- 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Accepted Manuscript
- Files:
-
-
(pdf, 280.2KB)
-
- Publisher copy:
- 10.1158/1078-0432.CCR-16-0234
-
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- Grant:
- 1047581 and 1104010 (to C.M. Hovens and N.M. Corcoran)
- Publisher:
- American Association for Cancer Research Publisher's website
- Journal:
- Clinical Cancer Research Journal website
- Volume:
- 23
- Issue:
- 3
- Pages:
- 630-635
- Publication date:
- 2016-11-18
- DOI:
- EISSN:
-
1557-3265
- ISSN:
-
1078-0432
- Pubs id:
-
pubs:693592
- URN:
-
uri:338aebfc-5e7e-4984-ba9e-060fb9cb1682
- UUID:
-
uuid:338aebfc-5e7e-4984-ba9e-060fb9cb1682
- Local pid:
- pubs:693592
- Paper number:
- 3
- Language:
- English
- Keywords:
- Copyright holder:
- American Association for Cancer Research
- Copyright date:
- 2016
- Notes:
-
Copyright © 2016 American Association for Cancer Research. This is the accepted manuscript version of the article. The final version is available online from the American Association for Cancer Research at: https://doi.org/10.1158/1078-0432.CCR-16-0234
Journal article
How subclonal modeling is changing the metastatic paradigm
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Australian Prostate
Cancer Research Centres
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+ National Health and Medical Research Council
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Francis Crick Institute
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