Published OnlineFirst April 18, 2019; DOI: 10.1158/0008-5472.CAN-18-3438 Cancer Translational Science Research MDM4 Is Targeted by 1q Gain and Drives Disease in Burkitt Lymphoma Jennifer Hullein€ 1,2, Mikołaj Słabicki1, Maciej Rosolowski3, Alexander Jethwa1,2, Stefan Habringer4, Katarzyna Tomska1, Roma Kurilov5, Junyan Lu6, Sebastian Scheinost1, Rabea Wagener7,8, Zhiqin Huang9, Marina Lukas1, Olena Yavorska6, Hanne Helfrich10,Rene Scholtysik11, Kyle Bonneau12, Donato Tedesco12,RalfKuppers€ 11, Wolfram Klapper13, Christiane Pott14, Stephan Stilgenbauer10, Birgit Burkhardt15, Markus Lof€ fler3, Lorenz H. Trumper€ 16, Michael Hummel17, Benedikt Brors5, Marc Zapatka9, Reiner Siebert7,8, Markus Kreuz3, Ulrich Keller4,18, Wolfgang Huber6, and Thorsten Zenz1,19 Abstract Oncogenic MYC activation promotes proliferation in growth in a xenograft model in a p53-dependent manner. Burkitt lymphoma, but also induces cell-cycle arrest and Small molecule inhibition of the MDM4–p53 interaction apoptosis mediated by p53, a tumor suppressor that is was effective only in TP53wt Burkitt lymphoma cell lines. mutated in 40% of Burkitt lymphoma cases. To identify Moreover, primary TP53wt Burkitt lymphoma samples fre- molecular dependencies in Burkitt lymphoma, we per- quently acquired gains of chromosome 1q, which includes formed RNAi-based, loss-of-function screening in eight the MDM4 locus, and showed elevated MDM4 mRNA levels. Burkitt lymphoma cell lines and integrated non-Burkitt 1q gain was associated with TP53wt across 789 cancer cell lymphoma RNAi screens and genetic data. We identified lines and MDM4 was essential in the TP53wt-context in 216 76 genes essential to Burkitt lymphoma, including genes cell lines representing 19 cancer entities from the Achilles associated with hematopoietic cell differentiation (FLI1, Project. Our findings highlight the critical role of p53 as a BCL11A) or B-cell development and activation (PAX5, tumor suppressor in Burkitt lymphoma and identify MDM4 CDKN1B, JAK2, CARD11) and found a number of con- as a functional target of 1q gain in a wide range of cancers text-specific dependencies including oncogene addiction in that is therapeutically targetable. cell lines with TCF3/ID3 or MYD88 mutation. The strongest genotype–phenotype association was seen for TP53.MDM4, Significance: Targeting MDM4 to alleviate degradation of a negative regulator of TP53,wasessentialinTP53 wild-type p53 can be exploited therapeutically across Burkitt lymphoma (TP53wt) Burkitt lymphoma cell lines. MDM4 knockdown and other cancers with wild-type p53 harboring 1q gain, the activated p53, induced cell-cycle arrest, and decreased tumor most frequent copy number alteration in cancer. 1Molecular Therapy in Hematology and Oncology & Department of Translational (CBF), Charite, Berlin, Germany. 19Department of Medical Oncology and Hema- Oncology, NCT and DKFZ, Heidelberg, Germany. 2Faculty of Biosciences, tology, University Hospital Zurich, Zurich, Switzerland. Heidelberg University, Heidelberg, Germany. 3Department for Statistics and Epidemiology, Institute for Medical Informatics, Leipzig, Germany. 4III. Medical Note: Supplementary data for this article are available at Cancer Research Department of Hematology and Medical Oncology, Technical University of Online (http://cancerres.aacrjournals.org/). Munich, Germany. 5Division of Applied Bioinformatics, DKFZ, Heidelberg, Germany. 6European Molecular Biology Laboratory (EMBL), Heidelberg, M. Rosolowski, R. Scholtysik, R. Kuppers,€ W. Klapper, C. Pott, S. Stilgenbauer, B. Germany. 7Institute of Human Genetics, Ulm University & Ulm University Medical Burkhardt, M. Lof€ fler, L.H. Trumper,€ M. Hummel, R. Siebert, M. Kreuz, T. Zenz are Center, Germany. 8Institute of Human Genetics, University of Kiel, Kiel, Germany. members of the MMML consortium. 9Division of Molecular Genetics, DKFZ, Heidelberg, Germany. 10Department of Internal Medicine III, University of Ulm, Ulm, Germany. 11Institute of Cell Biology M. Słabicki is the co-first author and T. Zenz is the lead author. (Cancer Research), University of Duisburg-Essen, Medical School, Essen, Germany, and the German Cancer Consortium (DKTK). 12Cellecta, Inc., Mountain This manuscript is available on BioRxiv: https://doi.org/10.1101/289363. View, California. 13Department of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital Schleswig-Holstein, Campus Kiel, Corresponding Author: Thorsten Zenz, University Hospital and University of Christian-Albrechts-University Kiel, Kiel, Germany. 14Second Medical Depart- Zurich, Zurich€ 8091, Germany. Phone: 41-44-255 9469; E-mail: ment, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany. [email protected] 15Department of Pediatric Hematology and Oncology, NHL-BFM Study Center, Cancer Res 2019;79:3125–38 University Children's Hospital, Munster,€ Germany. 16Department of Hematology € € and Medical Oncology, Gottingen University Medical Center, Gottingen, doi: 10.1158/0008-5472.CAN-18-3438 Germany. 17Institute of Pathology, Charite–University Medicine Berlin, Berlin, Germany. 18Division of Hematology and Oncology at Campus Benjamin Franklin Ó2019 American Association for Cancer Research. www.aacrjournals.org 3125 Downloaded from cancerres.aacrjournals.org on September 30, 2021. © 2019 American Association for Cancer Research. Published OnlineFirst April 18, 2019; DOI: 10.1158/0008-5472.CAN-18-3438 Hullein€ et al. Introduction RNAi screen and shRNA-mediated knockdown The RNAi screen was performed as described previously (17) Burkitt lymphoma is an aggressive B-cell lymphoma that is with modifications using the DECIPHER Human Module I characterized by translocation of the MYC gene to immunoglob- pooled lentiviral shRNA library (#DHPAC-M1-P) targeting ulin loci (1). Although oncogenic MYC promotes cell growth and 5,045 genes in key signaling pathways with four to five shRNAs proliferation, it also evokes failsafe mechanisms such as p53 per gene (Cellecta). shRNA representation was determined two activation that have to be overcome for transformation (2). About and 14 days posttransduction using high-throughput sequencing. 40% of Burkitt lymphoma acquire TP53 mutations evading MYC- P values for shRNA depletion were calculated using the edgeR induced stress signals (3, 4). package (18) and collapsed into gene scores using weighted Recent mutational cartography efforts in Burkitt lymphoma Z-transformation (19). P values for differential shRNA viability identified additional recurrent mutations in TCF3, ID3, effects were calculated as described previously using public soft- GNA13, RET, PIK3R1, DDX3X, FBXO11,andtheSWI/SNF ware and collapsed into gene scores using Kolmogorov–Smirnov genes ARID1A and SMARCA4 (5–8). Burkitt lymphoma also statistics (https://software.broadinstitute.org/GENE-E/index.html). display copy number alterations (CNA) in addition to the RNAi results in non-Burkitt lymphoma cell lines screened with the MYC translocation, targeting chromosomes 1q, 13q31, 17p13 same library were provided by Cellecta as raw read counts and (including TP53), and 9p21.2 (including CDKN2A;refs.9, genome-wide RNAi results in 216 cell lines were publically available 10). A gain of 1q is found in 30% of Burkitt lymphoma and as log -transformed shRNA fold changes (13). Single shRNAs were often affects large regions (11), which has contributed to the 2 coexpressed with RFP constitutively from the pRSI12-U6-(sh)-UbiC- limited understanding of oncogenic mechanisms involved. TagRFP-2A-Puro vector backbone. shRNA cytotoxicity was deter- The implications of these mutations and CNAs are currently mined by transduction of 50% of cells and relative RFP-loss com- unclear. pared with a scrambled shRNA (shNT). RNAi-based genomics screens allow querying of functional dependencies in an unbiased fashion and in high through- Genetic annotation of cell lines put. Using panels of representative cell lines, context-specific Mutations in Burkitt lymphoma cell lines were identified from vulnerabilities have been linked to genetic and pathologic genomic DNA using a self-designed amplicon panel (20) or from subgroups (12). The Achilles Project reported comprehensive RNA sequencing on the Illumina HiSeq2000. Sequences were screening data in 501 cell lines using RNAi (13, 14). While mapped against the human reference genome hg19 using the activating mutations caused direct oncogene addiction, as STAR alignment tool. Mutations were called as described previ- seen in cell lines with BRAF, KRAS,orPI3K mutation, ously (21). Genetic information for non-Burkitt lymphoma cell secondary gene dependencies were observed for loss-of- lines was extracted from Cancer Cell Line Encyclopedia (CCLE; function mutations in tumor suppressor genes, such as https://portals.broadinstitute.org/ccle/home) and COSMIC ARID1A (15). Integration of gene expression and drug sen- (GDSC, http://www.cancerrxgene.org/). sitivity profiles may provide further insight into the molec- ular basis of diseases and might be used to tailor targeted RT-qPCR therapies (16). Total RNA was isolated with RNeasy Mini Kit (Qiagen) and on- For a comprehensive dissection of molecular dependencies column DNase I (Qiagen) digestion. RNA was reverse-transcribed in Burkitt lymphoma, we performed a loss-of-function RNAi by SuperScript III First-Strand Synthesis SuperMix (Invitrogen) screen across a panel of genetically characterized Burkitt lym- and quantified using QuantiFast SYBR Green RT-PCR (Qiagen) or phoma cell lines and intersected our findings on genotype- Power SYBR