High Throughput Multi-Omics Approaches for Clinical Trial Evaluation and Drug Discovery.
High Throughput Multi-Omics Approaches for Clinical Trial Evaluation and Drug Discovery.
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DOI：
10.3389/fimmu.2021.590742
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发表时间：
2021
影响因子：
7.3
通讯作者：
Krieg C
中科院分区：
文献类型：
--
作者：
Zielinski JM;Luke JJ;Guglietta S;Krieg C
高通量单细胞多组学平台，例如质谱流式细胞术（飞行时间流式细胞术；CyTOF）、高维成像（> 6 个标记物；Hyperion、MIBIscope、CODEX、MACSima）和最近发展的基因组流式细胞术（Citeseq 或 REAPseq）使人们能够对许多生物学和临床问题（例如造血、移植、癌症和自身免疫）获得前所未有的见解。与不断采用新的单细胞分析方法以及随后从这些平台收集的大数据相结合，创建了细胞类型以及细胞和亚细胞相互作用网络的完整图谱。这些图册为参考和数据挖掘方法构建了理想的科学发现环境，这些方法常常揭示新的细胞疾病网络。在这篇综述中，我们将讨论如何在单细胞水平上组合和融合不同组学工作流程来检查细胞表型、免疫效应器功能，甚至动态变化，例如样品中甚至特定组织位置中不同细胞的代谢组状态。我们将讨论预印本平台如何帮助优化工作流程和可重复性以及社区推广。我们还将很快讨论如何利用单细胞多组学方法来加速临床试验期间细胞生物标志物的发现，以预测对治疗的反应，跟踪反应性细胞类型，并定义新的可药物靶标途径。单细胞蛋白质组方法已经改变了我们探索疾病和治疗过程中细胞机制的方式。该领域当前的挑战是我们如何向科学界分享这些颠覆性技术，同时仍然包括新方法，例如基因组细胞术和单细胞代谢组学。
High throughput single cell multi-omics platforms, such as mass cytometry (cytometry by time-of-flight; CyTOF), high dimensional imaging (>6 marker; Hyperion, MIBIscope, CODEX, MACSima) and the recently evolved genomic cytometry (Citeseq or REAPseq) have enabled unprecedented insights into many biological and clinical questions, such as hematopoiesis, transplantation, cancer, and autoimmunity. In synergy with constantly adapting new single-cell analysis approaches and subsequent accumulating big data collections from these platforms, whole atlases of cell types and cellular and sub-cellular interaction networks are created. These atlases build an ideal scientific discovery environment for reference and data mining approaches, which often times reveals new cellular disease networks. In this review we will discuss how combinations and fusions of different -omic workflows on a single cell level can be used to examine cellular phenotypes, immune effector functions, and even dynamic changes, such as metabolomic state of different cells in a sample or even in a defined tissue location. We will touch on how pre-print platforms help in optimization and reproducibility of workflows, as well as community outreach. We will also shortly discuss how leveraging single cell multi-omic approaches can be used to accelerate cellular biomarker discovery during clinical trials to predict response to therapy, follow responsive cell types, and define novel druggable target pathways. Single cell proteome approaches already have changed how we explore cellular mechanism in disease and during therapy. Current challenges in the field are how we share these disruptive technologies to the scientific communities while still including new approaches, such as genomic cytometry and single cell metabolomics.