CRISPR–Cas: a tool for cancer research and therapeutics

Abstract

In the past decade, the development of a genome-editing technology mediated by CRISPR has made genetic engineering easier than ever, both in vitro and in vivo. CRISPR systems have enabled important advances in cancer research by accelerating the development of study models or as a tool in genetic screening studies, including those aiming to discover and validate therapeutic targets. In this Review, we discuss these applications as well as new potential uses of CRISPR to assist in cancer detection or the development of anticancer therapies.

Key points

  • CRISPR systems have been extensively applied to edit genes and genomic sequences in order to develop cancer models, providing a rapid, simple and low-cost system with which to identify and study genetic determinants of cancer and therapeutic targets.

  • CRISPR systems have been widely adapted in cancer research to facilitate the discovery of new targets; many high-throughput in vitro and in vivo genetic screening studies have been performed with CRISPR.

  • CRISPR systems are being robustly adapted to improve the efficacy of immunotherapies by enhancing their potency, mitigating toxicity, reducing manufacturing cost and facilitating the discovery and development of new immunotherapeutic strategies.

  • The delivery of CRISPR to tumours might inhibit tumour growth directly and indirectly. As a diagnosis platform, CRISPR could be used to detect low numbers of cancer cells or rare mutations in clinical samples.

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Fig. 1: Mechanisms of gene editing.
Fig. 2: Applications of CRISPR in cancer research.
Fig. 3: CRISPR for cancer modelling in cells and mice.
Fig. 4: CRISPR for genetic screening.
Fig. 5: CRISPR in immuno-oncology.
Fig. 6: CRISPR for cancer detection.

References

  1. 1.

    Jinek, M. et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–821 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Jinek, M. et al. RNA-programmed genome editing in human cells. eLife 2, e00471 (2013).

    PubMed  PubMed Central  Google Scholar 

  3. 3.

    Mali, P. et al. RNA-guided human genome engineering via Cas9. Science 339, 823–826 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Cong, L. et al. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819–823 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Cox, D. B., Platt, R. J. & Zhang, F. Therapeutic genome editing: prospects and challenges. Nat. Med. 21, 121–131 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Xue, W. et al. CRISPR-mediated direct mutation of cancer genes in the mouse liver. Nature 514, 380–385 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Chen, S. et al. Genome-wide CRISPR screen in a mouse model of tumor growth and metastasis. Cell 160, 1246–1260 (2014).

    Google Scholar 

  8. 8.

    Manguso, R. T. et al. In vivo CRISPR screening identifies Ptpn2 as a cancer immunotherapy target. Nature 547, 413–418 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Drost, J. et al. Use of CRISPR-modified human stem cell organoids to study the origin of mutational signatures in cancer. Science 358, 234–238 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Platt, R. J. et al. CRISPR-Cas9 knockin mice for genome editing and cancer modeling. Cell 159, 440–455 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Matano, M. et al. Modeling colorectal cancer using CRISPR-Cas9-mediated engineering of human intestinal organoids. Nat. Med. 21, 256–262 (2015).

    CAS  Google Scholar 

  12. 12.

    Sanchez-Rivera, F. J. & Jacks, T. Applications of the CRISPR-Cas9 system in cancer biology. Nat. Rev. Cancer 15, 387–395 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Lin, A., Giuliano, C. J., Sayles, N. M. & Sheltzer, J. M. CRISPR/Cas9 mutagenesis invalidates a putative cancer dependency targeted in on-going clinical trials. eLife 6, e24179 (2017).

    PubMed  PubMed Central  Google Scholar 

  14. 14.

    Chow, R. D. et al. AAV-mediated direct in vivo CRISPR screen identifies functional suppressors in glioblastoma. Nat. Neurosci. 20, 1329–1341 (2017).

  15. 15.

    Shi, J. et al. Discovery of cancer drug targets by CRISPR-Cas9 screening of protein domains. Nat. Biotechnol. 33, 661–667 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Wang, T., Wei, J. J., Sabatini, D. M. & Lander, E. S. Genetic screens in human cells using the CRISPR-Cas9 system. Science 343, 80–84 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Shalem, O. et al. Genome-scale CRISPR-Cas9 knockout screening in human cells. Science 343, 84–87 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Eyquem, J. et al. Targeting a CAR to the TRAC locus with CRISPR/Cas9 enhances tumour rejection. Nature 543, 113–117 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Ren, J. et al. Multiplex genome editing to generate universal CAR T cells resistant to PD1 inhibition. Clin. Cancer Res. 23, 2255–2266 (2017).

    CAS  PubMed  Google Scholar 

  20. 20.

    Legut, M., Dolton, G., Mian, A. A., Ottmann, O. & Sewell, A. CRISPR-mediated TCR replacement generates superior anticancer transgenic T cells. Blood 131, 311–322 (2017).

    PubMed  Google Scholar 

  21. 21.

    Rouet, P., Smih, F. & Jasin, M. Introduction of double-strand breaks into the genome of mouse cells by expression of a rare-cutting endonuclease. Mol. Cell. Biol. 14, 8096–8106 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Lieber, M. R., Ma, Y., Pannicke, U. & Schwarz, K. Mechanism and regulation of human non-homologous DNA end-joining. Nat. Rev. Mol. Cell Biol. 4, 712–720 (2003).

    CAS  PubMed  Google Scholar 

  23. 23.

    Urnov, F. D., Rebar, E. J., Holmes, M. C., Zhang, H. S. & Gregory, P. D. Genome editing with engineered zinc finger nucleases. Nat. Rev. Genetics 11, 636–646 (2010).

    CAS  PubMed  Google Scholar 

  24. 24.

    Joung, J. K. & Sander, J. D. TALENs: a widely applicable technology for targeted genome editing. Nat. Rev. Mol. Cell Biol. 14, 49–55 (2013).

    CAS  PubMed  Google Scholar 

  25. 25.

    Kleinstiver, B. P. et al. Engineered CRISPR-Cas9 nucleases with altered PAM specificities. Nature 523, 481–485 (2015).

    PubMed  PubMed Central  Google Scholar 

  26. 26.

    Hu, J. H. et al. Evolved Cas9 variants with broad PAM compatibility and high DNA specificity. Nature 556, 57–63 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Nishimasu, H. et al. Engineered CRISPR-Cas9 nuclease with expanded targeting space. Science 361, 1259–1262 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Ran, F. A. et al. In vivo genome editing using Staphylococcus aureus Cas9. Nature 520, 186–191 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Hou, Z. et al. Efficient genome engineering in human pluripotent stem cells using Cas9 from Neisseria meningitidis. Proc. Natl Acad. Sci. USA 110, 15644–15649 (2013).

    CAS  PubMed  Google Scholar 

  30. 30.

    Zetsche, B. et al. Cpf1 is a single RNA-guided endonuclease of a class 2 CRISPR-Cas system. Cell 163, 759–771 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Fu, Y. et al. High-frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells. Nat. Biotechnol. 31, 822–826 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Fu, Y., Sander, J. D., Reyon, D., Cascio, V. M. & Joung, J. K. Improving CRISPR-Cas nuclease specificity using truncated guide RNAs. Nat. Biotechnol. 32, 279–284 (2013).

    Google Scholar 

  33. 33.

    Chen, J. S. et al. Enhanced proofreading governs CRISPR–Cas9 targeting accuracy. Nature 550, 407 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Kleinstiver, B. P. et al. High-fidelity CRISPR-Cas9 nucleases with no detectable genome-wide off-target effects. Nature 529, 490–495 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Slaymaker, I. M. et al. Rationally engineered Cas9 nucleases with improved specificity. Science 351, 84–88 (2016).

    CAS  PubMed  Google Scholar 

  36. 36.

    Guilinger, J. P., Thompson, D. B. & Liu, D. R. Fusion of catalytically inactive Cas9 to FokI nuclease improves the specificity of genome modification. Nat. Biotechnol. 32, 577–582 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Tsai, S. Q. et al. Dimeric CRISPR RNA-guided FokI nucleases for highly specific genome editing. Nat. Biotechnol. 32, 569–576 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Bolukbasi, M. F. et al. DNA-binding domain fusions enhance the targeting range and precision of Cas9. Nat. Methods 12, 1150–1156 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Ran, F. A. et al. Double nicking by RNA-guided CRISPR Cas9 for enhanced genome editing specificity. Cell 154, 1380–1389 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Yin, H. et al. Partial DNA-guided Cas9 enables genome editing with reduced off-target activity. Nat. Chem. Biol. 14, 311–316 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Vanoli, F. et al. CRISPR-Cas9-guided oncogenic chromosomal translocations with conditional fusion protein expression in human mesenchymal cells. Proc. Natl Acad. Sci. USA 114, 3696–3701 (2017).

    CAS  PubMed  Google Scholar 

  42. 42.

    Ghezraoui, H. et al. Chromosomal translocations in human cells are generated by canonical nonhomologous end-joining. Mol. Cell 55, 829–842 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Li, Y. et al. A versatile reporter system for CRISPR-mediated chromosomal rearrangements. |Genome Biol. 16, 111 (2015).

    PubMed  PubMed Central  Google Scholar 

  44. 44.

    Blasco, R. B. et al. Simple and rapid in vivo generation of chromosomal rearrangements using CRISPR/Cas9 technology. Cell Rep. 9, 1219–1227 (2014).

    CAS  PubMed  Google Scholar 

  45. 45.

    Maddalo, D. et al. In vivo engineering of oncogenic chromosomal rearrangements with the CRISPR/Cas9 system. Nature 516, 423–427 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Lin, S., Staahl, B. T., Alla, R. K. & Doudna, J. A. Enhanced homology-directed human genome engineering by controlled timing of CRISPR / Cas9 delivery. eLife 3, e04766 (2015).

    Google Scholar 

  47. 47.

    Suzuki, K. et al. In vivo genome editing via CRISPR/Cas9 mediated homology-independent targeted integration. Nature 540, 144–149 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Chu, V. T. et al. Increasing the efficiency of homology-directed repair for CRISPR-Cas9-induced precise gene editing in mammalian cells. Nat. Biotechnol. 33, 543–548 (2015).

    CAS  PubMed  Google Scholar 

  49. 49.

    Deng, C. & Capecchi, M. R. Reexamination of gene targeting frequency as a function of the extent of homology between the targeting vector and the target locus. Mol. Cell. Biol. 12, 3365–3371 (1992).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Gilbert, L. A. et al. Genome-scale CRISPR-mediated control of gene repression and activation. Cell 159, 647–661 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. 51.

    Gilbert, L. A. et al. CRISPR-mediated modular RNA-guided regulation of transcription in eukaryotes. Cell 154, 442–451 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. 52.

    Qi, L. S. et al. Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell 152, 1173–1183 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53.

    Larson, M. H. et al. CRISPR interference (CRISPRi) for sequence-specific control of gene expression. Nat. Protoc. 8, 2180–2196 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. 54.

    Cheng, A. W. et al. Multiplexed activation of endogenous genes by CRISPR-on, an RNA-guided transcriptional activator system. Cell Res. 23, 1163–1171 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. 55.

    Zalatan, J. G. et al. Engineering complex synthetic transcriptional programs with CRISPR RNA scaffolds. Cell 160, 339–350 (2015).

    CAS  PubMed  Google Scholar 

  56. 56.

    Konermann, S. et al. Genome-scale transcriptional activation by an engineered CRISPR-Cas9 complex. Nature 517, 583–588 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. 57.

    Chavez, A. et al. Highly efficient Cas9-mediated transcriptional programming. Nat. Methods 12, 326–328 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58.

    Tanenbaum, M. E., Gilbert, L. A., Qi, L. S., Weissman, J. S. & Vale, R. D. A protein tagging system for signal amplification in gene expression and fluorescence imaging. Cell 159, 635–646 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. 59.

    Zafra, M. P. et al. Optimized base editors enable efficient editing in cells, organoids and mice. Nat. Biotechnol. 36, 888–893 (2018).

    Google Scholar 

  60. 60.

    Komor, A. C., Kim, Y. B., Packer, M. S., Zuris, J. A. & Liu, D. R. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature 533, 420 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. 61.

    Li, X. et al. Base editing with a Cpf1-cytidine deaminase fusion. Nat. Biotechnol. 36, 324–327 (2018).

    CAS  PubMed  Google Scholar 

  62. 62.

    Nishida, K. et al. Targeted nucleotide editing using hybrid prokaryotic and vertebrate adaptive immune systems. Science 353, aaf8729 (2016).

    PubMed  Google Scholar 

  63. 63.

    Gaudelli, N. M. et al. Programmable base editing of A·T to G·C in genomic DNA without DNA cleavage. Nature 551, 464 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. 64.

    Walrath, J. C., Hawes, J. J., Van Dyke, T. & Reilly, K. M. Genetically engineered mouse models in cancer research. Adv. Cancer Res. 106, 113–164 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. 65.

    Fellmann, C., Gowen, B. G., Lin, P. C., Doudna, J. A. & Corn, J. E. Cornerstones of CRISPR-Cas in drug discovery and therapy. Nat. Rev. Drug Discov. 16, 89–100 (2017).

    CAS  PubMed  Google Scholar 

  66. 66.

    Papagiannakopoulos, T. et al. Circadian rhythm disruption promotes lung tumorigenesis. Cell Metab. 24, 324–331 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. 67.

    Wanzel, M. et al. CRISPR-Cas9–based target validation for p53-reactivating model compounds. Nat. Chem. Biol. 12, 22 (2015).

    PubMed  PubMed Central  Google Scholar 

  68. 68.

    Smurnyy, Y. et al. DNA sequencing and CRISPR-Cas9 gene editing for target validation in mammalian cells. Nat. Chem. Biol. 10, 623 (2014).

    CAS  PubMed  Google Scholar 

  69. 69.

    Neggers, J. E. et al. Target identification of small molecules using large-scale CRISPR-Cas mutagenesis scanning of essential genes. Nat. Commun. 9, 502 (2018).

    PubMed  PubMed Central  Google Scholar 

  70. 70.

    Donovan, K. F. et al. Creation of novel protein variants with CRISPR/Cas9-mediated mutagenesis: turning a screening by-product into a discovery tool. PLOS ONE 12, e0170445 (2017).

    PubMed  PubMed Central  Google Scholar 

  71. 71.

    Ipsaro, J. J. et al. Rapid generation of drug-resistance alleles at endogenous loci using CRISPR-Cas9 indel mutagenesis. PLOS ONE 12, e0172177 (2017).

    PubMed  PubMed Central  Google Scholar 

  72. 72.

    Torres, R. et al. Engineering human tumour-associated chromosomal translocations with the RNA-guided CRISPR-Cas9 system. Nat. Commun. 5, 3964 (2014).

    CAS  PubMed  Google Scholar 

  73. 73.

    Heckl, D. et al. Generation of mouse models of myeloid malignancy with combinatorial genetic lesions using CRISPR-Cas9 genome editing. Nat. Biotechnol. 32, 941–946 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  74. 74.

    Plouffe, S. W. et al. Characterization of Hippo pathway components by gene inactivation. Mol. Cell 64, 993–1008 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. 75.

    Katainen, R. et al. CTCF/cohesin-binding sites are frequently mutated in cancer. Nat. Genet. 47, 818–821 (2015).

    CAS  PubMed  Google Scholar 

  76. 76.

    Guo, Y. et al. CRISPR inversion of CTCF sites alters genome topology and enhancer/promoter function. Cell 162, 900–910 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. 77.

    Seino, T. et al. Human pancreatic tumor organoids reveal loss of stem cell niche factor dependence during disease progression. Cell Stem Cell 22, 454–467 (2018).

    CAS  PubMed  Google Scholar 

  78. 78.

    Lee, J. et al. Reconstituting development of pancreatic intraepithelial neoplasia from primary human pancreas duct cells. Nat. Commun. 8, 14686 (2017).

    PubMed  PubMed Central  Google Scholar 

  79. 79.

    Verissimo, C. S. et al. Targeting mutant RAS in patient-derived colorectal cancer organoids by combinatorial drug screening. eLife 5, e18489 (2016).

    PubMed  PubMed Central  Google Scholar 

  80. 80.

    Drost, J. et al. Sequential cancer mutations in cultured human intestinal stem cells. Nature 521, 43–47 (2015).

    CAS  Google Scholar 

  81. 81.

    Mou, H., Kennedy, Z., Anderson, D. G., Yin, H. & Xue, W. Precision cancer mouse models through genome editing with CRISPR-Cas9. Genome Med. 7, 53 (2015).

    PubMed  PubMed Central  Google Scholar 

  82. 82.

    Winters, I. P., Murray, C. W. & Winslow, M. M. Towards quantitative and multiplexed in vivo functional cancer genomics. Nat. Rev. Genet. 19, 741–755 (2018).

    CAS  PubMed  Google Scholar 

  83. 83.

    Roper, J. et al. In vivo genome editing and organoid transplantation models of colorectal cancer and metastasis. Nat. Biotechnol. 35, 569–576 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  84. 84.

    Sanchez-Rivera, F. J. et al. Rapid modelling of cooperating genetic events in cancer through somatic genome editing. Nature 516, 428–431 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  85. 85.

    Rogers, Z. N. et al. A quantitative and multiplexed approach to uncover the fitness landscape of tumor suppression in vivo. Nat. Methods 14, 737–742 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  86. 86.

    Chiou, S. H. et al. Pancreatic cancer modeling using retrograde viral vector delivery and in vivo CRISPR/Cas9-mediated somatic genome editing. Genes Dev. 29, 1576–1585 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. 87.

    Yin, H., Kauffman, K. J. & Anderson, D. G. Delivery technologies for genome editing. Nat. Rev. Drug Discov. 16, 387–399 (2017).

    CAS  PubMed  Google Scholar 

  88. 88.

    Zuckermann, M. et al. Somatic CRISPR/Cas9-mediated tumour suppressor disruption enables versatile brain tumour modelling. Nat. Commun. 6, 7391 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  89. 89.

    Annunziato, S. et al. Modeling invasive lobular breast carcinoma by CRISPR/Cas9-mediated somatic genome editing of the mammary gland. Genes Dev. 30, 1470–1480 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. 90.

    O’Rourke, K. P. et al. Transplantation of engineered organoids enables rapid generation of metastatic mouse models of colorectal cancer. Nat. Biotechnol. 35, 577–582 (2017).

    PubMed  PubMed Central  Google Scholar 

  91. 91.

    Rogers, Z. N. et al. Mapping the in vivo fitness landscape of lung adenocarcinoma tumor suppression in mice. Nat. Genet. 50, 483–486 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  92. 92.

    Walter, D. M. et al. Systematic in vivo inactivation of chromatin-regulating enzymes identifies Setd2 as a potent tumor suppressor in lung adenocarcinoma. Cancer Res. 77, 1719–1729 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  93. 93.

    Chu, V. T. et al. Efficient CRISPR-mediated mutagenesis in primary immune cells using CrispRGold and a C57BL/6 Cas9 transgenic mouse line. Proc. Natl Acad. Sci. USA 113, 12514–12519 (2016).

    CAS  PubMed  Google Scholar 

  94. 94.

    Malina, A. et al. Repurposing CRISPR/Cas9 for in situ functional assays. Genes Dev. 27, 2602–2614 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  95. 95.

    Winters, I. P. et al. Multiplexed in vivo homology-directed repair and tumor barcoding enables parallel quantification of Kras variant oncogenicity. Nat. Commun. 8, 2053 (2017).

    PubMed  PubMed Central  Google Scholar 

  96. 96.

    Yin, H. et al. Therapeutic genome editing by combined viral and non-viral delivery of CRISPR system components in vivo. Nat. Biotechnol. 34, 328–333 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  97. 97.

    Wang, D. et al. Adenovirus-mediated somatic genome editing of Pten by CRISPR/Cas9 in mouse liver in spite of Cas9-specific immune responses. Hum. Gene Ther. 26, 432–442 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  98. 98.

    Huang, J. et al. Generation and comparison of CRISPR-Cas9 and Cre-mediated genetically engineered mouse models of sarcoma. Nat. Commun. 8, 15999 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  99. 99.

    Carroll, K. J. et al. A mouse model for adult cardiac-specific gene deletion with CRISPR/Cas9. Proc. Natl Acad. Sci. USA 113, 338–343 (2016).

    CAS  PubMed  Google Scholar 

  100. 100.

    Dow, L. E. et al. Inducible in vivo genome editing with CRISPR-Cas9. Nat. Biotechnol. 33, 390–394 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  101. 101.

    Weber, J. et al. CRISPR/Cas9 somatic multiplex-mutagenesis for high-throughput functional cancer genomics in mice. Proc. Natl Acad. Sci. USA 112, 13982–13987 (2015).

    CAS  PubMed  Google Scholar 

  102. 102.

    Xu, C. et al. piggyBac mediates efficient in vivo CRISPR library screening for tumorigenesis in mice. Proc. Natl Acad. Sci. USA 114, 722–727 (2017).

    CAS  PubMed  Google Scholar 

  103. 103.

    Maresch, R. et al. Multiplexed pancreatic genome engineering and cancer induction by transfection-based CRISPR/Cas9 delivery in mice. Nat. Commun. 7, 10770 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  104. 104.

    Billon, P. et al. CRISPR-mediated base editing enables efficient disruption of eukaryotic genes through induction of STOP codons. Mol. Cell 67, 1068–1079 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  105. 105.

    Liu, Z. et al. Efficient generation of mouse models of human diseases via ABE- and BE-mediated base editing. Nat. Commun. 9, 2338 (2018).

    PubMed  PubMed Central  Google Scholar 

  106. 106.

    Hart, T. et al. High-resolution CRISPR screens reveal fitness genes and genotype-specific cancer liabilities. Cell 163, 1515–1526 (2015).

    CAS  PubMed  Google Scholar 

  107. 107.

    Wang, T. et al. Identification and characterization of essential genes in the human genome. Science 350, 1096–1101 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  108. 108.

    Steinhart, Z. et al. Genome-wide CRISPR screens reveal a Wnt-FZD5 signaling circuit as a druggable vulnerability of RNF43-mutant pancreatic tumors. Nat. Med. 23, 60–68 (2017).

    CAS  PubMed  Google Scholar 

  109. 109.

    Fei, T. et al. Genome-wide CRISPR screen identifies HNRNPL as a prostate cancer dependency regulating RNA splicing. Proc. Natl Acad. Sci. USA 114, E5207–E5215 (2017).

    CAS  PubMed  Google Scholar 

  110. 110.

    Parnas, O. et al. A genome-wide CRISPR screen in primary immune cells to dissect regulatory networks. Cell 162, 675–686 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  111. 111.

    Patel, S. J. et al. Identification of essential genes for cancer immunotherapy. Nature 548, 537–542 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  112. 112.

    Klann, T. S. et al. CRISPR–Cas9 epigenome editing enables high-throughput screening for functional regulatory elements in the human genome. Nat. Biotechnol. 35, 561 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  113. 113.

    Krall, E. B. et al. KEAP1 loss modulates sensitivity to kinase targeted therapy in lung cancer. eLife 6, e18970 (2017).

    PubMed  PubMed Central  Google Scholar 

  114. 114.

    Ruiz, S. et al. A genome-wide CRISPR screen identifies CDC25A as a determinant of sensitivity to ATR inhibitors. Mol. Cell 62, 307–313 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  115. 115.

    Katigbak, A. et al. A CRISPR/Cas9 functional screen identifies rare tumor suppressors. Sci. Rep. 6, 38968 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  116. 116.

    Braun, C. J. et al. Versatile in vivo regulation of tumor phenotypes by dCas9-mediated transcriptional perturbation. Proc. Natl Acad. Sci. USA 113, E3892–E3900 (2016).

    CAS  PubMed  Google Scholar 

  117. 117.

    Kodama, M. et al. In vivo loss-of-function screens identify KPNB1 as a new druggable oncogene in epithelial ovarian cancer. Proc. Natl Acad. Sci. USA 114, E7301–E7310 (2017).

    CAS  PubMed  Google Scholar 

  118. 118.

    Song, C. Q. et al. Genome-wide CRISPR screen identifies regulators of mitogen-activated protein kinase as suppressors of liver tumors in mice. Gastroenterology 152, 1161–1173 (2017).

    CAS  PubMed  Google Scholar 

  119. 119.

    Anderson, G. R. et al. A landscape of therapeutic cooperativity in KRAS mutant cancers reveals principles for controlling tumor evolution. Cell Rep. 20, 999–1015 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  120. 120.

    Wang, T. et al. Gene essentiality profiling reveals gene networks and synthetic lethal interactions with oncogenic Ras. Cell 168, 890–903 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  121. 121.

    Shen, J. P. et al. Combinatorial CRISPR-Cas9 screens for de novo mapping of genetic interactions. Nat. Methods 14, 573–576 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  122. 122.

    Han, K. et al. Synergistic drug combinations for cancer identified in a CRISPR screen for pairwise genetic interactions. Nat. Biotechnol. 35, 463–474 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  123. 123.

    Wong, A. S. et al. Multiplexed barcoded CRISPR-Cas9 screening enabled by CombiGEM. Proc. Natl Acad. Sci. USA 113, 2544–2549 (2016).

    CAS  PubMed  Google Scholar 

  124. 124.

    Datlinger, P. et al. Pooled CRISPR screening with single-cell transcriptome readout. Nat. Methods 14, 297 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  125. 125.

    Sanjana, N. E. et al. High-resolution interrogation of functional elements in the noncoding genome. Science 353, 1545–1549 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  126. 126.

    Cheng, J. et al. A Molecular Chipper technology for CRISPR sgRNA library generation and functional mapping of noncoding regions. Nat. Commun. 7, 11178 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  127. 127.

    Zhu, S. et al. Genome-scale deletion screening of human long non-coding RNAs using a paired-guide RNA CRISPR-Cas9 library. Nat. Biotechnol. 34, 1279–1286 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  128. 128.

    Korkmaz, G. et al. Functional genetic screens for enhancer elements in the human genome using CRISPR-Cas9. Nat. Biotechnol. 34, 192–198 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  129. 129.

    Diao, Y. et al. A new class of temporarily phenotypic enhancers identified by CRISPR/Cas9-mediated genetic screening. Genome Res. 26, 397–405 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  130. 130.

    Perez, A. R. et al. GuideScan software for improved single and paired CRISPR guide RNA design. Nat. Biotechnol. 35, 347–349 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  131. 131.

    Doench, J. G. et al. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nat. Biotechnol. 34, 184–191 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  132. 132.

    Sheel, A. & Xue, W. Genomic amplifications cause false positives in CRISPR screens. Cancer Discov. 6, 824–826 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  133. 133.

    Aguirre, A. J. et al. Genomic copy number dictates a gene-independent cell response to CRISPR-Cas9 targeting. Cancer Discov. 6, 914–929 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  134. 134.

    Munoz, D. M. et al. CRISPR screens provide a comprehensive assessment of cancer vulnerabilities but generate false-positive hits for highly amplified genomic regions. Cancer Discov. 6, 900–913 (2016).

    CAS  PubMed  Google Scholar 

  135. 135.

    Meyers, R. M. et al. Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells. Nat. Genet. 49, 1779–1784 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  136. 136.

    Khalil, D. N., Smith, E. L., Brentjens, R. J. & Wolchok, J. D. The future of cancer treatment: immunomodulation, CARs and combination immunotherapy. Nat. Rev. Clin. Oncol. 13, 273–290 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  137. 137.

    Morris, E. C. & Stauss, H. J. Optimizing T cell receptor gene therapy for hematologic malignancies. Blood 127, 3305–3311 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  138. 138.

    Lim, W. A. & June, C. H. The principles of engineering immune cells to treat cancer. Cell 168, 724–740 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  139. 139.

    Schachter, J. et al. Pembrolizumab versus ipilimumab for advanced melanoma: final overall survival results of a multicentre, randomised, open-label phase 3 study (KEYNOTE-006). Lancet 390, 1853–1862 (2017).

    CAS  PubMed  Google Scholar 

  140. 140.

    Rizvi, N. A. et al. Activity and safety of nivolumab, an anti-PD-1 immune checkpoint inhibitor, for patients with advanced, refractory squamous non-small-cell lung cancer (CheckMate 063): a phase 2, single-arm trial. Lancet. Oncol. 16, 257–265 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  141. 141.

    Maus, M. V. et al. Adoptive immunotherapy for cancer or viruses. Annu. Rev. Immunol. 32, 189–225 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  142. 142.

    Brudno, J. N. & Kochenderfer, J. N. Chimeric antigen receptor T cell therapies for lymphoma. Nat. Rev. Clin. Oncol. 15, 31–46 (2018).

    CAS  PubMed  Google Scholar 

  143. 143.

    D’Aloia, M. M., Zizzari, I. G., Sacchetti, B., Pierelli, L. & Alimandi, M. CAR-T cells: the long and winding road to solid tumors. Cell Death Dis. 9, 282 (2018).

    PubMed  PubMed Central  Google Scholar 

  144. 144.

    Davila, M. L. & Brentjens, R. J. CD19-targeted CAR T cells as novel cancer immunotherapy for relapsed or refractory B-cell acute lymphoblastic leukemia. Clin. Adv. Hematol. Oncol. 14, 802–808 (2016).

    PubMed  PubMed Central  Google Scholar 

  145. 145.

    Zheng, P. P., Kros, J. M. & Li, J. Approved CAR T cell therapies: ice bucket challenges on glaring safety risks and long-term impacts. Drug Discov. Today 23, 1175–1182 (2018).

    PubMed  Google Scholar 

  146. 146.

    Wang, X. & Rivière, I. Clinical manufacturing of CAR T cells: foundation of a promising therapy. Mol. Ther. Oncolytics 3, 16015 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  147. 147.

    Prasad, V. Immunotherapy: tisagenlecleucel — the first approved CAR-T cell therapy: implications for payers and policy makers. Nat. Rev. Clin. Oncol. 15, 11–12 (2018).

    PubMed  Google Scholar 

  148. 148.

    Qasim, W. et al. Molecular remission of infant B-ALL after infusion of universal TALEN gene-edited CAR T cells. Sci. Transl Med. 9, eaaj2013 (2017).

    PubMed  Google Scholar 

  149. 149.

    Ghosh, A. et al. Donor CD19 CAR T cells exert potent graft-versus-lymphoma activity with diminished graft-versus-host activity. Nat. Med. 23, 242–249 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  150. 150.

    Yang, Y., Jacoby, E. & Fry, T. J. Challenges and opportunities of allogeneic donor-derived CAR T cells. Curr. Opin. Hematol. 22, 509–515 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  151. 151.

    Rupp, L. J. et al. CRISPR/Cas9-mediated PD-1 disruption enhances anti-tumor efficacy of human chimeric antigen receptor T cells. Sci. Rep. 7, 737 (2017).

    PubMed  PubMed Central  Google Scholar 

  152. 152.

    Weber, J. S., Kahler, K. C. & Hauschild, A. Management of immune-related adverse events and kinetics of response with ipilimumab. J. Clin. Oncol. 30, 2691–2697 (2012).

    CAS  PubMed  Google Scholar 

  153. 153.

    Bonifant, C. L., Jackson, H. J., Brentjens, R. J. & Curran, K. J. Toxicity and management in CAR T cell therapy. Mol. Ther. Oncolytics 3, 16011 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  154. 154.

    Dudley, M. E. et al. Adoptive cell therapy for patients with metastatic melanoma: evaluation of intensive myeloablative chemoradiation preparative regimens. J. Clin. Oncol. 26, 5233–5239 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  155. 155.

    Wherry, E. J. & Kurachi, M. Molecular and cellular insights into T cell exhaustion. Nat. Rev. Immunol. 15, 486–499 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  156. 156.

    Singer, M. et al. A distinct gene module for dysfunction uncoupled from activation in tumor-infiltrating T cells. Cell 166, 1500–1511 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  157. 157.

    Cyranoski, D. Chinese scientists to pioneer first human CRISPR trial. Nature 535, 476–477 (2016).

    CAS  PubMed  Google Scholar 

  158. 158.

    Lu, Y. et al. A phase I trial of PD-1 deficient engineered T cells with CRISPR/Cas9 in patients with advanced non-small cell lung cancer. J. Clin. Oncol. 36, 3050–3050 (2018).

    Google Scholar 

  159. 159.

    June, C. H., Riddell, S. R. & Schumacher, T. N. Adoptive cellular therapy: a race to the finish line. Sci. Transl Med. 7, 280ps7 (2015).

    PubMed  Google Scholar 

  160. 160.

    Rapoport, A. P. et al. NY-ESO-1-specific TCR-engineered T cells mediate sustained antigen-specific antitumor effects in myeloma. Nat. Med. 21, 914–921 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  161. 161.

    Yin, H. et al. Structure-guided chemical modification of guide RNA enables potent non-viral in vivo genome editing. Nat. Biotechnol. 35, 1179–1187 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  162. 162.

    Chew, W. L. et al. A multifunctional AAV-CRISPR-Cas9 and its host response. Nat. Methods 13, 868–874 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  163. 163.

    Charlesworth, C. T. et al. Identification of pre-existing adaptive immunity to Cas9 proteins in humans. Preprint at BioRxiv https://www.biorxiv.org/content/early/2018/01/05/243345 (2018).

  164. 164.

    Kay, M. A. State-of-the-art gene-based therapies: the road ahead. Nat. Rev. Genetics 12, 316–328 (2011).

    CAS  PubMed  Google Scholar 

  165. 165.

    Ihry, R. J. et al. p53 inhibits CRISPR-Cas9 engineering in human pluripotent stem cells. Nat. Med. 24, 939–946 (2018).

    CAS  PubMed  Google Scholar 

  166. 166.

    Haapaniemi, E., Botla, S., Persson, J., Schmierer, B. & Taipale, J. CRISPR-Cas9 genome editing induces a p53-mediated DNA damage response. Nat. Med. 24, 927–930 (2018).

    CAS  PubMed  Google Scholar 

  167. 167.

    Kosicki, M., Tomberg, K. & Bradley, A. Repair of double-strand breaks induced by CRISPR–Cas9 leads to large deletions and complex rearrangements. Nat. Biotechnol. 36, 765–771 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  168. 168.

    Straathof, K. C. et al. An inducible caspase 9 safety switch for T cell therapy. Blood 105, 4247–4254 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  169. 169.

    Roth, T. L. et al. Reprogramming human T cell function and specificity with non-viral genome targeting. Nature 559, 405–409 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  170. 170.

    Chen, Z. H. et al. Targeting genomic rearrangements in tumor cells through Cas9-mediated insertion of a suicide gene. Nat. Biotechnol. 35, 543–550 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  171. 171.

    Kim, H. H. et al. Targeting mutant KRAS with CRISPR-Cas9 controls tumor growth. Genome Res. 28, 374–382 (2018).

    CAS  PubMed Central  Google Scholar 

  172. 172.

    Jubair, L. & McMillan, N. A. J. The therapeutic potential of CRISPR/Cas9 systems in oncogene-addicted cancer types: virally driven cancers as a model system. Mol. Ther. Nucleic Acids 8, 56–63 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  173. 173.

    Abudayyeh, O. O. et al. C2c2 is a single-component programmable RNA-guided RNA-targeting CRISPR effector. Science 353, aaf5573 (2016).

    PubMed  PubMed Central  Google Scholar 

  174. 174.

    East-Seletsky, A. et al. Two distinct RNase activities of CRISPR-C2c2 enable guide-RNA processing and RNA detection. Nature 538, 270–273 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  175. 175.

    Gootenberg, J. S. et al. Nucleic acid detection with CRISPR-Cas13a/C2c2. Science 356, 438–442 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  176. 176.

    Gootenberg, J. S. et al. Multiplexed and portable nucleic acid detection platform with Cas13, Cas12a, and Csm6. Science 360, 439–444 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  177. 177.

    Myhrvold, C. et al. Field-deployable viral diagnostics using CRISPR-Cas13. Science 360, 444–448 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  178. 178.

    Chen, J. S. et al. CRISPR-Cas12a target binding unleashes indiscriminate single-stranded DNase activity. Science 360, 436–439 (2018).

    CAS  PubMed  Google Scholar 

  179. 179.

    Lee, S. H. et al. CUT-PCR: CRISPR-mediated, ultrasensitive detection of target DNA using PCR. Oncogene 36, 6823 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  180. 180.

    Lareau, C. et al. Response to “Unexpected mutations after CRISPR–Cas9 editing in vivo”. Nat. Methods 15, 238–239 (2017).

    Google Scholar 

  181. 181.

    Wilson, C. J. et al. The experimental design and data interpretation in ‘Unexpected mutations after CRISPR Cas9 editing in vivo’ by Schaefer et al. are insufficient to support the conclusions drawn by the authors. Preprint at BioRxiv https://www.biorxiv.org/content/early/2017/07/10/153338 (2017).

  182. 182.

    Schumann, K. et al. Generation of knock-in primary human T cells using Cas9 ribonucleoproteins. Proc. Natl Acad. Sci. USA 112, 10437–10442 (2015).

    CAS  PubMed  Google Scholar 

  183. 183.

    Hendel, A. et al. Chemically modified guide RNAs enhance CRISPR-Cas genome editing in human primary cells. Nat. Biotechnol. 33, 985–989 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  184. 184.

    Dever, D. P. et al. CRISPR/Cas9 beta-globin gene targeting in human haematopoietic stem cells. Nature 539, 384–389 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  185. 185.

    Housden, B. E. et al. Loss-of-function genetic tools for animal models: cross-species and cross-platform differences. Nat. Rev. Genetics 18, 24–40 (2017).

    CAS  PubMed  Google Scholar 

  186. 186.

    Rossi, A. et al. Genetic compensation induced by deleterious mutations but not gene knockdowns. Nature 524, 230–233 (2015).

    CAS  PubMed  Google Scholar 

  187. 187.

    Daude, N. et al. Knockout of the prion protein (PrP)-like Sprn gene does not produce embryonic lethality in combination with PrP(C)-deficiency. Proc. Natl Acad. Sci. USA 109, 9035–9040 (2012).

    CAS  PubMed  Google Scholar 

  188. 188.

    Lu, H. et al. Compensatory induction of MYC expression by sustained CDK9 inhibition via a BRD4-dependent mechanism. eLife 4, e06535 (2015).

    PubMed  PubMed Central  Google Scholar 

  189. 189.

    Marx, V. Choosing CRISPR-based screens in cancer. Nat. Methods 14, 343 (2017).

    CAS  PubMed  Google Scholar 

  190. 190.

    Normile, D. China sprints ahead in CRISPR therapy race. Science 358, 20–21 (2017).

    CAS  PubMed  Google Scholar 

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Acknowledgements

H.Y. acknowledges funding from the National Natural Science Foundation of China 31871345 and a startup package from Wuhan University.

Authors contributions

H.Y. and W.X. researched different sections of the manuscript, and D.G.A. provided key opinions and oversaw data research. All authors discussed content and reviewed and edited the manuscript before submission.

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Correspondence to Hao Yin or Wen Xue or Daniel G. Anderson.

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H.Y., W.X. and D.G.A. have applied for CRISPR-related patents, one of which has been issued. D.G.A. is a scientific co-founder of CRISPR Therapeutics.

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Yin, H., Xue, W. & Anderson, D.G. CRISPR–Cas: a tool for cancer research and therapeutics. Nat Rev Clin Oncol 16, 281–295 (2019). https://doi.org/10.1038/s41571-019-0166-8

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