Multiomic analysis identifies a high-risk signature that predicts early clinical failure in DLBCL

Multiomic analysis identifies a high-risk signature that predicts early clinical failure in DLBCL

Abstract Recent genetic and molecular classification of DLBCL has advanced our knowledge of disease biology, yet were not designed to predict early events and guide anticipatory selection of novel therapies. To address this unmet need, we used an integrative multiomic approach to identify a signatur...

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Bibliographic Details
Main Authors: Kerstin Wenzl, Matthew E. Stokes, Joseph P. Novak, Allison M. Bock, Sana Khan, Melissa A. Hopper, Jordan E. Krull, Abigail R. Dropik, Janek S. Walker, Vivekananda Sarangi, Raphael Mwangi, Maria Ortiz, Nicholas Stong, C. Chris Huang, Matthew J. Maurer, Lisa Rimsza, Brian K. Link, Susan L. Slager, Yan Asmann, Patrizia Mondello, Ryan Morin, Stephen M. Ansell, Thomas M. Habermann, Thomas E. Witzig, Andrew L. Feldman, Rebecca L. King, Grzegorz Nowakowski, James R. Cerhan, Anita K. Gandhi, Anne J. Novak
Format: Article
Language:English
Published: Nature Publishing Group 2024-06-01
Series:Blood Cancer Journal
Online Access:https://doi.org/10.1038/s41408-024-01080-0

Internet

https://doi.org/10.1038/s41408-024-01080-0

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