{"title":"癌症中的无细胞DNA片段组学","authors":"W.H. Adrian Tsui, Peiyong Jiang, Y.M. Dennis Lo","doi":"10.1016/j.ccell.2025.09.006","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":9670,"journal":{"name":"Cancer Cell","volume":"19 1","pages":""},"PeriodicalIF":44.5000,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cell-free DNA fragmentomics in cancer\",\"authors\":\"W.H. Adrian Tsui, Peiyong Jiang, Y.M. Dennis Lo\",\"doi\":\"10.1016/j.ccell.2025.09.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":9670,\"journal\":{\"name\":\"Cancer Cell\",\"volume\":\"19 1\",\"pages\":\"\"},\"PeriodicalIF\":44.5000,\"publicationDate\":\"2025-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Cell\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.ccell.2025.09.006\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Cell","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.ccell.2025.09.006","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
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.
期刊介绍:
Cancer Cell is a journal that focuses on promoting major advances in cancer research and oncology. The primary criteria for considering manuscripts are as follows:
Major advances: Manuscripts should provide significant advancements in answering important questions related to naturally occurring cancers.
Translational research: The journal welcomes translational research, which involves the application of basic scientific findings to human health and clinical practice.
Clinical investigations: Cancer Cell is interested in publishing clinical investigations that contribute to establishing new paradigms in the treatment, diagnosis, or prevention of cancers.
Insights into cancer biology: The journal values clinical investigations that provide important insights into cancer biology beyond what has been revealed by preclinical studies.
Mechanism-based proof-of-principle studies: Cancer Cell encourages the publication of mechanism-based proof-of-principle clinical studies, which demonstrate the feasibility of a specific therapeutic approach or diagnostic test.