Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Cornerstones of CRISPR–Cas in drug discovery and therapy

Key Points

  • CRISPR–Cas tools are easily programmable RNA-guided nucleases that are derived from microbial adaptive immune systems and enable rapid genome engineering in vitro and in vivo.

  • Paired with the rapid expansion of genomic information, CRISPR–Cas enables facile genetic manipulation, even in previously difficult contexts such as human cells. Gene knockout via error-prone repair, such as non-homologous end joining (NHEJ), works well in nearly all cell types, whereas knock-in via homology-directed repair (HDR) is more variable.

  • CRISPR–Cas holds the promise to transform the discovery and development of therapies to treat complex heritable and somatic disorders. Early applications in the field of cancer immunotherapy are entering clinical trials.

  • CRISPR–Cas gene editing expedites the generation of accurate cellular and animal models of human disease to facilitate drug discovery and validation. CRISPR–Cas could be used in all species that are commonly used during a typical preclinical drug development campaign.

  • The low barrier to deploying CRISPR–Cas technology has enabled its rapid spread throughout the scientific community and is revolutionizing biomedical research. CRISPR–Cas systems are excellent tools for large-scale functional screens using gene knockout (CRISPRn), inhibition (CRISPRi) or activation (CRISPRa).

  • Further evolution of CRISPR–Cas9 may enable cures for Mendelian diseases in somatic tissues by directly correcting the underlying disease-causing mutations. Pioneering work with zinc-finger nuclease (ZFN)-based and transcription activator-like effector nuclease (TALEN)-based therapies will determine the path to therapeutic gene editing with CRISPR–Cas.

Abstract

The recent development of CRISPR–Cas systems as easily accessible and programmable tools for genome editing and regulation is spurring a revolution in biology. Paired with the rapid expansion of reference and personalized genomic sequence information, technologies based on CRISPR–Cas are enabling nearly unlimited genetic manipulation, even in previously difficult contexts, including human cells. Although much attention has focused on the potential of CRISPR–Cas to cure Mendelian diseases, the technology also holds promise to transform the development of therapies to treat complex heritable and somatic disorders. In this Review, we discuss how CRISPR–Cas can affect the next generation of drugs by accelerating the identification and validation of high-value targets, uncovering high-confidence biomarkers and developing differentiated breakthrough therapies. We focus on the promises, pitfalls and hurdles of this revolutionary gene-editing technology, discuss key aspects of different CRISPR–Cas screening platforms and offer our perspectives on the best practices in genome engineering.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Pipeline of CRISPR–Cas-assisted drug discovery.
Figure 2: CRISPR–Cas in the generation of cellular models and large-scale screens.
Figure 3: Applications of CRISPR–Cas in in vivo screens and the generation of animal models.

References

  1. 1

    Crick, F. Central dogma of molecular biology. Nature 227, 561–563 (1970).

    CAS  PubMed  Google Scholar 

  2. 2

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

    CAS  Article  Google Scholar 

  3. 3

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

    CAS  Article  Google Scholar 

  4. 4

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

    Article  Google Scholar 

  5. 5

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

    CAS  Article  Google Scholar 

  6. 6

    Cho, S. W., Kim, S., Kim, J. M. & Kim, J.-S. Targeted genome engineering in human cells with the Cas9 RNA-guided endonuclease. Nat. Biotechnol. 31, 230–232 (2013). References 2–6 describe the development and first use of the CRISPR–Cas9 system for genome editing in mammalian cells.

    CAS  Google Scholar 

  7. 7

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

    CAS  PubMed  PubMed Central  Google Scholar 

  8. 8

    Hopkins, A. L. & Groom, C. R. The druggable genome. Nat. Rev. Drug Discov. 1, 727–730 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9

    Wright, A. V., Nuñez, J. K. & Doudna, J. A. Biology and applications of CRISPR systems: harnessing nature's toolbox for genome engineering. Cell 164, 29–44 (2016).

    CAS  Google Scholar 

  10. 10

    Doudna, J. A. & Charpentier, E. The new frontier of genome engineering with CRISPR–Cas9. Science 346, 1258096 (2014).

    PubMed  PubMed Central  Google Scholar 

  11. 11

    Hsu, P. D., Lander, E. S. & Zhang, F. Development and applications of CRISPR–Cas9 for genome engineering. Cell 157, 1262–1278 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12

    Moore, J. K. & Haber, J. E. Cell cycle and genetic requirements of two pathways of nonhomologous end-joining repair of double-strand breaks in Saccharomyces cerevisiae. Mol. Cell. Biol. 16, 2164–2173 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13

    Guirouilh-Barbat, J. et al. Impact of the KU80 pathway on NHEJ-induced genome rearrangements in mammalian cells. Mol. Cell 14, 611–623 (2004).

    CAS  Google Scholar 

  14. 14

    Roth, D. B. & Wilson, J. H. Nonhomologous recombination in mammalian cells: role for short sequence homologies in the joining reaction. Mol. Cell. Biol. 6, 4295–4304 (1986).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15

    Resnick, M. A. The repair of double-strand breaks in DNA; a model involving recombination. J. Theor. Biol. 59, 97–106 (1976).

    CAS  PubMed  Google Scholar 

  16. 16

    Orr-Weaver, T. L., Szostak, J. W. & Rothstein, R. J. Yeast transformation: a model system for the study of recombination. Proc. Natl Acad. Sci. USA 78, 6354–6358 (1981).

    CAS  PubMed  Google Scholar 

  17. 17

    Szostak, J. W., Orr-Weaver, T. L., Rothstein, R. J. & Stahl, F. W. The double-strand-break repair model for recombination. Cell 33, 25–35 (1983).

    CAS  Google Scholar 

  18. 18

    Lin, F. L., Sperle, K. & Sternberg, N. Model for homologous recombination during transfer of DNA into mouse L cells: role for DNA ends in the recombination process. Mol. Cell. Biol. 4, 1020–1034 (1984).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. 19

    Jasin, M., de Villiers, J., Weber, F. & Schaffner, W. High frequency of homologous recombination in mammalian cells between endogenous and introduced SV40 genomes. Cell 43, 695–703 (1985).

    CAS  PubMed  Google Scholar 

  20. 20

    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 

  21. 21

    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 

  22. 22

    Gilbert, L. A. et al. CRISPR-mediated modular RNA-guided regulation of transcription in eukaryotes. Cell 154, 442–451 (2013). References 20–22 describe the development and application of CRISPRi and CRISPRa.

    CAS  Article  Google Scholar 

  23. 23

    The Cancer Genome Atlas Research Network. Comprehensive genomic characterization of squamous cell lung cancers. Nature 489, 519–525 (2012).

  24. 24

    The Cancer Genome Atlas Research Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature 487, 330–337 (2012).

  25. 25

    The Cancer Genome Atlas Research Network. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 455, 1061–1068 (2013).

  26. 26

    The Cancer Genome Atlas Research Network. Integrated genomic analyses of ovarian carcinoma. Nature 474, 609–615 (2011).

  27. 27

    The Cancer Genome Atlas Research Network. Comprehensive molecular portraits of human breast tumours. Nature 490, 61–70 (2012).

  28. 28

    Barretina, J. et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483, 603–607 (2012).

    CAS  Article  Google Scholar 

  29. 29

    ENCODE Project Consortium. The ENCODE (ENCyclopedia Of DNA Elements) Project. Science 306, 636–640 (2004).

  30. 30

    ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

  31. 31

    Thon, N., Kreth, S. & Kreth, F.-W. Personalized treatment strategies in glioblastoma: MGMT promoter methylation status. Onco. Targets Ther. 6, 1363–1372 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32

    Shirasawa, S., Furuse, M., Yokoyama, N. & Sasazuki, T. Altered growth of human colon cancer cell lines disrupted at activated Ki-ras. Science 260, 85–88 (1993).

    CAS  PubMed  Google Scholar 

  33. 33

    Sur, S. et al. A panel of isogenic human cancer cells suggests a therapeutic approach for cancers with inactivated p53. Proc. Natl Acad. Sci. USA 106, 3964–3969 (2009).

    CAS  PubMed  Google Scholar 

  34. 34

    Torrance, C. J., Agrawal, V., Vogelstein, B. & Kinzler, K. W. Use of isogenic human cancer cells for high-throughput screening and drug discovery. Nat. Biotechnol. 19, 940–945 (2001).

    CAS  PubMed  Google Scholar 

  35. 35

    Yun, J. et al. Glucose deprivation contributes to the development of KRAS pathway mutations in tumor cells. Science 325, 1555–1559 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36

    Ran, F. A. et al. Genome engineering using the CRISPR–Cas9 system. Nat. Protoc. 8, 2281–2308 (2013).

    CAS  Article  Google Scholar 

  37. 37

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

    CAS  PubMed  Google Scholar 

  38. 38

    Grobarczyk, B., Franco, B., Hanon, K. & Malgrange, B. Generation of isogenic human iPS cell line precisely corrected by genome editing using the CRISPR/Cas9 system. Stem Cell Rev. 11, 774–787 (2015).

    CAS  Google Scholar 

  39. 39

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

    CAS  PubMed  Google Scholar 

  40. 40

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

    CAS  PubMed  Google Scholar 

  41. 41

    Carette, J. E. et al. Haploid genetic screens in human cells identify host factors used by pathogens. Science 326, 1231–1235 (2009).

    CAS  Google Scholar 

  42. 42

    Carette, J. E. et al. Ebola virus entry requires the cholesterol transporter Niemann–Pick C1. Nature 477, 340–343 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43

    Shi, J. et al. Discovery of cancer drug targets by CRISPR–Cas9 screening of protein domains. Nat. Biotechnol. 33, 661–667 (2015). This article shows how CRISPRn-mediated targeting of functional protein domains improves knockout screening.

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44

    Kasap, C., Elemento, O. & Kapoor, T. M. DrugTargetSeqR: a genomics- and CRISPR–Cas9-based method to analyze drug targets. Nat. Chem. Biol. 10, 626–628 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45

    Smurnyy, Y. et al. DNA sequencing and CRISPR–Cas9 gene editing for target validation in mammalian cells. Nat. Chem. Biol. 10, 623–625 (2014).

    CAS  PubMed  Google Scholar 

  46. 46

    Chen, J., Ye, Y., Sun, H. & Shi, G. Association between KRAS codon 13 mutations and clinical response to anti-EGFR treatment in patients with metastatic colorectal cancer: results from a meta-analysis. Cancer Chemother. Pharmacol. 71, 265–272 (2013).

    CAS  PubMed  Google Scholar 

  47. 47

    Vogelstein, B. et al. Cancer genome landscapes. Science 339, 1546–1558 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48

    Paix, A. et al. Scalable and versatile genome editing using linear DNAs with microhomology to Cas9 Sites in Caenorhabditis elegans. Genetics 198, 1347–1356 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49

    Paix, A., Schmidt, H. & Seydoux, G. Cas9-assisted recombineering in C. elegans: genome editing using in vivo assembly of linear DNAs. Nucleic Acids Res. 44, e128 (2016).

    PubMed  PubMed Central  Google Scholar 

  50. 50

    Richardson, C. D., Ray, G. J., DeWitt, M. A., Curie, G. L. & Corn, J. E. Enhancing homology-directed genome editing by catalytically active and inactive CRISPR–Cas9 using asymmetric donor DNA. Nat. Biotechnol. 34, 339–344 (2016). Here, mechanism-guided design of ssDNA templates is used for efficient HDR.

    CAS  PubMed  Google Scholar 

  51. 51

    Paquet, D. et al. Efficient introduction of specific homozygous and heterozygous mutations using CRISPR/Cas9. Nature 533, 125–129 (2016).

    CAS  Google Scholar 

  52. 52

    Nakade, S. et al. Microhomology-mediated end-joining-dependent integration of donor DNA in cells and animals using TALENs and CRISPR/Cas9. Nat. Commun. 5, 5560 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53

    Sakuma, T., Nakade, S., Sakane, Y., Suzuki, K.-I. T. & Yamamoto, T. MMEJ-assisted gene knock-in using TALENs and CRISPR–Cas9 with the PITCh systems. Nat. Protoc. 11, 118–133 (2016).

    CAS  PubMed  Google Scholar 

  54. 54

    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 

  55. 55

    He, X. et al. Knock-in of large reporter genes in human cells via CRISPR/Cas9-induced homology-dependent and independent DNA repair. Nucleic Acids Res. 44, e85 (2016)

    PubMed  PubMed Central  Google Scholar 

  56. 56

    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, 420–424 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. 57

    Nishida, K. et al. Targeted nucleotide editing using hybrid prokaryotic and vertebrate adaptive immune systems. Science 353, aaf8729 (2016). References 56 and 57 show the engineering of chimeric Cas enzymes for position-specific base editing.

    PubMed  Google Scholar 

  58. 58

    Cheung, H. W. et al. Systematic investigation of genetic vulnerabilities across cancer cell lines reveals lineage-specific dependencies in ovarian cancer. Proc. Natl Acad. Sci. USA 108, 12372–12377 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. 59

    Fellmann, C. & Lowe, S. W. Stable RNA interference rules for silencing. Nat. Cell Biol. 16, 10–18 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. 60

    Deans, R. M. et al. Parallel shRNA and CRISPR–Cas9 screens enable antiviral drug target identification. Nat. Chem. Biol. 12, 361–366 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. 61

    Jae, L. T. et al. Lassa virus entry requires a trigger-induced receptor switch. Science 344, 1506–1510 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. 62

    Blomen, V. A. et al. Gene essentiality and synthetic lethality in haploid human cells. Science 350, 1092–1096 (2015).

    CAS  Google Scholar 

  63. 63

    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 

  64. 64

    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 

  65. 65

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

    CAS  Google Scholar 

  66. 66

    Koike-Yusa, H., Li, Y., Tan, E.-P., Velasco-Herrera, M. D. C. & Yusa, K. Genome-wide recessive genetic screening in mammalian cells with a lentiviral CRISPR-guide RNA library. Nat. Biotechnol. 32, 267–273 (2014). References 65 and 66 are pioneering genome-wide CRISPRn screens.

    CAS  Google Scholar 

  67. 67

    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). This article describes the development of an improved sgRNA design tool.

    CAS  PubMed  PubMed Central  Google Scholar 

  68. 68

    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 

  69. 69

    Aguirre, A. J. et al. Genomic copy number dictates a gene-independent cell response to CRISPR/Cas9 targeting. Cancer Discov. 6, 914–929 (2016). References 64, 68 and 69 show that CRISPR–Cas9 can generate false-positive effects at amplified loci.

    CAS  PubMed  PubMed Central  Google Scholar 

  70. 70

    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).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. 71

    Marceau, C. D. et al. Genetic dissection of Flaviviridae host factors through genome-scale CRISPR screens. Nature 535, 159–163 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. 72

    Chen, S. et al. Genome-wide CRISPR screen in a mouse model of tumor growth and metastasis. Cell 160, 1246–1260 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. 73

    Mandegar, M. A. et al. CRISPR interference efficiently induces specific and reversible gene silencing in human iPSCs. Cell Stem Cell 18, 541–553 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  74. 74

    Kampmann, M. et al. Next-generation libraries for robust RNA interference-based genome-wide screens. Proc. Natl Acad. Sci. USA 112, E3384–E3391 (2015).

    CAS  PubMed  Google Scholar 

  75. 75

    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 

  76. 76

    Hilton, I. B. et al. Epigenome editing by a CRISPR–Cas9-based acetyltransferase activates genes from promoters and enhancers. Nat. Biotechnol. 33, 510–517 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. 77

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

    CAS  PubMed  Google Scholar 

  78. 78

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

    CAS  PubMed  PubMed Central  Google Scholar 

  79. 79

    Chakraborty, S. et al. A CRISPR/Cas9-based system for reprogramming cell lineage specification. Stem Cell Rep. 3, 940–947 (2014).

    CAS  Google Scholar 

  80. 80

    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 

  81. 81

    Chavez, A. et al. Comparison of Cas9 activators in multiple species. Nat. Methods 13, 563–567 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  82. 82

    Sidik, S. M. et al. A genome-wide CRISPR screen in Toxoplasma identifies essential apicomplexan genes. Cell 166, 1423–1435.e12 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  83. 83

    Canver, M. C. et al. BCL11A enhancer dissection by Cas9-mediated in situ saturating mutagenesis. Nature 527, 192–197 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  84. 84

    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 

  85. 85

    Wang, H. et al. One-step generation of mice carrying mutations in multiple genes by CRISPR/Cas-mediated genome engineering. Cell 153, 910–918 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  86. 86

    Yang, H. et al. One-step generation of mice carrying reporter and conditional alleles by CRISPR/Cas-mediated genome engineering. Cell 154, 1370–1379 (2013). References 85 and 86 show one-step generation of multi-allelic genetically engineered mouse models.

    CAS  PubMed  PubMed Central  Google Scholar 

  87. 87

    Chen, S., Lee, B., Lee, A. Y.-F., Modzelewski, A. J. & He, L. Highly efficient mouse genome editing by CRISPR ribonucleoprotein electroporation of zygotes. J. Biol. Chem. 291, 14457–14467 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  88. 88

    Wang, W. et al. Delivery of Cas9 protein into mouse zygotes through a series of electroporation dramatically increases the efficiency of model creation. J. Genet. Genomics 43, 319–327 (2016).

    PubMed  PubMed Central  Google Scholar 

  89. 89

    Qin, W. et al. Efficient CRISPR/Cas9-mediated genome editing in mice by zygote electroporation of nuclease. Genetics 200, 423–430 (2015). References 87–89 show direct zygote editing by electroporation of Cas9 RNP or Cas9 mRNA and sgRNA.

    CAS  PubMed  PubMed Central  Google Scholar 

  90. 90

    Premsrirut, P. K. K. et al. A rapid and scalable system for studying gene function in mice using conditional RNA interference. Cell 145, 145–158 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  91. 91

    Beard, C., Hochedlinger, K., Plath, K., Wutz, A. & Jaenisch, R. Efficient method to generate single-copy transgenic mice by site-specific integration in embryonic stem cells. Genesis 44, 23–28 (2006).

    CAS  Google Scholar 

  92. 92

    Nagy, A. et al. Embryonic stem cells alone are able to support fetal development in the mouse. Development 110, 815–821 (1990).

    CAS  Google Scholar 

  93. 93

    Nagy, A., Rossant, J., Nagy, R., Abramow-Newerly, W. & Roder, J. C. Derivation of completely cell culture-derived mice from early-passage embryonic stem cells. Proc. Natl Acad. Sci. USA 90, 8424–8428 (1993).

    CAS  Google Scholar 

  94. 94

    Sanchez-Rivera, F. J. et al. Rapid modelling of cooperating genetic events in cancer through somatic genome editing. Nature 516, 428–431 (2014). References 94 and 95 describe somatic gene editing in mice.

    CAS  PubMed  PubMed Central  Google Scholar 

  95. 95

    Xue, W. et al. CRISPR-mediated direct mutation of cancer genes in the mouse liver. Nature 514, 380–384 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  96. 96

    Sanchez-Rivera, F. J., Jacks, T., Sánchez-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 

  97. 97

    Yin, H. et al. Genome editing with Cas9 in adult mice corrects a disease mutation and phenotype. Nat. Biotechnol. 32, 551–553 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  98. 98

    Tabebordbar, M. et al. In vivo gene editing in dystrophic mouse muscle and muscle stem cells. Science 351, 407–411 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  99. 99

    Long, C. et al. Postnatal genome editing partially restores dystrophin expression in a mouse model of muscular dystrophy. Science 351, 400–403 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  100. 100

    Nelson, C. E. et al. In vivo genome editing improves muscle function in a mouse model of Duchenne muscular dystrophy. Science 351, 403–407 (2016).

    CAS  Google Scholar 

  101. 101

    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 

  102. 102

    Choi, P. S. & Meyerson, M. Targeted genomic rearrangements using CRISPR/Cas technology. Nat. Commun. 5, 3728 (2014). References 101 and 102 describe the in situ generation of somatic chromosomal rearrangements.

    CAS  PubMed  PubMed Central  Google Scholar 

  103. 103

    DuPage, M. & Jacks, T. Genetically engineered mouse models of cancer reveal new insights about the antitumor immune response. Curr. Opin. Immunol. 25, 192–199 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  104. 104

    Li, D. et al. Heritable gene targeting in the mouse and rat using a CRISPR–Cas system. Nat. Biotechnol. 31, 681–683 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  105. 105

    Zou, Q. et al. Generation of gene-target dogs using CRISPR/Cas9 system. J. Mol. Cell Biol. 7, 580–583 (2015).

    PubMed  Google Scholar 

  106. 106

    Niu, Y. et al. Generation of gene-modified cynomolgus monkey via Cas9/RNA-mediated gene targeting in one-cell embryos. Cell 156, 836–843 (2014). This article describes the pioneering application of gene editing with Cas9 in non-human primates.

    CAS  PubMed  PubMed Central  Google Scholar 

  107. 107

    Chen, Y. et al. Functional disruption of the dystrophin gene in rhesus monkey using CRISPR/Cas9. Hum. Mol. Genet. 24, 3764–3774 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  108. 108

    Yang, L. et al. Genome-wide inactivation of porcine endogenous retroviruses (PERVs). Science 350, 1101–1104 (2015).

    CAS  PubMed  Google Scholar 

  109. 109

    Matsuoka, Y., Lamirande, E. W. & Subbarao, K. The ferret model for influenza. Curr. Protoc. Microbiol. http://dx.doi.org/10.1002/9780471729259.mc15g02s13 (2009).

  110. 110

    Clark, S., Hall, Y. & Williams, A. Animal models of tuberculosis: guinea pigs. Cold Spring Harb. Perspect. Med. 5, a018572 (2015).

    PubMed Central  Google Scholar 

  111. 111

    Tsai, S. Q. et al. GUIDE-seq enables genome-wide profiling of off-target cleavage by CRISPR–Cas nucleases. Nat. Biotechnol. 33, 187–197 (2015).

    CAS  Google Scholar 

  112. 112

    Crosetto, N. et al. Nucleotide-resolution DNA double-strand break mapping by next-generation sequencing. Nat. Methods 10, 361–365 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  113. 113

    Kuscu, C., Arslan, S., Singh, R., Thorpe, J. & Adli, M. Genome-wide analysis reveals characteristics of off-target sites bound by the Cas9 endonuclease. Nat. Biotechnol. 32, 677–683 (2014).

    CAS  Google Scholar 

  114. 114

    Gori, J. L. et al. Delivery and specificity of CRISPR–Cas9 genome editing technologies for human gene therapy. Hum. Gene Ther. 26, 443–451 (2015).

    CAS  PubMed  Google Scholar 

  115. 115

    O'Geen, H., Yu, A. S. & Segal, D. J. How specific is CRISPR/Cas9 really? Curr. Opin. Chem. Biol. 29, 72–78 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  116. 116

    Bolukbasi, M. F., Gupta, A. & Wolfe, S. A. Creating and evaluating accurate CRISPR–Cas9 scalpels for genomic surgery. Nat. Methods 13, 41–50 (2016).

    CAS  PubMed  Google Scholar 

  117. 117

    Hsu, P. D. et al. DNA targeting specificity of RNA-guided Cas9 nucleases. Nat. Biotechnol. 31, 827–832 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  118. 118

    Lin, Y. et al. CRISPR/Cas9 systems have off-target activity with insertions or deletions between target DNA and guide RNA sequences. Nucleic Acids Res. 42, 7473–7485 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  119. 119

    Stemmer, M., Thumberger, T., Del Sol Keyer, M., Wittbrodt, J. & Mateo, J. L. CCTop: an intuitive, flexible and reliable CRISPR/Cas9 target prediction tool. PLoS ONE 10, e0124633 (2015).

    PubMed  PubMed Central  Google Scholar 

  120. 120

    Bae, S., Park, J. & Kim, J.-S. Cas-OFFinder: a fast and versatile algorithm that searches for potential off-target sites of Cas9 RNA-guided endonucleases. Bioinformatics 30, 1473–1475 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  121. 121

    Heigwer, F., Kerr, G. & Boutros, M. E-CRISP: fast CRISPR target site identification. Nat. Methods 11, 122–123 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  122. 122

    Haeussler, M. et al. Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR. Genome Biol. 17, 148 (2016).

    PubMed  PubMed Central  Google Scholar 

  123. 123

    Labun, K., Montague, T. G., Gagnon, J. A., Thyme, S. B. & Valen, E. CHOPCHOP v2: a web tool for the next generation of CRISPR genome engineering. Nucleic Acids Res. 44, W272–W276 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  124. 124

    Mali, P. et al. CAS9 transcriptional activators for target specificity screening and paired nickases for cooperative genome engineering. Nat. Biotechnol. 31, 833–838 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  125. 125

    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 

  126. 126

    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 

  127. 127

    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 

  128. 128

    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 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  129. 129

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

    PubMed  PubMed Central  Google Scholar 

  130. 130

    Slaymaker, I. M. et al. Rationally engineered Cas9 nucleases with improved specificity. Science 351, 84–88 (2016). References 129 and 130 describe the development of a Cas9 nuclease with reduced off-target activity.

    CAS  PubMed  PubMed Central  Google Scholar 

  131. 131

    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 

  132. 132

    Davis, K. M., Pattanayak, V., Thompson, D. B., Zuris, J. A. & Liu, D. R. Small molecule-triggered Cas9 protein with improved genome-editing specificity. Nat. Chem. Biol. 11, 316–318 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  133. 133

    Nihongaki, Y., Kawano, F., Nakajima, T. & Sato, M. Photoactivatable CRISPR–Cas9 for optogenetic genome editing. Nat. Biotechnol. 33, 755–760 (2015).

    CAS  PubMed  Google Scholar 

  134. 134

    Oakes, B. L. et al. Profiling of engineering hotspots identifies an allosteric CRISPR–Cas9 switch. Nat. Biotechnol. 34, 646–651 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  135. 135

    Maus, M. V., Grupp, S. A., Porter, D. L. & June, C. H. Antibody-modified T cells: CARs take the front seat for hematologic malignancies. Blood 123, 2625–2635 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  136. 136

    Torikai, H. et al. A foundation for universal T-cell based immunotherapy: T cells engineered to express a CD19-specific chimeric-antigen-receptor and eliminate expression of endogenous TCR. Blood 119, 5697–5705 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  137. 137

    Qasim, W. et al. First clinical application of TALEN engineered universal CAR19 T cells in B-ALL. Blood 126, 2046 (2015).

    Google Scholar 

  138. 138

    Torikai, H. et al. Toward eliminating HLA class I expression to generate universal cells from allogeneic donors. Blood 122, 1341–1349 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  139. 139

    Lloyd, A., Vickery, O. N. & Laugel, B. Beyond the antigen receptor: editing the genome of T-cells for cancer adoptive cellular therapies. Front. Immunol. 4, 221 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  140. 140

    Hoos, A. Development of immuno-oncology drugs — from CTLA4 to PD1 to the next generations. Nat. Rev. Drug Discov. 15, 235–247 (2016).

    CAS  PubMed  Google Scholar 

  141. 141

    Cyranoski, D. CRISPR gene-editing tested in a person for the first time. Nature 539, 479 (2016).

    CAS  PubMed  Google Scholar 

  142. 142

    Sadelain, M., Papapetrou, E. P. & Bushman, F. D. Safe harbours for the integration of new DNA in the human genome. Nat. Rev. Cancer 12, 51–58 (2012).

    CAS  Google Scholar 

  143. 143

    Kalos, M. & June, C. H. Adoptive T cell transfer for cancer immunotherapy in the era of synthetic biology. Immunity 39, 49–60 (2013).

    CAS  PubMed  Google Scholar 

  144. 144

    Tebas, P. et al. Gene editing of CCR5 in autologous CD4 T cells of persons infected with HIV. N. Engl. J. Med. 370, 901–910 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  145. 145

    Hütter, G. et al. Long-term control of HIV by CCR5 Delta32/Delta32 stem-cell transplantation. N. Engl. J. Med. 360, 692–698 (2009).

    PubMed  Google Scholar 

  146. 146

    Perez, E. E. et al. Establishment of HIV-1 resistance in CD4+ T cells by genome editing using zinc-finger nucleases. Nat. Biotechnol. 26, 808–816 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  147. 147

    Holt, N. et al. Human hematopoietic stem/progenitor cells modified by zinc-finger nucleases targeted to CCR5 control HIV-1 in vivo. Nat. Biotechnol. 28, 839–847 (2010). References 144 and 147 use ex vivo gene editing with ZFNs for HIV therapy.

    CAS  PubMed  PubMed Central  Google Scholar 

  148. 148

    Yang, L. et al. Optimization of scarless human stem cell genome editing. Nucleic Acids Res. 41, 9049–9061 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  149. 149

    Mandal, P. K. et al. Efficient ablation of genes in human hematopoietic stem and effector cells using CRISPR/Cas9. Cell Stem Cell 15, 643–652 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  150. 150

    Hoban, M. D. et al. Correction of the sickle cell disease mutation in human hematopoietic stem/progenitor cells. Blood 125, 2597–2604 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  151. 151

    Wang, J. et al. Homology-driven genome editing in hematopoietic stem and progenitor cells using ZFN mRNA and AAV6 donors. Nat. Biotechnol. 33, 1256–1263 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  152. 152

    DeWitt, M. A. et al. Selection-free genome editing of the sickle mutation in human adult hematopoietic stem/progenitor cells. Sci. Transl Med. 8, 360ra134 (2016).

    PubMed  PubMed Central  Google Scholar 

  153. 153

    Cao, A. & Galanello, R. Beta-thalassemia. Genet. Med. 12, 61–76 (2010).

    CAS  PubMed  Google Scholar 

  154. 154

    Bauer, D. E. et al. An erythroid enhancer of BCL11A subject to genetic variation determines fetal hemoglobin level. Science 342, 253–257 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  155. 155

    Vierstra, J. et al. Functional footprinting of regulatory DNA. Nat. Methods 12, 927–930 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  156. 156

    Roberts, S. A. et al. Engineering Factor Viii for hemophilia gene therapy. J. Genet. Syndr. Gene Ther. 1, S1–006 (2011).

    PubMed  PubMed Central  Google Scholar 

  157. 157

    Stripecke, R. et al. Immune response to green fluorescent protein: implications for gene therapy. Gene Ther. 6, 1305–1312 (1999).

    CAS  PubMed  Google Scholar 

  158. 158

    Cavazzana, M. et al. Outcomes of gene therapy for severe sickle disease and beta-thalassemia major via transplantation of autologous hematopoietic stem cells transduced ex vivo with a lentiviral β-AT87Q-globin vector. Blood 126, abstr. 202 (2015).

    Google Scholar 

  159. 159

    Kanter, J. et al. Initial results from study Hgb-206: a phase 1 study evaluating gene therapy by transplantation of autologous CD34+ stem cells transduced ex vivo with the lentiglobin BB305 lentiviral vector in subjects with severe sickle cell disease. Blood 126, abstr. 3233 (2015).

    Google Scholar 

Download references

Acknowledgements

The authors thank members of the Doudna and Corn laboratories, as well as F. Urnov for insightful comments and discussions. C.F. is supported by a US National Institutes of Health K99/R00 Pathway to Independence Award (K99GM118909) from the National Institute of General Medical Sciences (NIGMS). The Innovative Genomics Initiative (IGI) is supported by the Li Ka Shing Foundation.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Jacob E. Corn.

Ethics declarations

Competing interests

J.A.D. is employed by the Howard Hughes Medical Institute (HHMI) and works at the University at California (UC), Berkeley, USA. UC Berkeley and HHMI have patents pending for CRISPR technologies on which J.A.D. and J.E.C. are inventors. J.A.D. is the executive director and J.E.C is the scientific director of the Innovative Genomics Initiative (IGI) at UC Berkeley and University of California, San Francisco. J.A.D. is a co-founder of Editas Medicine, Intellia Therapeutics and Caribou Biosciences, and a scientific adviser to Caribou, Intellia, eFFECTOR Therapeutics and Driver. J.E.C. is a consultant to or has funded research collaborations with AstraZeneca, CRISPR Therapeutics, Editas Medicine, Genentech, Intellia and Pfizer.

Related links

PowerPoint slides

Supplementary information

Supplementary information S1 (table)

Partial list of natural and engineered Cas9 variants (PDF 193 kb)

Glossary

Non-homologous end joining

(NHEJ). The repair of double-strand DNA breaks by direct ligation of the broken ends. No homology is required to promote the end-joining reaction, and it can result in the introduction of small non-templated insertions or deletions (indels).

Homology-directed repair

(HDR). The repair of double-strand DNA breaks using an endogenous or exogenous DNA template with homology to regions flanking the break.

CRISPRa

The activation of transcription through RNA-guided recruitment of a catalytically inactive Cas9 fused to transcriptional activators.

CRISPRi

The inhibition of transcription through RNA-guided recruitment of a catalytically inactive Cas9 fused to transcriptional repressors.

CRISPR nuclease

(CRISPRn). Targeting a DNA sequence with catalytically active Cas9 to generate a double-strand break or a nick.

Backcrossing

The process of breeding a hybrid organism with an individual genetically similar to one of its parents, with the objective of diluting the genetic contribution of the other parent to subsequent generations.

Protospacer adjacent motif

(PAM). Short genomic sequence adjacent to the sequence targeted by the guide RNA that is required for recognition by Cas effectors. This sequence varies based on the identity of the effector (for example, Cas9 versus Cpf1) and species (for example, Streptococcus pyogenes versus Francisella novicida).

Investigational new drugs

(INDs). A designation used to describe drugs that have permission from the US Food and Drug Administration (FDA) to be shipped across state lines, thus allowing these drugs to be tested in human clinical trials. IND applications are reviewed by the FDA to ensure that testing of the drug in humans does not pose excessive risk to the patient.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Fellmann, C., Gowen, B., Lin, PC. et al. Cornerstones of CRISPR–Cas in drug discovery and therapy. Nat Rev Drug Discov 16, 89–100 (2017). https://doi.org/10.1038/nrd.2016.238

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing