Open Access
Med Sci (Paris)
Volume 35, Number 4, Avril 2019
Page(s) 309 - 315
Section M/S Revues
Published online 30 April 2019
  1. Hess GT, Tycko J, Yao D, Bassik MC. Methods and applications of CRISPR-mediated base editing in eukaryotic genomes. Mol Cell 2017 ; 68 : 26–43. [CrossRef] [PubMed] [Google Scholar]
  2. Arber W.. Restriction endonucleases. Angew Chem Int Ed Engl 1978 ; 17 : 73–79. [CrossRef] [PubMed] [Google Scholar]
  3. Redondo P, Prieto J, Munoz IG, et al. Molecular basis of xeroderma pigmentosum group C DNA recognition by engineered meganucleases. Nature 2008 ; 456 : 107–111. [CrossRef] [PubMed] [Google Scholar]
  4. Stoddard BL. Homing endonucleases : from microbial genetic invaders to reagents for targeted DNA modification. Structure 2011 ; 19 : 7–15. [CrossRef] [PubMed] [Google Scholar]
  5. Urnov FD, Miller JC, Lee YL, et al. Highly efficient endogenous human gene correction using designed zinc-finger nucleases. Nature 2005 ; 435 : 646–651. [CrossRef] [PubMed] [Google Scholar]
  6. Tebas P, Stein D, Tang WW, et al. Gene editing of CCR5 in autologous CD4 T cells of persons infected with HIV. N Engl J Med 2014 ; 370 : 901–910. [Google Scholar]
  7. Sunderland M, Peggs Z. succesful translation and future prospects of TALEN editing for leukemia patients. Expert Opin Biol Ther 2018 ; 18 : 725–726. [Google Scholar]
  8. Cellectis. la FDA autorise l’essai clinique pour UCART22 en leucémie lymphoblastique aiguë à cellules B. [Google Scholar]
  9. Jordan B.. Les débuts de CRISPR en thérapie génique. Med Sci (Paris) 2016 ; 32 : 1035–1037. [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]
  10. Sharma R, Anguela XM, Doyon Y, et al. In vivo genome editing of the albumin locus as a platform for protein replacement therapy. Blood 2015 ; 126 : 1777–1784. [Google Scholar]
  11. Hirsch T, Rothoeft T, Teig N, et al. Regeneration of the entire human epidermis using transgenic stem cells. Nature 2017 ; 551 : 327–332. [CrossRef] [PubMed] [Google Scholar]
  12. Lee C, Bao G, Porteus MH, et al. Gene editing with Crispr-Cas9 for treating beta-hemoglobinopathies. Blood 2015; 126. [Google Scholar]
  13. Charlesworth C, Desphande P, Dever D, et al. Identification of pre-existing adaptive immunity to Cas9 proteins in humans. BioXriv 2018. [Google Scholar]
  14. Simhadri VL, McGill J, McMahon S, et al. Prevalence of pre-existing antibodies to CRISPR-associated nuclease Cas9 in the USA population. Mol Ther Methods Clin Dev 2018 ; 10 : 105–112. [CrossRef] [PubMed] [Google Scholar]
  15. Crudele JM, Chamberlain JS. Cas9 immunity creates challenges for CRISPR gene editing therapies. Nat Commun 2018 ; 9 : 3497. [CrossRef] [PubMed] [Google Scholar]
  16. Chen Y, Zhang Y. Application of the CRISPR/Cas9 system to drug resistance in breast cancer. Adv Sci (Weinh) 2018 ; 5 : 1700964. [CrossRef] [PubMed] [Google Scholar]
  17. Bredel M, Jacoby E. Chemogenomics : an emerging strategy for rapid target and drug discovery. Nat Rev Genet 2004 ; 5 : 262–275. [CrossRef] [PubMed] [Google Scholar]
  18. la Villa P.. miniaturisation pour la découverte de candidats médicaments. L’Actualité Chimique 2017; 67–70. [Google Scholar]
  19. Ks N. les modificateurs de la réponse biologique pour réduire l’inflammation : pleins feux sur les rusques d’infection. Pediatr Child Health 2012 ; 17 : 151–154. [CrossRef] [Google Scholar]
  20. Arnoldo A, Kittanakom S, Heisler LE, et al. A genome scale overexpression screen to reveal drug activity in human cells. Genome Med 2014 ; 6 : 32. [CrossRef] [PubMed] [Google Scholar]
  21. Konermann S, Brigham MD, Trevino AE, et al. Genome-scale transcriptional activation by an engineered CRISPR-Cas9 complex. Nature 2015 ; 517 : 583–588. [CrossRef] [PubMed] [Google Scholar]
  22. Rusk N.. CRISPR gain-of-function screens. Nat Methods 2015 ; 12 : 102–103. [CrossRef] [PubMed] [Google Scholar]
  23. le Sage C, Lawo S, Panicker P, et al. Dual direction CRISPR transcriptional regulation screening uncovers gene networks driving drug resistance. Sci Rep 2017 ; 7 : 17693. [CrossRef] [PubMed] [Google Scholar]
  24. Lin S, Liu K, Zhang Y, et al. Pharmacological targeting of p38 MAP-kinase 6 (MAP2K6) inhibits the growth of esophageal adenocarcinoma. Cell Signal 2018 ; 51 : 222–232. [CrossRef] [PubMed] [Google Scholar]
  25. Banerjee S, Ji C, Mayfield JE, et al. Ancient drug curcumin impedes 26S proteasome activity by direct inhibition of dual-specificity tyrosine-regulated kinase 2. Proc Natl Acad Sci USA 2018 ; 115 : 8155–8160. [CrossRef] [Google Scholar]
  26. Sabatine MS, Giugliano RP, Keech AC, et al. Evolocumab and clinical outcomes in patients with cardiovascular disease. N Engl J Med 2017 ; 376 : 1713–1722. [Google Scholar]
  27. Tao W, Yang A, Deng Z, Sun Y. CRISPR/Cas9-Based editing of streptomyces for discovery, characterization, and production of natural products. Front Microbiol 2018 ; 9 : 1660. [CrossRef] [PubMed] [Google Scholar]
  28. Zhang MM, Wong FT, Wang Y, et al. CRISPR-Cas9 strategy for activation of silent Streptomyces biosynthetic gene clusters. Nat Chem Biol 2017. 10.1038/nchembio.2341 [Google Scholar]
  29. Li L, Zheng G, Chen J, et al. Multiplexed site-specific genome engineering for overproducing bioactive secondary metabolites in actinomycetes. Metab Eng 2017 ; 40 : 80–92. [CrossRef] [PubMed] [Google Scholar]
  30. Birling MC, Herault Y, Pavlovic G. Modeling human disease in rodents by CRISPR/Cas9 genome editing. Mamm Genome 2017 ; 28 : 291–301. [CrossRef] [PubMed] [Google Scholar]
  31. Bhatia S, Daschkey S, Lang F, et al. Mouse models for pre-clinical drug testing in leukemia. Expert Opin Drug Discov 2016 ; 11 : 1081–1091. [CrossRef] [PubMed] [Google Scholar]
  32. hutchinson L, Kirk R. high drug attrition rates- where are we going wrong ? Nat Rev Clin Oncol 2011; 8. [Google Scholar]
  33. Perlman RL. Mouse models of human disease : an evolutionary perspective. Evol Med Public Health 2016 ; 2016 : 170–176. [PubMed] [Google Scholar]
  34. Takahashi T.. Organoids for drug discovery and personalized medicine. Annu Rev Pharmacol Toxicol 2019 ; 59 : 447–462. [Google Scholar]
  35. Borestrom C, Jonebring A, Guo J, et al. A CRISP(e)R view on kidney organoids allows generation of an induced pluripotent stem cell-derived kidney model for drug discovery. Kidney Int 2018 ; 94 : 1099–1110. [CrossRef] [PubMed] [Google Scholar]
  36. Clayton NP, Burwell A, Jensen H, et al. Preparation of three-dimensional (3-D) human liver (HepaRG) cultures for histochemical and immunohistochemical staining and light microscopic evaluation. Toxicol Pathol 2018 ; 46 : 653–659. [CrossRef] [PubMed] [Google Scholar]
  37. Higuchi Y, Kawai K, Kanaki T, et al. Functional polymer-dependent 3D culture accelerates the differentiation of HepaRG cells into mature hepatocytes. Hepatol Res 2016 ; 46 : 1045–1057. [CrossRef] [PubMed] [Google Scholar]
  38. Drost J, Clevers H. Organoids in cancer research. Nat Rev Cancer 2018 ; 18 : 407–418. [Google Scholar]
  39. Watanabe M, Buth JE, Vishlaghi N, et al. Self-organized cerebral organoids with human-specific features predict effective drugs to combat Zika virus infection. Cell Rep 2017 ; 21 : 517–532. [CrossRef] [PubMed] [Google Scholar]
  40. Vassilev LT, Vu BT, Graves B, et al. In vivo activation of the p53 pathway by small-molecule antagonists of MDM2. Science 2004 ; 303 : 844–848. [Google Scholar]
  41. Boccardo F, Canobbio L I. 5-fluorouracil, twenty-five years later. An appraisal. Chemioterapia 1983 ; 2 : 88–96. [Google Scholar]
  42. Auclair G, Weber M. Mechanisms of DNA methylation and demethylation in mammals. Biochimie 2012 ; 94 : 2202–2211. [CrossRef] [PubMed] [Google Scholar]
  43. Holtzman L, Gersbach CA. Editing the epigenome : reshaping the genomic landscape. Annu Rev Genomics Hum Genet 2018 ; 19 : 43–71. [CrossRef] [PubMed] [Google Scholar]
  44. Bian S, Repic M, Guo Z, et al. Genetically engineered cerebral organoids model brain tumor formation. Nat Methods 2018 ; 15 : 631–639. [CrossRef] [PubMed] [Google Scholar]

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