追踪药物性肝损伤细胞异质性的单细胞全息技术:技术前景与应用展望

hLife Pub Date : 2024-07-01 DOI:10.1016/j.hlife.2024.01.004
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引用次数: 0

摘要

药物性肝损伤(DILI)仍然是临床诊断和治疗决策中的一个严重问题。它是人体内累积的药物代谢成有毒成分产生反应性代谢产物的结果,然后产生氧化应激、细胞器应激反应和致命后果(肝坏死或凋亡)等初始后果。然而,DILI 复杂性的特殊性质阻碍了其机理研究,人们对其潜在的发病机制仍然知之甚少。基因组、表观基因组、转录组、蛋白质组和新陈代谢技术的进步使单细胞全息技术和方法成为研究细胞异质性和细胞间关系的强大工具。由于肝脏含有不同空间、分子和功能特性的异质细胞类型,它们在细胞类型特异性 omics 重编程之前相互影响,并在具有异质特性的肝细胞遇到毒性损伤时发挥不可替代的作用。单细胞全局组学,尤其是单细胞转录组学和单细胞蛋白质组学,已被用于探索DILI的机制和预测风险因素。在这篇综述中,我们将讨论基于单细胞组学的 DILI 相关研究技术的最新发展和未来展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Single-cell omics in tracing cellular heterogeneity of drug-induced liver injury: Technological landscape and prospective application

Single-cell omics in tracing cellular heterogeneity of drug-induced liver injury: Technological landscape and prospective application

Drug-induced liver injury (DILI) remains a serious problem in clinics for both diagnoses and treatment decisions. It is a result of accumulated drugs in human bodies metabolized into toxic constituents generating reactive metabolites, and then arise initial consequences of oxidative stress, organelle stress responses, and lethal consequences (liver necrosis or apoptosis). However, the idiosyncratic nature of DILI complexes its mechanistic studies and still little is known of its potential etiopathogenesis for certain. Single-cell omics technology and approaches serve as powerful tools for investigating cellular heterogeneity and relationships from measurements of up to millions of individual cells at an unprecedented resolution, which are achieved by advances in genome, epigenome, transcriptome, proteome, and metabolism technologies. As liver contains heterogeneous cell types of distinct spatial, molecular, and functional properties, they interact with each other to precede cell type-specific omics reprogramming and play an irreplaceable role in liver cells with heterogeneous properties upon encountering toxic insults. Single-cell omics, especially single-cell transcriptomics and single-cell proteomics, have been utilized for exploring the mechanisms of DILI and prediction for risk factors. In this review, we discuss the recent development and future perspectives of single-cell omics-based technologies for DILI-related research.

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