Response to Nature letter "Tumour evolution inferred by single-cell sequencing."

Using a single-cell sequencing platform, this report demonstrated that cancer evolution is the result of punctuated clonal expansions with few persistent intermediates(1). This is a significant contribution that illustrates both the power of single-cell sequencing and, in particular, the long-ignored stochastic and discontinuous pattern of somatic cell evolution.

Cancer is a process of somatic evolution(2,3), however, the pattern of cancer evolution remains unclear. Many believe that it is a stepwise evolutionary process where mutations accumulate over time(4). Assuming this is true, drivers of the process should be identifiable and targetable. However, this linear model failed to identify "magic bullet" cancer genes and cannot explain the diverse karyotypes associated with most cancers. This timely report not only offers insight of this heterogeneity at the single cell level, but also reinforces many previous findings on the patterns of cancer evolution. Some important issues need to be further discussed, however.

First, the evolutionary pattern of cancer at the genome level is far more punctuated than at the gene copy level as the same clonal DNA sequence (building material) can be shuffled and packaged to form a variety of non-clonal genomes (karyotypic architectures)(5). In other words, clonal expansion is often observed at the gene level but not at the genome level. By watching evolution in action, we traced the karyotypic evolution of cancer using in vitro immortalization models of human and mouse cells using multiple-color spectral karyotyping(6). To our surprise, we have observed two phases of cancer evolution, namely a stochastic discontinuous (punctuated) phase where there are no persistent intermediates and a Darwinian stepwise phase where intermediates can easily be identified(7,8). During the punctuated phase, non-clonal chromosomal aberrations (NCCAs) dominate, and the majority of cells display different karyotypes, indicating increased genome heterogeneity. In contrast, during the stepwise phase clonal chromosomal aberrations (CCAs) dominate, with the majority of cells sharing similar karyotypes. Interestingly, there are multiple cycles of NCCA/CCA dynamics during the cancer evolutionary process. We have further linked the punctuated phase with macro-cellular evolution (genome alterations create new systems) and the stepwise phase with micro-cellular evolution (gene mutations modify existing systems)(9). We concluded that punctuated cancer evolution represents a common pattern for cancer evolution and predicted that similar patterns would be identified at gene levels(10). The present report supports the concept of punctuated cancer evolution, which questions the current strategies of treating cancer as a process of linear stepwise evolution. For instance, are cancer genome sequencing projects, which have and will continue to generate diverse data sets rather than common patterns of mutations, of clinical utility(11)?

Second, since cancer evolution consists of macro- (i.e., genome alterations) and micro-evolution (i.e., gene level changes), the somatic evolutionary tree should reflect such differences. It has been demonstrated that the frequencies of structural NCCAs (e.g., stochastic translocated chromosomes) are more influential than numerical NCCAs (e.g., aneuploidy) for tumorigenicity(12). This factor should also be considered when constructing a somatic evolutionary tree.

Third, we would like to correct a minor point. The authors misquoted the mutator phenotype and stochastic progression models as being gradual models of cancer evolution. In fact, the mutator phenotype model aims to explain the mechanism behind the high mutation rates in cancer without favoring the stepwise model(13), while the stochastic model introduced the punctuated model for somatic cell evolution(6). We have been actively promoting the stochastic punctuated model for years(2,8).

Lastly, higher resolution images of bin counts and copy number profiles of single cell representatives of major aneuploidy subpopulations HT16P-A and T16M-A are needed (Fig. 4e in ref. 1). Current images appear to be identical, and some variance is expected by chance alone.

Steven D. Horne, Joshua B. Stevens Ph.D., Batoul Y. Abdallah, Henry H.Q. Heng Ph.D.

References

1. Navin, N. et al. Tumour evolution inferred by single-cell sequencing. Nature 472, 90-94 (2011).

2. Heng, H.H. et al. The evolutionary mechanism of cancer. J. Cell. Biochem. 109, 1072-1084 (2010).

3. Goymer, P. Natural selection: the evolution of cancer. Nature 454, 1046-1048 (2008).

4. Nowell, P.C. The clonal evolution of tumor cell populations. Science 194, 23-28 (1976).

5. Heng, H.H. et al. Decoding the genome beyond sequencing: the new phase of
genomic research. Genomics article in press. doi:10.1016/j.ygeno.2011.05.008 (2011).

6. Heng, H.H. et al. Stochastic cancer progression driven by non-clonal chromosome aberrations. J. Cell. Physiol. 208, 461-472 (2006).

7. Gould, S.J., Eldredge, N. Punctuated equilibrium comes of age. Nature 366, 223-227 (1993).

8. Heng, H.H. Elimination of altered karyotypes by sexual reproduction preserves species identity. Genome 50, 517-524 (2007).

9. Heng, H.H. The genome-centric concept: resynthesis of evolutionary theory. BioEssays 31, 512-525 (2009).

10. Ye, C.J., Liu, G., Bremer, S.W. & Heng, H.H. The dynamics of cancer chromosomes and genomes. Cytogenet. Genome Res. 118, 237-246 (2007).

11. Heng, H.H. Cancer genome sequencing: the challenges ahead. Bioessays 29, 783-794 (2007).

12. Ye, C.J. et al. Genome based cell population heterogeneity promotes tumorigenicity: the evolutionary mechanism of cancer. J. Cell. Physiol. 219, 288-300 (2009).

13. Bielas, J.H., Loeb, K.R., Rubin, B.P., True, L.D. & Loeb, L.A. Human cancers express a mutator phenotype. Proc. Natl Acad. Sci. USA 103, 18238-18242 (2006).