14 June 2024

Clinical validation of a cell-free DNA fragmentome assay for augmentation of lung cancer early detection

(Cancer Discovery, IF: 29.1)

  • Peter J. Mazzone, Peter B. Bach, Jacob Carey, Caitlin A. Schonewolf, Katalin Bognar, Manmeet S. Ahluwalia, Marcia Cruz-Correa, David Gierada, Sonali Kotagiri, Kathryn Lloyd, Fabien Maldonado, Jesse D. Ortendahl, Lecia V. Sequist, Gerard A. Silvestri, Nichole Tanner, Jeffrey C. Thompson, Anil Vachani, Kwok-Kin Wong, Ali H. Zaidi, Joseph Catallini, Ariel Gershman, Keith Lumbard, Laurel K. Millberg, Jeff Nawrocki, Carter Portwood, Aakanksha Rangnekar, Carolina Campos Sheridan, Niti Trivedi, Tony Wu, Yuhua Zong, Lindsey Cotton, Allison Ryan, Christopher Cisar, Alessandro Leal, Nicholas Dracopoli, Robert B. Scharpf, Victor E. Velculescu, Luke R. G. Pike


Abstract 摘要

Lung cancer screening via annual low-dose computed tomography (LDCT) 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 an LDCT. Changes in genome-wide cell-free DNA (cfDNA) 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 then validated it in a held-out group of 382 cases and controls. The validation demonstrated high sensitivity for lung cancer, and consistency across demographic groups and comorbid conditions. Applying test performance to the screening eligible population in a five-year model with modest utilization assumptions suggested the potential to prevent thousands of lung cancer deaths.