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Evaluating cell lines as tumour models by comparison of genomic profiles

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  • Silvia Domcke

    (Computational Biology Center, Memorial Sloan-Kettering Cancer Center
    Technische Universität München, Lichtenbergstraße 4, 85747 Garching bei München, Germany)

  • Rileen Sinha

    (Computational Biology Center, Memorial Sloan-Kettering Cancer Center)

  • Douglas A. Levine

    (Memorial Sloan-Kettering Cancer Center)

  • Chris Sander

    (Computational Biology Center, Memorial Sloan-Kettering Cancer Center)

  • Nikolaus Schultz

    (Computational Biology Center, Memorial Sloan-Kettering Cancer Center)

Abstract

Cancer cell lines are frequently used as in vitro tumour models. Recent molecular profiles of hundreds of cell lines from The Cancer Cell Line Encyclopedia and thousands of tumour samples from the Cancer Genome Atlas now allow a systematic genomic comparison of cell lines and tumours. Here we analyse a panel of 47 ovarian cancer cell lines and identify those that have the highest genetic similarity to ovarian tumours. Our comparison of copy-number changes, mutations and mRNA expression profiles reveals pronounced differences in molecular profiles between commonly used ovarian cancer cell lines and high-grade serous ovarian cancer tumour samples. We identify several rarely used cell lines that more closely resemble cognate tumour profiles than commonly used cell lines, and we propose these lines as the most suitable models of ovarian cancer. Our results indicate that the gap between cell lines and tumours can be bridged by genomically informed choices of cell line models for all tumour types.

Suggested Citation

  • Silvia Domcke & Rileen Sinha & Douglas A. Levine & Chris Sander & Nikolaus Schultz, 2013. "Evaluating cell lines as tumour models by comparison of genomic profiles," Nature Communications, Nature, vol. 4(1), pages 1-10, October.
    • Handle: RePEc:nat:natcom:v:4:y:2013:i:1:d:10.1038_ncomms3126
    DOI: 10.1038/ncomms3126
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    6. Yurou Chen & Yulong Qiang & Jiachen Fan & Qian Zheng & Leilei Yan & Guanlan Fan & Xiaofei Song & Nan Zhang & Qiongying Lv & Jiaqiang Xiong & Jingtao Wang & Jing Cao & Yanyan Liu & Jie Xiong & Wei Zhan, 2024. "Aggresome formation promotes ASK1/JNK signaling activation and stemness maintenance in ovarian cancer," Nature Communications, Nature, vol. 15(1), pages 1-18, December.

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