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A concerted effort to sequence matched primary and metastatic tumors is vastly improving our ability to understand metastasis in humans. Compelling evidence has emerged that supports the existence of diverse and surprising metastatic patterns. Enhancing these efforts is a new class of algorithms that facilitate high-resolution subclonal modeling of metastatic spread. Here we summarize how subclonal models of metastasis are influencing the metastatic paradigm. Clin Cancer Res; 23(3); 630-5. ©2016 AACR.

Original publication




Journal article


Clinical cancer research : an official journal of the American Association for Cancer Research

Publication Date





630 - 635


Cancer Research UK Cambridge Institute, University of Cambridge, United Kingdom.


Clone Cells, Animals, Humans, Mice, Neoplasm Metastasis, Disease Progression, DNA, Neoplasm, Sequence Analysis, DNA, DNA Mutational Analysis, Cell Communication, Cell Lineage, Mutation, Algorithms, Models, Biological, Time Factors, Neoplastic Stem Cells, Neoplastic Cells, Circulating, Whole Genome Sequencing