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dc.contributor.authorWong, Siu Lun
dc.contributor.authorCui, Cheryl
dc.contributor.authorPregernig, Gabriela
dc.contributor.authorMilani, Pamela
dc.contributor.authorChoi, Gigi C. G.
dc.contributor.authorAdam, Miriam
dc.contributor.authorPerli, Samuel D.
dc.contributor.authorKazer, Samuel Weisgurt
dc.contributor.authorGaillard de Saint Germain, Alethe
dc.contributor.authorHermann, Mario
dc.contributor.authorShalek, Alexander K
dc.contributor.authorFraenkel, Ernest
dc.contributor.authorLu, Timothy K
dc.date.accessioned2017-01-12T14:34:58Z
dc.date.available2017-01-12T14:34:58Z
dc.date.issued2016-02
dc.date.submitted2015-09
dc.identifier.issn0027-8424
dc.identifier.issn1091-6490
dc.identifier.urihttp://hdl.handle.net/1721.1/106350
dc.description.abstractThe orchestrated action of genes controls complex biological phenotypes, yet the systematic discovery of gene and drug combinations that modulate these phenotypes in human cells is labor intensive and challenging to scale. Here, we created a platform for the massively parallel screening of barcoded combinatorial gene perturbations in human cells and translated these hits into effective drug combinations. This technology leverages the simplicity of the CRISPR-Cas9 system for multiplexed targeting of specific genomic loci and the versatility of combinatorial genetics en masse (CombiGEM) to rapidly assemble barcoded combinatorial genetic libraries that can be tracked with high-throughput sequencing. We applied CombiGEM-CRISPR to create a library of 23,409 barcoded dual guide-RNA (gRNA) combinations and then perform a high-throughput pooled screen to identify gene pairs that inhibited ovarian cancer cell growth when they were targeted. We validated the growth-inhibiting effects of specific gene sets, including epigenetic regulators KDM4C/BRD4 and KDM6B/BRD4, via individual assays with CRISPR-Cas–based knockouts and RNA-interference–based knockdowns. We also tested small-molecule drug pairs directed against our pairwise hits and showed that they exerted synergistic antiproliferative effects against ovarian cancer cells. We envision that the CombiGEM-CRISPR platform will be applicable to a broad range of biological settings and will accelerate the systematic identification of genetic combinations and their translation into novel drug combinations that modulate complex human disease phenotypes.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grants DP2OD008435, P50GM098792, and R01 NS089076)en_US
dc.description.sponsorshipUnited States. Office of Naval Research (Grant N00014-13-1-0424)en_US
dc.description.sponsorshipUnited States. Defense Threat Reduction Agencyen_US
dc.description.sponsorshipLawrence Ellison Foundation (New Scholar in Aging Award)en_US
dc.description.sponsorshipCroucher Foundationen_US
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canada (Postdoctoral Fellowship)en_US
dc.language.isoen_US
dc.publisherNational Academy of Sciences (U.S.)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1073/pnas.1517883113en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourcePNASen_US
dc.titleMultiplexed barcoded CRISPR-Cas9 screening enabled by CombiGEMen_US
dc.typeArticleen_US
dc.identifier.citationWong, Alan S. L. et al. “Multiplexed Barcoded CRISPR-Cas9 Screening Enabled by CombiGEM.” Proceedings of the National Academy of Sciences 113.9 (2016): 2544–2549. © 2016 National Academy of Sciencesen_US
dc.contributor.departmentMassachusetts Institute of Technology. Synthetic Biology Centeren_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Medical Engineering & Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemistryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Research Laboratory of Electronicsen_US
dc.contributor.departmentRagon Institute of MGH, MIT and Harvarden_US
dc.contributor.mitauthorWong, Siu Lun
dc.contributor.mitauthorCui, Cheryl
dc.contributor.mitauthorPregernig, Gabriela
dc.contributor.mitauthorMilani, Pamela
dc.contributor.mitauthorChoi, Gigi C. G.
dc.contributor.mitauthorAdam, Miriam
dc.contributor.mitauthorPerli, Samuel D.
dc.contributor.mitauthorKazer, Samuel Weisgurt
dc.contributor.mitauthorGaillard de Saint Germain, Alethe
dc.contributor.mitauthorHermann, Mario
dc.contributor.mitauthorShalek, Alexander K
dc.contributor.mitauthorFraenkel, Ernest
dc.contributor.mitauthorLu, Timothy K
dc.relation.journalProceedings of the National Academy of Sciencesen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsWong, Alan S. L.; Choi, Gigi C. G.; Cui, Cheryl H.; Pregernig, Gabriela; Milani, Pamela; Adam, Miriam; Perli, Samuel D.; Kazer, Samuel W.; Gaillard, Aleth; Hermann, Mario; Shalek, Alex K.; Fraenkel, Ernest; Lu, Timothy K.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-5744-0873
dc.identifier.orcidhttps://orcid.org/0000-0002-0160-8742
dc.identifier.orcidhttps://orcid.org/0000-0001-7284-6337
dc.identifier.orcidhttps://orcid.org/0000-0003-0250-0474
dc.identifier.orcidhttps://orcid.org/0000-0002-8346-2184
dc.identifier.orcidhttps://orcid.org/0000-0002-7380-9594
dc.identifier.orcidhttps://orcid.org/0000-0001-9179-7972
dc.identifier.orcidhttps://orcid.org/0000-0001-9249-8181
dc.identifier.orcidhttps://orcid.org/0000-0002-9999-6690
mit.licensePUBLISHER_POLICYen_US


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