| Literature DB >> 27864419 |
Geoff Macintyre1, Peter Van Loo2,3, Niall M Corcoran4,5, David C Wedge6, Florian Markowetz7, Christopher M Hovens8,5.
Abstract
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. ©2016 American Association for Cancer Research.Entities:
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Year: 2016 PMID: 27864419 DOI: 10.1158/1078-0432.CCR-16-0234
Source DB: PubMed Journal: Clin Cancer Res ISSN: 1078-0432 Impact factor: 12.531