Quantitative evidence for early metastatic seeding in colorectal cancer
Both the timing and molecular determinants of metastasis are unknown, hindering treatment and prevention efforts. Here we characterize the evolutionary dynamics of this lethal process by analyzing exome-sequencing data from 118 biopsies from 23 patients with colorectal cancer with metastases to the...
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Published in | Nature genetics Vol. 51; no. 7; pp. 1113 - 1122 |
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Main Authors | , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Nature Publishing Group US
01.07.2019
Nature Publishing Group |
Subjects | |
Online Access | Get full text |
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Summary: | Both the timing and molecular determinants of metastasis are unknown, hindering treatment and prevention efforts. Here we characterize the evolutionary dynamics of this lethal process by analyzing exome-sequencing data from 118 biopsies from 23 patients with colorectal cancer with metastases to the liver or brain. The data show that the genomic divergence between the primary tumor and metastasis is low and that canonical driver genes were acquired early. Analysis within a spatial tumor growth model and statistical inference framework indicates that early disseminated cells commonly (81%, 17 out of 21 evaluable patients) seed metastases while the carcinoma is clinically undetectable (typically, less than 0.01 cm
3
). We validated the association between early drivers and metastasis in an independent cohort of 2,751 colorectal cancers, demonstrating their utility as biomarkers of metastasis. This conceptual and analytical framework provides quantitative in vivo evidence that systemic spread can occur early in colorectal cancer and illuminates strategies for patient stratification and therapeutic targeting of the canonical drivers of tumorigenesis.
Analysis of evolutionary dynamics of colorectal cancers and paired distant brain or liver metastases provides evidence that early disseminated cancer cells seed metastases before the carcinoma is clinically detectable. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 These authors contributed equally to this work Present address: Veracyte Inc, South San Francisco, California Z.H implemented the computational and mathematical models, performed simulation studies and statistical analyses. J.D. implemented the genomic data analysis pipeline, analyzed and visualized genomic data and provided statistical advice. Z.M processed clinical samples and generated the genomic data. Z.H, R.S, and J.A.S analyzed the genomic data. Z.H, J.D, R.S, J.A.S. and C.C interpreted the data. J.S.S contributed to simulation studies. C.S, A.S.B, P.B performed pathology review. A.S.B and M.P performed immunohistochemistry. M.P, P.B, F.L, C.Cr, A.F, HJ.L contributed clinical samples and expertise. Z.H and C.C wrote the manuscript, which was reviewed by all authors. C.C conceived of and supervised the study. Author contributions |
ISSN: | 1061-4036 1546-1718 |
DOI: | 10.1038/s41588-019-0423-x |