Proteogenomics refines the molecular classification of chronic lymphocytic leukemia

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 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 () and Sascha Dietrich ()
Additional contact information
Sophie A. Herbst: University of Heidelberg
Mattias Vesterlund: Karolinska Institute and Science for Life Laboratory
Alexander J. Helmboldt: European Molecular Biology Laboratory (EMBL)
Rozbeh Jafari: Karolinska Institute and Science for Life Laboratory
Ioannis Siavelis: Karolinska Institute and Science for Life Laboratory
Matthias Stahl: Karolinska Institute and Science for Life Laboratory
Eva C. Schitter: University of Heidelberg
Nora Liebers: University of Heidelberg
Berit J. Brinkmann: University of Heidelberg
Felix Czernilofsky: University of Heidelberg
Tobias Roider: University of Heidelberg
Peter-Martin Bruch: University of Heidelberg
Murat Iskar: German Cancer Research Center (DKFZ)
Adam Kittai: The Ohio State University
Ying Huang: The Ohio State University
Junyan Lu: European Molecular Biology Laboratory (EMBL)
Sarah Richter: University of Heidelberg
Georgios Mermelekas: Karolinska Institute and Science for Life Laboratory
Husen Muhammad Umer: Karolinska Institute and Science for Life Laboratory
Mareike Knoll: University of Heidelberg
Carolin Kolb: University of Heidelberg
Angela Lenze: University of Heidelberg
Xiaofang Cao: Karolinska Institute and Science for Life Laboratory
Cecilia Österholm: Karolinska Institutet
Linus Wahnschaffe: University of Cologne
Carmen Herling: University of Cologne
Sebastian Scheinost: National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ)
Matthias Ganzinger: Heidelberg University
Larry Mansouri: Karolinska Institutet
Katharina Kriegsmann: University of Heidelberg
Mark Kriegsmann: University of Heidelberg
Simon Anders: Center for Molecular Biology of the University of Heidelberg (ZMBH)
Marc Zapatka: German Cancer Research Center (DKFZ)
Giovanni Poeta: University of Tor Vergata
Antonella Zucchetto: Clinical and Experimental Onco-Hematology Unit, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS
Riccardo Bomben: Clinical and Experimental Onco-Hematology Unit, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS
Valter Gattei: Clinical and Experimental Onco-Hematology Unit, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS
Peter Dreger: University of Heidelberg
Jennifer Woyach: The Ohio State University
Marco Herling: University of Cologne
Carsten Müller-Tidow: University of Heidelberg
Richard Rosenquist: Karolinska Institutet
Stephan Stilgenbauer: University of Ulm
Thorsten Zenz: National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ)
Wolfgang Huber: European Molecular Biology Laboratory (EMBL)
Eugen Tausch: University of Ulm
Janne Lehtiö: Karolinska Institute and Science for Life Laboratory
Sascha Dietrich: University of Heidelberg

Nature Communications, 2022, vol. 13, issue 1, 1-18

Abstract: Abstract 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.

Date: 2022
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DOI: 10.1038/s41467-022-33385-8

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