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A pan-cancer compendium of 1,294 plasma cell-free DNA methylomes and fragmentomes enabling multicancer detection

计算生物学 DNA甲基化 生物 混淆 DNA 遗传学 稳健性(进化) 生物信息学 癌症 核小体 DNA分析 Ensembl公司 基因组 仿形(计算机编程) 计算机科学 基因组学 CpG站点 简编 癌症检测 工作流程 甲基化 猎枪 癌症生物标志物 人类基因组 核酸酶 癌细胞系 癌细胞
作者
Yong Zeng,Dor Abelman,Althaf Singhawansa,Nicholas Cheng,Yuanchang Fang,Sasha Main,Emma Bell,Wenbin Ye,Ping Luo,Samantha L. Wilson,Eric Y. Stutheit-Zhao,Derek Wong,Nadia Znassi,K. Chen,Suluxan Mohanraj,Enrique Sanz-Garcia,Faiyaz Notta,Anand Ghanekar,Philip Awadalla,Benjamin H. Lok
出处
期刊:Nature cancer [Nature Portfolio]
卷期号:7 (2): 384-398 被引量:6
标识
DOI:10.1038/s43018-026-01116-3
摘要

Cell-free DNA analysis via methylation and fragmentation profiling has advanced minimally invasive cancer detection; however, broader application has been limited by small cohorts and inconsistent data processing. Here we collated 1,074 cfMeDIP-seq profiles across 9 studies, comprising cancer samples from 11 cancer types, carriers of Li-Fraumeni syndrome and healthy controls. We developed a uniform computational workflow to mitigate technical and biological confounders across cohorts. This analysis identified 14,202 pancancer differentially methylated regions for cancer detection, along with cancer-specific markers for subtype monitoring. Fragmentomic profiling revealed distinguishing differences in 5′ end motifs, fragment lengths and nucleosome footprints across cancers. Integrating methylome and fragmentome features enhanced cancer detection and classification. Validation in 220 independent samples, including 3 cancer types absent from the primary dataset, confirmed the robustness of our findings. Altogether, this work provides a pancancer cell-free DNA resource of 1,294 samples to support future methylome and fragmentome studies. Zeng et al. analyzed cfDNA methylation and fragmentomic data from 1,294 patient plasma samples across 14 major cancer types to present a comprehensive landscape of pancancer and cancer-specific cell-free DNA methylation and fragmentomic features.
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