{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Mazzone PJ"],"funding":["Stand Up To Cancer","Dr. Miriam and Sheldon G. Adelson Medical Research Foundation","Honorable Tina Brozman Foundation (Tina's Wish)","Commonwealth Foundation (CF)","Stand Up To Cancer (SU2C)","Dr. Miriam and Sheldon G. Adelson Medical Research Foundation (AMRF)","NCI NIH HHS","Cole Foundation","Gray Foundation","Commonwealth Foundation","Cole Foundation (CF)","Honorable Tina Brozman Foundation"],"pagination":["2224-2242"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11528203"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["14(11)"],"pubmed_abstract":["Lung cancer screening via annual low-dose computed tomography has poor adoption. We conducted a prospective case-control study among 958 individuals eligible for lung cancer screening to develop a blood-based lung cancer detection test that when positive is followed by a low-dose computed tomography. Changes in genome-wide cell-free DNA fragmentation profiles (fragmentomes) in peripheral blood reflected genomic and chromatin characteristics of lung cancer. We applied machine learning to fragmentome features to identify individuals who were more or less likely to have lung cancer. We trained the classifier using 576 cases and controls from study samples and validated it in a held-out group of 382 cases and controls. The validation demonstrated high sensitivity for lung cancer and consistenc"],"journal":["Cancer discovery"],"pubmed_title":["Clinical Validation of a Cell-Free DNA Fragmentome Assay for Augmentation of Lung Cancer Early Detection."],"pmcid":["PMC11528203"],"funding_grant_id":["P30 CA006973","UG1 CA233259","R01 CA121113","P30 CA008748","P50 CA062924","U01 CA271896"],"pubmed_authors":["Schonewolf CA","Silvestri GA","Nawrocki J","Kotagiri S","Lumbard K","Sheridan CC","Leal A","Bach PB","Gierada D","Wong KK","Scharpf RB","Velculescu VE","Bognar K","Sequist LV","Millberg LK","Pike LRG","Vachani A","Mazzone PJ","Wu T","Cotton L","Zaidi AH","Gershman A","Zong Y","Maldonado F","Portwood C","Catallini J","Ortendahl JD","Carey J","Trivedi N","Rangnekar A","Ryan A","Cisar C","Ahluwalia MS","Thompson JC","Tanner N","Cruz-Correa M","Lloyd K","Dracopoli N"],"additional_accession":[]},"is_claimable":false,"name":"Clinical Validation of a Cell-Free DNA Fragmentome Assay for Augmentation of Lung Cancer Early Detection.","description":"Lung cancer screening via annual low-dose computed tomography has poor adoption. We conducted a prospective case-control study among 958 individuals eligible for lung cancer screening to develop a blood-based lung cancer detection test that when positive is followed by a low-dose computed tomography. Changes in genome-wide cell-free DNA fragmentation profiles (fragmentomes) in peripheral blood reflected genomic and chromatin characteristics of lung cancer. We applied machine learning to fragmentome features to identify individuals who were more or less likely to have lung cancer. We trained the classifier using 576 cases and controls from study samples and validated it in a held-out group of 382 cases and controls. The validation demonstrated high sensitivity for lung cancer and consistenc","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Nov","modification":"2026-07-16T03:05:04.953Z","creation":"2025-04-04T00:29:43.393Z"},"accession":"S-EPMC11528203","cross_references":{"pubmed":["38829053"],"doi":["10.1158/2159-8290.CD-24-0519"]}}