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空间转录组学:疾病理解和药物发现的有力工具。

Spatial Transcriptomics: A Powerful Tool in Disease Understanding and Drug Discovery.

机构信息

Beijing Key Laboratory of Traditional Chinese Medicine Basic Research on Prevention and Treatment for Major Diseases, Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing 100700, China.

Analysis of Complex Effects of Proprietary Chinese Medicine, Hunan Provincial Key Laboratory, Yongzhou City, Hunan Province, China.

出版信息

Theranostics. 2024 May 11;14(7):2946-2968. doi: 10.7150/thno.95908. eCollection 2024.

DOI:10.7150/thno.95908
PMID:38773973
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11103497/
Abstract

Recent advancements in modern science have provided robust tools for drug discovery. The rapid development of transcriptome sequencing technologies has given rise to single-cell transcriptomics and single-nucleus transcriptomics, increasing the accuracy of sequencing and accelerating the drug discovery process. With the evolution of single-cell transcriptomics, spatial transcriptomics (ST) technology has emerged as a derivative approach. Spatial transcriptomics has emerged as a hot topic in the field of omics research in recent years; it not only provides information on gene expression levels but also offers spatial information on gene expression. This technology has shown tremendous potential in research on disease understanding and drug discovery. In this article, we introduce the analytical strategies of spatial transcriptomics and review its applications in novel target discovery and drug mechanism unravelling. Moreover, we discuss the current challenges and issues in this research field that need to be addressed. In conclusion, spatial transcriptomics offers a new perspective for drug discovery.

摘要

近年来,现代科学的进步为药物发现提供了强大的工具。转录组测序技术的快速发展催生了单细胞转录组学和单核转录组学,提高了测序的准确性并加速了药物发现过程。随着单细胞转录组学的发展,空间转录组学(ST)技术应运而生。近年来,空间转录组学已成为组学研究领域的热门话题;它不仅提供了基因表达水平的信息,还提供了基因表达的空间信息。这项技术在疾病理解和药物发现的研究中显示出了巨大的潜力。本文介绍了空间转录组学的分析策略,并综述了其在新靶点发现和药物作用机制阐明中的应用。此外,我们还讨论了该研究领域当前需要解决的挑战和问题。总之,空间转录组学为药物发现提供了新的视角。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bb69/11103497/a792b1ea7217/thnov14p2946g006.jpg
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