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Citations to this article

Drug-perturbation-based stratification of blood cancer
Sascha Dietrich, … , Wolfgang Huber, Thorsten Zenz
Sascha Dietrich, … , Wolfgang Huber, Thorsten Zenz
Published December 11, 2017
Citation Information: J Clin Invest. 2018;128(1):427-445. https://doi.org/10.1172/JCI93801.
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Research Article Hematology Oncology Article has an altmetric score of 30

Drug-perturbation-based stratification of blood cancer

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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.

Authors

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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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
E Pramil, LH Bastian, T Denèfle, F Nemati, M Xiao, E Lardé, K Maloum, D Roos-Weil, E Chapiro, ML Garff-Tavernier, F Davi, D Decaudin, M Sarfati, F Nguyen-Khac, H Merle-Béral, P Karoyan, SA Susin
Blood Advances 2019
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
Cancers 2019
The dawn of a new era in treating T-PLL
A Schrader, T Braun, M Herling
Oncotarget 2019
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

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