Chapter title |
Cancer and Zebrafish
|
---|---|
Chapter number | 7 |
Book title |
Cancer and Zebrafish
|
Published in |
Advances in experimental medicine and biology, May 2016
|
DOI | 10.1007/978-3-319-30654-4_7 |
Pubmed ID | |
Book ISBNs |
978-3-31-930652-0, 978-3-31-930654-4
|
Authors |
Huang, Xiaoqian, Agrawal, Ira, Li, Zhen, Zheng, Weiling, Lin, Qingsong, Gong, Zhiyuan, Xiaoqian Huang, Ira Agrawal, Zhen Li, Weiling Zheng, Qingsong Lin, Zhiyuan Gong |
Editors |
David M. Langenau |
Abstract |
The past decade has witnessed a remarkable advancement of the zebrafish model in cancer research. With the rapid development of genomic tools, it is increasingly feasible to perform genome-wide analyses to identify changes associated with cancer in a wide array of model organisms. These genomic tools, particularly transcriptomic analyses using DNA microarray and RNA sequencing platforms, have now become widely used in zebrafish cancer models to uncover novel biology and common molecular pathways underlying hepatocellular carcinoma, intrahepatic cholangiocarcinoma, melanoma, embryonal rhabdomyosarcoma (ERMS), T cell acute lymphoblastic leukemia (T-ALL), Ewing's sarcoma and glioma. An important finding from these studies is the high similarity and conservation of molecular pathways that underlie cancer in complementary zebrafish models and their human counterparts. Finally, these transcriptomic tools have also proven effective in the development and the validation of specific assays for chemical compound screening. In the future, other genomic tools, such as epigenetic, proteomic and metabolomic tools will likely be incorporated into zebrafish cancer studies, further refining our understanding of cancer. |
X Demographics
Geographical breakdown
Country | Count | As % |
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France | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 24 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 5 | 21% |
Student > Bachelor | 3 | 13% |
Researcher | 3 | 13% |
Student > Ph. D. Student | 3 | 13% |
Professor > Associate Professor | 2 | 8% |
Other | 3 | 13% |
Unknown | 5 | 21% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 9 | 38% |
Medicine and Dentistry | 5 | 21% |
Agricultural and Biological Sciences | 3 | 13% |
Veterinary Science and Veterinary Medicine | 1 | 4% |
Unknown | 6 | 25% |