Genetic and epigenetic heterogeneity in cancer: A genome-centric perspective

Authors

  • Henry H.Q. Heng,

    Corresponding author
    1. Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Michigan
    2. Department of Pathology, Wayne State University School of Medicine, Detroit, Michigan
    3. Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, Michigan
    • Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, MI, 48201.
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  • Steven W. Bremer,

    1. Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Michigan
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  • Joshua B. Stevens,

    1. Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Michigan
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  • Karen J. Ye,

    1. SeeDNA Biotech, Inc., Windsor, Ontario, Canada
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  • Guo Liu,

    1. Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Michigan
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  • Christine J. Ye

    1. Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Michigan
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Abstract

Genetic and epigenetic heterogeneity (the main form of non-genetic heterogeneity) are key elements in cancer progression and drug resistance, as they provide needed population diversity, complexity, and robustness. Despite drastically increased evidence of multiple levels of heterogeneity in cancer, the general approach has been to eliminate the “noise” of heterogeneity to establish genetic and epigenetic patterns. In particular, the appreciation of new types of epigenetic regulation like non-coding RNA, have led to the hope of solving the mystery of cancer that the current genetic theories seem to be unable to achieve. In this mini-review, we have briefly analyzed a number of mis-conceptions regarding cancer heterogeneity, followed by the re-evaluation of cancer heterogeneity within a framework of the genome-centric concept of evolution. The analysis of the relationship between gene, epigenetic and genome level heterogeneity, and the challenges of measuring heterogeneity among multiple levels have been discussed. Further, we propose that measuring genome level heterogeneity represents an effective strategy in the study of cancer and other types of complex diseases, as emphasis on the pattern of system evolution rather than specific pathways provides a global and synthetic approach. Compared to the degree of heterogeneity, individual molecular pathways will have limited predictability during stochastic cancer evolution where genome dynamics (reflected by karyotypic heterogeneity) will dominate. J. Cell. Physiol. 220: 538–547, 2009. © 2009 Wiley-Liss, Inc.

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