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Fuentes-Rodriguez A, Mitchell A, Guérin SL, Landreville S. Recent Advances in Molecular and Genetic Research on Uveal Melanoma. Cells 2024; 13:1023. [PMID: 38920653 PMCID: PMC11201764 DOI: 10.3390/cells13121023] [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: 04/10/2024] [Revised: 06/08/2024] [Accepted: 06/09/2024] [Indexed: 06/27/2024] Open
Abstract
Uveal melanoma (UM), a distinct subtype of melanoma, presents unique challenges in its clinical management due to its complex molecular landscape and tendency for liver metastasis. This review highlights recent advancements in understanding the molecular pathogenesis, genetic alterations, and immune microenvironment of UM, with a focus on pivotal genes, such as GNAQ/11, BAP1, and CYSLTR2, and delves into the distinctive genetic and chromosomal classifications of UM, emphasizing the role of mutations and chromosomal rearrangements in disease progression and metastatic risk. Novel diagnostic biomarkers, including circulating tumor cells, DNA and extracellular vesicles, are discussed, offering potential non-invasive approaches for early detection and monitoring. It also explores emerging prognostic markers and their implications for patient stratification and personalized treatment strategies. Therapeutic approaches, including histone deacetylase inhibitors, MAPK pathway inhibitors, and emerging trends and concepts like CAR T-cell therapy, are evaluated for their efficacy in UM treatment. This review identifies challenges in UM research, such as the limited treatment options for metastatic UM and the need for improved prognostic tools, and suggests future directions, including the discovery of novel therapeutic targets, immunotherapeutic strategies, and advanced drug delivery systems. The review concludes by emphasizing the importance of continued research and innovation in addressing the unique challenges of UM to improve patient outcomes and develop more effective treatment strategies.
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Affiliation(s)
- Aurélie Fuentes-Rodriguez
- Department of Ophthalmology and Otorhinolaryngology-Cervico-Facial Surgery, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (A.F.-R.); (A.M.); (S.L.G.)
- Hôpital du Saint-Sacrement, Regenerative Medicine Division, CHU de Québec-Université Laval Research Centre, Quebec City, QC G1S 4L8, Canada
- Centre de Recherche en Organogénèse Expérimentale de l‘Université Laval/LOEX, Quebec City, QC G1J 1Z4, Canada
- Université Laval Cancer Research Center, Quebec City, QC G1R 3S3, Canada
| | - Andrew Mitchell
- Department of Ophthalmology and Otorhinolaryngology-Cervico-Facial Surgery, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (A.F.-R.); (A.M.); (S.L.G.)
- Hôpital du Saint-Sacrement, Regenerative Medicine Division, CHU de Québec-Université Laval Research Centre, Quebec City, QC G1S 4L8, Canada
- Centre de Recherche en Organogénèse Expérimentale de l‘Université Laval/LOEX, Quebec City, QC G1J 1Z4, Canada
- Université Laval Cancer Research Center, Quebec City, QC G1R 3S3, Canada
| | - Sylvain L. Guérin
- Department of Ophthalmology and Otorhinolaryngology-Cervico-Facial Surgery, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (A.F.-R.); (A.M.); (S.L.G.)
- Hôpital du Saint-Sacrement, Regenerative Medicine Division, CHU de Québec-Université Laval Research Centre, Quebec City, QC G1S 4L8, Canada
- Centre de Recherche en Organogénèse Expérimentale de l‘Université Laval/LOEX, Quebec City, QC G1J 1Z4, Canada
| | - Solange Landreville
- Department of Ophthalmology and Otorhinolaryngology-Cervico-Facial Surgery, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (A.F.-R.); (A.M.); (S.L.G.)
- Hôpital du Saint-Sacrement, Regenerative Medicine Division, CHU de Québec-Université Laval Research Centre, Quebec City, QC G1S 4L8, Canada
- Centre de Recherche en Organogénèse Expérimentale de l‘Université Laval/LOEX, Quebec City, QC G1J 1Z4, Canada
- Université Laval Cancer Research Center, Quebec City, QC G1R 3S3, Canada
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Hu F, Zhu Y, Tian J, Xu H, Xue Q. Single-Cell Sequencing Combined with Transcriptome Sequencing Constructs a Predictive Model of Key Genes in Multiple Sclerosis and Explores Molecular Mechanisms Related to Cellular Communication. J Inflamm Res 2024; 17:191-210. [PMID: 38226354 PMCID: PMC10788626 DOI: 10.2147/jir.s442684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 12/28/2023] [Indexed: 01/17/2024] Open
Abstract
Background Multiple sclerosis (MS) causes chronic inflammation and demyelination of the central nervous system and comprises a class of neurodegenerative diseases in which interactions between multiple immune cell types mediate the involvement of MS development. However, the early diagnosis and treatment of MS remain challenging. Methods Gene expression profiles of MS patients were obtained from the Gene Expression Omnibus (GEO) database. Single-cell and intercellular communication analyses were performed to identify candidate gene sets. Predictive models were constructed using LASSO regression. Relationships between genes and immune cells were analyzed by single sample gene set enrichment analysis (ssGSEA). The molecular mechanisms of key genes were explored using gene enrichment analysis. An miRNA network was constructed to search for target miRNAs related to key genes, and related transcription factors were searched by transcriptional regulation analysis. We utilized the GeneCard database to detect the correlations between disease-regulated genes and key genes. We verified the mRNA expression of 4 key genes by reverse transcription-quantitative PCR (RT‒qPCR). Results Monocyte marker genes were selected as candidate gene sets. CD3D, IL2RG, MS4A6A, and NCF2 were found to be the key genes by LASSO regression. We constructed a prediction model with AUC values of 0.7569 and 0.719. The key genes were closely related to immune factors and immune cells. We explored the signaling pathways and molecular mechanisms involving the key genes by gene enrichment analysis. We obtained and visualized the miRNAs associated with the key genes using the miRcode database. We also predicted the transcription factors involved. We used validated key genes in MS patients, several of which were confirmed by RT‒qPCR. Conclusion The prediction model constructed with the CD3D, IL2RG, MS4A6A, and NCF2 genes has good diagnostic efficacy and provides new ideas for the diagnosis and treatment of MS.
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Affiliation(s)
- Fangzhou Hu
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215000, People’s Republic of China
| | - Yunfei Zhu
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215000, People’s Republic of China
| | - Jingluan Tian
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215000, People’s Republic of China
| | - Hua Xu
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215000, People’s Republic of China
- Department of Neurology, Affiliated Jintan Hospital of Jiangsu University, Changzhou Jintan First People’s Hospital, Changzhou, Jiangsu, 215006, People’s Republic of China
| | - Qun Xue
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215000, People’s Republic of China
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