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PDXliver: a database of liver cancer patient derived xenograft mouse models.
- Source :
-
BMC Cancer . 5/9/2018, Vol. 18 Issue 1, p550-550. 1p. - Publication Year :
- 2018
-
Abstract
- <bold>Background: </bold>Liver cancer is the second leading cause of cancer-related deaths and characterized by heterogeneity and drug resistance. Patient-derived xenograft (PDX) models have been widely used in cancer research because they reproduce the characteristics of original tumors. However, the current studies of liver cancer PDX mice are scattered and the number of available PDX models are too small to represent the heterogeneity of liver cancer patients. To improve this situation and to complement available PDX models related resources, here we constructed a comprehensive database, PDXliver, to integrate and analyze liver cancer PDX models.<bold>Description: </bold>Currently, PDXliver contains 116 PDX models from Chinese liver cancer patients, 51 of them were established by the in-house PDX platform and others were curated from the public literatures. These models are annotated with complete information, including clinical characteristics of patients, genome-wide expression profiles, germline variations, somatic mutations and copy number alterations. Analysis of expression subtypes and mutated genes show that PDXliver represents the diversity of human patients. Another feature of PDXliver is storing drug response data of PDX mice, which makes it possible to explore the association between molecular profiles and drug sensitivity. All data can be accessed via the Browse and Search pages. Additionally, two tools are provided to interactively visualize the omics data of selected PDXs or to compare two groups of PDXs.<bold>Conclusion: </bold>As far as we known, PDXliver is the first public database of liver cancer PDX models. We hope that this comprehensive resource will accelerate the utility of PDX models and facilitate liver cancer research. The PDXliver database is freely available online at: http://www.picb.ac.cn/PDXliver/. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14712407
- Volume :
- 18
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- BMC Cancer
- Publication Type :
- Academic Journal
- Accession number :
- 129544170
- Full Text :
- https://doi.org/10.1186/s12885-018-4459-6