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Review
. 2024 Sep 17;5(9):101736.
doi: 10.1016/j.xcrm.2024.101736.

Mining nucleic acid "omics" to boost liquid biopsy in cancer

Affiliations
Review

Mining nucleic acid "omics" to boost liquid biopsy in cancer

Ann Tivey et al. Cell Rep Med. .

Abstract

Treatments for cancer patients are becoming increasingly complex, and there is a growing desire from clinicians and patients for biomarkers that can account for this complexity to support informed decisions about clinical care. To achieve precision medicine, the new generation of biomarkers must reflect the spatial and temporal heterogeneity of cancer biology both between patients and within an individual patient. Mining the different layers of 'omics in a multi-modal way from a minimally invasive, easily repeatable, liquid biopsy has increasing potential in a range of clinical applications, and for improving our understanding of treatment response and resistance. Here, we detail the recent developments and methods allowing exploration of genomic, epigenomic, transcriptomic, and fragmentomic layers of 'omics from liquid biopsy, and their integration in a range of applications. We also consider the specific challenges that are posed by the clinical implementation of multi-omic liquid biopsies.

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Conflict of interest statement

Declaration of interests F.M. is a co-inventor on multiple patents related to cfDNA analysis and has consulted for Roche Dx. A.C., S.M.H., D.G.R., and C.D. are co-inventors on a patent relating to cfDNA analysis. R.J.L. has received a speaker fee from Pierre Fabre and research funding from Bristol Myers Squibb, AstraZeneca, and Pierre Fabre. C.D. has received research funding/educational research grants since 2020 from the following: AstraZeneca, Amgen, Carrick Therapeutics, Merck AG, Bayer, Boehringer Ingelheim, BMS, Novartis, Celgene, Epigene Therapeutics Inc, and Menarini. C.D. has received honoraria for consultancy and/or advisory boards from Merck, AstraZeneca, GRAIL, and Boehringer Ingelheim.

Figures

None
Graphical abstract
Figure 1
Figure 1
The potential of multi-omic liquid analytes
Figure 2
Figure 2
Applications of longitudinal multi-omic liquid biopsy (A and B) (A) Potential changes in cfDNA at different time points during cancer diagnosis and treatment including tumor-derived ctDNA (red), immune-cell-derived cfDNA (purple), and normal tissue-derived cfDNA during toxicity (green). (B) 'Omic applications that could be fulfilled by different 'omic layers at different time points.

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