Integrative Multi-Omics Approaches in Cancer Research: From Biological Networks to Clinical Subtypes.
Integrative Multi-Omics Approaches in Cancer Research: From Biological Networks to Clinical Subtypes.
复制标题
癌症研究中的综合多组学方法：从生物网络到临床亚型。
DOI：
10.14348/molcells.2021.0042
复制
发表时间：
2021-07-31
影响因子：
3.8
通讯作者：
An JY
中科院分区：
文献类型：
--
作者：
Heo YJ;Hwa C;Lee GH;Park JM;An JY
多组学方法是整合来自同一患者的多个组学数据集的新框架，以更好地了解癌症的分子和临床特征。现在，广泛的新兴组学和多视图聚类算法为进一步将癌症分类为亚型提供了前所未有的机会，提高了这些亚型的生存预测和治疗结果，并通过不同的分子层了解关键的病理生理过程。在这篇综述中，我们概述了多组学方法在癌症研究中的概念和原理。我们还介绍了针对癌症患者多层数据集的多组学算法和集成方法的最新进展。最后，我们总结了各种癌症的大规模多组学研究的最新发现及其对患者亚型和药物开发的影响。
Multi-omics approaches are novel frameworks that integrate multiple omics datasets generated from the same patients to better understand the molecular and clinical features of cancers. A wide range of emerging omics and multi-view clustering algorithms now provide unprecedented opportunities to further classify cancers into subtypes, improve the survival prediction and therapeutic outcome of these subtypes, and understand key pathophysiological processes through different molecular layers. In this review, we overview the concept and rationale of multi-omics approaches in cancer research. We also introduce recent advances in the development of multi-omics algorithms and integration methods for multiple-layered datasets from cancer patients. Finally, we summarize the latest findings from large-scale multi-omics studies of various cancers and their implications for patient subtyping and drug development.