Data availability
All source data (including P values) are available in Supplementary Table 5. Raw FASTQ files have been deposited in the Sequence Read Archive under accession number PRJNA859154. Processed RNA-seq data (transcripts per million values and differentially expressed genes) are available in Supplementary Table 2.
Code availability
Code for analysis and data visualization is available at https://github.com/lukedow/iBE.git.
References
Goodwin, S., McPherson, J. D. & McCombie, W. R. Coming of age: ten years of next-generation sequencing technologies. Nat. Rev. Genet. 17, 333–351 (2016).
Article
CAS
PubMed
PubMed Central
Google Scholar
Landrum, M. J. et al. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 44, D862–D868 (2016).
Article
CAS
PubMed
Google Scholar
Vogelstein, B. et al. Cancer genome landscapes. Science 339, 1546–1558 (2013).
Article
CAS
PubMed
PubMed Central
Google Scholar
Vivanco, I. et al. Differential sensitivity of glioma- versus lung cancer-specific EGFR mutations to EGFR kinase inhibitors. Cancer Discov. 2, 458–471 (2012).
Article
CAS
PubMed
PubMed Central
Google Scholar
Hyman, D. M. et al. AKT inhibition in solid tumors with AKT1 mutations. J. Clin. Oncol. 35, 2251–2259 (2017).
Article
CAS
PubMed
PubMed Central
Google Scholar
Vasan, N. et al. Double PIK3CA mutations in cis increase oncogenicity and sensitivity to PI3Kα inhibitors. Science 366, 714–723 (2019).
Article
CAS
PubMed
PubMed Central
Google Scholar
Findlay, G. M. et al. Accurate classification of BRCA1 variants with saturation genome editing. Nature 562, 217–222 (2018).
Article
CAS
PubMed
PubMed Central
Google Scholar
Zafra, M. P. et al. Optimized base editors enable efficient editing in cells, organoids and mice. Nat. Biotechnol. 36, 888–893 (2018).
Article
CAS
PubMed
PubMed Central
Google Scholar
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).
Article
CAS
PubMed
PubMed Central
Google Scholar
Gaudelli, N. M. et al. Programmable base editing of A•T to G•C in genomic DNA without DNA cleavage. Nature 551, 464–471 (2017).
Article
CAS
PubMed
PubMed Central
Google Scholar
Gaudelli, N. M. et al. Directed evolution of adenine base editors with increased activity and therapeutic application. Nat. Biotechnol. 38, 892–900 (2020).
Article
CAS
PubMed
Google Scholar
Komor, A. C. et al. Improved base excision repair inhibition and bacteriophage Mu Gam protein yields C:G-to-T:A base editors with higher efficiency and product purity. Sci. Adv. 3, eaao4774 (2017).
Article
PubMed
PubMed Central
Google Scholar
Rothgangl, T. et al. In vivo adenine base editing of PCSK9 in macaques reduces LDL cholesterol levels. Nat. Biotechnol. 39, 949–957 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Villiger, L. et al. In vivo cytidine base editing of hepatocytes without detectable off-target mutations in RNA and DNA. Nat. Biomed. Eng. 5, 179–189 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Villiger, L. et al. Treatment of a metabolic liver disease by in vivo genome base editing in adult mice. Nat. Med. 24, 1519–1525 (2018).
Article
CAS
PubMed
Google Scholar
Song, C.-Q. et al. Adenine base editing in an adult mouse model of tyrosinaemia. Nat. Biomed. Eng. 4, 125–130 (2019).
Yeh, W. H., Chiang, H., Rees, H. A., Edge, A. S. B. & Liu, D. R. In vivo base editing of post-mitotic sensory cells. Nat. Commun. 9, 2184 (2018).
Article
PubMed
PubMed Central
Google Scholar
Banskota, S. et al. Engineered virus-like particles for efficient in vivo delivery of therapeutic proteins. Cell 185, 250–265 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Ryu, S. M. et al. Adenine base editing in mouse embryos and an adult mouse model of Duchenne muscular dystrophy. Nat. Biotechnol. 36, 536–539 (2018).
Article
CAS
PubMed
Google Scholar
Yang, L. et al. Amelioration of an inherited metabolic liver disease through creation of a de novo start codon by cytidine base editing. Mol. Ther. 28, 1673–1683 (2020).
Article
CAS
PubMed
PubMed Central
Google Scholar
Dow, L. E. et al. Conditional reverse tet-transactivator mouse strains for the efficient induction of TRE-regulated transgenes in mice. PLoS ONE 9, e95236 (2014).
Article
PubMed
PubMed Central
Google Scholar
Premsrirut, P. K. et al. A rapid and scalable system for studying gene function in mice using conditional RNA interference. Cell 145, 145–158 (2011).
Article
CAS
PubMed
PubMed Central
Google Scholar
Grunewald, J. et al. CRISPR DNA base editors with reduced RNA off-target and self-editing activities. Nat. Biotechnol. 37, 1041–1048 (2019).
Article
CAS
PubMed
PubMed Central
Google Scholar
Yan, N. et al. Cytosine base editors induce off-target mutations and adverse phenotypic effects in transgenic mice. Nat. Commun. 14, 1784 (2023).
Article
CAS
PubMed
PubMed Central
Google Scholar
Zehir, A. et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat. Med. 23, 703–713 (2017).
Article
CAS
PubMed
PubMed Central
Google Scholar
Zafra, M. P. et al. An in vivo Kras allelic series reveals distinct phenotypes of common oncogenic variants. Cancer Discov. 10, 1654–1671 (2020).
Article
CAS
PubMed
PubMed Central
Google Scholar
Schatoff, E. M. et al. Distinct CRC-associated APC mutations dictate response to tankyrase inhibition. Cancer Discov. 9, 1358–1371 (2019).
Katti, A. et al. GO: a functional reporter system to identify and enrich base editing activity. Nucleic Acids Res. 48, 2841–2852 (2020).
Article
CAS
PubMed
PubMed Central
Google Scholar
Sanchez-Rivera, F. J. et al. Base editing sensor libraries for high-throughput engineering and functional analysis of cancer-associated single nucleotide variants. Nat. Biotechnol. 40, 862–873 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Mehta, A. & Merkel, O. M. Immunogenicity of Cas9 protein. J. Pharm. Sci. 109, 62–67 (2020).
Article
CAS
PubMed
Google Scholar
Chew, W. L. et al. A multifunctional AAV–CRISPR–Cas9 and its host response. Nat. Methods 13, 868–874 (2016).
Article
CAS
PubMed
PubMed Central
Google Scholar
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).
Article
CAS
PubMed
PubMed Central
Google Scholar
Ruiz de Galarreta, M. et al. β-catenin activation promotes immune escape and resistance to anti-PD-1 therapy in hepatocellular carcinoma. Cancer Discov. 9, 1124–1141 (2019).
Calvisi, D. F. et al. Activation of the canonical Wnt/β-catenin pathway confers growth advantages in c-Myc/E2F1 transgenic mouse model of liver cancer. J. Hepatol. 42, 842–849 (2005).
Article
CAS
PubMed
Google Scholar
Hingorani, S. R. et al. Trp53R172H and KrasG12D cooperate to promote chromosomal instability and widely metastatic pancreatic ductal adenocarcinoma in mice. Cancer Cell 7, 469–483 (2005).
Article
CAS
PubMed
Google Scholar
Alsner, J. et al. A comparison between p53 accumulation determined by immunohistochemistry and TP53 mutations as prognostic variables in tumours from breast cancer patients. Acta Oncol. 47, 600–607 (2008).
Article
CAS
PubMed
Google Scholar
Freed-Pastor, W. A. & Prives, C. Mutant p53: one name, many proteins. Genes Dev. 26, 1268–1286 (2012).
Article
CAS
PubMed
PubMed Central
Google Scholar
Bartek, J., Iggo, R., Gannon, J. & Lane, D. P. Genetic and immunochemical analysis of mutant p53 in human breast cancer cell lines. Oncogene 5, 893–899 (1990).
CAS
PubMed
Google Scholar
Maresch, R. et al. Multiplexed pancreatic genome engineering and cancer induction by transfection-based CRISPR/Cas9 delivery in mice. Nat. Commun. 7, 10770 (2016).
Article
CAS
PubMed
PubMed Central
Google Scholar
Park, J. S. et al. Pancreatic cancer induced by in vivo electroporation-enhanced sleeping beauty transposon gene delivery system in mouse. Pancreas 43, 614–618 (2014).
Article
CAS
PubMed
Google Scholar
Annunziato, S. et al. In situ CRISPR–Cas9 base editing for the development of genetically engineered mouse models of breast cancer. EMBO J. 39, e102169 (2020).
Zhou, C. et al. Off-target RNA mutation induced by DNA base editing and its elimination by mutagenesis. Nature 571, 275–278 (2019).
Article
CAS
PubMed
Google Scholar
Arbab, M. et al. Determinants of base editing outcomes from target library analysis and machine learning. Cell 182, 463–480 (2020).
Article
CAS
PubMed
PubMed Central
Google Scholar
Marquart, K. F. et al. Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens. Nat. Commun. 12, 5114 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Pallaseni, A. et al. Predicting base editing outcomes using position-specific sequence determinants. Nucleic Acids Res. 50, 3551–3564 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Park, J. & Kim, H. K. Prediction of base editing efficiencies and outcomes using DeepABE and DeepCBE. Methods Mol. Biol. 2606, 23–32 (2023).
Article
PubMed
Google Scholar
Kim, Y. et al. High-throughput functional evaluation of human cancer-associated mutations using base editors. Nat. Biotechnol. 40, 874–884 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
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).
Article
PubMed
PubMed Central
Google Scholar
Bock, D. et al. In vivo prime editing of a metabolic liver disease in mice. Sci. Transl. Med. 14, eabl9238 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Davis, J. R. et al. Efficient prime editing in mouse brain, liver and heart with dual AAVs. Nat. Biotechnol. https://doi.org/10.1038/s41587-023-01758-z (2023).
Dow, L. E. et al. A pipeline for the generation of shRNA transgenic mice. Nat. Protoc. 7, 374–393 (2012).
Article
CAS
PubMed
PubMed Central
Google Scholar
O’Rourke, K. P., Ackerman, S., Dow, L. E. & Lowe, S. W. Isolation, culture, and maintenance of mouse intestinal stem cells. Bio Protoc. 6, e1733 (2016).
PubMed
Google Scholar
Huch, M. et al. Unlimited in vitro expansion of adult bi-potent pancreas progenitors through the Lgr5/R-spondin axis. EMBO J. 32, 2708–2721 (2013).
Article
CAS
PubMed
PubMed Central
Google Scholar
Zafra, M. P. et al. An in vivo Kras allelic series reveals distinct phenotypes of common ocogenic variants. Cancer Discov. 10, 1654–1671 (2020).
Amen, A. M. et al. Endogenous spacing enables co-processing of microRNAs and efficient combinatorial RNAi. Cell Rep. Methods 2, 100239 (2022).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Article
CAS
PubMed
Google Scholar
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Article
PubMed
PubMed Central
Google Scholar
Finn, J. D. et al. A single administration of CRISPR/Cas9 lipid nanoparticles achieves robust and persistent in vivo genome editing. Cell Rep. 22, 2227–2235 (2018).
Article
CAS
PubMed
Google Scholar
Paffenholz Stella, V. et al. Senescence induction dictates response to chemo- and immunotherapy in preclinical models of ovarian cancer. Proc. Natl Acad. Sci. USA 119, e2117754119 (2022).
Article
PubMed
PubMed Central
Google Scholar
Leibold, J. et al. Somatic tissue engineering in mouse models reveals an actionable role for WNT pathway alterations in prostate cancer metastasis. Cancer Discov. 10, 1038–1057 (2020).
Article
CAS
PubMed
PubMed Central
Google Scholar
Download references
Acknowledgements
We thank members of the Dow laboratory for advice and comments on the preparation of the paper. We would like to acknowledge K. Tsanov and J. Leibold for assistance and advice in setting up the pancreas EPO protocol. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health (NIH). This work was supported by a project grant from the NIH (R01CA229773), P01 CA087497 (S.W.L.), an MSKCC Functional Genomics Initiative grant (S.W.L.), an Agilent Technologies Thought Leader Award (S.W.L.) and support from Synthego under a Synthego Innovator Award (L.E.D.). A.K. was supported by an F31 Ruth L. Kirschstein Predoctoral Individual National Research Service Award (F31-CA247351-02). A.V. was supported by a Postdoctoral Fellowship from the Human Frontier Scientific Program (LT0011/2023-L). B.J.D. was supported by an F31 Ruth L. Kirschstein Predoctoral Individual National Research Service Award (F31-CA261061-01). E.E.G. is the Kenneth G. and Elaine A. Langone Fellow of the Damon Runyon Cancer Research Foundation (DRG-2343-18). F.J.S.R. was supported by the MSKCC TROT program (5T32CA160001) and a GMTEC Postdoctoral Researcher Innovation Grant and is a Howard Hughes Medical Institute (HHMI) Hanna Gray Fellow. S.W.L. is an HHMI investigator.
Author information
Author notes
Miguel Foronda
Present address: Memorial Sloan Kettering Cancer Center, New York, NY, USA
Maria Paz Zafra
Present address: Biosanitary Research Institute (IBS)–Granada, Granada, Spain
Francisco J. Sánchez Rivera
Present address: David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
Francisco J. Sánchez Rivera
Present address: Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
These authors contributed equally: Alyna Katti, Adrián Vega-Pérez.
Authors and Affiliations
Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
Alyna Katti, Adrián Vega-Pérez, Miguel Foronda, Jill Zimmerman, Maria Paz Zafra, Elizabeth Granowsky, Sukanya Goswami, Eric E. Gardner, Bianca J. Diaz, Maria Teresa Calvo Fernandez & Lukas E. Dow
Graduate School of Medical Sciences, Weill Cornell Medicine, New York, NY, USA
Alyna Katti, Jill Zimmerman, Bianca J. Diaz & Lukas E. Dow
Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
Janelle M. Simon, Alexandra Wuest, Wei Luan, Scott W. Lowe & Francisco J. Sánchez Rivera
Synthego Corporation, Redwood City, CA, USA
Anastasia P. Kadina, John A. Walker II & Kevin Holden
Howard Hughes Medical Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
Scott W. Lowe
Department of Medicine, Weill Cornell Medicine, New York, NY, USA
Lukas E. Dow
Contributions
A.K. and A.V.P. designed and performed experiments, analyzed data and wrote the paper. M.F., J.Z., M.P.Z., S.G., E.G., J.S., W.L, B.J.D., M.C.F., K.H. and F.J.S.R. performed experiments and/or analyzed data. S.W.L. supervised experimental work. L.E.D. designed and supervised experiments, analyzed data and wrote the paper.
Corresponding author
Ethics declarations
Competing interests
L.E.D. is a scientific advisor and holds equity in Mirimus, Inc. L.E.D. has received consulting fees and/or honoraria from Volastra Therapeutics, Revolution Medicines, Repare Therapeutics, Fog Pharma and Frazier Healthcare Partners. S.W.L is an advisor for and has equity in the following biotechnology companies: ORIC Pharmaceuticals, Faeth Therapeutics, Blueprint Medicines, Geras Bio, Mirimus, Inc., PMV Pharmaceuticals and Constellation Pharmaceuticals. S.W.L. acknowledges receiving funding and research support from Agilent Technologies for the purposes of massively parallel oligo synthesis. K.H., A.P.K. and J.A.W. are employees and shareholders of Synthego Corporation.
Peer review
Peer review information
Nature Biotechnology thanks the anonymous reviewers for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Regulatable BE expression in vivo.
a. Calculated BE3RA transgene copy number in iBEhem and iBEhom using a Taqman quantiative PCR assay with genomic DNA from H11-LSL-Cas9 mice as a reference. Data are presented as mean values ± s.e.m. (*pother SNVs found in pooled clones for each condition (on and off dox) for both sgRNAs. c. Sequencing analysis at cancer gene sites in cell conditions (right) described in a. Solid blue boxes represent on-target activity of the sgRNA, dotted orange boxes signify on-target ‘bystander’ editing within the gRNA window. d. Quantification of C>T and C>other SNVs found across both targets. 2-way ANOVA test for multiple comparisons was used to evaluate statistical significance across conditions. Data are presented as mean values ± s.e.m. p-values are displayed.
Extended Data Fig. 6 iBE does not induce off target RNA editing in organoids.
a. Schematic of experimental set up in iBE derived pancreatic organoids. Organoids were transduced and selected with GFPGO reporter (mScarlet+). Organoids maintained off dox were then split into dox conditions to induce BE expression for 4 days and then split again into + and – dox conditions for an additional day. b. Editing of organoids in each condition (OFF, D4, D8, and D4 sw) was quantified by flow cytometry, calculating the percentage of GFP+ cells within the mScarlet+ population. Data are presented as mean values ± s.e.m. One-way ANOVA with Tukey’s correction c. PCA analysis of RNA sequencing data from OFF, D8, and D4 SW organoids. Colors correspond to dox condition and shape delineates organoid replicate/mouse origin (n=3). d. Volcano plots from RNA-seq data comparing iBE pancreatic organoids culture on dox-containing media vs regular media. e. Off-target RNA editing analysis, processed as described for Supplementary Fig. 4. No significant differences in RNA variants were observed, n=3, one-way ANOVA with Tukey’s correction. Data are presented as mean values ± s.e.m. For all data shown, n=3 independent organoid lines/condition.
Extended Data Fig. 7 Editing dynamics of iBE organoids.
a. Flow cytometry analysis of three independent pancreatic KP mutant organoid lines integrated with GFPGO reporter following dox treatment for 0-8 days (black), transient exposure for 2h or 12h (grey), or transient exposure then re-treatment at 4 days (green). b. Targeted deep sequencing quantification of target C:G to T:A conversion at the ApcQ1405X locus in 2D small intestinal derived iBE cell line following dox addition for 21 days (dark blue), or transient dox treatment for 3 days and withdrawn for 18 days (light blue). c. Targeted deep sequencing quantification of indel conversion of b. Data are presented as mean values ± s.e.m. (*pT/A/G and indel conversion in small intestinal iBE organoids nucleofected with plasmid (light blue) or synthetic (indigo) gRNAs (ApcQ1405, Trp53Q97, CR8.OS2) as indicated, with and without dox treatment. b. Targeted deep sequencing quantification of target C>T/A/G and indel conversion in small intestinal iBE organoids nucleofected with synthetic gRNAs targeting cancer associated SNVs from Fig. 2f. c-j. Quantification of collateral editing of adjacent cytosines for samples shown in Fig. 2f. Predicted translation of each quantified read is shown below with targeted amino acid substitution (dark grey) and additional amino acid substitution (pink). All data are presented as mean values ± s.e.m.
Extended Data Fig. 9 Analysis of collateral editing before and after functional selection.
a-h. Quantification of collateral editing of adjacent cytosines for data shown in Fig. 2f, unselected (white) and selected (color) in small intestinal iBE organoids nucleofected with various synthetic gRNAs targeting cancer associated SNVs.
Extended Data Fig. 10 In situ base editing with iBE by synthetic gRNA delivery drives liver tumors.
a. HTVI delivery of synthetic gRNAs with SB-Myc as in Fig. 4. BF, H&E images, and IF staining for ß-catenin (green) and glutamine synthetase (GS, red) in livers with tumors. Number of transfected mice with palpable tumors is shown below each column. b. Quantification of target C:G to T:A conversion from tumors described in a). Each point corresponds to an isolated bulk tumor. (n=2-7 mice for a given gRNA target). Individual editing data color-coded by animal in Supplementary Fig. 3. All data are presented as mean values ± s.e.m.
Supplementary information
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
Reprints and Permissions
About this article
Cite this article
Katti, A., Vega-Pérez, A., Foronda, M. et al. Generation of precision preclinical cancer models using regulated in vivo base editing.
Nat Biotechnol (2023). https://doi.org/10.1038/s41587-023-01900-x
Download citation
Received: 14 July 2022
Accepted: 10 July 2023
Published: 10 August 2023
DOI: https://doi.org/10.1038/s41587-023-01900-x
>>> Read full article>>>
Copyright for syndicated content belongs to the linked Source : Nature.com – https://www.nature.com/articles/s41587-023-01900-x
