Title |
Emerging Technologies to Create Inducible and Genetically Defined Porcine Cancer Models
|
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Published in |
Frontiers in Genetics, February 2016
|
DOI | 10.3389/fgene.2016.00028 |
Pubmed ID | |
Authors |
Lawrence B. Schook, Laurie Rund, Karine R. Begnini, Mariana H. Remião, Fabiana K. Seixas, Tiago Collares |
Abstract |
There is an emerging need for new animal models that address unmet translational cancer research requirements. Transgenic porcine models provide an exceptional opportunity due to their genetic, anatomic, and physiological similarities with humans. Due to recent advances in the sequencing of domestic animal genomes and the development of new organism cloning technologies, it is now very feasible to utilize pigs as a malleable species, with similar anatomic and physiological features with humans, in which to develop cancer models. In this review, we discuss genetic modification technologies successfully used to produce porcine biomedical models, in particular the Cre-loxP System as well as major advances and perspectives the CRISPR/Cas9 System. Recent advancements in porcine tumor modeling and genome editing will bring porcine models to the forefront of translational cancer research. |
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Geographical breakdown
Country | Count | As % |
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Switzerland | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Denmark | 1 | 2% |
Unknown | 45 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 9 | 20% |
Student > Bachelor | 7 | 15% |
Researcher | 6 | 13% |
Student > Ph. D. Student | 5 | 11% |
Student > Doctoral Student | 3 | 7% |
Other | 7 | 15% |
Unknown | 9 | 20% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 14 | 30% |
Agricultural and Biological Sciences | 13 | 28% |
Nursing and Health Professions | 3 | 7% |
Pharmacology, Toxicology and Pharmaceutical Science | 2 | 4% |
Veterinary Science and Veterinary Medicine | 2 | 4% |
Other | 4 | 9% |
Unknown | 8 | 17% |