How subclonal modeling is changing the metastatic paradigm
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Geoff Macintyre Peter Van Loo Niall M Corcoran David C Wedge Florian Markowetz Christopher M HovensAbstract
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.
Journal details
Journal Clinical cancer research
Volume 23
Issue number 3
Pages 630-635
Publication date
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Publisher website (DOI) 10.1158/1078-0432.ccr-16-0234
Europe PubMed Central 27864419
Pubmed 27864419
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