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Ovarian Cancer pp 139–169Cite as

Deep Transcriptome Profiling of Ovarian Cancer Cells Using Next-Generation Sequencing Approach

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1049))

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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Author information

Authors and Affiliations

  1. Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University, Hangzhou, Zhejiang Province, P. R. China

    Lisha Li, Jie Liu, Wei Yu, Xiaoyan Lou, Bingding Huang & Biaoyang Lin

Authors
  1. Lisha Li
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  2. Jie Liu
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  3. Wei Yu
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  4. Xiaoyan Lou
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  5. Bingding Huang
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  6. Biaoyang Lin
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Editor information

Editors and Affiliations

  1. Group of Experimental Therapeutics, Federal State Institution N.N.Petrov Res Institute of Oncology, St. Petersburg, Russia

    Anastasia Malek

  2. Labs of Molecular Tumor Pathology & Func, Charité - Universitatsmedizin Berlin, Berlin, Germany

    Oleg Tchernitsa

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© 2013 Springer Science+Business Media, New York

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Li, L., Liu, J., Yu, W., Lou, X., Huang, B., Lin, B. (2013). Deep Transcriptome Profiling of Ovarian Cancer Cells Using Next-Generation Sequencing Approach. In: Malek, A., Tchernitsa, O. (eds) Ovarian Cancer. Methods in Molecular Biology, vol 1049. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-547-7_12

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  • DOI: https://doi.org/10.1007/978-1-62703-547-7_12

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-546-0

  • Online ISBN: 978-1-62703-547-7

  • eBook Packages: Springer Protocols

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