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Identification of high-quality cancer prognostic markers and metastasis network modules

Author

Listed:
  • Jie Li

    (Computational Chemistry and Bioinformatics Group, Biotechnology Research Institute, National Research Council Canada)

  • Anne E.G. Lenferink

    (Receptor, Signaling and Proteomics Group, Biotechnology Research Institute, National Research Council Canada)

  • Yinghai Deng

    (Computational Chemistry and Bioinformatics Group, Biotechnology Research Institute, National Research Council Canada)

  • Catherine Collins

    (Receptor, Signaling and Proteomics Group, Biotechnology Research Institute, National Research Council Canada)

  • Qinghua Cui

    (Computational Chemistry and Bioinformatics Group, Biotechnology Research Institute, National Research Council Canada
    †Present address: Department of Medical Informatics, Peking University Health Science Center, Beijing 100083, China.)

  • Enrico O. Purisima

    (Computational Chemistry and Bioinformatics Group, Biotechnology Research Institute, National Research Council Canada
    Center for Bioinformatics, McGill University)

  • Maureen D. O'Connor-McCourt

    (Receptor, Signaling and Proteomics Group, Biotechnology Research Institute, National Research Council Canada)

  • Edwin Wang

    (Computational Chemistry and Bioinformatics Group, Biotechnology Research Institute, National Research Council Canada
    Center for Bioinformatics, McGill University)

Abstract

There has been great interest in attempting to identify gene expression signatures that predict cancer survival. In this study a new algorithm is developed to analyse gene expression datasets that accurately classify both ER+ and ER− breast cancers into low- and high-risk groups.

Suggested Citation

  • Jie Li & Anne E.G. Lenferink & Yinghai Deng & Catherine Collins & Qinghua Cui & Enrico O. Purisima & Maureen D. O'Connor-McCourt & Edwin Wang, 2010. "Identification of high-quality cancer prognostic markers and metastasis network modules," Nature Communications, Nature, vol. 1(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:1:y:2010:i:1:d:10.1038_ncomms1033
    DOI: 10.1038/ncomms1033
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    Cited by:

    1. Jianchun Wu & Zhihong Fang & Jing Xu & Weikang Zhu & Yan Li & Yongchun Yu, 2015. "Prognostic Value and Clinicopathology Significance of MicroRNA-200c Expression in Cancer: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-13, June.
    2. Yishai Shimoni, 2018. "Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification," PLOS Computational Biology, Public Library of Science, vol. 14(2), pages 1-15, February.

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