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Cancer Res. 2017 May 15;77(10):2557-2563. doi: 10.1158/0008-5472.CAN-16-3099.

Models in Translational Oncology: A Public Resource Database for Preclinical Cancer Research.

Author information

1
Information Technology, German Cancer Research Center, Heidelberg, Germany.
2
Tumor Models, German Cancer Research Center Heidelberg, Germany.
3
Vascular Oncology and Metastasis, German Cancer Research Center, Heidelberg, Germany.
4
Vascular Biology and Tumor Angiogenesis, Medical Faculty Mannheim, Heidelberg University Heidelberg, Germany.
5
German Cancer Consortium, Heidelberg, Germany.
6
Tumor Models, German Cancer Research Center Heidelberg, Germany. k.mueller-decker@dkfz.de.

Abstract

The devastating diseases of human cancer are mimicked in basic and translational cancer research by a steadily increasing number of tumor models, a situation requiring a platform with standardized reports to share model data. Models in Translational Oncology (MiTO) database was developed as a unique Web platform aiming for a comprehensive overview of preclinical models covering genetically engineered organisms, models of transplantation, chemical/physical induction, or spontaneous development, reviewed here. MiTO serves data entry for metastasis profiles and interventions. Moreover, cell lines and animal lines including tool strains can be recorded. Hyperlinks for connection with other databases and file uploads as supplementary information are supported. Several communication tools are offered to facilitate exchange of information. Notably, intellectual property can be protected prior to publication by inventor-defined accessibility of any given model. Data recall is via a highly configurable keyword search. Genome editing is expected to result in changes of the spectrum of model organisms, a reason to open MiTO for species-independent data. Registered users may deposit own model fact sheets (FS). MiTO experts check them for plausibility. Independently, manually curated FS are provided to principle investigators for revision and publication. Importantly, noneditable versions of reviewed FS can be cited in peer-reviewed journals. Cancer Res; 77(10); 2557-63. ©2017 AACR.

PMID:
28507049
DOI:
10.1158/0008-5472.CAN-16-3099
[Indexed for MEDLINE]
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