Multiomics in cancer biomarker discovery and cancer subtyping.

Adv Clin Chem

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. Electronic address:

Published: January 2025

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.

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Source
http://dx.doi.org/10.1016/bs.acc.2024.10.004DOI Listing

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