TFAP2A were found to be associated with TNM staging and lymphatic metastasis of OSCC patients. RELA upregulation promoted OSCC progression, as manifested by increased levels of proliferation, invasion, and migration of OSCC cells. We also demonstrated that RELA was directly bound to the promoter of TFAP2A transcription, which activated multiple malignant and metastatic phenotypes. Furthermore, TFAP2A activated the Wnt/β-catenin signaling by targeting the promoter regions of β-catenin. The study found that RELA is critical for promoting the progression of OSCC via the RELA-TFAP2A-Wnt/β-catenin signaling pathway. The RELA-TFAP2A-Wnt/β-catenin signaling pathway is a potential target for reducing the aggressiveness of OSCC.
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Affiliation(s)
- Kaicheng Yang
- Department of Stomatology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
| | - Jianguang Zhao
- Department of Stomatology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
| | - Shenghui Liu
- Department of Otolaryngology Head and Neck, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
| | - Shasha Man
- Department of Stomatology, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
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2
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Smyth LJ, Dahlström EH, Syreeni A, Kerr K, Kilner J, Doyle R, Brennan E, Nair V, Fermin D, Nelson RG, Looker HC, Wooster C, Andrews D, Anderson K, McKay GJ, Cole JB, Salem RM, Conlon PJ, Kretzler M, Hirschhorn JN, Sadlier D, Godson C, Florez JC, Forsblom C, Maxwell AP, Groop PH, Sandholm N, McKnight AJ. Epigenome-wide meta-analysis identifies DNA methylation biomarkers associated with diabetic kidney disease. Nat Commun 2022; 13:7891. [PMID: 36550108 PMCID: PMC9780337 DOI: 10.1038/s41467-022-34963-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 11/14/2022] [Indexed: 12/24/2022] Open
Abstract
Type 1 diabetes affects over nine million individuals globally, with approximately 40% developing diabetic kidney disease. Emerging evidence suggests that epigenetic alterations, such as DNA methylation, are involved in diabetic kidney disease. Here we assess differences in blood-derived genome-wide DNA methylation associated with diabetic kidney disease in 1304 carefully characterised individuals with type 1 diabetes and known renal status from two cohorts in the United Kingdom-Republic of Ireland and Finland. In the meta-analysis, we identify 32 differentially methylated CpGs in diabetic kidney disease in type 1 diabetes, 18 of which are located within genes differentially expressed in kidneys or correlated with pathological traits in diabetic kidney disease. We show that methylation at 21 of the 32 CpGs predict the development of kidney failure, extending the knowledge and potentially identifying individuals at greater risk for diabetic kidney disease in type 1 diabetes.
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Affiliation(s)
- Laura J Smyth
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Emma H Dahlström
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, 00290, Helsinki, Finland
| | - Anna Syreeni
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, 00290, Helsinki, Finland
| | - Katie Kerr
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Jill Kilner
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Ross Doyle
- Diabetes Complications Research Centre, Conway Institute, School of Medicine, University College Dublin, Dublin, Ireland
| | - Eoin Brennan
- Diabetes Complications Research Centre, Conway Institute, School of Medicine, University College Dublin, Dublin, Ireland
| | - Viji Nair
- Department of Medicine-Nephrology, University of Michigan School of Medicine, Ann Arbor, MI, 48109, USA
| | - Damian Fermin
- Department of Pediatrics-Nephrology, University of Michigan School of Medicine, Ann Arbor, MI, 48109, USA
| | - Robert G Nelson
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Helen C Looker
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Christopher Wooster
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Darrell Andrews
- Diabetes Complications Research Centre, Conway Institute, School of Medicine, University College Dublin, Dublin, Ireland
| | - Kerry Anderson
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Gareth J McKay
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Joanne B Cole
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Rany M Salem
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Peter J Conlon
- Department of Nephrology and Transplantation, Beaumont Hospital and Department of Medicine Royal College of Surgeons in Ireland, Dublin 9, Ireland
| | - Matthias Kretzler
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Joel N Hirschhorn
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA
- Department of Pediatrics and Genetics, Harvard Medical School, Boston, MA, USA
| | | | - Catherine Godson
- Diabetes Complications Research Centre, Conway Institute, School of Medicine, University College Dublin, Dublin, Ireland
| | - Jose C Florez
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Carol Forsblom
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, 00290, Helsinki, Finland
| | - Alexander P Maxwell
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
- Regional Nephrology Unit, Belfast City Hospital, Belfast, Northern Ireland, UK
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, 00290, Helsinki, Finland
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, 00290, Helsinki, Finland.
| | - Amy Jayne McKnight
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK.
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3
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Joshi H, Vastrad B, Joshi N, Vastrad C. Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy. SAGE Open Med 2022; 10:20503121221137005. [PMID: 36385790 PMCID: PMC9661593 DOI: 10.1177/20503121221137005] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Accepted: 10/18/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives: The underlying molecular mechanisms of diabetic nephropathy have yet not been investigated clearly. In this investigation, we aimed to identify key genes involved in the pathogenesis and prognosis of diabetic nephropathy. Methods: We downloaded next-generation sequencing data set GSE142025 from Gene Expression Omnibus database having 28 diabetic nephropathy samples and nine normal control samples. The differentially expressed genes between diabetic nephropathy and normal control samples were analyzed. Biological function analysis of the differentially expressed genes was enriched by Gene Ontology and REACTOME pathways. Then, we established the protein–protein interaction network, modules, miRNA-differentially expressed gene regulatory network and transcription factor-differentially expressed gene regulatory network. Hub genes were validated by using receiver operating characteristic curve analysis. Results: A total of 549 differentially expressed genes were detected including 275 upregulated and 274 downregulated genes. The biological process analysis of functional enrichment showed that these differentially expressed genes were mainly enriched in cell activation, integral component of plasma membrane, lipid binding, and biological oxidations. Analyzing the protein–protein interaction network, miRNA-differentially expressed gene regulatory network and transcription factor-differentially expressed gene regulatory network, we screened hub genes MDFI, LCK, BTK, IRF4, PRKCB, EGR1, JUN, FOS, ALB, and NR4A1 by the Cytoscape software. The receiver operating characteristic curve analysis confirmed that hub genes were of diagnostic value. Conclusions: Taken above, using integrated bioinformatics analysis, we have identified key genes and pathways in diabetic nephropathy, which could improve our understanding of the cause and underlying molecular events, and these key genes and pathways might be therapeutic targets for diabetic nephropathy.
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Affiliation(s)
- Harish Joshi
- Endocrine and Diabetes Care Center, Hubbali, India
| | - Basavaraj Vastrad
- Department of Pharmaceutical Chemistry, KLE Society’s College of Pharmacy, Gadag, India
| | - Nidhi Joshi
- Dr. D. Y. Patil Medical College, Kolhapur, India
| | - Chanabasayya Vastrad
- Biostatistics and Bioinformatics, Chanabasava Nilaya, Dharwad, India
- Chanabasayya Vastrad, Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, India.
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4
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Papadopoulos T, Krochmal M, Cisek K, Fernandes M, Husi H, Stevens R, Bascands JL, Schanstra JP, Klein J. Omics databases on kidney disease: where they can be found and how to benefit from them. Clin Kidney J 2016; 9:343-52. [PMID: 27274817 PMCID: PMC4886900 DOI: 10.1093/ckj/sfv155] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2015] [Accepted: 12/21/2015] [Indexed: 02/07/2023] Open
Abstract
In the recent decades, the evolution of omics technologies has led to advances in all biological fields, creating a demand for effective storage, management and exchange of rapidly generated data and research discoveries. To address this need, the development of databases of experimental outputs has become a common part of scientific practice in order to serve as knowledge sources and data-sharing platforms, providing information about genes, transcripts, proteins or metabolites. In this review, we present omics databases available currently, with a special focus on their application in kidney research and possibly in clinical practice. Databases are divided into two categories: general databases with a broad information scope and kidney-specific databases distinctively concentrated on kidney pathologies. In research, databases can be used as a rich source of information about pathophysiological mechanisms and molecular targets. In the future, databases will support clinicians with their decisions, providing better and faster diagnoses and setting the direction towards more preventive, personalized medicine. We also provide a test case demonstrating the potential of biological databases in comparing multi-omics datasets and generating new hypotheses to answer a critical and common diagnostic problem in nephrology practice. In the future, employment of databases combined with data integration and data mining should provide powerful insights into unlocking the mysteries of kidney disease, leading to a potential impact on pharmacological intervention and therapeutic disease management.
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Affiliation(s)
- Theofilos Papadopoulos
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Toulouse, France; Université Toulouse III Paul-Sabatier, Toulouse, France
| | - Magdalena Krochmal
- Biotechnology Division, Biomedical Research Foundation Academy of Athens, Athens, Greece; Institute for Molecular Cardiovascular Research, Universitätsklinikum RWTH Aachen, Aachen, Germany
| | | | - Marco Fernandes
- BHF Glasgow Cardiovascular Research Centre , University of Glasgow , Glasgow , UK
| | - Holger Husi
- BHF Glasgow Cardiovascular Research Centre , University of Glasgow , Glasgow , UK
| | - Robert Stevens
- School of Computer Science , University of Manchester , Manchester , UK
| | - Jean-Loup Bascands
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Toulouse, France; Université Toulouse III Paul-Sabatier, Toulouse, France
| | - Joost P Schanstra
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Toulouse, France; Université Toulouse III Paul-Sabatier, Toulouse, France
| | - Julie Klein
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Toulouse, France; Université Toulouse III Paul-Sabatier, Toulouse, France
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5
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Ferenbach DA, Bonventre JV. Acute kidney injury and chronic kidney disease: From the laboratory to the clinic. Nephrol Ther 2016; 12 Suppl 1:S41-8. [PMID: 26972097 DOI: 10.1016/j.nephro.2016.02.005] [Citation(s) in RCA: 80] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Chronic kidney disease and acute kidney injury have traditionally been considered as separate entities with different etiologies. This view has changed in recent years, with chronic kidney disease recognized as a major risk factor for the development of new acute kidney injury, and acute kidney injury now accepted to lead to de novo or accelerated chronic and end stage kidney diseases. Patients with existing chronic kidney disease appear to be less able to mount a complete 'adaptive' repair after acute insults, and instead repair maladaptively, with accelerated fibrosis and rates of renal functional decline. This article reviews the epidemiological studies in man that have demonstrated the links between these two processes. We also examine clinical and experimental research in areas of importance to both acute and chronic disease: acute and chronic renal injury to the vasculature, the pericyte and leukocyte populations, the signaling pathways implicated in injury and repair, and the impact of cellular stress and increased levels of growth arrested and senescent cells. The importance and therapeutic potential raised by these processes for acute and chronic injury are discussed.
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Affiliation(s)
- David A Ferenbach
- Renal Division and Biomedical Engineering Division, Brigham and Women's Hospital, Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA; Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Joseph V Bonventre
- Renal Division and Biomedical Engineering Division, Brigham and Women's Hospital, Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA; Harvard-Massachusetts Institute of Technology, Division of Health Sciences and Technology, Cambridge, Massachusetts, USA; Harvard Stem Cell Institute, Cambridge, Massachusetts, USA.
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