Journal article
Multiomic analysis identifies a high-risk signature that predicts early clinical failure in DLBCL
Blood cancer journal (New York), Vol.14(1), 100
06/20/2024
DOI: 10.1038/s41408-024-01080-0
PMCID: PMC11189905
PMID: 38902256
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 signature at diagnosis that will identify DLBCL at high risk of early clinical failure. Tumor biopsies from 444 newly diagnosed DLBCL were analyzed by WES and RNAseq. A combination of weighted gene correlation network analysis and differential gene expression analysis was used to identify a signature associated with high risk of early clinical failure independent of IPI and COO. Further analysis revealed the signature was associated with metabolic reprogramming and identified cases with a depleted immune microenvironment. Finally, WES data was integrated into the signature and we found that inclusion of
ARID1A
mutations resulted in identification of 45% of cases with an early clinical failure which was validated in external DLBCL cohorts. This novel and integrative approach is the first to identify a signature at diagnosis, in a real-world cohort of DLBCL, that identifies patients at high risk for early clinical failure and may have significant implications for design of therapeutic options.
Details
- Title: Subtitle
- Multiomic analysis identifies a high-risk signature that predicts early clinical failure in DLBCL
- Creators
- Kerstin Wenzl - Mayo Clinic in ArizonaMatthew E. Stokes - Bristol-Myers SquibbJoseph P. Novak - Mayo Clinic in ArizonaAllison M. Bock - Mayo Clinic in ArizonaSana Khan - Mayo ClinicMelissa A. Hopper - Mayo Clinic in ArizonaJordan E. Krull - Mayo Clinic in ArizonaAbigail R. Dropik - Mayo Clinic in ArizonaJanek S. Walker - Mayo Clinic in ArizonaVivekananda Sarangi - Mayo Clinic in FloridaRaphael Mwangi - Mayo Clinic in FloridaMaria Ortiz - Informatics and Predictive Sciences, Celgene Institute for Translational Research Europe (CITRE), Seville, SpainNicholas Stong - Bristol-Myers SquibbC. Chris Huang - Bristol-Myers SquibbMatthew J. Maurer - Mayo ClinicLisa Rimsza - Mayo Clinic in ArizonaBrian K. Link - University of IowaSusan L. Slager - Mayo Clinic in FloridaRyan Morin - BC Cancer AgencyYan Asmann - Mayo Clinic in FloridaStephen M. Ansell - Mayo Clinic in ArizonaPatrizia Mondello - Mayo Clinic in ArizonaThomas M. Habermann - Mayo Clinic in ArizonaThomas E. Witzig - Mayo Clinic in ArizonaAndrew L. Feldman - Mayo Clinic in ArizonaRebecca L. King - Mayo Clinic in ArizonaGrzegorz Nowakowski - Mayo Clinic in ArizonaJames R. Cerhan - Mayo Clinic in FloridaAnita K. Gandhi - Bristol-Myers SquibbAnne J. Novak - Mayo Clinic in Arizona
- Resource Type
- Journal article
- Publication Details
- Blood cancer journal (New York), Vol.14(1), 100
- Publisher
- Nature Publishing Group UK
- DOI
- 10.1038/s41408-024-01080-0
- PMID
- 38902256
- PMCID
- PMC11189905
- ISSN
- 2044-5385
- eISSN
- 2044-5385
- Language
- English
- Date published
- 06/20/2024
- Academic Unit
- Hematology, Oncology, and Blood & Marrow Transplantation; Epidemiology; Internal Medicine
- Record Identifier
- 9984648572602771
Metrics
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