{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["7(2)"],"submitter":["Zeng Y"],"pubmed_abstract":["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 methy"],"journal":["Nature cancer"],"pagination":["384-398"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12948677"],"repository":["biostudies-literature"],"pubmed_title":["A pan-cancer compendium of 1,294 plasma cell-free DNA methylomes and fragmentomes enabling multicancer detection."],"pmcid":["PMC12948677"],"pubmed_authors":["Lok BH","He HH","Ye W","Wong D","Lupien M","Stutheit-Zhao EY","Cheng N","De Carvalho DD","Bratman SV","Hoffman MM","Zadeh G","Chen K","Pugh TJ","Sanz-Garcia E","Bell E","Awadalla P","Zeng Y","Wilson SL","Znassi N","Notta F","Fang Y","Ghanekar A","Kim RH","Luo P","Abelman DD","Main SC","Mohanraj S","Singhawansa A"],"additional_accession":[]},"is_claimable":false,"name":"A pan-cancer compendium of 1,294 plasma cell-free DNA methylomes and fragmentomes enabling multicancer detection.","description":"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 methy","dates":{"release":"2026-01-01T00:00:00Z","publication":"2026 Feb","modification":"2026-07-16T23:10:03.973Z","creation":"2026-07-12T03:11:15.401Z"},"accession":"S-EPMC12948677","cross_references":{"pubmed":["41714824"],"doi":["10.1038/s43018-026-01116-3"]}}