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.
Sascha Dietrich, Małgorzata Oleś, Junyan Lu, Leopold Sellner, Simon Anders, Britta Velten, Bian Wu, Jennifer Hüllein, Michelle da Silva Liberio, Tatjana Walther, Lena Wagner, Sophie Rabe, Sonja Ghidelli-Disse, Marcus Bantscheff, Andrzej K. Oleś, Mikołaj Słabicki, Andreas Mock, Christopher C. Oakes, Shihui Wang, Sina Oppermann, Marina Lukas, Vladislav Kim, Martin Sill, Axel Benner, Anna Jauch, Lesley Ann Sutton, Emma Young, Richard Rosenquist, Xiyang Liu, Alexander Jethwa, Kwang Seok Lee, Joe Lewis, Kerstin Putzker, Christoph Lutz, Davide Rossi, Andriy Mokhir, Thomas Oellerich, Katja Zirlik, Marco Herling, Florence Nguyen-Khac, Christoph Plass, Emma Andersson, Satu Mustjoki, Christof von Kalle, Anthony D. Ho, Manfred Hensel, Jan Dürig, Ingo Ringshausen, Marc Zapatka, Wolfgang Huber, Thorsten Zenz
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Longitudinal omics data and preclinical treatment identify proteasome inhibition as therapy for ibrutinib-resistant CLL
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Adapted to Survive: Targeting Cancer Cells with BH3 Mimetics
Montero J, Haq R |
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Deep Morphology Learning Enhances Ex Vivo Drug Profiling-Based Precision Medicine
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Influence of cryopreservation on drug responses and gene expression of AML cells: Implications for the use of biobanked tissues
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British Journal of Haematology | 2022 |
Longitudinal analyses of CLL in mice identify leukemia-related clonal changes including a Myc gain predicting poor outcome in patients
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Journal of Translational Medicine | 2021 |
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Ex Vivo Analysis of Primary Tumor Specimens for Evaluation of Cancer Therapeutics
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Ex vivo drug screening defines novel drug sensitivity patterns for informing personalized therapy in myeloid neoplasms
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Chronic lymphocytic leukemias with trisomy 12 show a distinct DNA methylation profile linked to altered chromatin activation
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Genetics of “high-risk” chronic lymphocytic leukemia in the times of chemoimmunotherapy
A Ring, T Zenz |
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The proliferative history shapes the DNA methylome of B-cell tumors and predicts clinical outcome
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Energy metabolism is co-determined by genetic variants in chronic lymphocytic leukemia and influences drug sensitivity
J Lu, M Böttcher, T Walther, D Mougiakakos, T Zenz, W Huber |
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Novel CHK1 inhibitor MU380 exhibits significant single-agent activity in TP53-mutated chronic lymphocytic leukemia cells
M Boudny, J Zemanova, P Khirsariya, M Borsky, J Verner, J Cerna, A Oltova, V Seda, M Mraz, J Jaros, Z Jaskova, M Spunarova, Y Brychtova, K Soucek, S Drapela, M Kasparkova, J Mayer, K Paruch, M Trbusek |
Haematologica | 2019 |
Targeting chronic lymphocytic leukemia with N-methylated thrombospondin-1–derived peptides overcomes drug resistance
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Combined chemosensitivity and chromatin profiling prioritizes drug combinations in CLL
C Schmidl, GI Vladimer, AF Rendeiro, S Schnabl, T Krausgruber, C Taubert, N Krall, T Pemovska, M Araghi, B Snijder, R Hubmann, A Ringler, K Runggatscher, D Demirtas, OL de la Fuente, M Hilgarth, C Skrabs, E Porpaczy, M Gruber, G Hoermann, S Kubicek, PB Staber, M Shehata, G Superti-Furga, U Jäger, C Bock |
Nature Chemical Biology | 2019 |
JAK/STAT-Activating Genomic Alterations Are a Hallmark of T-PLL
L Wahnschaffe, T Braun, S Timonen, AK Giri, A Schrader, P Wagle, H Almusa, P Johansson, D Bellanger, C López, C Haferlach, MH Stern, J Dürig, R Siebert, S Mustjoki, T Aittokallio, M Herling |
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The dawn of a new era in treating T-PLL
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Developmental subtypes assessed by DNA methylation-iPLEX forecast the natural history of chronic lymphocytic leukemia
B Giacopelli, Q Zhao, AS Ruppert, A Agyeman, C Weigel, YZ Wu, MM Gerber, KG Rabe, MC Larson, J Lu, JS Blachly, KA Rogers, WG Wierda, JR Brown, KR Rai, M Keating, LZ Rassenti, TJ Kipps, T Zenz, TD Shanafelt, NE Kay, LV Abruzzo, KR Coombes, JA Woyach, JC Byrd, CC Oakes |
Blood | 2019 |
Optimized Xenograft Protocol for Chronic Lymphocytic Leukemia Results in High Engraftment Efficiency for All CLL Subgroups
S Decker, A Zwick, SK Saleem, S Kissel, A Rettig, K Aumann, C Dierks |
International journal of molecular sciences | 2019 |
Multi-kernel linear mixed model with adaptive lasso for prediction analysis on high-dimensional multi-omics data
J Li, Q Lu, Y Wen, R Schwartz |
Bioinformatics | 2019 |
Adaptive penalization in high-dimensional regression and classification with external covariates using variational Bayes
B Velten, W Huber |
Biostatistics (Oxford, England) | 2019 |
HIF-1α is over-expressed in leukemic cells from TP53 -disrupted patients and is a promising therapeutic target in chronic lymphocytic leukemia
V Griggio, C Vitale, M Todaro, C Riganti, J Kopecka, C Salvetti, R Bomben, MD Bo, D Magliulo, D Rossi, G Pozzato, L Bonello, M Marchetti, P Omedè, AA Kodipad, L Laurenti, GD Poeta, FR Mauro, R Bernardi, T Zenz, V Gattei, G Gaidano, R Foà, M Massaia, M Boccadoro, M Coscia |
Haematologica | 2019 |
Phenotype-based drug screening reveals association between venetoclax response and differentiation stage in acute myeloid leukemia
H Kuusanmäki, AM Leppä, P Pölönen, M Kontro, O Dufva, D Deb, B Yadav, O Brück, A Kumar, H Everaus, BT Gjertsen, M Heinäniemi, K Porkka, S Mustjoki, CA Heckman |
Haematologica | 2019 |
Mutations in the RAS-BRAF-MAPK-ERK pathway define a specific subgroup of patients with adverse clinical features and provide new therapeutic options in chronic lymphocytic leukemia
N Giménez, A Martínez-Trillos, A Montraveta, M Lopez-Guerra, L Rosich, F Nadeu, JG Valero, M Aymerich, L Magnano, M Rozman, E Matutes, J Delgado, T Baumann, E Gine, M González, M Alcoceba, MJ Terol, B Navarro, E Colado, AR Payer, XS Puente, C López-Otín, A Lopez-Guillermo, E Campo, D Colomer, N Villamor |
Haematologica | 2018 |
Machine learning and feature selection for drug response prediction in precision oncology applications
M Ali, T Aittokallio |
Biophysical Reviews | 2018 |
How to find the right drug for each patient? Advances and challenges in pharmacogenomics
A Kalamara, L Tobalina, J Saez-Rodriguez |
Current Opinion in Systems Biology | 2018 |
AKT/mTORC2 Inhibition Activates FOXO1 Function in CLL Cells Reducing B-Cell Receptor-Mediated Survival
E Cosimo, A Tarafdar, MW Moles, AK Holroyd, N Malik, MA Catherwood, J Hay, KM Dunn, AM Macdonald, SM Guichard, D O'Rourke, MT Leach, OJ Sansom, SC Cosulich, AM McCaig, AM Michie |
Clinical cancer research | 2018 |
Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets.
Argelaguet R, Velten B, Arnol D, Dietrich S, Zenz T, Marioni JC, Buettner F, Huber W, Stegle O |
Molecular Systems Biology | 2018 |