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Awuah WA, Roy S, Tan JK, Adebusoye FT, Qiang Z, Ferreira T, Ahluwalia A, Shet V, Yee ALW, Abdul‐Rahman T, Papadakis M. Exploring the current landscape of single-cell RNA sequencing applications in gastric cancer research. J Cell Mol Med 2024; 28:e18159. [PMID: 38494861 PMCID: PMC10945075 DOI: 10.1111/jcmm.18159] [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: 07/24/2023] [Revised: 12/22/2023] [Accepted: 01/12/2024] [Indexed: 03/19/2024] Open
Abstract
Gastric cancer (GC) represents a major global health burden and is responsible for a significant number of cancer-related fatalities. Its complex nature, characterized by heterogeneity and aggressive behaviour, poses considerable challenges for effective diagnosis and treatment. Single-cell RNA sequencing (scRNA-seq) has emerged as an important technique, offering unprecedented precision and depth in gene expression profiling at the cellular level. By facilitating the identification of distinct cell populations, rare cells and dynamic transcriptional changes within GC, scRNA-seq has yielded valuable insights into tumour progression and potential therapeutic targets. Moreover, this technology has significantly improved our comprehension of the tumour microenvironment (TME) and its intricate interplay with immune cells, thereby opening avenues for targeted therapeutic strategies. Nonetheless, certain obstacles, including tumour heterogeneity and technical limitations, persist in the field. Current endeavours are dedicated to refining protocols and computational tools to surmount these challenges. In this narrative review, we explore the significance of scRNA-seq in GC, emphasizing its advantages, challenges and potential applications in unravelling tumour heterogeneity and identifying promising therapeutic targets. Additionally, we discuss recent developments, ongoing efforts to overcome these challenges, and future prospects. Although further enhancements are required, scRNA-seq has already provided valuable insights into GC and holds promise for advancing biomedical research and clinical practice.
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Affiliation(s)
| | - Sakshi Roy
- School of MedicineQueen's University BelfastBelfastUK
| | | | | | - Zekai Qiang
- Department of Oncology & MetabolismThe University of SheffieldSheffieldUK
| | - Tomas Ferreira
- Department of Clinical Neurosciences, School of Clinical MedicineUniversity of CambridgeCambridgeUK
| | | | - Vallabh Shet
- Faculty of MedicineBangalore Medical College and Research InstituteBangaloreKarnatakaIndia
| | | | | | - Marios Papadakis
- Department of Surgery II, University Hospital Witten‐HerdeckeUniversity of Witten‐HerdeckeWuppertalGermany
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Singh S, Pandey AK, Prajapati VK. From genome to clinic: The power of translational bioinformatics in improving human health. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2024; 139:1-25. [PMID: 38448133 DOI: 10.1016/bs.apcsb.2023.11.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Translational bioinformatics (TBI) has transformed healthcare by providing personalized medicine and tailored treatment options by integrating genomic data and clinical information. In recent years, TBI has bridged the gap between genome and clinical data because of significant advances in informatics like quantum computing and utilizing state-of-the-art technologies. This chapter discusses the power of translational bioinformatics in improving human health, from uncovering disease-causing genes and variations to establishing new therapeutic techniques. We discuss key application areas of bioinformatics in clinical genomics, such as data sources and methods used in translational bioinformatics, the impact of translational bioinformatics on human health, and how machine learning and artificial intelligence are being used to mine vast amounts of data for drug development and precision medicine. We also look at the problems, constraints, and ethical concerns connected with exploiting genomic data and the future of translational bioinformatics and its potential impact on medicine and human health. Ultimately, this chapter emphasizes the great potential of translational bioinformatics to alter healthcare and enhance patient outcomes.
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Affiliation(s)
- Satyendra Singh
- Department of Biochemistry, School of Life Sciences, Central University of Rajasthan, Bandarsindri, Kishangarh, Ajmer, Rajasthan, India
| | - Anurag Kumar Pandey
- College of Biotechnology, Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut, Uttar Pradesh, India
| | - Vijay Kumar Prajapati
- Department of Biochemistry, University of Delhi South Campus, Dhaula Kuan, New Delhi, India.
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Wang R, Gao Y, Wen S, Guo X. BNIPL is a promising biomarker of laryngeal cancer: novel insights from bioinformatics analysis and experimental validation. BMC Med Genomics 2024; 17:45. [PMID: 38302910 PMCID: PMC10832104 DOI: 10.1186/s12920-024-01811-z] [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: 04/11/2023] [Accepted: 01/18/2024] [Indexed: 02/03/2024] Open
Abstract
BACKGROUND Laryngeal cancer (LC) is a malignant tumor with high incidence and mortality. We aim to explore key genes as novel biomarkers to find potential target of LC in clinic diagnosis and treatment. METHODS We retrieved GSE143224 and GSE84957 datasets from the Gene Expression Omnibus database to screen the differentially expressed genes (DEGs). Hub genes were identified from protein-protein interaction networks and further determined using receiver operating characteristic curves and principal component analysis. The expression of hub gene was verified by quantitative real time polymerase chain reaction. The transfection efficiency of BCL2 interacting protein like (BNIPL) was measured by western blot. Proliferation, migration, and invasion abilities were detected by Cell Counting Kit-8, wound-healing, and transwell assays, respectively. RESULTS Total 96 overlapping DEGs were screened out from GSE143224 and GSE84957 datasets. Six hub genes (BNIPL, KRT4, IGFBP3, MMP10, MMP3, and TGFBI) were identified from PPI network. BNIPL was selected as the target gene. The receiver operating characteristic curves of BNIPL suggested that the false positive rate was 18.5% and the true positive rate was 81.5%, showing high predictive values for LC. The expression level of BNIPL was downregulated in TU212 and TU686 cells. Additionally, overexpression of BNIPL suppressed the proliferation, migration, and invasion of TU212 and TU686 cells. CONCLUSION BNIPL is a novel gene signature involved in LC progression, which exerts an inhibitory effect on LC development. These findings provide a novel insight into the pathogenesis of LC.
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Affiliation(s)
- Rui Wang
- Department of Otolaryngology Head and Neck Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, No. 99, Longcheng Street, Taiyuan City, Shanxi Province, 030032, China
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province, 430030, China
| | - Ying Gao
- Department of Otolaryngology Head and Neck Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, No. 99, Longcheng Street, Taiyuan City, Shanxi Province, 030032, China
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province, 430030, China
| | - Shuxin Wen
- Department of Otolaryngology Head and Neck Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, No. 99, Longcheng Street, Taiyuan City, Shanxi Province, 030032, China.
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province, 430030, China.
| | - Xiudong Guo
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province, 430030, China
- Department of Head Neck and Breast Oncology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan City, Shanxi Province, 030032, China
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