Abstract 4186: syngenomic fingerprint: the biomic characterization of the mouse syngeneic tumor models

PRIME, John E, MOSELY, Suzanne, KOOPMANN, Jens-Oliver, WANG, Dennis YQ, GREENAWALT, Danielle, HARPER, James, AHDESMAKI, Miika J, LEYLAND, Rebecca, HARRIS, Olivia, STEWART, Ross, BROHAWN, Philip, HIGGS, Brandon, LANGFORD, Bryony, HERATH, Athula, KOZARSKI, Robert, COATES-ULRICHSEN, Jane, ANDERTON, Judith, MORROW, Michelle, SAINSON, Richard CA and WILKINSON, Robert W (2016). Abstract 4186: syngenomic fingerprint: the biomic characterization of the mouse syngeneic tumor models. Cancer Research, 76 (14 Sup), p. 4186.

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Official URL: http://cancerres.aacrjournals.org/content/76/14_Su...
Open Access URL: http://cancerres.aacrjournals.org/content/76/14_Su... (Published)
Link to published version:: https://doi.org/10.1158/1538-7445.AM2016-4186


The pre-clinical assessment of immuno-oncology (IO) therapies can be enabled by the use of murine syngeneic tumors established in immuno-competent mice. With the aims of selecting relevant models and of minimizing animal experimentation by reducing the number of models tested, the full characterisation of syngeneic models at the transcriptomic and genomic level is a key objective for pre-clinical scientists. Model characterisation includes global aCGH, exon array analysis and FACS profiling alongside exome sequencing. The model data is undergoing hypothesis free and driven analyses which are already generating valuable insights. Comparison of in vivo tumor samples with their in vitro equivalents has highlighted enrichment for a number of immune pathways; as has the comparison of different tumor lines. The genomic, transcriptomic and ‘proteomic’ model data are being integrated to give a functional output which will act as a ‘Syngenomic Fingerprint’ for each model. The resulting Syngenomic fingerprints will help pre-clinical scientists to refine their in vivo plans through an improved understanding of the limits and advantages as well as the clinical relevance of some of our preclinical models. It is also supporting the targeted modification of models to better match specific human cancer types.

Item Type: Article
Uncontrolled Keywords: 1112 Oncology And Carcinogenesis; Oncology & Carcinogenesis
Identification Number: https://doi.org/10.1158/1538-7445.AM2016-4186
Page Range: p. 4186
SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 01 Apr 2019 14:51
Last Modified: 18 Mar 2021 05:49
URI: https://shura.shu.ac.uk/id/eprint/23040

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