How Mitotic Errors Contribute to Karyotypic Diversity in Cancer
Introduction
At the crux of carcinogenesis lies complexity. Amongst a single tumor, cell-to-cell variability is manifest in many different properties: karyotype, morphology, enzyme receptors, ability to metastasize, mutations, and drug resistance. While seemingly chaotic per cell, the tumor as a whole is much like a mosaic displaying interdependency and organization. For this reason it has been called a species (Duesberg and Rasnick, 2000, Duesberg et al., 2011, Huxley, 1956, Klein et al., 2010, Van Valen and Maiorana, 1991, Vincent, 2010), a society of cells (Heppner, 1984), and a complex ecosystem (Heppner, 1984, Merlo et al., 2006, Sachs and Hlatky, 2010). Whereas it is likely that a myriad of mechanisms contribute to cancer complexity, in this chapter we specifically focus on how mitotic defects contribute to the complexity of the cancer cell karyotype. It has long been known that cancer cells are characterized by aneuploid karyotypes (Bayreuther and Klein, 1958, Chu and Giles, 1958, Hauschka and Levan, 1958), and an increasing body of work has unveiled a causal relationship between aneuploidy and tumorigenesis [reviewed in (Cimini, 2008, Pavelka et al., 2010a, Sen, 2000)]. A key role of aneuploidy in tumorigenesis and tumor progression is also indicated by the fact that measuring DNA indices or ploidy is clinically informative as a prognostic indicator in various cancers (Atkin and Kay, 1979). For instance, ploidy measurements in different types of cancer (Frankfurt et al., 1985, Grote et al., 2001, Jakobsen, 1984, Jakobsen et al., 1988, Kallioniemi et al., 1987, Susini et al., 2011) are as, if not more, accurate when predicting survival than other widely used measures such as the prostate-specific antigen (PSA) test (Stamey, 2004, Vickers et al., 2011).
Karyotypic analysis also indicates that there is wide variability in the chromosome number within the same cancer cell population, suggesting that errors in mitotic chromosome segregation are recurrent in cancer cells. In the remaining part of this chapter, we will start by reviewing what is known about intratumor karyotypic diversity. Next, we will describe the mitotic mechanisms that promote chromosome mis-segregation in cancer cells, and thus can produce karyotypic diversity.
Section snippets
Preneoplastic Aneuploidy
Aneuploidy is ubiquitous in cancer (Gebhart and Liehr, 2000, Mertens et al., 1997, Mitelman et al., 2011, Weaver and Cleveland, 2006), and was proposed to have a causal role in cancer already over a century ago (Boveri, 1902, Boveri, 1914). Over the years, the idea that aneuploidy plays a causal role in the origin of cancer has been supported by substantial experimental evidence. For example, random aneuploidy appears after carcinogen application but before transformation in Chinese hamster (
How Mitotic Errors Contribute to the Karyotypic Diversity of Cancer Cells
The goal of mitosis is to accurately segregate the replicated chromosomes into two daughter cells. This is achieved through the interaction between the sister chromatids of each replicated chromosome with microtubules from opposite poles of the mitotic spindle (Fig. 3). This interaction occurs at the kinetochore, a specialized protein structure that assembles at the centromeric region of each chromatid [for review see (Cheeseman and Desai, 2008, Maiato et al., 2004, Santaguida and Musacchio,
Conclusion
We summarized in this chapter how errors in mitotic chromosome segregation produce karyotypic diversity in cancer cells. Although a recent study identified a phenomenon, termed chromothripsis, by which a massive genomic rearrangement occurs in a single step (Stephens et al., 2011), this only appears to occur in a minor fraction of all cancers. Instead, the mitotic errors most commonly observed in cancer cells do not cause massive chromosome mis-segregation, rather yield small changes in the
Acknowledgments
We would like to thank the members of the Cimini Lab for helpful discussion, and P. Duesberg (UC Berkeley) for sharing unpublished data. Work in the Cimini lab is supported by NSF Grant MCB-0842551 and HFSP Grant RGY0069/2010.
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