Inferring the Origin of Metastases from Cancer Phylogenies
- PMID: 26260528
- PMCID: PMC4833389
- DOI: 10.1158/0008-5472.CAN-15-1889
Inferring the Origin of Metastases from Cancer Phylogenies
Abstract
Determining the evolutionary history of metastases is a key problem in cancer biology. Several recent studies have presented inferences regarding the origin of metastases based on phylogenies of cancer lineages. Many of these studies have concluded that the observed monophyly of metastatic subclones favored metastasis-to-metastasis spread ("a metastatic cascade" rather than parallel metastases from the primary tumor). In this article, we argue that identifying a monophyletic clade of metastatic subclones does not provide sufficient evidence to unequivocally establish a history of metastatic cascades. In the absence of a complete phylogeny of the subclones within the primary tumor, a scenario of parallel metastatic events from the primary tumor is an equally plausible interpretation. Future phylogenetic studies on the origin of metastases should obtain a complete phylogeny of subclones within the primary tumor. This complete phylogeny may be obtainable by ultra-deep sequencing and phasing of large sections or by targeted sequencing of many small, spatially heterogeneous sections, followed by phylogenetic reconstruction using well-established molecular evolutionary models. In addition to resolving the evolutionary history of metastases, a complete phylogeny of subclones within the primary tumor facilitates the identification of driver mutations by application of phylogeny-based tests of natural selection.
©2015 American Association for Cancer Research.
Conflict of interest statement
Figures


References
-
- Shpak M, Churchill GA. The information content of a character under a Markov model of evolution. Molecular Phylogenetics and Evolution. 2000;17:231–243. - PubMed
-
- Townsend JP. Profiling phylogenetic informativeness. Systematic Biology. 2006;56:222–231. - PubMed
-
- Townsent JP, Su Z, Tekle YI. Phylogenetic signal and noise: predicting the power off a data set to resolve phylogeny. Systematic Biology. 2012;61:835–849. - PubMed
Publication types
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources