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Carrasco M, Wang C, Søviknes AM, Bjørlykke Y, Abadpour S, Paulo JA, Tjora E, Njølstad P, Ghabayen J, Nermoen I, Lyssenko V, Chera S, Ghila LM, Vaudel M, Scholz H, Ræder H. Spatial Environment Affects HNF4A Mutation-Specific Proteome Signatures and Cellular Morphology in hiPSC-Derived β-Like Cells. Diabetes 2022; 71:862-869. [PMID: 35043148 PMCID: PMC8965667 DOI: 10.2337/db20-1279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 01/03/2022] [Indexed: 11/13/2022]
Abstract
Studies of monogenic diabetes are particularly useful because we can gain insight into the molecular events of pancreatic β-cell failure. Maturity-onset diabetes of the young 1 (MODY1) is a form of monogenic diabetes caused by a mutation in the HNF4A gene. Human-induced pluripotent stem cells (hiPSCs) provide an excellent tool for disease modeling by subsequently directing differentiation toward desired pancreatic islet cells, but cellular phenotypes in terminally differentiated cells are notoriously difficult to detect. Re-creating a spatial (three-dimensional [3D]) environment may facilitate phenotype detection. We studied MODY1 by using hiPSC-derived pancreatic β-like patient and isogenic control cell lines in two different 3D contexts. Using size-adjusted cell aggregates and alginate capsules, we show that the 3D context is critical to facilitating the detection of mutation-specific phenotypes. In 3D cell aggregates, we identified irregular cell clusters and lower levels of structural proteins by proteome analysis, whereas in 3D alginate capsules, we identified altered levels of glycolytic proteins in the glucose sensing apparatus by proteome analysis. Our study provides novel knowledge on normal and abnormal function of HNF4A, paving the way for translational studies of new drug targets that can be used in precision diabetes medicine in MODY.
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Affiliation(s)
- Manuel Carrasco
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Center for Cancer Biomarkers, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Chencheng Wang
- Department of Transplant Medicine and Institute for Surgical Research, Oslo University Hospital, Oslo, Norway
- Hybrid Technology Hub–Centre of Excellence, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Anne M. Søviknes
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Yngvild Bjørlykke
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
| | - Shadab Abadpour
- Department of Transplant Medicine and Institute for Surgical Research, Oslo University Hospital, Oslo, Norway
- Hybrid Technology Hub–Centre of Excellence, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Joao A. Paulo
- Department of Cell Biology, Harvard Medical School, Boston, MA
| | - Erling Tjora
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
| | - Pål Njølstad
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
| | - Jonas Ghabayen
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ingrid Nermoen
- Department of Endocrinology, Akershus University Hospital, Lorenskog, Norway
| | - Valeriya Lyssenko
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Simona Chera
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Luiza M. Ghila
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Marc Vaudel
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Hanne Scholz
- Department of Transplant Medicine and Institute for Surgical Research, Oslo University Hospital, Oslo, Norway
- Hybrid Technology Hub–Centre of Excellence, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Helge Ræder
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
- Corresponding author: Helge Ræder,
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Meng X, Wang ZF, Lou QY, Rankine AN, Zheng WX, Zhang ZH, Zhang L, Gu H. Long non-coding RNAs in head and neck squamous cell carcinoma: Diagnostic biomarkers, targeted therapies, and prognostic roles. Eur J Pharmacol 2021; 902:174114. [PMID: 33901464 DOI: 10.1016/j.ejphar.2021.174114] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 04/09/2021] [Accepted: 04/19/2021] [Indexed: 12/24/2022]
Abstract
At present, emerging evidence shows that non-coding RNAs (ncRNAs) play crucial roles for development of multiple tumors. Amongst these ncRNAs, long non-coding RNAs (lncRNAs) play prominent roles in physiological and pathological processes. LncRNAs are RNA transcripts larger than 200 nucleotides and have been shown to serve important regulatory roles in different types of cancer via interactions with DNA, RNA and proteins. Head and neck squamous cell carcinoma (HNSCC) is one of the most malignant tumors with low survival rates in advanced stages. Recently, lncRNAs have been demonstrated to be involved in a wide range of biological processes, including proliferation, metastasis, and prognosis of HNSCC. Therefore, this review describes molecular mechanisms of up- or down-regulation of lncRNAs and expounds their functions in pathology and clinical practices in HNSCC. It also highlights their potential clinical applications as biomarkers for the diagnosis, prognosis, and treatment of HNSCC. However, studies on lncRNAs are still not comprehensive, and more investigations are needed in the future.
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Affiliation(s)
- Xiang Meng
- College & Hospital of Stomatology, Anhui Medical University, Key Lab. of Oral Diseases Research of Anhui Province, Hefei, 230032, China.
| | - Zi-Fei Wang
- School of Stomatology, Anhui Medical University, Hefei, 230032, China.
| | - Qiu-Yue Lou
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, 230032, China.
| | - Abigail N Rankine
- Clinical Medicine in Chinese (MBBS), Anhui Medical University, Hefei, 230032, China.
| | - Wan-Xin Zheng
- School of Stomatology, Anhui Medical University, Hefei, 230032, China.
| | - Zi-Hao Zhang
- School of Stomatology, Anhui Medical University, Hefei, 230032, China.
| | - Lei Zhang
- College & Hospital of Stomatology, Anhui Medical University, Key Lab. of Oral Diseases Research of Anhui Province, Hefei, 230032, China; Periodontal Department, Anhui Stomatology Hospital Affiliated to Anhui Medical University, Hefei, 230032, China.
| | - Hao Gu
- Department of Immunology, School of Basic Medical Sciences, Anhui Medical University, Hefei, 230032, China.
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Ghila L, Legøy TA, Mathisen AF, Abadpour S, Paulo JA, Scholz H, Ræder H, Chera S. Chronically Elevated Exogenous Glucose Elicits Antipodal Effects on the Proteome Signature of Differentiating Human iPSC-Derived Pancreatic Progenitors. Int J Mol Sci 2021; 22:3698. [PMID: 33918250 DOI: 10.3390/ijms22073698] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 03/22/2021] [Accepted: 03/27/2021] [Indexed: 12/14/2022] Open
Abstract
The past decade revealed that cell identity changes, such as dedifferentiation or transdifferentiation, accompany the insulin-producing β-cell decay in most diabetes conditions. Mapping and controlling the mechanisms governing these processes is, thus, extremely valuable for managing the disease progression. Extracellular glucose is known to influence cell identity by impacting the redox balance. Here, we use global proteomics and pathway analysis to map the response of differentiating human pancreatic progenitors to chronically increased in vitro glucose levels. We show that exogenous high glucose levels impact different protein subsets in a concentration-dependent manner. In contrast, regardless of concentration, glucose elicits an antipodal effect on the proteome landscape, inducing both beneficial and detrimental changes in regard to achieving the desired islet cell fingerprint. Furthermore, we identified that only a subgroup of these effects and pathways are regulated by changes in redox balance. Our study highlights a complex effect of exogenous glucose on differentiating pancreas progenitors characterized by a distinct proteome signature.
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Braverman-Gross C, Benvenisty N. Modeling Maturity Onset Diabetes of the Young in Pluripotent Stem Cells: Challenges and Achievements. Front Endocrinol (Lausanne) 2021; 12:622940. [PMID: 33692757 PMCID: PMC7937923 DOI: 10.3389/fendo.2021.622940] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 01/06/2021] [Indexed: 12/17/2022] Open
Abstract
Maturity onset diabetes of the young (MODY), is a group of monogenic diabetes disorders. Rodent models for MODY do not fully recapitulate the human phenotypes, calling for models generated in human cells. Human pluripotent stem cells (hPSCs), capable of differentiation towards pancreatic cells, possess a great opportunity to model MODY disorders in vitro. Here, we review the models for MODY diseases in hPSCs to date and the molecular lessons learnt from them. We also discuss the limitations and challenges that these types of models are still facing.
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