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 cm3). 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.
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A.S.B. has received research support from Daiichi Sankyo and honoraria for lectures, consultation or advisory board participation from Roche Bristol-Myers Squibb, Merck and Daiichi Sankyo as well as travel support from Roche, Amgen and AbbVie. M.P. has received honoraria for lectures, consultation or advisory board participation from the following for-profit companies: Bayer, Bristol-Myers Squibb, Novartis, Gerson Lehrman Group, CMC Contrast, GlaxoSmithKline, Mundipharma, Roche, Astra Zeneca, AbbVie, Lilly, Medahead, Daiichi Sankyo and Merck Sharp & Dome. P.B. has received travel support, honoraria for lectures, consultation or advisory board participation from the following for-profit companies: Biocartis, Novartis, Pfizer, Roche and Roche Diagnostics. C. Curtis is a scientific advisor to GRAIL and reports stock options as well as consulting for GRAIL and Genentech.
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Vanharanta, S. & Massagué, J. Origins of metastatic traits. Cancer Cell 24, 410–421 (2013).
Turajlic, S. & Swanton, C. Metastasis as an evolutionary process. Science 352, 169–175 (2016).
Lambert, A. W., Pattabiraman, D. R. & Weinberg, R. A. Emerging biological principles of metastasis. Cell 168, 670–691 (2017).
Jones, S. et al. Comparative lesion sequencing provides insights into tumor evolution. Proc. Natl Acad. Sci. USA 105, 4283–4288 (2008).
Campbell, P. J. et al. The patterns and dynamics of genomic instability in metastatic pancreatic cancer. Nature 467, 1109–1113 (2010).
Yachida, S. et al. Distant metastasis occurs late during the genetic evolution of pancreatic cancer. Nature 467, 1114–1117 (2010).
Yates, L. R. et al. Genomic evolution of breast cancer metastasis and relapse. Cancer Cell 32, 169–184 (2017).
van de Vijver, M. J. et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med 347, 1999–2009 (2002).
Ramaswamy, S., Ross, K. N., Lander, E. S. & Golub, T. R. A molecular signature of metastasis in primary solid tumors. Nat. Genet. 33, 49–54 (2003).
Sänger, N. et al. Disseminated tumor cells in the bone marrow of patients with ductal carcinoma in situ. Int J. Cancer 129, 2522–2526 (2011).
Husemann, Y. et al. Systemic spread is an early step in breast cancer. Cancer Cell 13, 58–68 (2008).
Rhim, A. D. et al. EMT and dissemination precede pancreatic tumor formation. Cell 148, 349–361 (2012).
Hosseini, H. et al. Early dissemination seeds metastasis in breast cancer. Nature 540, 552–558 (2016).
Siegel, R. L. et al. Colorectal cancer statistics, 2017. CA Cancer J. Clin. 67, 177–193 (2017).
Andres, A. et al. Surgical management of patients with colorectal cancer and simultaneous liver and lung metastases. Br. J. Surg. 102, 691–699 (2015).
Vatandoust, S., Price, T. J. & Karapetis, C. S. Colorectal cancer: metastases to a single organ. World J. Gastroenterol. 21, 11767–11776 (2015).
Christensen, T. D., Spindler, K. L., Palshof, J. A. & Nielsen, D. L. Systematic review: brain metastases from colorectal cancer—incidence and patient characteristics. BMC Cancer 16, 260 (2016).
Fearon, E. R. & Vogelstein, B. A genetic model for colorectal tumorigenesis. Cell 61, 759–767 (1990).
Sottoriva, A. et al. A Big Bang model of human colorectal tumor growth. Nat. Genet. 47, 209–216 (2015).
Ryser, M. D., Min, B. H., Siegmund, K. D. & Shibata, D. Spatial mutation patterns as markers of early colorectal tumor cell mobility. Proc. Natl Acad. Sci. USA 115, 5774–5779 (2018).
Uchi, R. et al. Integrated multiregional analysis proposing a new model of colorectal cancer evolution. PLoS Genet. 12, e1005778 (2016).
Suzuki, Y. et al. Multiregion ultra-deep sequencing reveals early intermixing and variable levels of intratumoral heterogeneity in colorectal cancer. Mol. Oncol. 11, 124–139 (2017).
Sun, R. et al. Between-region genetic divergence reflects the mode and tempo of tumor evolution. Nat. Genet. 49, 1015–1024 (2017).
Bozic, I., Gerold, J. M. & Nowak, M. A. Quantifying clonal and subclonal passenger mutations in cancer evolution. PLoS Comput. Biol. 12, e1004731 (2016).
Hong, W. S., Shpak, M. & Townsend, J. P. Inferring the origin of metastases from cancer phylogenies. Cancer Res. 75, 4021–4025 (2015).
Naxerova, K. & Jain, R. K. Using tumour phylogenetics to identify the roots of metastasis in humans. Nat. Rev. Clin. Oncol. 12, 258–272 (2015).
Zhao, Z. M. et al. Early and multiple origins of metastatic lineages within primary tumors. Proc. Natl Acad. Sci. USA 113, 2140–2145 (2016).
Schwartz, R. & Schaffer, A. A. The evolution of tumour phylogenetics: principles and practice. Nat. Rev. Genet. 18, 213–229 (2017).
Kim, T. M. et al. Subclonal genomic architectures of primary and metastatic colorectal cancer based on intratumoral genetic heterogeneity. Clin. Cancer Res. 21, 4461–4472 (2015).
Leung, M. L. et al. Single-cell DNA sequencing reveals a late-dissemination model in metastatic colorectal cancer. Genome Res. 27, 1287–1299 (2017).
Lim, B. et al. Genome-wide mutation profiles of colorectal tumors and associated liver metastases at the exome and transcriptome levels. Oncotarget 6, 22179–22190 (2015).
Yaeger, R. et al. Clinical sequencing defines the genomic landscape of metastatic colorectal cancer. Cancer Cell 33, 125–136 (2018).
The AACR Project GENIE Consortium AACR Project GENIE: powering precision medicine through an international consortium. Cancer Discov. 7, 818–831 (2017).
Lee, S. Y. et al. Comparative genomic analysis of primary and synchronous metastatic colorectal cancers. PLoS One 9, e90459 (2014).
Xie, T. et al. Patterns of somatic alterations between matched primary and metastatic colorectal tumors characterized by whole-genome sequencing. Genomics 104, 234–241 (2014).
Brannon, A. R. et al. Comparative sequencing analysis reveals high genomic concordance between matched primary and metastatic colorectal cancer lesions. Genome Biol. 15, 454 (2014).
Tan, I. B. et al. High-depth sequencing of over 750 genes supports linear progression of primary tumors and metastases in most patients with liver-limited metastatic colorectal cancer. Genome Biol. 16, 32 (2015).
Gonzalez-Perez, A. et al. IntOGen-mutations identifies cancer drivers across tumor types. Nat. Methods 10, 1081–1082 (2013).
The Cancer Genome Atlas Network Comprehensive molecular characterization of human colon and rectal cancer. Nature 487, 330–337 (2012).
Martincorena, I. et al. Universal patterns of selection in cancer and somatic tissues. Cell 171, 1029–1041 (2017).
Mamlouk, S. et al. DNA copy number changes define spatial patterns of heterogeneity in colorectal cancer. Nat. Commun. 8, 14093 (2017).
Yano, J. M. et al. Indigenous bacteria from the gut microbiota regulate host serotonin biosynthesis. Cell 161, 264–276 (2015).
Hayakawa, Y. et al. Nerve growth factor promotes gastric tumorigenesis through aberrant cholinergic signaling. Cancer Cell 31, 21–34 (2017).
Weir, B. S. & Cockerham, C. C. Estimating F-statistics for the analysis of population-structure. Evolution 38, 1358–1370 (1984).
Fitch, W. M. Toward defining course of evolution: minimum change for a specific tree topology. Syst. Zool. 20, 406 (1971).
Naxerova, K. et al. Origins of lymphatic and distant metastases in human colorectal cancer. Science 357, 55–60 (2017).
Beaumont, M. A., Zhang, W. & Balding, D. J. Approximate Bayesian computation in population genetics. Genetics 162, 2025–2035 (2002).
Marjoram, P. & Tavaré, S. Modern computational approaches for analysing molecular genetic variation data. Nat. Rev. Genet. 7, 759–770 (2006).
Sottoriva, A., Spiteri, I., Shibata, D., Curtis, C. & Tavare, S. Single-molecule genomic data delineate patient-specific tumor profiles and cancer stem cell organization. Cancer Res. 73, 41–49 (2013).
Fumagalli, A. et al. Genetic dissection of colorectal cancer progression by orthotopic transplantation of engineered cancer organoids. Proc. Natl Acad. Sci. USA 114, E2357–E2364 (2017).
Boutin, A. T. et al. Oncogenic Kras drives invasion and maintains metastases in colorectal cancer. Genes Dev. 31, 370–382 (2017).
Wang, Z. et al. Mutational analysis of the tyrosine phosphatome in colorectal cancers. Science 304, 1164–1166 (2004).
Zhang, X. et al. Identification of STAT3 as a substrate of receptor protein tyrosine phosphatase T. Proc. Natl Acad. Sci. USA 104, 4060–4064 (2007).
Lui, V. W. et al. Frequent mutation of receptor protein tyrosine phosphatases provides a mechanism for STAT3 hyperactivation in head and neck cancer. Proc. Natl Acad. Sci. USA 111, 1114–1119 (2014).
Turajlic, S. et al. Tracking cancer evolution reveals constrained routes to metastases: TRACERx Renal. Cell 173, 581–594 (2018).
Rogers, Z. N. et al. Mapping the in vivo fitness landscape of lung adenocarcinoma tumor suppression in mice. Nat. Genet. 50, 483–486 (2018).
Cohen, J. D. et al. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science 359, 926–930 (2018).
Tie, J. et al. Circulating tumor DNA analysis detects minimal residual disease and predicts recurrence in patients with stage II colon cancer. Sci. Transl. Med. 8, 346ra92 (2016).
Casadaban, L. et al. Adjuvant chemotherapy is associated with improved survival in patients with stage II colon cancer. Cancer 122, 3277–3287 (2016).
Berghoff, A. S. et al. Differential role of angiogenesis and tumour cell proliferation in brain metastases according to primary tumour type: analysis of 639 cases. Neuropathol. Appl. Neurobiol. 41, e41–e55 (2015).
Berghoff, A. S. et al. Invasion patterns in brain metastases of solid cancers. Neuro-oncol. 15, 1664–1672 (2013).
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
Cibulskis, K. et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat. Biotechnol. 31, 213–219 (2013).
Koboldt, D. C. et al. VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res. 22, 568–576 (2012).
Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010).
Costello, M. et al. Discovery and characterization of artifactual mutations in deep coverage targeted capture sequencing data due to oxidative DNA damage during sample preparation. Nucleic Acids Res. 41, e67 (2013).
Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
Ha, G. et al. TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data. Genome Res. 24, 1881–1893 (2014).
Ha, G. et al. Integrative analysis of genome-wide loss of heterozygosity and mono-allelic expression at nucleotide resolution reveals disrupted pathways in triple-negative breast cancer. Genome Res. 22, 1995–2007 (2012).
Li, B. & Li, J. Z. A general framework for analyzing tumor subclonality using SNP array and DNA sequencing data. Genome Biol. 15, 473 (2014).
Felsenstein, J. Phylogeny inference package. Cladistics 5, 164–166 (1989).
Siegmund, K. D., Marjoram, P., Woo, Y. J., Tavaré, S. & Shibata, D. Inferring clonal expansion and cancer stem cell dynamics from DNA methylation patterns in colorectal cancers. Proc. Natl Acad. Sci. USA 106, 4828–4833 (2009).
Lloyd, M. C. et al. Darwinian dynamics of intratumoral heterogeneity: not solely random mutations but also variable environmental selection forces. Cancer Res. 76, 3136–3144 (2016).
Sarapata, E. A. & de Pillis, L. G. A comparison and catalog of intrinsic tumor growth models. Bull. Math. Biol. 76, 2010–2024 (2014).
Finlay, I. G., Meek, D., Brunton, F. & McArdle, C. S. Growth rate of hepatic metastases in colorectal carcinoma. Br. J. Surg. 75, 641–644 (1988).
Kather, J. N. et al. Identification of a characteristic vascular belt zone in human colorectal cancer. PLoS One 12, e0171378 (2017).
Bozic, I. et al. Accumulation of driver and passenger mutations during tumor progression. Proc. Natl Acad. Sci. USA 107, 18545–18550 (2010).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Tavaré, S., Balding, D. J., Griffiths, R. C. & Donnelly, P. Inferring coalescence times from DNA sequence data. Genetics 145, 505–518 (1997).
Zhao, J., Siegmund, K. D., Shibata, D. & Marjoram, P. Ancestral inference in tumors: how much can we know? J. Theor. Biol. 359, 136–145 (2014).
Csilléry, K., François, O. & Blum, M. G. abc: an R package for approximate Bayesian computation (ABC). Methods Ecol. Evol. 3, 475–479 (2012).
C. Curtis is supported by the National Institutes of Health through the NIH Director’s Pioneer Award (DP1-CA238296) and NCI Cancer Target Discovery and Development Network (CA217851). This work was funded in part by grants from the American Cancer Society (IRG–58-007-54), the Emerson Collective Cancer Research Fund and a gift from the Wunderglo Foundation to C. Curtis. Z.H. is supported by an Innovative Genomics Initiative (IGI) Postdoctoral Fellowship. The project was supported in part by Cancer Center Support Grants from the National Cancer Institute to the Stanford Cancer Institute (P30CA124435) and the University of Southern California Norris Comprehensive Cancer Center (P30CA014089). We thank J. Caswell-Jin and A. Harpak for critical feedback on the manuscript. This study is dedicated to the memory of G. Borges, a tireless cancer warrior.
Supplementary Figures 1–26, Supplementary Tables 1 and 5–7, and Supplementary Note
Somatic SNVs, indels, allele frequencies, cancer cell fraction and LOH status for individual patients and tumor regions
Colorectal cancer and pan-cancer driver gene lists
Gene ontology enrichment analyses
Enrichment of driver gene modules in the MSK-Impact and MSKImpact plus GENIE cohorts