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

Johannes Bloehdorn,Hartmut Döhner,Christof Schneider,Gulnara Akylzhanova,Olivier Elemento,Catherine J Wu,Michael Hallek,Billy Michael Chelliah Jebaraj,Donna Neuberg ,Matthew Carter ,John G Gribben ,Sandra Robrecht,Mark S Cragg,Lars Bullinger,Kirsten Fischer,Harvey E Johnston,Julia Krzykalla,Tetyana Klymenko,Barbara Eichhorst,Axel Benner,Eugen Tausch,Tadeusz Robak,Adam Giza,Stephan Stilgenbauer,Heng Pan,Martin Weisser,Lekh N Dahal,Karlheinz Holzmann,Ru-Fang Yeh,Andrejs Braun,Dan A Landau,Annika Scheffold,Amaro Taylor-Weiner,Daniel Mertens

doi:10.1038/s41467-021-25403-y

Abstract

Knowledge of the genomic landscape of chronic lymphocytic leukemia (CLL) grows increasingly detailed, providing challenges in contextualizing the accumulated information. To define the underlying networks, we here perform a multi-platform molecular characterization. We identify major subgroups characterized by genomic instability (GI) or activation of epithelial-mesenchymal-transition (EMT)-like programs, which subdivide into non-inflammatory and inflammatory subtypes. GI CLL exhibit disruption of genome integrity, DNA-damage response and are associated with mutagenesis mediated through activation-induced cytidine deaminase or defective mismatch repair. TP53 wild-type and mutated/deleted cases constitute a transcriptionally uniform entity in GI CLL and show similarly poor progression-free survival at relapse. EMT-like CLL exhibit high genomic stability, reduced benefit from the addition of rituximab and EMT-like differentiation is inhibited by induction of DNA damage. This work extends the perspective on CLL biology and risk categories in TP53 wild-type CLL. Furthermore, molecular targets identified within each subgroup provide opportunities for new treatment approaches.

Highlights

Knowledge of the genomic landscape of chronic lymphocytic leukemia (CLL) grows increasingly detailed, providing challenges in contextualizing the accumulated information
To explore tumor heterogeneity in CLL, we performed consensus clustering (CC) on CLL8 gene expression profiles (GEP) data (n = 337, Supplementary Table 1) using 2359 variably expressed genes corresponding to a standard deviation (SD) of >0.5
We considered if the error rate through defective DNA repair in genomic instability (GI) might be exacerbated in situations of increased AID activity

Summary

Introduction

Knowledge of the genomic landscape of chronic lymphocytic leukemia (CLL) grows increasingly detailed, providing challenges in contextualizing the accumulated information. We aim to delineate refined biological categories of CLL and identify cooperating pathogenic mechanisms which facilitate distinct pathways or microenvironmental interaction during disease development and evolution. We address this by performing a comprehensive characterization incorporating gene expression profiles (GEP) from two independent phases III CLL trial cohorts comprising 726 treatment-naive and relapsed patient samples. Discovered biologic subgroups are validated in the independent sample set of relapsed patients enrolled onto the REACH trial[16] and confirmed in vivo using relevant genetically modified mouse models Both the CLL8 and REACH trials were conducted as independent pivotal phase III multicenter trials to evaluate treatment with immunochemotherapy[15,16]. They, provide an ideal basis for the correlation of biological characteristics and treatment outcome

Objectives

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Conclusion