Laser capture microdissection for biomedical research: towards high-throughput, multi-omics, and single-cell resolution

Wenbo Guo; Yining Hu; Jingyang Qian; Lidan Zhu; Junyun Cheng; Jie Liao; Xiaohui Fan

doi:10.1016/j.jgg.2023.07.011

Volume 50 Issue 9

Sep. 2023

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Article Navigation > Journal of Genetics and Genomics > 2023 > 50(9): 641-651

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Laser capture microdissection for biomedical research: towards high-throughput, multi-omics, and single-cell resolution

doi: 10.1016/j.jgg.2023.07.011

a. Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China;
b. National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, Zhejiang 314100, China

Funds:

This work was supported by the National Natural Science Foundation of China (81973701 and 82204772), the Natural Science Foundation of Zhejiang Province (LZ20H290002), the Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine (ZYYCXTD-D-202002), the China Postdoctoral Science Foundation (2022M712811), and Westlake Laboratory (Westlake Laboratory of Life Sciences and Biomedicine).

Received Date: 2023-04-28
Revised Date: 2023-07-28
Accepted Date: 2023-07-28
Publish Date: 2023-08-05

Abstract

Abstract

Spatial omics technologies have become powerful methods to provide valuable insights into cells and tissues within a complex context, significantly enhancing our understanding of the intricate and multifaceted biological system. With an increasing focus on spatial heterogeneity, there is a growing need for unbiased, spatially resolved omics technologies. Laser capture microdissection (LCM) is a cutting-edge method for acquiring spatial information that can quickly collect regions of interest (ROIs) from heterogeneous tissues, with resolutions ranging from single cells to cell populations. Thus, LCM has been widely used for studying the cellular and molecular mechanisms of diseases. This review focuses on the differences among four types of commonly used LCM technologies and their applications in omics and disease research. Key attributes of application cases are also highlighted, such as throughput and spatial resolution. In addition, we comprehensively discuss the existing challenges and the great potential of LCM in biomedical research, disease diagnosis, and targeted therapy from the perspective of high-throughput, multi-omics, and single-cell resolution.
- Laser capture microdissection,
- Spatial omics,
- Single-cell resolution,
- Multiplexed barcoding,
- Disease microenvironment

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References(103)

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