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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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Autores principales: Herbst, Sophie A., Vesterlund, Mattias, Helmboldt, Alexander J., Jafari, Rozbeh, Siavelis, Ioannis, Stahl, Matthias, Schitter, Eva C., Liebers, Nora, Brinkmann, Berit J., Czernilofsky, Felix, Roider, Tobias, Bruch, Peter-Martin, Iskar, Murat, Kittai, Adam, Huang, Ying, Lu, Junyan, Richter, Sarah, Mermelekas, Georgios, Umer, Husen Muhammad, Knoll, Mareike, Kolb, Carolin, Lenze, Angela, Cao, Xiaofang, Österholm, Cecilia, Wahnschaffe, Linus, Herling, Carmen, Scheinost, Sebastian, Ganzinger, Matthias, Mansouri, Larry, Kriegsmann, Katharina, Kriegsmann, Mark, Anders, Simon, Zapatka, Marc, Del Poeta, Giovanni, Zucchetto, Antonella, Bomben, Riccardo, Gattei, Valter, Dreger, Peter, Woyach, Jennifer, Herling, Marco, Müller-Tidow, Carsten, Rosenquist, Richard, Stilgenbauer, Stephan, Zenz, Thorsten, Huber, Wolfgang, Tausch, Eugen, Lehtiö, Janne, Dietrich, Sascha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9584885/
https://www.ncbi.nlm.nih.gov/pubmed/36266272
http://dx.doi.org/10.1038/s41467-022-33385-8
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author Herbst, Sophie A.
Vesterlund, Mattias
Helmboldt, Alexander J.
Jafari, Rozbeh
Siavelis, Ioannis
Stahl, Matthias
Schitter, Eva C.
Liebers, Nora
Brinkmann, Berit J.
Czernilofsky, Felix
Roider, Tobias
Bruch, Peter-Martin
Iskar, Murat
Kittai, Adam
Huang, Ying
Lu, Junyan
Richter, Sarah
Mermelekas, Georgios
Umer, Husen Muhammad
Knoll, Mareike
Kolb, Carolin
Lenze, Angela
Cao, Xiaofang
Österholm, Cecilia
Wahnschaffe, Linus
Herling, Carmen
Scheinost, Sebastian
Ganzinger, Matthias
Mansouri, Larry
Kriegsmann, Katharina
Kriegsmann, Mark
Anders, Simon
Zapatka, Marc
Del Poeta, Giovanni
Zucchetto, Antonella
Bomben, Riccardo
Gattei, Valter
Dreger, Peter
Woyach, Jennifer
Herling, Marco
Müller-Tidow, Carsten
Rosenquist, Richard
Stilgenbauer, Stephan
Zenz, Thorsten
Huber, Wolfgang
Tausch, Eugen
Lehtiö, Janne
Dietrich, Sascha
author_facet Herbst, Sophie A.
Vesterlund, Mattias
Helmboldt, Alexander J.
Jafari, Rozbeh
Siavelis, Ioannis
Stahl, Matthias
Schitter, Eva C.
Liebers, Nora
Brinkmann, Berit J.
Czernilofsky, Felix
Roider, Tobias
Bruch, Peter-Martin
Iskar, Murat
Kittai, Adam
Huang, Ying
Lu, Junyan
Richter, Sarah
Mermelekas, Georgios
Umer, Husen Muhammad
Knoll, Mareike
Kolb, Carolin
Lenze, Angela
Cao, Xiaofang
Österholm, Cecilia
Wahnschaffe, Linus
Herling, Carmen
Scheinost, Sebastian
Ganzinger, Matthias
Mansouri, Larry
Kriegsmann, Katharina
Kriegsmann, Mark
Anders, Simon
Zapatka, Marc
Del Poeta, Giovanni
Zucchetto, Antonella
Bomben, Riccardo
Gattei, Valter
Dreger, Peter
Woyach, Jennifer
Herling, Marco
Müller-Tidow, Carsten
Rosenquist, Richard
Stilgenbauer, Stephan
Zenz, Thorsten
Huber, Wolfgang
Tausch, Eugen
Lehtiö, Janne
Dietrich, Sascha
author_sort Herbst, Sophie A.
collection PubMed
description 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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spelling pubmed-95848852022-10-22 Proteogenomics refines the molecular classification of chronic lymphocytic leukemia Herbst, Sophie A. Vesterlund, Mattias Helmboldt, Alexander J. Jafari, Rozbeh Siavelis, Ioannis Stahl, Matthias Schitter, Eva C. Liebers, Nora Brinkmann, Berit J. Czernilofsky, Felix Roider, Tobias Bruch, Peter-Martin Iskar, Murat Kittai, Adam Huang, Ying Lu, Junyan Richter, Sarah Mermelekas, Georgios Umer, Husen Muhammad Knoll, Mareike Kolb, Carolin Lenze, Angela Cao, Xiaofang Österholm, Cecilia Wahnschaffe, Linus Herling, Carmen Scheinost, Sebastian Ganzinger, Matthias Mansouri, Larry Kriegsmann, Katharina Kriegsmann, Mark Anders, Simon Zapatka, Marc Del Poeta, Giovanni Zucchetto, Antonella Bomben, Riccardo Gattei, Valter Dreger, Peter Woyach, Jennifer Herling, Marco Müller-Tidow, Carsten Rosenquist, Richard Stilgenbauer, Stephan Zenz, Thorsten Huber, Wolfgang Tausch, Eugen Lehtiö, Janne Dietrich, Sascha Nat Commun Article 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. Nature Publishing Group UK 2022-10-20 /pmc/articles/PMC9584885/ /pubmed/36266272 http://dx.doi.org/10.1038/s41467-022-33385-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Herbst, Sophie A.
Vesterlund, Mattias
Helmboldt, Alexander J.
Jafari, Rozbeh
Siavelis, Ioannis
Stahl, Matthias
Schitter, Eva C.
Liebers, Nora
Brinkmann, Berit J.
Czernilofsky, Felix
Roider, Tobias
Bruch, Peter-Martin
Iskar, Murat
Kittai, Adam
Huang, Ying
Lu, Junyan
Richter, Sarah
Mermelekas, Georgios
Umer, Husen Muhammad
Knoll, Mareike
Kolb, Carolin
Lenze, Angela
Cao, Xiaofang
Österholm, Cecilia
Wahnschaffe, Linus
Herling, Carmen
Scheinost, Sebastian
Ganzinger, Matthias
Mansouri, Larry
Kriegsmann, Katharina
Kriegsmann, Mark
Anders, Simon
Zapatka, Marc
Del Poeta, Giovanni
Zucchetto, Antonella
Bomben, Riccardo
Gattei, Valter
Dreger, Peter
Woyach, Jennifer
Herling, Marco
Müller-Tidow, Carsten
Rosenquist, Richard
Stilgenbauer, Stephan
Zenz, Thorsten
Huber, Wolfgang
Tausch, Eugen
Lehtiö, Janne
Dietrich, Sascha
Proteogenomics refines the molecular classification of chronic lymphocytic leukemia
title Proteogenomics refines the molecular classification of chronic lymphocytic leukemia
title_full Proteogenomics refines the molecular classification of chronic lymphocytic leukemia
title_fullStr Proteogenomics refines the molecular classification of chronic lymphocytic leukemia
title_full_unstemmed Proteogenomics refines the molecular classification of chronic lymphocytic leukemia
title_short Proteogenomics refines the molecular classification of chronic lymphocytic leukemia
title_sort proteogenomics refines the molecular classification of chronic lymphocytic leukemia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9584885/
https://www.ncbi.nlm.nih.gov/pubmed/36266272
http://dx.doi.org/10.1038/s41467-022-33385-8
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