Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA.
Fluidigm Corporation, South San Francisco, CA, USA.
Expert Rev Proteomics. 2021 Oct;18(10):845-861. doi: 10.1080/14789450.2021.1984886. Epub 2021 Dec 14.
Laser Capture Microdissection (LCM) uses a laser to isolate, or capture, specific cells of interest in a complex heterogeneous tissue section, under direct microscopic visualization. Recently, there has been a surge of publications using LCM for tissue spatial molecular profiling relevant to a wide range of research topics.
We summarize the many advances in tissue Laser Capture Proteomics (LCP) using mass spectrometry for discovery, and protein arrays for signal pathway network mapping. This review emphasizes: a) transition of LCM phosphoproteomics from the lab to the clinic for individualized cancer therapy, and b) the emerging frontier of LCM single cell molecular analysis combining proteomics with genomic, and transcriptomic analysis. The search strategy was based on the combination of MeSH terms with expert refinement.
LCM is complemented by a rich set of instruments, methodology protocols, and analytical A.I. (artificial intelligence) software for basic and translational research. Resolution is advancing to the tissue single cell level. A vision for the future evolution of LCM is presented. Emerging LCM technology is combining digital and AI guided remote imaging with automation, and telepathology, to a achieve multi-omic profiling that was not previously possible.
激光捕获显微切割(LCM)使用激光在直接显微镜可视化下,从复杂的异质组织切片中分离或捕获特定的感兴趣细胞。最近,使用 LCM 进行与广泛研究主题相关的组织空间分子分析的出版物大量涌现。
我们总结了使用质谱进行发现的组织激光捕获蛋白质组学(LCP)的许多进展,以及用于信号通路网络映射的蛋白质阵列。本综述强调:a)LCM 磷酸蛋白质组学从实验室到个体化癌症治疗的临床的转变,以及 b)将蛋白质组学与基因组和转录组分析相结合的 LCM 单细胞分子分析的新兴前沿。搜索策略基于 MeSH 术语与专家细化的组合。
LCM 通过一套丰富的仪器、方法学协议和分析人工智能(AI)软件进行补充,用于基础和转化研究。分辨率正在推进到组织单细胞水平。提出了对 LCM 未来发展的展望。新兴的 LCM 技术正在将数字和 AI 引导的远程成像与自动化和远程病理学相结合,以实现以前不可能实现的多组学分析。