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PDXliver: a database of liver cancer patient derived xenograft mouse models.
He, Sheng; Hu, Bo; Li, Chao; Lin, Ping; Tang, Wei-Guo; Sun, Yun-Fan; Feng, Fang-You-Min; Guo, Wei; Li, Jia; Xu, Yang; Yao, Qian-Lan; Zhang, Xin; Qiu, Shuang-Jian; Zhou, Jian; Fan, Jia; Li, Yi-Xue; Li, Hong; Yang, Xin-Rong.
Afiliación
  • He S; School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
  • Hu B; CAS Key Laboratory for Computational Biology, CAS-MPG Partner Institute for Computing Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
  • Li C; University of the Chinese Academy of Sciences, Beijing, 100049, China.
  • Lin P; Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Shanghai, 200032, China.
  • Tang WG; CAS Key Laboratory for Computational Biology, CAS-MPG Partner Institute for Computing Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
  • Sun YF; CAS Key Laboratory for Computational Biology, CAS-MPG Partner Institute for Computing Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
  • Feng FY; University of the Chinese Academy of Sciences, Beijing, 100049, China.
  • Guo W; Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Shanghai, 200032, China.
  • Li J; Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Shanghai, 200032, China.
  • Xu Y; School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
  • Yao QL; CAS Key Laboratory for Computational Biology, CAS-MPG Partner Institute for Computing Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
  • Zhang X; University of the Chinese Academy of Sciences, Beijing, 100049, China.
  • Qiu SJ; Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Shanghai, 200032, China.
  • Zhou J; School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
  • Fan J; CAS Key Laboratory for Computational Biology, CAS-MPG Partner Institute for Computing Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
  • Li YX; University of the Chinese Academy of Sciences, Beijing, 100049, China.
  • Li H; Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Shanghai, 200032, China.
  • Yang XR; School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200031, China.
BMC Cancer ; 18(1): 550, 2018 May 09.
Article en En | MEDLINE | ID: mdl-29743053
ABSTRACT

BACKGROUND:

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. DESCRIPTION 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.

CONCLUSION:

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/.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bases de Datos como Asunto / Ensayos Antitumor por Modelo de Xenoinjerto / Modelos Animales de Enfermedad / Neoplasias Hepáticas Tipo de estudio: Prognostic_studies Límite: Animals / Female / Humans / Male / Middle aged Idioma: En Revista: BMC Cancer Asunto de la revista: NEOPLASIAS Año: 2018 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bases de Datos como Asunto / Ensayos Antitumor por Modelo de Xenoinjerto / Modelos Animales de Enfermedad / Neoplasias Hepáticas Tipo de estudio: Prognostic_studies Límite: Animals / Female / Humans / Male / Middle aged Idioma: En Revista: BMC Cancer Asunto de la revista: NEOPLASIAS Año: 2018 Tipo del documento: Article País de afiliación: China