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Zhang W, Song LN, You YF, Qi FN, Cui XH, Yi MX, Zhu G, Chang RA, Zhang HJ. Application of artificial intelligence in the prediction of immunotherapy efficacy in hepatocellular carcinoma: Current status and prospects. Artif Intell Gastroenterol 2024; 5:90096. [DOI: 10.35712/aig.v5.i1.90096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 01/28/2024] [Accepted: 03/12/2024] [Indexed: 04/29/2024] Open
Abstract
Artificial Intelligence (AI) has increased as a potent tool in medicine, with promising oncology applications. The emergence of immunotherapy has transformed the treatment terrain for hepatocellular carcinoma (HCC), offering new hope to patients with this challenging malignancy. This article examines the role and future of AI in forecasting the effectiveness of immunotherapy in HCC. We highlight the potential of AI to revolutionize the prediction of therapy response, thus improving patient selection and clinical outcomes. The article further outlines the challenges and future research directions in this emerging field.
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Affiliation(s)
- Wei Zhang
- Research Center of Clinical Medicine and Department of General Surgery, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
| | - Li-Ning Song
- Research Center of Clinical Medicine and Department of General Surgery, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
| | - Yun-Fei You
- Research Center of Clinical Medicine and Department of General Surgery, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
| | - Feng-Nan Qi
- Research Center of Clinical Medicine and Department of General Surgery, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
| | - Xiao-Hong Cui
- Department of General Surgery, Shanghai Electric Power Hospital, Shanghai 200050, China
| | - Ming-Xun Yi
- Research Center of Clinical Medicine and Department of General Surgery, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
| | - Guang Zhu
- Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Ren-An Chang
- Research Center of Clinical Medicine and Department of General Surgery, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
| | - Hai-Jian Zhang
- Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong, China
- Research Center of Clinical Medicine, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
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Shekarkar Azgomi M, Badami GD, Lo Pizzo M, Tamburini B, Dieli C, La Manna MP, Dieli F, Caccamo N. Integrated Analysis of Single-Cell and Bulk RNA Sequencing Data Reveals Memory-like NK Cell Subset Associated with Mycobacterium tuberculosis Latency. Cells 2024; 13:293. [PMID: 38391906 PMCID: PMC10886487 DOI: 10.3390/cells13040293] [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: 12/22/2023] [Revised: 02/01/2024] [Accepted: 02/03/2024] [Indexed: 02/24/2024] Open
Abstract
Natural killer (NK) cells are innate-like lymphocytes that belong to the family of type-1 innate lymphoid cells and rapidly respond to virus-infected and tumor cells. In this study, we have combined scRNA-seq data and bulk RNA-seq data to define the phenotypic and molecular characteristics of peripheral blood NK cells. While the role of NK cells in immune surveillance against virus infections and tumors has been well established, their contribution to protective responses to other intracellular microorganisms, such as Mycobacterium tuberculosis (Mtb), is still poorly understood. In this study, we have combined scRNA-seq data and bulk RNA-seq data to illuminate the molecular characteristics of circulating NK cells in patients with active tuberculosis (TB) disease and subjects with latent Mtb infection (LTBI) and compared these characteristics with those of healthy donors (HDs) and patients with non-TB other pulmonary infectious diseases (ODs). We show here that the NK cell cluster was significantly increased in LTBI subjects, as compared to patients with active TB or other non-TB pulmonary diseases and HD, and this was mostly attributable to the expansion of an NK cell population expressing KLRC2, CD52, CCL5 and HLA-DRB1, which most likely corresponds to memory-like NK2.1 cells. These data were validated by flow cytometry analysis in a small cohort of samples, showing that LTBI subjects have a significant expansion of NK cells characterized by the prevalence of memory-like CD52+ NKG2C+ NK cells. Altogether, our results provide some new information on the role of NK cells in protective immune responses to Mtb.
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Affiliation(s)
- Mojtaba Shekarkar Azgomi
- Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, 90127 Palermo, Italy; (M.S.A.); (G.D.B.); (M.L.P.); (B.T.); (C.D.); (M.P.L.M.); (N.C.)
- Department of Biomedicine, Neurosciences and Advanced Diagnostic (BND), University of Palermo, 90127 Palermo, Italy
| | - Giusto Davide Badami
- Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, 90127 Palermo, Italy; (M.S.A.); (G.D.B.); (M.L.P.); (B.T.); (C.D.); (M.P.L.M.); (N.C.)
| | - Marianna Lo Pizzo
- Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, 90127 Palermo, Italy; (M.S.A.); (G.D.B.); (M.L.P.); (B.T.); (C.D.); (M.P.L.M.); (N.C.)
| | - Bartolo Tamburini
- Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, 90127 Palermo, Italy; (M.S.A.); (G.D.B.); (M.L.P.); (B.T.); (C.D.); (M.P.L.M.); (N.C.)
- Department of Health Promotion, Mother and Childcare, Internal Medicine and Medical Specialties, University of Palermo, 90129 Palermo, Italy
| | - Costanza Dieli
- Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, 90127 Palermo, Italy; (M.S.A.); (G.D.B.); (M.L.P.); (B.T.); (C.D.); (M.P.L.M.); (N.C.)
| | - Marco Pio La Manna
- Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, 90127 Palermo, Italy; (M.S.A.); (G.D.B.); (M.L.P.); (B.T.); (C.D.); (M.P.L.M.); (N.C.)
- Department of Biomedicine, Neurosciences and Advanced Diagnostic (BND), University of Palermo, 90127 Palermo, Italy
| | - Francesco Dieli
- Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, 90127 Palermo, Italy; (M.S.A.); (G.D.B.); (M.L.P.); (B.T.); (C.D.); (M.P.L.M.); (N.C.)
- Department of Biomedicine, Neurosciences and Advanced Diagnostic (BND), University of Palermo, 90127 Palermo, Italy
| | - Nadia Caccamo
- Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), Azienda Ospedaliera Universitaria Policlinico (AOUP) Paolo Giaccone, University of Palermo, 90127 Palermo, Italy; (M.S.A.); (G.D.B.); (M.L.P.); (B.T.); (C.D.); (M.P.L.M.); (N.C.)
- Department of Biomedicine, Neurosciences and Advanced Diagnostic (BND), University of Palermo, 90127 Palermo, Italy
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