Reprogramming of miRNA networks in cancer and leukemia

  1. Carlo M. Croce2,16
  1. 1 Data Mining for Analysis of Microarrays, Department of Morphology and Embryology, Università degli Studi, Ferrara 44100, Italy;
  2. 2 Comprehensive Cancer Center, Ohio State University, Columbus, Ohio 43210, USA;
  3. 3 Biomedical Informatics, Ohio State University, Columbus, Ohio 43210, USA;
  4. 4 Department of Chemistry, The Scripps Research Institute, La Jolla, California 92037, USA;
  5. 5 Department of Pathology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA;
  6. 6 Department of Urology, Thomas Jefferson University, Kimmel Cancer Center, Philadelphia, Pennsylvania 19107, USA;
  7. 7 Istituto Tumori, Milano 20133, Italy;
  8. 8 Laboratory of Human Carcinogenesis, National Institutes of Health, Bethesda, Maryland 20892, USA;
  9. 9 Department of Medicine, Moores Cancer Center, University of California, San Diego, La Jolla, California 92093, USA;
  10. 10 Institut für Pathologie, Charité-Universitätsmedizin, Berlin 10117, Germany;
  11. 11 Oncogenesis and Molecular Virology Unit, Institut Pasteur, Paris Cedex 05 75251, France;
  12. 12 Nuclear Organization and Oncogenesis Unit/INSERM U993, Institut Pasteur, Paris Cedex 15 75724, France;
  13. 13 Experimental Therapeutics & Cancer Genetics, MD Anderson Cancer Center, Houston, Texas 77030, USA;
  14. 14 Division of Pathology, II University of Rome “La Sapienza,” Ospedale Santo Andrea, Rome 00189, Italy;
  15. 15 Department of Surgery, Thomas Jefferson University Medical College, Philadelphia, Pennsylvania 19107, USA

    Abstract

    We studied miRNA profiles in 4419 human samples (3312 neoplastic, 1107 nonmalignant), corresponding to 50 normal tissues and 51 cancer types. The complexity of our database enabled us to perform a detailed analysis of microRNA (miRNA) activities. We inferred genetic networks from miRNA expression in normal tissues and cancer. We also built, for the first time, specialized miRNA networks for solid tumors and leukemias. Nonmalignant tissues and cancer networks displayed a change in hubs, the most connected miRNAs. hsa-miR-103/106 were downgraded in cancer, whereas hsa-miR-30 became most prominent. Cancer networks appeared as built from disjointed subnetworks, as opposed to normal tissues. A comparison of these nets allowed us to identify key miRNA cliques in cancer. We also investigated miRNA copy number alterations in 744 cancer samples, at a resolution of 150 kb. Members of miRNA families should be similarly deleted or amplified, since they repress the same cellular targets and are thus expected to have similar impacts on oncogenesis. We correctly identified hsa-miR-17/92 family as amplified and the hsa-miR-143/145 cluster as deleted. Other miRNAs, such as hsa-miR-30 and hsa-miR-204, were found to be physically altered at the DNA copy number level as well. By combining differential expression, genetic networks, and DNA copy number alterations, we confirmed, or discovered, miRNAs with comprehensive roles in cancer. Finally, we experimentally validated the miRNA network with acute lymphocytic leukemia originated in Mir155 transgenic mice. Most of miRNAs deregulated in these transgenic mice were located close to hsa-miR-155 in the cancer network.

    Footnotes

    • ↵16 Corresponding author.

      E-mail carlo.croce{at}osumc.edu; fax (614) 292-4110.

    • [Supplemental material is available online at http://www.genome.org. The microarray data from this study have been submitted to ArrayExpress (http://www.ebi.ac.uk/microarray-as/ae) under accession nos. E-TABM-969–E-TABM-975.]

    • Article is online at http://www.genome.org/cgi/doi/10.1101/gr.098046.109.

      • Received July 3, 2009.
      • Accepted February 8, 2010.
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    1. doi: 10.1101/gr.098046.109 Genome Res. 20: 589-599 Copyright © 2010 by Cold Spring Harbor Laboratory Press

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