Synergistic drug combinations for cancer identified in a CRISPR screen for pairwise genetic interactions

Nature Biotechnology

Volumn 35, Issue 5, 2017, Pages 463-474

  Han, Kyuho ^a   Jeng, Edwin E ^a   Hess, Gaelen T ^a   Morgens, David W ^a   Li, Amy ^a   Bassik, Michael C ^a  

^a STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOTECHNOLOGY;

CLONING AND SEQUENCING; COMBINATION THERAPY; DRUG COMBINATIONS; GENETIC INTERACTION; GENETIC SCREENING; HIGH THROUGHPUT; SCORING METHODS; SYNTHETIC LETHAL;

DISEASES;

IMATINIB; LENTIVIRUS VECTOR; PROTEIN BCL X; PROTEIN MCL 1; RICIN; RNA; ANTINEOPLASTIC AGENT; TUMOR PROTEIN;

ANIMAL CELL; ARTICLE; CANCER COMBINATION CHEMOTHERAPY; CELL DEATH; CELL SURVIVAL; CLUSTERED REGULARLY INTERSPACED SHORT PALINDROMIC REPEAT; CONTROLLED STUDY; DRUG POTENTIATION; EXCISION REPAIR; FALSE NEGATIVE RESULT; FALSE POSITIVE RESULT; GENE EXPRESSION; GENE EXPRESSION SYSTEM; GENE INTERACTION; GENE LIBRARY; GENE TARGETING; HUMAN; HUMAN CELL; K-562 CELL LINE; MALIGNANT NEOPLASM; MOUSE; NONHUMAN; PHENOTYPE; PRIORITY JOURNAL; PROMOTER REGION; PROTEIN PROTEIN INTERACTION; PSEUDOMONAS AERUGINOSA; SCORING SYSTEM; DRUG SCREENING; GENETICS; NEOPLASMS, EXPERIMENTAL; PROCEDURES;

ANTINEOPLASTIC COMBINED CHEMOTHERAPY PROTOCOLS; CLUSTERED REGULARLY INTERSPACED SHORT PALINDROMIC REPEATS; DRUG SCREENING ASSAYS, ANTITUMOR; DRUG SYNERGISM; HUMANS; K562 CELLS; NEOPLASM PROTEINS; NEOPLASMS, EXPERIMENTAL;

EID: 85018234086     PISSN: 10870156     EISSN: 15461696     Source Type: Journal    
DOI: 10.1038/nbt.3834     Document Type: Article

References (77)

1. Jia, J. et al. Mechanisms of drug combinations: interaction and network perspectives. Nat. Rev. Drug Discov. 8, 111-128 (2009).
2. Ashburn, T.T. & Thor, K.B. Drug repositioning: identifying and developing new uses for existing drugs. Nat. Rev. Drug Discov. 3, 673-683 (2004).
3. Al-Lazikani, B., Banerji, U. & Workman, P. Combinatorial drug therapy for cancer in the post-genomic era. Nat. Biotechnol. 30, 679-692 (2012).
4. Sun, X., Vilar, S. & Tatonetti, N.P. High-throughput methods for combinatorial drug discovery. Sci. Transl. Med. 5, 205rv1 (2013).
5. Collins, S.R., Weissman, J.S. & Krogan, N.J. From information to knowledge: new technologies for defning gene function. Nat. Methods 6, 721-723 (2009).
6. Costanzo, M. et al. A global genetic interaction network maps a wiring diagram of cellular function. Science http://dx.doi.org/10.1126/science.aaf1420 (2016).
7. Schuldiner, M. et al. Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profle. Cell 123, 507-519 (2005).
8. Jonikas, M.C. et al. Comprehensive characterization of genes required for protein folding in the endoplasmic reticulum. Science 323, 1693-1697 (2009).
9. Bandyopadhyay, S. et al. Rewiring of genetic networks in response to DNA damage. Science 330, 1385-1389 (2010).
10. Collins, S.R. et al. Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map. Nature 446, 806-810 (2007).
11. Dixon, S.J., Costanzo, M., Baryshnikova, A., Andrews, B. & Boone, C. Systematic mapping of genetic interaction networks. Annu. Rev. Genet. 43, 601-625 (2009).
12. Frost, A. et al. Functional repurposing revealed by comparing S. pombe and S. cerevisiae genetic interactions. Cell 149, 1339-1352 (2012).
13. Horn, T. et al. Mapping of signaling networks through synthetic genetic interaction analysis by RNAi. Nat. Methods 8, 341-346 (2011).
14. Roguev, A. et al. Quantitative genetic-interaction mapping in mammalian cells. Nat. Methods 10, 432-437 (2013).
15. Bassik, M.C. et al. A systematic mammalian genetic interaction map reveals pathways underlying ricin susceptibility. Cell 152, 909-922 (2013).
16. Srivas, R. et al. A network of conserved synthetic lethal interactions for exploration of precision cancer therapy. Mol. Cell 63, 514-525 (2016).
17. Wong, A.S.L., Choi, G.C.G., Cheng, A.A., Purcell, O. & Lu, T.K. Massively parallel high-order combinatorial genetics in human cells. Nat. Biotechnol. 33, 952-961 (2015).
18. Jinek, M. et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816-821 (2012).
19. Mali, P. et al. RNA-guided human genome engineering via Cas9. Science 339, 823-826 (2013).
20. Cong, L. et al. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819-823 (2013).
21. Tsai, S.Q. et al. Dimeric CRISPR RNA-guided FokI nucleases for highly specifc genome editing. Nat. Biotechnol. 32, 569-576 (2014).
22. Xie, K., Minkenberg, B. & Yang, Y. Boosting CRISPR/Cas9 multiplex editing capability with the endogenous tRNA-processing system. Proc. Natl. Acad. Sci. USA 112, 3570-3575 (2015).
23. Wong, A.S.L. et al. Multiplexed barcoded CRISPR-Cas9 screening enabled by CombiGEM. Proc. Natl. Acad. Sci. USA 113, 2544-2549 (2016).
24. Vidigal, J.A. & Ventura, A. Rapid and effcient one-step generation of paired gRNA CRISPR-Cas9 libraries. Nat. Commun. 6, 8083 (2015).
25. Sack, L.M., Davoli, T., Xu, Q., Li, M.Z. & Elledge, S.J. Sources of error in mammalian genetic screens. G3 (Bethesda) 6, 2781-2790 (2016).
26. Zhu, F. et al. Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery. Nucleic Acids Res. 40, D1128-D1136 (2012).
27. Wishart, D.S. et al. DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res. 34, D668-D672 (2006).
28. Pawson, A.J. et al. The IUPHAR/BPS Guide to PHARMACOLOGY: an expert-driven knowledgebase of drug targets and their ligands. Nucleic Acids Res. 42, D1098-D1106 (2014).
29. Morgens, D.W. et al. Genome-scale measurement of off-target activity using Cas9 toxicity in high-throughput screens. Nat. Commun (in press). (2017).
30. Deans, R.M. et al. Parallel shRNA and CRISPR-Cas9 screens enable antiviral drug target identifcation. Nat. Chem. Biol. 12, 361-366 (2016).
31. Kampmann, M., Bassik, M.C. & Weissman, J.S. Integrated platform for genome-wide screening and construction of high-density genetic interaction maps in mammalian cells. Proc. Natl. Acad. Sci. USA 110, E2317-E2326 (2013).
32. Gilbert, L.A. et al. Genome-scale CRISPR-mediated control of gene repression and activation. Cell 159, 647-661 (2014).
33. Collins, S.R., Schuldiner, M., Krogan, N.J. & Weissman, J.S. A strategy for extracting and analyzing large-scale quantitative epistatic interaction data. Genome Biol. 7, R63 (2006).
34. Fischer, B. et al. A map of directional genetic interactions in a metazoan cell. eLife 4, 1-21 (2015).
35. Blomen, V.A. et al. Gene essentiality and synthetic lethality in haploid human cells. Science 350, 1092-1096 (2015).
36. Brazil, D.P., Yang, Z.Z. & Hemmings, B.A. Advances in protein kinase B signalling: AKTion on multiple fronts. Trends Biochem. Sci. 29, 233-242 (2004).
37. Saurabh, K. et al. The PIM family of oncoproteins: small kinases with huge implications in myeloid leukemogenesis and as therapeutic targets. Oncotarget 5, 8503-8514 (2014).
38. Chen, J.L., Limnander, A. & Rothman, P.B. Pim-1 and Pim-2 kinases are required for effcient pre-B-cell transformation by v-Abl oncogene. Blood 111, 1677-1685 (2008).
39. Johannes, L. & Popoff, V. Tracing the retrograde route in protein traffcking. Cell 135, 1175-1187 (2008).
40. Moreau, D. et al. Genome-wide RNAi screens identify genes required for Ricin and PE intoxications. Dev. Cell 21, 231-244 (2011).
41. Morgens, D.W., Deans, R.M., Li, A. & Bassik, M.C. Systematic comparison of CRISPR/Cas9 and RNAi screens for essential genes. Nat. Biotechnol. 34, 634-636 (2016).
42. Wang, W. et al. Mannosidase 2, alpha 1 defciency is associated with ricin resistance in embryonic stem (ES) cells. PLoS One 6, e22993 (2011).
43. Bar-Peled, L. et al. A Tumor suppressor complex with GAP activity for the Rag GTPases that signal amino acid suffciency to mTORC1. Science 340, 1100-1106 (2013).
44. Margueron, R. & Reinberg, D. The Polycomb complex PRC2 and its mark in life. Nature 469, 343-349 (2011).
45. Szklarczyk, D. et al. STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 43, D447-D452 (2015).
46. Parnas, O. et al. A genome-wide CRISPR screen in primary immune cells to dissect regulatory networks. Cell 162, 675-686 (2015).
47. Chen, S. et al. Genome-wide CRISPR screen in a mouse model of tumor growth and metastasis. Cell 160, 1246-1260 (2015).
48. Brinkman, E.K., Chen, T., Amendola, M. & van Steensel, B. Easy quantitative assessment of genome editing by sequence trace decomposition. Nucleic Acids Res. 42, e168 (2014).
49. Lord, C.J., Tutt, A.N.J. & Ashworth, A. Synthetic lethality and cancer therapy: lessons learned from the development of PARP inhibitors. Annu. Rev. Med. 66, 455-470 (2015).
50. Sultana, R. et al. Synthetic lethal targeting of DNA double-strand break repair defcient cells by human apurinic/apyrimidinic endonuclease inhibitors. Int. J. Cancer 131, 2433-2444 (2012).
51. Riabinska, A. et al. Therapeutic targeting of a robust non-oncogene addiction to PRKDC in ATM-defective tumors. Sci. Transl. Med. 5, 189ra78 (2013).
52. Austin, C.J.D., Kahlert, J., Kassiou, M. & Rendina, L.M. The translocator protein (TSPO): a novel target for cancer chemotherapy. Int. J. Biochem. Cell Biol. 45, 1212-1216 (2013).
53. Placzek, W.J. et al. A survey of the anti-apoptotic Bcl-2 subfamily expression in cancer types provides a platform to predict the effcacy of Bcl-2 antagonists in cancer therapy. Cell Death Dis. 1, e40 (2010).
54. Bixby, D. & Talpaz, M. Seeking the causes and solutions to imatinib-resistance in chronic myeloid leukemia. Leukemia 25, 7-22 (2011).
55. Delbridge, A.R.D., Grabow, S., Strasser, A. & Vaux, D.L. Thirty years of BCL-2: translating cell death discoveries into novel cancer therapies. Nat. Rev. Cancer 16, 99-109 (2016).
56. Aichberger, K.J. et al. Identifcation of mcl-1 as a BCR/ABL-dependent target in chronic myeloid leukemia (CML): evidence for cooperative antileukemic effects of imatinib and mcl-1 antisense oligonucleotides. Blood 105, 3303-3311 (2005).
57. Dai, Y., Rahmani, M., Corey, S.J., Dent, P. & Grant, S. A Bcr/Abl-independent, Lyn-dependent form of imatinib mesylate (STI-571) resistance is associated with altered expression of Bcl-2. J. Biol. Chem. 279, 34227-34239 (2004).
58. Berns, K. et al. A large-scale RNAi screen in human cells identifes new components of the p53 pathway. Nature 428, 431-437 (2004).
59. Friedman, A. & Perrimon, N. A functional RNAi screen for regulators of receptor tyrosine kinase and ERK signalling. Nature 444, 230-234 (2006).
60. Mendes-Pereira, A.M. et al. Genome-wide functional screen identifes a compendium of genes affecting sensitivity to tamoxifen. Proc. Natl. Acad. Sci. USA 109, 2730-2735 (2012).
61. Eichhorn, P.J.A. et al. Phosphatidylinositol 3-kinase hyperactivation results in lapatinib resistance that is reversed by the mTOR/phosphatidylinositol 3-kinase inhibitor NVP-BEZ235. Cancer Res. 68, 9221-9230 (2008).
62. Corcoran, R.B. et al. Synthetic lethal interaction of combined BCL-XL and MEK inhibition promotes tumor regressions in KRAS mutant cancer models. Cancer Cell 23, 121-128 (2013).
63. Prahallad, A. et al. Unresponsiveness of colon cancer to BRAF(V600E) inhibition through feedback activation of EGFR. Nature 483, 100-103 (2012).
64. Opferman, J.T. Attacking cancer's Achilles heel: antagonism of anti-apoptotic BCL-2 family members. FEBS J. 283, 2661-2675 (2016).
65. Leverson, J.D. et al. Potent and selective small-molecule MCL-1 inhibitors demonstrate on-target cancer cell killing activity as single agents and in combination with ABT-263 (navitoclax). Cell Death Dis. 6, e1590 (2015).
66. Chonghaile, T.N. et al. Maturation stage of T-cell acute lymphoblastic leukemia determines BCL-2 versus BCL-XL dependence and sensitivity to ABT-199. Cancer Discov. 4, 1074-1087 (2014).
67. Ko, T.K., Chuah, C.T.H., Huang, J.W.J., Ng, K.-P. & Ong, S.T. The BCL2 inhibitor ABT-199 signifcantly enhances imatinib-induced cell death in chronic myeloid leukemia progenitors. Oncotarget 5, 9033-9038 (2014).
68. Hong, H.-Y., Choi, J., Cho, Y.-W. & Kim, B.-C. Cdc25A promotes cell survival by stimulating NF-κB activity through IκB-α phosphorylation and destabilization. Biochem. Biophys. Res. Commun. 420, 293-296 (2012).
69. Bassi, Z.I., Audusseau, M., Riparbelli, M.G., Callaini, G. & D'Avino, P.P. Citron kinase controls a molecular network required for midbody formation in cytokinesis. Proc. Natl. Acad. Sci. USA 110, 9782-9787 (2013).
70. Chen, B. et al. Dynamic imaging of genomic loci in living human cells by an optimized CRISPR/Cas system. Cell 155, 1479-1491 (2013).
71. Shalem, O., Sanjana, E.N.,Hartenian, E. & Zhang, F. Genome-Scale CRISPR-Cas9 Knockout. Science 343, 84-88 (2014).
72. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S.L. Ultrafast and memory-effcient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).
73. Kampmann, M., Bassik, M.C. & Weissman, J.S. Functional genomics platform for pooled screening and generation of mammalian genetic interaction maps. Nat. Protoc. 9, 1825-1847 (2014).
74. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498-2504 (2003).
75. Chatr-aryamontri, A. et al. The BioGRID interaction database: 2015 update. Nucleic Acids Res. 43, D470-D478 (2015).
76. Eisen, M.B., Spellman, P.T., Brown, P.O. & Botstein, D. Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95, 14863-14868 (1998).
77. Saldanha, A.J. Java Treeview-extensible visualization of microarray data. Bioinformatics 20, 3246-3248 (2004).