Chapter title |
Deep transcriptome profiling of ovarian cancer cells using next-generation sequencing approach.
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Chapter number | 12 |
Book title |
Ovarian Cancer
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Published in |
Methods in molecular biology, January 2013
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DOI | 10.1007/978-1-62703-547-7_12 |
Pubmed ID | |
Book ISBNs |
978-1-62703-546-0, 978-1-62703-547-7
|
Authors |
Lisha Li, Jie Liu, Wei Yu, Xiaoyan Lou, Bingding Huang, Biaoyang Lin, Li, Lisha, Liu, Jie, Yu, Wei, Lou, Xiaoyan, Huang, Bingding, Lin, Biaoyang |
Abstract |
The next-generation sequencing technology allows identification and cataloging of almost all mRNAs, even those with only one or a few transcripts per cell. To understand the chemotherapy response program in ovarian cancer cells at deep transcript sequencing levels, we applied two next-generation sequencing technologies to study two ovarian chemotherapy response models: the in vitro acquired cisplatin-resistant cell line model (IGROV-1-CP and IGROV1) and the in vivo ovarian cancer tissue resistant model. We identified 3,422 signatures (2,957 genes) that are significantly differentially expressed between IGROV1 and IGROV-1-CP cells (P < .001). Our database offers the first comprehensive view of the digital transcriptomes of ovarian cancer cell lines and tissues with different chemotherapy response phenotypes. |
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United States | 1 | 100% |
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Members of the public | 1 | 100% |
Mendeley readers
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Unknown | 19 | 100% |
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Researcher | 5 | 26% |
Student > Bachelor | 4 | 21% |
Other | 3 | 16% |
Student > Ph. D. Student | 2 | 11% |
Student > Master | 1 | 5% |
Other | 1 | 5% |
Unknown | 3 | 16% |
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Medicine and Dentistry | 2 | 11% |
Unknown | 3 | 16% |