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J Clin Invest. 2018 Jan 2;128(1):427-445. doi: 10.1172/JCI93801. Epub 2017 Dec 11.

Drug-perturbation-based stratification of blood cancer.

Author information

1
European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
2
Department of Medicine V, University Hospital Heidelberg, Heidelberg, Germany.
3
Molecular Therapy in Hematology and Oncology, and Department of Translational Oncology, National Center for Tumor Diseases and German Cancer Research Centre, Heidelberg, Germany.
4
Molecular Medicine Partnership Unit (MMPU), Heidelberg, Germany.
5
Cellzome, Heidelberg, Germany.
6
Division of Hematology, Departments of Internal Medicine and Biomedical Informatics, The Ohio State University, Columbus, Ohio, USA.
7
Division of Epigenomics and Cancer Risk Factors, German Cancer Research Centre, Heidelberg, Germany.
8
Division of Biostatistics, German Cancer Research Centre, Heidelberg, Germany.
9
Institute of Human Genetics, University of Heidelberg, Heidelberg, Germany.
10
Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.
11
European Molecular Biology Laboratory (EMBL), Chemical Biology Core Facility, Heidelberg, Germany.
12
Department of Translational Medicine, Amedeo Avogadro University of Eastern Piedmont, Novara, Italy; Division of Hematology, Oncology Institute of Southern Switzerland, Bellinzona, Switzerland.
13
Friedrich-Alexander-University of Erlangen-Nürnberg, Department of Chemistry and Pharmacy, Organic Chemistry II, Erlangen, Germany.
14
Hematology/Oncology, Department of Medicine, Johann Wolfgang Goethe University, Frankfurt, Germany; Department of Haematology, Cambridge Institute of Medical Research, University of Cambridge, Cambridge, United Kingdom.
15
German Consortium for Translational Cancer Research (DKTK), Heidelberg, Germany.
16
Department of Hematology/Oncology, University Hospital Freiburg, Freiburg, Germany and Tumorzentrum ZeTuP Chur, Chur, Schweiz.
17
Department of Internal Medicine I, University Hospital Cologne, Cologne, Germany.
18
INSERM U1138, Université Pierre et Marie Curie-Paris and Service d'Hématologie Biologique, Hôpital Pitié-Salpêtrière, Paris, France.
19
Hematology Research Unit Helsinki, University of Helsinki, Helsinki, Finland and Department of Hematology, Comprehensive Cancer Centre, Helsinki University Hospital, Helsinki, Finland.
20
Heidelberg Centre for Personalized Oncology, DKFZ-HIPO, DKFZ, Heidelberg, Germany.
21
Mannheim Oncology Practice, Mannheim, Germany.
22
Department of Hematology, University Hospital Essen, Essen, Germany.
23
Department of Hematology, University of Cambridge, Cambridge, United Kingdom.
24
Division of Molecular Genetics, German Cancer Research Centre, Heidelberg, Germany.
25
Department of Hematology, University of Zürich, Zürich, Switzerland.

Abstract

As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non-BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.

KEYWORDS:

B cell receptor; Drug screens; Hematology; Leukemias; Oncology

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