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Genetic Modification of Cancer Cells Using Non-Viral, Episomal S/MAR Vectors for In Vivo Tumour Modelling

Overview of attention for article published in PLOS ONE, October 2012
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Title
Genetic Modification of Cancer Cells Using Non-Viral, Episomal S/MAR Vectors for In Vivo Tumour Modelling
Published in
PLOS ONE, October 2012
DOI 10.1371/journal.pone.0047920
Pubmed ID
Authors

Orestis Argyros, Suet Ping Wong, Kate Gowers, Richard Paul Harbottle

Abstract

The development of genetically marked animal tumour xenografts is an area of ongoing research to enable easier and more reliable testing of cancer therapies. Genetically marked tumour models have a number of advantages over conventional tumour models, including the easy longitudinal monitoring of therapies and the reduced number of animals needed for trials. Several different methods have been used in previous studies to mark tumours genetically, however all have limitations, such as genotoxicity and other artifacts related to the usage of integrating viral vectors. Recently, we have generated an episomally maintained plasmid DNA (pDNA) expression system based on Scaffold/Matrix Attachment Region (S/MAR), which permits long-term luciferase transgene expression in the mouse liver. Here we describe a further usage of this pDNA vector with the human Ubiquitin C promoter to create stably transfected human hepatoma (Huh7) and human Pancreatic Carcinoma (MIA-PaCa2) cell lines, which were delivered into "immune deficient" mice and monitored longitudinally over time using a bioluminometer. Both cell lines revealed sustained episomal long-term luciferase expression and formation of a tumour showing the pathological characteristics of hepatocellular carcinoma (HCC) and pancreatic carcinoma (PaCa), respectively. This is the first demonstration that a pDNA vector can confer sustained episomal luciferase transgene expression in various mouse tumour models and can thus be readily utilised to follow tumour formation without interfering with the cellular genome.

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Geographical breakdown

Country Count As %
Germany 1 3%
Unknown 31 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 34%
Student > Master 7 22%
Student > Ph. D. Student 4 13%
Student > Postgraduate 3 9%
Other 2 6%
Other 2 6%
Unknown 3 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 44%
Biochemistry, Genetics and Molecular Biology 10 31%
Unspecified 1 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Immunology and Microbiology 1 3%
Other 2 6%
Unknown 3 9%