Applications of Omics Technologies for Three-DimensionalIn VitroDisease Models

组学 疾病 代谢组学 杠杆(统计) 表观遗传学 蛋白质组学 计算生物学 系统生物学 新兴技术 基因组学 数据科学 生物 生物信息学 计算机科学 医学 人工智能 基因组 病理 DNA甲基化 遗传学 基因表达 基因
作者
Vera M. Pieters,Ileana L. Co,Nila C. Wu,Alison P. McGuigan
出处
期刊:Tissue Engineering Part C-methods [Mary Ann Liebert]
卷期号:27 (3): 183-199 被引量:6
标识
DOI:10.1089/ten.tec.2020.0300
摘要

Omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, multiomics, and integrated modalities, have greatly contributed to our understanding of various diseases by enabling researchers to probe the molecular wiring of cellular systems in a high-throughput and precise manner. With the development of tissue-engineered three-dimensional (3D) in vitro disease models, such as organoids and spheroids, there is potential of integrating omics technologies with 3D disease models to elucidate the complex links between genotype and phenotype. These 3D disease models have been used to model cancer, infectious disease, toxicity, neurological disorders, and others. In this review, we provide an overview of omics technologies, highlight current and emerging studies, discuss the associated experimental design considerations, barriers and challenges of omics technologies, and provide an outlook on the future applications of omics technologies with 3D models. Overall, this review aims to provide a valuable resource for tissue engineers seeking to leverage omics technologies for diving deeper into biological discovery. Impact statement With the emergence of three-dimensional (3D) in vitro disease models, tissue engineers are increasingly interested to investigate these systems to address biological questions related to disease mechanism, drug target discovery, therapy resistance, and more. Omics technologies are a powerful and high-throughput approach, but their application for 3D disease models is not maximally utilized. This review illustrates the achievements and potential of using omics technologies to leverage the full potential of 3D in vitro disease models. This will improve the quality of such models, advance our understanding of disease, and contribute to therapy development.
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