Proteogenomics refines the molecular classification of chronic lymphocytic leukemia
Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer ent...
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
20 October 2022
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| In: |
Nature Communications
Year: 2022, Volume: 13, Pages: 1-18 |
| ISSN: | 2041-1723 |
| DOI: | 10.1038/s41467-022-33385-8 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1038/s41467-022-33385-8 Verlag, kostenfrei, Volltext: https://www.nature.com/articles/s41467-022-33385-8 
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| Author Notes: | Sophie A. Herbst, Mattias Vesterlund, Alexander J. Helmboldt, Rozbeh Jafari, Ioannis Siavelis, Matthias Stahl, Eva C. Schitter, Nora Liebers, Berit J. Brinkmann, Felix Czernilofsky, Tobias Roider, Peter-Martin Bruch, Murat Iskar, Adam Kittai, Ying Huang, Junyan Lu, Sarah Richter, Georgios Mermelekas, Husen Muhammad Umer, Mareike Knoll, Carolin Kolb, Angela Lenze, Xiaofang Cao, Cecilia Österholm, Linus Wahnschaffe, Carmen Herling, Sebastian Scheinost, Matthias Ganzinger, Larry Mansouri, Katharina Kriegsmann, Mark Kriegsmann, Simon Anders, Marc Zapatka, Giovanni Del Poeta, Antonella Zucchetto, Riccardo Bomben, Valter Gattei, Peter Dreger, Jennifer Woyach, Marco Herling, Carsten Müller-Tidow, Richard Rosenquist, Stephan Stilgenbauer, Thorsten Zenz, Wolfgang Huber, Eugen Tausch, Janne Lehtiö, Sascha Dietrich |
MARC
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| 245 | 1 | 0 | |a Proteogenomics refines the molecular classification of chronic lymphocytic leukemia |c Sophie A. Herbst, Mattias Vesterlund, Alexander J. Helmboldt, Rozbeh Jafari, Ioannis Siavelis, Matthias Stahl, Eva C. Schitter, Nora Liebers, Berit J. Brinkmann, Felix Czernilofsky, Tobias Roider, Peter-Martin Bruch, Murat Iskar, Adam Kittai, Ying Huang, Junyan Lu, Sarah Richter, Georgios Mermelekas, Husen Muhammad Umer, Mareike Knoll, Carolin Kolb, Angela Lenze, Xiaofang Cao, Cecilia Österholm, Linus Wahnschaffe, Carmen Herling, Sebastian Scheinost, Matthias Ganzinger, Larry Mansouri, Katharina Kriegsmann, Mark Kriegsmann, Simon Anders, Marc Zapatka, Giovanni Del Poeta, Antonella Zucchetto, Riccardo Bomben, Valter Gattei, Peter Dreger, Jennifer Woyach, Marco Herling, Carsten Müller-Tidow, Richard Rosenquist, Stephan Stilgenbauer, Thorsten Zenz, Wolfgang Huber, Eugen Tausch, Janne Lehtiö, Sascha Dietrich |
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| 520 | |a Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68). Unsupervised clustering of the proteome data reveals six subgroups. Five of these proteomic groups are associated with genetic features, while one group is only detectable at the proteome level. This new group is characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). Classifiers developed to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n = 165, n = 169) confirm that ASB-CLL comprises about 20% of CLL patients. The inferior overall survival in ASB-CLL is also independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling. | ||
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