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Genome-Wide Sirna Screen for Modulators of Cell Death Induced by Proteasome Inhibitor Bortezomib

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Genome-Wide Sirna Screen for Modulators of Cell Death Induced by Proteasome Inhibitor Bortezomib Published OnlineFirst May 11, 2010; DOI: 10.1158/0008-5472.CAN-09-4428 Published OnlineFirst on May 11, 2010 as 10.1158/0008-5472.CAN-09-4428 Integrated Systems and Technologies Cancer Research Genome-Wide siRNA Screen for Modulators of Cell Death Induced by Proteasome Inhibitor Bortezomib Siquan Chen1, Jonathan L. Blank2, Theodore Peters1, Xiaozhen J. Liu2, David M. Rappoli1, Michael D. Pickard3, Saurabh Menon1, Jie Yu2, Denise L. Driscoll2, Trupti Lingaraj2, Anne L. Burkhardt2, Wei Chen2, Khristofer Garcia1, Darshan S. Sappal2, Jesse Gray1, Paul Hales1, Patrick J. Leroy2, John Ringeling1, Claudia Rabino2, James J. Spelman2, Jay P. Morgenstern1, and Eric S. Lightcap2 Abstract Multiple pathways have been proposed to explain how proteasome inhibition induces cell death, but me- chanisms remain unclear. To approach this issue, we performed a genome-wide siRNA screen to evaluate the genetic determinants that confer sensitivity to bortezomib (Velcade (R); PS-341). This screen identified 100 genes whose knockdown affected lethality to bortezomib and to a structurally diverse set of other proteasome inhibitors. A comparison of three cell lines revealed that 39 of 100 genes were commonly linked to cell death. We causally linked bortezomib-induced cell death to the accumulation of ASF1B, Myc, ODC1, Noxa, BNIP3, Gadd45α, p-SMC1A, SREBF1, and p53. Our results suggest that proteasome inhibition promotes cell death primarily by dysregulating Myc and polyamines, interfering with protein translation, and disrupting essential DNA damage repair pathways, leading to programmed cell death. Cancer Res; 70(11); OF1–9. ©2010 AACR. Introduction active oxygen species (ROS), stabilization of Myc and Noxa, and induction of endoplasmic reticulum (ER) stress, any of The primary targets of most cancer chemotherapies are which may trigger cell death (1–4). Despite the pleiotropic known. However, the downstream effect on the cell is gener- effects of proteasome inhibition, bortezomib is an effective ally poorly understood, particularly the sequence of events cancer chemotherapy which exploits key weaknesses that dif- directly involved in the commitment of the tumor cell to ferentiate tumor cells from normal cells. Determining the pri- die. This lack of knowledge is particularly profound for pro- mary mechanisms by which bortezomib induces tumor cell teasome inhibition because the majority of intracellular pro- death would increase our understanding of these key weak- teins can be degraded by the proteasome. As such, simply nesses and allow for better utilization of bortezomib in the showing that proteasome inhibition can result in the stabili- clinic. zation of a protein does not necessarily imply that it is mech- RNA interference (RNAi) has been widely adopted for func- anistically relevant and important for cell death. Prior studies tional genomic studies, including defining drug mechanism have suggested that bortezomib has an antitumor effect by (5). Genome-wide RNAi allows for different mechanisms to inhibition of antiapoptotic proteins (e.g., NFκBandBcl2), be ranked against each other, providing an evaluation of stabilization of tumor suppressors (e.g., p53), disruption their relative phenotypic dominance. Some limitations of of cell cycle, dysregulation of Fas or tumor necrosis factor– RNAi are that protein knockdown is transient, never results related apoptosis-inducing ligand pathways, increases in re- in complete elimination of the protein, and has various de- grees of off-target effects. Genetic redundancy may also mask the phenotype of targeted genes. Nevertheless, RNAi studies – Authors' Affiliations: 1Discovery Technologies, 2Discovery Oncology have provided powerful insights into drug mechanism (6 8). Biology, and 3Medical Biostatistics, Millennium Pharmaceuticals, Inc., Bortezomib induces death of most cell lines in culture Cambridge, Massachusetts within 72 hours, with an LC50 of ∼10 nmol/L. We performed Note: Supplementary data for this article are available at Cancer the genome-wide siRNA screen to identify genes whose Research Online (http://cancerres.aacrjournals.org/). knockdown affected the cytotoxicity of bortezomib using Current address for S. Chen: Cellular Screening Center, Institute for the colon cancer cell line HCT-116 because of its highly re- Genomics and Systems Biology, University of Chicago, GCIS, WSB03, 929 East 57th Street, Chicago, IL 60637. Current address for T. Peters: producible sensitivity to bortezomib and high transfectability Constellation Pharmaceuticals, 148 Sidney Street, Cambridge, MA when compared with other cell lines. The effect of the top 02139. Current address for D.M. Rappoli and J.P. Morgenstern: hits from the screen were also compared in A375 and HeLa Monsanto Biotechnology, 325 Vassar Street, Cambridge, MA 02139. cells, highly transfectable lines derived from melanoma and Corresponding Author: Eric S. Lightcap, Discovery Oncology Biology, Millennium Pharmaceuticals, Inc., 40 Landsdowne Street, Cambridge, cervical cancer, respectively. MA 02139. Phone: 617-551-3717; Fax: 617-551-8906; E-mail: eric.lightcap@ Herein, we show that bortezomib leads to cell death by in- mpi.com. terfering with ribosome function, essential DNA damage path- doi: 10.1158/0008-5472.CAN-09-4428 ways, and dysregulation of Myc. In particular, we examine the ©2010 American Association for Cancer Research. effect of bortezomib on protein translation initiation, www.aacrjournals.org OF1 Downloaded from cancerres.aacrjournals.org on September 25, 2021. © 2010 American Association for Cancer Research. Published OnlineFirst May 11, 2010; DOI: 10.1158/0008-5472.CAN-09-4428 Chen et al. especially eIF2α and mammalian target of rapamycin (SABiosciences) that is under the control of a minimal cyto- (mTOR), the effect of upregulation of Myc and ODC1 on megalovirus (CMV) promoter and tandem repeats of the polyamine homeostasis, and DNA damage signaling. In ad- E-box sequence using pCMV firefly luciferase for normaliza- dition, we show that a common set of 39 genes is respon- tion. Forty-eight hours after transfection, cells were treated sible for conferring sensitivity to proteasome inhibition in with 30 nmol/L bortezomib or vehicle for the indicated times multiple cell lines. Although these results do not account under normal or serum-starved conditions, after which lucif- for differences in bortezomib efficacy across tumor types erase activities were determined using Dual-Glo reagents seen in the clinic and cannot account for the effect of (Promega) as described in the Supplementary Data. the tumor microenvironment on bortezomib sensitivity, they provide a foundation for future studies exploring Polyamine high-performance liquid chromatography these issues. assay Polyamines were quantified by high-performance liquid Materials and Methods chromatography on an AccQTag column using the AccQTag method (Waters) with a modified acetonitrile gradient as Genome-wide screen and hit deconvolution specified in the Supplementary Data. HCT-116 cells were transfected with 15 nmol/L siRNA oligos (siGENOME SMARTpool, Dharmacon) using Dhar- Data treatment and statistics maFECT 2 (DH2) reagent (Dharmacon) in Opti-MEM All ATPlite fluorescence intensity values were log2 trans- (Invitrogen) in a BioCoat poly-D-lysine (PDL)–coated 384- formed (V). The Bliss Independence (BI) scores were calcu- well daughter plates (BD Biosciences). Forty-eight hours af- lated from the log2-transformed data as ter transfection, cells were treated with 0, 4, or 7 nmol/L V þ V − V − V ; bortezomib and incubated for a further 48 hours, after which xn g0 gn x0 viability was assessed using ATPlite reagent (Perkin-Elmer) where V is the mean of RNAi oligos treated with 4 nmol/L and luminescence was measured using a LEADseeker imaging xn (or 7 nmol/L) bortezomib, V is the mean of GL2 control system (GE Healthcare). g0 cells, V is the mean of GL2 cells treated with 4 nmol/L SMARTpool hits were deconvoluted in HCT-116, A375, and gn (or 7 nmol/L) bortezomib, and V is the mean of RNAi oligos HeLa cells again in sextuplicate, except that CELLCOAT x0 treated with 0 nmol/L bortezomib. 384-well PDL-coated black, clear-bottom plates (Greiner) The Rescue scores were calculated using log -transformed were used. For HCT-116 on the Greiner plates, DH2 lipid 2 data as min(V , V ) − V . was reduced from 0.075 to 0.057 μL/well. Bortezomib was gn x0 xn The SE was calculated for each of the equation variables. modestly more potent under these conditions, so concentra- These estimates were then squared, and the square root of tions of 2 nmol/L (LC ) and 5 nmol/L (LC ) were used. For 15 60 their sum was taken to give the SE of the score. Probabilities A375, changes included the use of DharmaFECT 4 (DH4) that gene knockdown was on target were calculated by using transfection reagent at 0.07 μL/well, 300 cells per well, and hypergeometric distribution function based on deconvoluted bortezomib treatments at 4 nmol/L (LC )and7nmol/L 5 oligo data as specified in the Supplementary Data. (LC55). For HeLa, changes included the use of DharmaFECT 1 (DH1) transfection reagent at 0.2 μL/well, 900 cells per well, and bortezomib treatments at 12 nmol/L (LC25)and Results 25 nmol/L (LC50). Bortezomib will be provided to qualified researchers once a standard Materials Transfer Agreement Design of screen has been executed. Gene knockdown in HCT-116 by 15 nmol/L Dharmacon SMARTpool siRNA was allowed to progress for 48 hours to Western blot and immunoprecipitation provide for adequate depletion of protein, followed by HCT-116 cells were treated with 30 nmol/L bortezomib 48 hours with two concentrations of bortezomib (LC15 and (LC90) or vehicle (0.1% DMSO) for the times indicated. Sam- LC60 at 48 h) or a vehicle control. These concentrations allow ples were prepared for SDS-PAGE and quantitative immuno- for the evaluation of either enhancement or suppression of blot analysis with antisera as specified in the Supplementary bortezomib-induced cell death by the SMARTpools, by which Data using tubulin as a normalization control (Supplementa- both activators and inhibitors of key pathways can be de- ry Fig. S2B). Myc was immunoprecipitated using anti-Myc tected.
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