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Evidence for the Complexity of MicroRNA-Mediated Regulation in Ovarian Cancer: A Systems Approach

Author

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  • Shubin W Shahab
  • Lilya V Matyunina
  • Roman Mezencev
  • L DeEtte Walker
  • Nathan J Bowen
  • Benedict B Benigno
  • John F McDonald

Abstract

MicroRNAs (miRNAs) are short (∼22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. Previous studies have shown that miRNAs inhibit the translation and facilitate the degradation of their targeted messenger RNAs (mRNAs) making them attractive candidates for use in cancer therapy. However, the potential clinical utility of miRNAs in cancer therapy rests heavily upon our ability to understand and accurately predict the consequences of fluctuations in levels of miRNAs within the context of complex tumor cells. To evaluate the predictive power of current models, levels of miRNAs and their targeted mRNAs were measured in laser captured micro-dissected (LCM) ovarian cancer epithelial cells (CEPI) and compared with levels present in ovarian surface epithelial cells (OSE). We found that the predicted inverse correlation between changes in levels of miRNAs and levels of their mRNA targets held for only ∼11% of predicted target mRNAs. We demonstrate that this low inverse correlation between changes in levels of miRNAs and their target mRNAs in vivo is not merely an artifact of inaccurate miRNA target predictions but the likely consequence of indirect cellular processes that modulate the regulatory effects of miRNAs in vivo. Our findings underscore the complexities of miRNA-mediated regulation in vivo and the necessity of understanding the basis of these complexities in cancer cells before the therapeutic potential of miRNAs can be fully realized.

Suggested Citation

  • Shubin W Shahab & Lilya V Matyunina & Roman Mezencev & L DeEtte Walker & Nathan J Bowen & Benedict B Benigno & John F McDonald, 2011. "Evidence for the Complexity of MicroRNA-Mediated Regulation in Ovarian Cancer: A Systems Approach," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-12, July.
    • Handle: RePEc:plo:pone00:0022508
    DOI: 10.1371/journal.pone.0022508
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    References listed on IDEAS

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    1. Xiaohui Xie & Jun Lu & E. J. Kulbokas & Todd R. Golub & Vamsi Mootha & Kerstin Lindblad-Toh & Eric S. Lander & Manolis Kellis, 2005. "Systematic discovery of regulatory motifs in human promoters and 3′ UTRs by comparison of several mammals," Nature, Nature, vol. 434(7031), pages 338-345, March.
    2. Jun Lu & Gad Getz & Eric A. Miska & Ezequiel Alvarez-Saavedra & Justin Lamb & David Peck & Alejandro Sweet-Cordero & Benjamin L. Ebert & Raymond H. Mak & Adolfo A. Ferrando & James R. Downing & Tyler , 2005. "MicroRNA expression profiles classify human cancers," Nature, Nature, vol. 435(7043), pages 834-838, June.
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