Choi Seunghwan, An Joon-Yong
School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, Republic of Korea.
School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, Republic of Korea; Department of Integrated Biomedical and Life Science, Korea University, Seoul, Republic of Korea; BK21FOUR R&E Center for Learning Health Systems, Korea University, Seoul, Republic of Korea; L-HOPE Program for Community-Based Total Learning Health Systems, Korea University, Seoul, Republic of Korea.
Adv Clin Chem. 2025;124:161-195. doi: 10.1016/bs.acc.2024.10.004. Epub 2024 Oct 29.
The advent of multiomics has ushered in a new era of cancer research characterized by integrated genomic, transcriptomic and proteomic analysis to unravel the complexities of cancer biology and facilitate the discovery of novel biomarkers. This chapter provides a comprehensive overview of the concept of multiomics, detailing the significant advances in the underlying technologies and their contributions to our understanding of cancer. It delves into the evolution of genomics and transcriptomics, breakthroughs in proteomics, and overarching progress in multiomic methodologies, highlighting their collective impact on cancer biomarker discovery. Furthermore, this chapter explores the computational methods essential for multiomic studies, including clustering techniques for delineating cancer subtypes, strategies for estimating molecular features and activities, and utility of pathway enrichment analyses for interpreting multiomic datasets. Particular focus has been placed on the application of these methods for identifying distinct cancer subtypes, thereby enabling a more personalized approach to cancer treatment. Through a detailed discussion of the scientific principles, technological advancements, and practical applications of multiomics, this chapter aims to underscore the pivotal role of multiomics in advancing cancer research and paving the way for personalized medicine. The insights provided herein not only illuminate the current landscape of cancer biomarker discovery, but also forecast future directions of multiomics research in oncology, advocating for a more integrated and nuanced approach to understanding and combating cancer.
多组学的出现开启了癌症研究的新时代,其特点是通过整合基因组、转录组和蛋白质组分析来揭示癌症生物学的复杂性,并促进新型生物标志物的发现。本章全面概述了多组学的概念,详细介绍了基础技术的重大进展及其对我们理解癌症的贡献。它深入探讨了基因组学和转录组学的发展、蛋白质组学的突破以及多组学方法的总体进展,突出了它们对癌症生物标志物发现的共同影响。此外,本章还探讨了多组学研究必不可少的计算方法,包括用于划分癌症亚型的聚类技术、估计分子特征和活性的策略,以及用于解释多组学数据集的通路富集分析的效用。特别关注了这些方法在识别不同癌症亚型方面的应用,从而实现更个性化的癌症治疗方法。通过对多组学的科学原理、技术进步和实际应用的详细讨论,本章旨在强调多组学在推进癌症研究和为个性化医疗铺平道路方面的关键作用。本文提供的见解不仅阐明了癌症生物标志物发现的当前状况,还预测了肿瘤学中多组学研究的未来方向,倡导采用更综合、细致入微的方法来理解和对抗癌症。