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Kesharwani A, Gujrati V. Multimodal techniques and strategies for chemical and metabolic imaging at the single-cell level. Curr Opin Biotechnol 2024; 88:103149. [PMID: 38810301 DOI: 10.1016/j.copbio.2024.103149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 05/13/2024] [Accepted: 05/13/2024] [Indexed: 05/31/2024]
Abstract
Single-cell chemical and metabolic imaging technologies provide unprecedented insights into individual cell dynamics, advancing our understanding of cellular processes, molecular interactions, and metabolic activities. Advances in fluorescence, Raman, optoacoustic (photoacoustic), or mass spectrometry methods have paved the way to characterize metabolites, signaling molecules, and other moieties within individual cells. These modalities can also lead to single-cell imaging capabilities by targeting endogenous cell contrast or by employing exogenous contrast generation techniques, including contrast agents that target specific cell structure or function. In this review, we present key developments, summarize recent applications in single-cell interrogation and imaging, and illustrate their advantages, limitations, and outlook.
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Affiliation(s)
- Ajay Kesharwani
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Neuherberg, Germany; Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Vipul Gujrati
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Neuherberg, Germany; Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine and Health, Technical University of Munich, Munich, Germany.
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Jiao R, Jiang W, Xu K, Luo Q, Wang L, Zhao C. Lipid metabolism analysis in esophageal cancer and associated drug discovery. J Pharm Anal 2024; 14:1-15. [PMID: 38352954 PMCID: PMC10859535 DOI: 10.1016/j.jpha.2023.08.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 07/27/2023] [Accepted: 08/29/2023] [Indexed: 02/16/2024] Open
Abstract
Esophageal cancer is an upper gastrointestinal malignancy with a bleak prognosis. It is still being explored in depth due to its complex molecular mechanisms of occurrence and development. Lipids play a crucial role in cells by participating in energy supply, biofilm formation, and signal transduction processes, and lipid metabolic reprogramming also constitutes a significant characteristic of malignant tumors. More and more studies have found esophageal cancer has obvious lipid metabolism abnormalities throughout its beginning, progress, and treatment resistance. The inhibition of tumor growth and the enhancement of antitumor therapy efficacy can be achieved through the regulation of lipid metabolism. Therefore, we reviewed and analyzed the research results and latest findings for lipid metabolism and associated analysis techniques in esophageal cancer, and comprehensively proved the value of lipid metabolic reprogramming in the evolution and treatment resistance of esophageal cancer, as well as its significance in exploring potential therapeutic targets and biomarkers.
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Affiliation(s)
- Ruidi Jiao
- Bionic Sensing and Intelligence Center, Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518000, China
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, Guangdong, 518116, China
- School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, 518000, China
| | - Wei Jiang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, Guangdong, 518116, China
| | - Kunpeng Xu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, Guangdong, 518116, China
| | - Qian Luo
- Bionic Sensing and Intelligence Center, Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518000, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Luhua Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, Guangdong, 518116, China
- School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, 518000, China
| | - Chao Zhao
- Bionic Sensing and Intelligence Center, Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518000, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Shenzhen Key Laboratory of Precision Diagnosis and Treatment of Depression, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518000, China
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