表观遗传学
DNA
癌细胞
生物
癌症
计算生物学
转录组
Boosting(机器学习)
癌症研究
生物信息学
后生
DNA测序
基因组不稳定性
计算机科学
基因组学
5-羟甲基胞嘧啶
临床试验
作者
WY Tsui,Peiyong Jiang,Yuk Ming Dennis Lo
出处
期刊:Cancer Cell
[Cell Press]
日期:2025-10-01
卷期号:43 (10): 1792-1814
被引量:33
标识
DOI:10.1016/j.ccell.2025.09.006
摘要
The analysis of cell-free DNA (cfDNA) fragmentation patterns, known as “fragmentomics,” has opened new opportunities in noninvasive cancer diagnostics. Due to its close relationships with genomic organization and cell death, cfDNA fragmentomics lies at the intersection of many aspects of cancer biology, including epigenetic dysregulation, transcriptomic alterations, and aberrant cellular turnover patterns. Recent advances in library preparation, sequencing technologies, and integrative epigenomic-fragmentomic analyses have uncovered novel fragmentomic features that reveal specific cellular dysfunctions in cancer. Additionally, cutting-edge artificial intelligence algorithms now harness high-dimensional fragmentomic features, boosting the precision and power of cancer detection. Promising results from recent clinical trials evaluating the utility of fragmentomic analyses in real-world settings support its potential. In this review, we explore the exciting frontiers of cfDNA fragmentomics, discuss critical unanswered questions, and highlight future directions to unlock the promise of fragmentomics-based liquid biopsies in cancer care. The analysis of cell-free DNA (cfDNA) fragmentation patterns, known as “fragmentomics,” has opened new opportunities in noninvasive cancer diagnostics. In this Review, Tsui et al. explore the exciting frontiers of cfDNA fragmentomics, discuss critical unanswered questions, and highlight future directions to unlock the promise of fragmentomics-based liquid biopsies in cancer care.
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