Multi-platform profiling characterizes molecular subgroups and resistance networks in chronic lymphocytic leukemia

Multi-platform profiling characterizes molecular subgroups and resistance networks in chronic lymphocytic leukemia

Chronic lymphocytic leukemia has been studied using multiple levels of omics data. Here, the authors use exome sequencing, SNP, protein and gene expression data to identify distinct biologic tumor subtypes with heterogeneous prognostic impact after chemo- or immunochemotherapy.

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Detalles Bibliográficos
Autores principales: Johannes Bloehdorn, Andrejs Braun, Amaro Taylor-Weiner, Billy Michael Chelliah Jebaraj, Sandra Robrecht, Julia Krzykalla, Heng Pan, Adam Giza, Gulnara Akylzhanova, Karlheinz Holzmann, Annika Scheffold, Harvey E. Johnston, Ru-Fang Yeh, Tetyana Klymenko, Eugen Tausch, Barbara Eichhorst, Lars Bullinger, Kirsten Fischer, Martin Weisser, Tadeusz Robak, Christof Schneider, John Gribben, Lekh N. Dahal, Mathew J. Carter, Olivier Elemento, Dan A. Landau, Donna S. Neuberg, Mark S. Cragg, Axel Benner, Michael Hallek, Catherine J. Wu, Hartmut Döhner, Stephan Stilgenbauer, Daniel Mertens
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Science
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Acceso en línea:https://doaj.org/article/fc98052a777c445bb5de9e2a3b17c607
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Sumario:Chronic lymphocytic leukemia has been studied using multiple levels of omics data. Here, the authors use exome sequencing, SNP, protein and gene expression data to identify distinct biologic tumor subtypes with heterogeneous prognostic impact after chemo- or immunochemotherapy.

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