激光捕获显微切割
组学
生物
背景(考古学)
计算生物学
吞吐量
数据科学
计算机科学
生物信息学
遗传学
基因
电信
基因表达
古生物学
无线
作者
Wenbo Guo,Yining Hu,Jingyang Qian,L Zhu,Junyun Cheng,Jie Liao,Xiaohui Fan
标识
DOI:10.1016/j.jgg.2023.07.011
摘要
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.
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