TY - JOUR T1 - Proteogenomics refines the molecular classification of chronic lymphocytic leukemia JF - bioRxiv DO - 10.1101/2022.03.01.481539 SP - 2022.03.01.481539 AU - Sophie A. Herbst AU - Mattias Vesterlund AU - Alexander J. Helmboldt AU - Rozbeh Jafari AU - Ioannis Siavelis AU - Matthias Stahl AU - Eva C. Schitter AU - Nora Liebers AU - Berit J. Brinkmann AU - Felix Czernilofsky AU - Tobias Roider AU - Peter-Martin Bruch AU - Murat Iskar AU - Adam Kittai AU - Ying Huang AU - Junyan Lu AU - Sarah Richter AU - Georgios Mermelekas AU - Husen Muhammad Umer AU - Mareike Knoll AU - Carolin Kolb AU - Angela Lenze AU - Xiaofang Cao AU - Cecilia Österholm AU - Linus Wahnschaffe AU - Carmen Herling AU - Sebastian Scheinost AU - Matthias Ganzinger AU - Larry Mansouri AU - Katharina Kriegsmann AU - Mark Kriegsmann AU - Simon Anders AU - Marc Zapatka AU - Giovanni Del Poeta AU - Antonella Zucchetto AU - Riccardo Bomben AU - Valter Gattei AU - Peter Dreger AU - Jennifer Woyach AU - Marco Herling AU - Carsten Müller-Tidow AU - Richard Rosenquist AU - Stephan Stilgenbauer AU - Thorsten Zenz AU - Wolfgang Huber AU - Eugen Tausch AU - Janne Lehtiö AU - Sascha Dietrich Y1 - 2022/01/01 UR - http://biorxiv.org/content/early/2022/03/07/2022.03.01.481539.abstract N2 - 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 characterized the proteome and transcriptome in-depth alongside genetic and ex-vivo drug response profiling in a clinically well annotated CLL discovery cohort (n= 68). Unsupervised clustering of the proteome data revealed six subgroups. Five of these proteomic groups were associated with genetic features, while one group was only detectable at the proteome level. This new group was characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). We developed classifiers to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n= 165, n= 169) and confirmed that ASB-CLL comprises about 20 % of CLL patients. The inferior overall survival observed in ASB-CLL was 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.Single sentence summary We performed the largest proteogenomic analysis of CLL, linked proteomic profiles to clinical outcomes, and discovered a new poor outcome subgroup (ASB-CLL).Competing Interest StatementThe authors have declared no competing interest. ER -