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A next-generation dual-recombinase system for time- and host-specific targeting of pancreatic cancer
Open accessAbstract
Genetically engineered mouse models (GEMMs) have dramatically improved our understanding of tumor evolution and therapeutic resistance. However, sequential genetic manipulation of gene expression and targeting of the host is almost impossible using conventional Cre-loxP–based models. We have developed an inducible dual-recombinase system by combining flippase-FRT (Flp-FRT) and Cre-loxP recombination technologies to improve GEMMs of pancreatic cancer. This enables investigation of multistep carcinogenesis, genetic manipulation of tumor subpopulations (such as cancer stem cells), selective targeting of the tumor microenvironment and genetic validation of therapeutic targets in autochthonous tumors on a genome-wide scale. As a proof of concept, we performed tumor cell–autonomous and nonautonomous targeting, recapitulated hallmarks of human multistep carcinogenesis, validated genetic therapy by 3-phosphoinositide-dependent protein kinase inactivation as well as cancer cell depletion and show that mast cells in the tumor microenvironment, which had been thought to be key oncogenic players, are dispensable for tumor formation.
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Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Provenzano, P. P., Cuevas, C., Chang, A. E., Goel, V. K., Von Hoff, D. D., & Hingorani, S. R. (2012) · Cancer Cell · doi:10.1016/j.ccr.2012.01.007 · Cited by 2,195
Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes
Initiative, A. P. C. G., Biankin, A. V., Waddell, N., Kassahn, K. S., Gingras, M.-C., Muthuswamy, L. B., Johns, A. L., Miller, D. K., Wilson, P. J., Patch, A.-M., et al. (2012) · Nature · doi:10.1038/nature11547 · Cited by 2,058
Oncogenic Kras maintains pancreatic tumors through regulation of anabolic glucose metabolism
Ying, H., Kimmelman, A. C., Lyssiotis, C. A., Hua, S., Chu, G. C., Fletcher-Sananikone, E., Locasale, J. W., Son, J., Zhang, H., Coloff, J. L., et al. (2012) · Cell · doi:10.1016/j.cell.2012.01.058 · Cited by 2,043
RAS oncogenes: weaving a tumorigenic web
Pylayeva-Gupta, Y., Grabocka, E., & Bar-Sagi, D. (2011) · Nature Reviews Cancer · doi:10.1038/nrc3106 · Cited by 1,789
A conditional knockout resource for the genome-wide study of mouse gene function
Skarnes, W. C., Rosen, B., West, A. P., Koutsourakis, M., Bushell, W., Iyer, V., Mujica, A. O., Thomas, M., Harrow, J., Cox, T., et al. (2011) · Nature · doi:10.1038/nature10163 · Cited by 1,708
Self-citationMutant p53 gain of function in two mouse models of Li-Fraumeni syndrome
Olive, K. P., Tuveson, D. A., Ruhe, Z. C., Yin, B., Willis, N. A., Bronson, R. T., Crowley, D., & Jacks, T. (2004) · Cell · doi:10.1016/j.cell.2004.11.004 · Cited by 1,308
A Genome-wide RNAi Screen Identifies Multiple Synthetic Lethal Interactions with the Ras Oncogene
Luo, J., Emanuele, M. J., Li, D., Creighton, C. J., Schlabach, M. R., Westbrook, T. F., Wong, K.-K., & Elledge, S. J. (2009) · Cell · doi:10.1016/j.cell.2009.05.006 · Cited by 1,017
Oncogenic Kras is required for both the initiation and maintenance of pancreatic cancer in mice
Collins, M. A., Bednar, F., Zhang, Y., Brisset, J.-C., Galbán, S., Galbán, C. J., Rakshit, S., Flannagan, K. S., Adsay, N. V., & Pasca di Magliano, M. (2012) · Journal of Clinical Investigation · doi:10.1172/jci59227 · Cited by 770
Oncogenic Kras-induced GM-CSF production promotes the development of pancreatic neoplasia
Pylayeva-Gupta, Y., Lee, K. E., Hajdu, C. H., Miller, G., & Bar-Sagi, D. (2012) · Cancer Cell · doi:10.1016/j.ccr.2012.04.024 · Cited by 721
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Engblom, C., Pfirschke, C., & Pittet, M. J. (2016) · Nature Reviews Cancer · doi:10.1038/nrc.2016.54 · Cited by 788
Chen, Y., Kim, J., Yang, S., Wang, H., Wu, C.-J., Sugimoto, H., LeBleu, V. S., & Kalluri, R. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.02.007 · Cited by 566
Stromal biology and therapy in pancreatic cancer: a changing paradigm
Neesse, A., Algül, H., Tuveson, D. A., & Gress, T. M. (2015) · Gut · doi:10.1136/gutjnl-2015-309304 · Cited by 559
Genetically engineered mouse models in oncology research and cancer medicine
Kersten, K., de Visser, K. E., van Miltenburg, M. H., & Jonkers, J. (2017) · EMBO Molecular Medicine · doi:10.15252/emmm.201606857 · Cited by 502
Non-redundant functions of EMT transcription factors
Stemmler, M. P., Eccles, R. L., Brabletz, S., & Brabletz, T. (2019) · Nature Cell Biology · doi:10.1038/s41556-018-0196-y · Cited by 524
Mutant KRAS-driven cancers depend on PTPN11/SHP2 phosphatase
Ruess, D. A., Heynen, G. J., Ciecielski, K. J., Ai, J., Berninger, A., Kabacaoglu, D., Görgülü, K., Dantes, Z., Wörmann, S. M., Diakopoulos, K. N., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0024-8 · Cited by 370
Self-citationHan, L., Wu, Y., Fang, K., Sweeney, S., Roesner, U. K., Parrish, M., Patel, K., Walter, T., Piermattei, J., Trimboli, A., et al. (2023) · Nature Communications · doi:10.1038/s41467-022-34464-6 · Cited by 369
Preclinical mouse solid tumour models: status quo, challenges and perspectives
Gengenbacher, N., Singhal, M., & Augustin, H. G. (2017) · Nature Reviews Cancer · doi:10.1038/nrc.2017.92 · Cited by 332
Microenvironmental Determinants of Pancreatic Cancer
Hessmann, E., Buchholz, S. M., Demir, I. E., Singh, S. K., Gress, T. M., Ellenrieder, V., & Neesse, A. (2020) · Physiological Reviews · doi:10.1152/physrev.00042.2019 · Cited by 331
(2022) · doi:10.1158/2159-8290.cd-20-1484 · Cited by 311
Chen, Y., Yang, S., Tavormina, J., Tampe, D., Zeisberg, M., Wang, H., Mahadevan, K. K., Wu, C.-J., Sugimoto, H., Chang, C.-C., et al. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.06.011 · Cited by 289
Large-scale design of robust genetic circuits with multiple inputs and outputs for mammalian cells
Weinberg, B. H., Pham, N. T. H., Caraballo, L. D., Lozanoski, T., Engel, A., Bhatia, S., & Wong, W. W. (2017) · Nature Biotechnology · doi:10.1038/nbt.3805 · Cited by 265
Genetically engineered pigs as models for human disease
Perleberg, C., Kind, A., & Schnieke, A. (2018) · Disease Models & Mechanisms · doi:10.1242/dmm.030783 · Cited by 222
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Pan, C., Schoppe, O., Parra-Damas, A., Cai, R., Todorov, M. I., Gondi, G., von Neubeck, B., Böğürcü-Seidel, N., Seidel, S., Sleiman, K., et al. (2019) · Cell · doi:10.1016/j.cell.2019.11.013 · Cited by 206
Self-citationBelow, C. R., Kelly, J., Brown, A., Humphries, J. D., Hutton, C., Xu, J., Lee, B. Y., Cintas, C., Zhang, X., Hernandez-Gordillo, V., et al. (2022) · Nature Materials · doi:10.1038/s41563-021-01085-1 · Cited by 194
A Classical Epithelial State Drives Acute Resistance to KRAS Inhibition in Pancreatic Cancer
Singhal, A., Styers, H. C., Rub, J., Li, Z., Torborg, S. R., Kim, J. Y., Grbovic-Huezo, O., Feng, H., Tarcan, Z. C., Sahin Ozkan, H., et al. (2024) · Cancer Discovery · doi:10.1158/2159-8290.cd-24-0740 · Cited by 84
Clonal dynamics following p53 loss of heterozygosity in Kras-driven cancers
Muzumdar, M. D., Dorans, K. J., Chung, K. M., Robbins, R., Tammela, T., Gocheva, V., Li, C. M.-C., & Jacks, T. (2016) · Nature Communications · doi:10.1038/ncomms12685 · Cited by 72
iSuRe-Cre is a genetic tool to reliably induce and report Cre-dependent genetic modifications
Fernández-Chacón, M., Casquero-García, V., Luo, W., Francesca Lunella, F., Ferreira Rocha, S., Del Olmo-Cabrera, S., & Benedito, R. (2019) · Nature Communications · doi:10.1038/s41467-019-10239-4 · Cited by 54
Pre-clinical Models of Metastasis in Pancreatic Cancer
Miquel, M., Zhang, S., & Pilarsky, C. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.748631 · Cited by 53
A dual genetic tracing system identifies diverse and dynamic origins of cardiac valve mesenchyme
Liu, K., Yu, W., Tang, M., Tang, J., Liu, X., Liu, Q., Li, Y., He, L., Zhang, L., Evans, S. M., et al. (2018) · Development · doi:10.1242/dev.167775 · Cited by 51
Genetic Mutations of Pancreatic Cancer and Genetically Engineered Mouse Models
Saiki, Y., Jiang, C., Ohmuraya, M., & Furukawa, T. (2021) · Cancers · doi:10.3390/cancers14010071 · Cited by 38
Metadata
- Authors
- Schönhuber, N., Seidler, B., Schuck, K., Veltkamp, C., Schachtler, C., Zukowska, M., Eser, S., Feyerabend, T. B., Paul, M. C., Eser, P., Klein, S., Lowy, A. M., Banerjee, R., Yang, F., Lee, C.-L., Moding, E. J., Kirsch, D. G., Scheideler, A., Alessi, D. R., Varela, I., Bradley, A., Kind, A., Schnieke, A. E., Rodewald, H.-R., Rad, R., Schmid, R. M., Schneider, G., & Saur, D.
- Venue
- Nature Medicine
- Published
- 2014-10-19
- Volume
- 20
- Issue
- 11
- Pages
- 1340-1347
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W2073405971
- Cited by
- 237
- References
- 10
- FWCI
- 6.75
- Type
- journal article
- Language
- en
- Open access
- bronze
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