Key Points
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Metastasis heterogeneity within and between patients is a substantial problem for the clinical management of advanced cancer and has both genetic and nongenetic origins.
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Recent advances in sequencing and acquisition of metastatic tissue are illuminating the phylogenetic relationship between primary tumours and metastases and the biology that underlies this evolutionary process.
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Few recurrent metastasis-specific mutational driver events have been identified to date, highlighting the potential importance of other mechanisms, such as increased epigenetic plasticity, in metastatic progression.
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Beyond heterogeneity in somatic tumour genetics, inherited germline polymorphisms may contribute substantially to differences in metastatic biology across populations.
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Additional larger, well-controlled genomics studies using metastatic samples will be critical for a better understanding of the contribution of somatic heterogeneity to the clinical course of metastatic disease.
Abstract
Tumour heterogeneity poses a substantial problem for the clinical management of cancer. Somatic evolution of the cancer genome results in genetically distinct subclones in the primary tumour with different biological properties and therapeutic sensitivities. The problem of heterogeneity is compounded in metastatic disease owing to the complexity of the metastatic process and the multiple biological hurdles that the tumour cell must overcome to establish a clinically overt metastatic lesion. New advances in sequencing technology and clinical sample acquisition are providing insights into the phylogenetic relationship of metastases and primary tumours at the level of somatic tumour genetics while also illuminating fundamental mechanisms of the metastatic process. In addition to somatically acquired genetic heterogeneity in the tumour cells, inherited population-based genetic heterogeneity can profoundly modify metastatic biology and further complicate the development of effective, broadly applicable antimetastatic therapies. Here, we examine how genetic heterogeneity impacts metastatic disease and the implications of current knowledge for future research endeavours and therapeutic interventions.
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References
Siegel, R. L., Miller, K. D. & Jemal, A. Cancer statistics, 2017. CA Cancer J. Clin. 67, 7–30 (2017).
Spano, D., Heck, C., De Antonellis, P., Christofori, G. & Zollo, M. Molecular networks that regulate cancer metastasis. Semin. Cancer Biol. 22, 234–249 (2012).
Sundquist, M., Brudin, L. & Tejler, G. Improved survival in metastatic breast cancer 1985–2016. Breast 31, 46–50 (2017).
Mariotto, A. B., Etzioni, R., Hurlbert, M., Penberthy, L. & Mayer, M. Estimation of the number of women living with metastatic breast cancer in the United States. Cancer Epidemiol. Biomarkers Prev. 26, 809–815 (2017).
Berry, D. A. et al. Effect of screening and adjuvant therapy on mortality from breast cancer. N. Engl. J. Med. 353, 1784–1792 (2005).
Tevaarwerk, A. J. et al. Survival in patients with metastatic recurrent breast cancer after adjuvant chemotherapy: little evidence of improvement over the past 30 years. Cancer 119, 1140–1148 (2013).
McGranahan, N. & Swanton, C. Clonal heterogeneity and tumor evolution: past, present, and the future. Cell 168, 613–628 (2017).
Magee, J. A., Piskounova, E. & Morrison, S. J. Cancer stem cells: impact, heterogeneity, and uncertainty. Cancer Cell 21, 283–296 (2012).
Natrajan, R. et al. Microenvironmental heterogeneity parallels breast cancer progression: a histology-genomic integration analysis. PLoS Med. 13, e1001961 (2016).
Greaves, M. & Maley, C. C. Clonal evolution in cancer. Nature 481, 306–313 (2012).
Nowell, P. C. The clonal evolution of tumor cell populations. Science 194, 23–28 (1976). This is the classic paper that describes the linear model of cancer progression.
Marusyk, A. et al. Non-cell-autonomous driving of tumour growth supports sub-clonal heterogeneity. Nature 514, 54–58 (2014).
Yates, L. R. & Campbell, P. J. Evolution of the cancer genome. Nat. Rev. Genet. 13, 795–806 (2012).
Calbo, J. et al. A functional role for tumor cell heterogeneity in a mouse model of small cell lung cancer. Cancer Cell 19, 244–256 (2011).
Weng, D. et al. Metastasis is an early event in mouse mammary carcinomas and is associated with cells bearing stem cell markers. Breast Cancer Res. 14, R18 (2012).
Rhim, A. D. et al. Detection of circulating pancreas epithelial cells in patients with pancreatic cystic lesions. Gastroenterology 146, 647–651 (2014).
Faison, W. J. et al. Whole genome single-nucleotide variation profile-based phylogenetic tree building methods for analysis of viral, bacterial and human genomes. Genomics 104, 1–7 (2014).
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).
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.e7 (2017).
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).
McCreery, M. Q. et al. Evolution of metastasis revealed by mutational landscapes of chemically induced skin cancers. Nat. Med. 21, 1514–1520 (2015).
Hosseini, H. et al. Early dissemination seeds metastasis in breast cancer. Nature 540, 552–558 (2016).
Harper, K. L. et al. Mechanism of early dissemination and metastasis in Her2+ mammary cancer. Nature 540, 588–592 (2016).
Sanborn, J. Z. et al. Phylogenetic analyses of melanoma reveal complex patterns of metastatic dissemination. Proc. Natl Acad. Sci. USA 112, 10995–11000 (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).
Naxerova, K. et al. Origins of lymphatic and distant metastases in human colorectal cancer. Science 357, 55–60 (2017).
Zhang, Y., Sun, Y. & Chen, H. Effect of tumor size on prognosis of node-negative lung cancer with sufficient lymph node examination and no disease extension. Onco Targets Ther. 9, 649–653 (2016).
Msaki, A. et al. A hypoxic signature marks tumors formed by disseminated tumor cells in the BALB-neuT mammary cancer model. Oncotarget 7, 33081–33095 (2016).
Joosse, S. A. & Pantel, K. Genetic traits for hematogeneous tumor cell dissemination in cancer patients. Cancer Metastasis Rev. 35, 41–48 (2016).
Talmadge, J. E., Wolman, S. R. & Fidler, I. J. Evidence for the clonal origin of spontaneous metastases. Science 217, 361–363 (1982). This paper provides experimental evidence indicating that metastatic lesions arise from a single 'seed' cell.
Wu, X. et al. Clonal selection drives genetic divergence of metastatic medulloblastoma. Nature 482, 529–533 (2012).
Gibson, W. J. et al. The genomic landscape and evolution of endometrial carcinoma progression and abdominopelvic metastasis. Nat. Genet. 48, 848–855 (2016).
Aceto, N. et al. Circulating tumor cell clusters are oligoclonal precursors of breast cancer metastasis. Cell 158, 1110–1122 (2014). This study suggests that clusters of tumour cells are more efficient at establishing metastatic lesions than single cells.
Cheung, K. J. et al. Polyclonal breast cancer metastases arise from collective dissemination of keratin 14-expressing tumor cell clusters. Proc. Natl Acad. Sci. USA 113, E854–863 (2016).
Maddipati, R. & Stanger, B. Z. Pancreatic cancer metastases harbor evidence of polyclonality. Cancer Discov. 5, 1086–1097 (2015).
McFadden, D. G. et al. Genetic and clonal dissection of murine small cell lung carcinoma progression by genome sequencing. Cell 156, 1298–1311 (2014).
Gundem, G. et al. The evolutionary history of lethal metastatic prostate cancer. Nature 520, 353–357 (2015).
Deryugina, E. I. & Kiosses, W. B. Intratumoral cancer cell intravasation can occur independent of invasion into the adjacent stroma. Cell Rep. 19, 601–616 (2017).
Husemann, Y. et al. Systemic spread is an early step in breast cancer. Cancer Cell 13, 58–68 (2008). This paper demonstrates that tumour cells can begin to disseminate very early in primary tumour evolution.
Riethmuller, G. & Klein, C. A. Early cancer cell dissemination and late metastatic relapse: clinical reflections and biological approaches to the dormancy problem in patients. Semin. Cancer Biol. 11, 307–311 (2001).
Butler, T. P. & Gullino, P. M. Quantitation of cell shedding into efferent blood of mammary adenocarcinoma. Cancer Res. 35, 512–516 (1975).
Kim, M. Y. et al. Tumor self-seeding by circulating cancer cells. Cell 139, 1315–1326 (2009). This is the first experimental demonstration of the possibility for transfer of cells between independent tumours.
Zhang, Y. et al. Tumor self-seeding by circulating tumor cells in nude mouse models of human osteosarcoma and a preliminary study of its mechanisms. J. Cancer Res. Clin. Oncol. 140, 329–340 (2014).
Johnson, D. B. et al. Acquired BRAF inhibitor resistance: a multicenter meta-analysis of the spectrum and frequencies, clinical behaviour, and phenotypic associations of resistance mechanisms. Eur. J. Cancer 51, 2792–2799 (2015).
Tomczak, K., Czerwinska, P. & Wiznerowicz, M. The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge. Contemp. Oncol. (Pozn.) 19, A68–A77 (2015).
Steeg, P. S., Bevilacqua, G., Pozzatti, R., Liotta, L. A. & Sobel, M. E. Altered expression of NM23, a gene associated with low tumor metastatic potential, during adenovirus 2 Ela inhibition of experimental metastasis. Cancer Res. 48, 6550–6554 (1988).
Yan, J., Yang, Q. & Huang, Q. Metastasis suppressor genes. Histol. Histopathol. 28, 285–292 (2013).
Seraj, M. J., Samant, R. S., Verderame, M. F. & Welch, D. R. Functional evidence for a novel human breast carcinoma metastasis suppressor, BRMS1, encoded at chromosome 11q13. Cancer Res. 60, 2764–2769 (2000).
Stafford, L. J., Vaidya, K. S. & Welch, D. R. Metastasis suppressors genes in cancer. Int. J. Biochem. Cell Biol. 40, 874–891 (2008).
Robinson, D. R. et al. Integrative clinical genomics of metastatic cancer. Nature 548, 297–303 (2017). This paper describes the largest genomic analysis to date of metastatic lesions from a variety of tumour sites.
Makohon-Moore, A. P. et al. Limited heterogeneity of known driver gene mutations among the metastases of individual patients with pancreatic cancer. Nat. Genet. 49, 358–366 (2017).
Brastianos, P. K. et al. Genomic characterization of brain metastases reveals branched evolution and potential therapeutic targets. Cancer Discov. 5, 1164–1177 (2015). The genomic studies performed in this manuscript highlight the similarities of metastases within an organ and the dissimilarities between organs.
Pereira, A. A. et al. Association between KRAS mutation and lung metastasis in advanced colorectal cancer. Br. J. Cancer 112, 424–428 (2015).
Margonis, G. A. et al. Association between specific mutations in KRAS codon 12 and colorectal liver metastasis. JAMA Surg. 150, 722–729 (2015).
Hong, M. K. et al. Tracking the origins and drivers of subclonal metastatic expansion in prostate cancer. Nat. Commun. 6, 6605 (2015).
McDonald, O. G. et al. Epigenomic reprogramming during pancreatic cancer progression links anabolic glucose metabolism to distant metastasis. Nat. Genet. 49, 367–376 (2017).
Genomes Project, C. et al. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).
Threadgill, D. W. et al. Targeted disruption of mouse EGF receptor: effect of genetic background on mutant phenotype. Science 269, 230–234 (1995). This paper highlights the substantial effect that genetic background can have on the expression of germline mutations.
Antoniou, A. C. et al. A locus on 19p13 modifies risk of breast cancer in BRCA1 mutation carriers and is associated with hormone receptor-negative breast cancer in the general population. Nat. Genet. 42, 885–892 (2010).
Struewing, J. P. et al. The risk of cancer associated with specific mutations of BRCA1 and BRCA2 among Ashkenazi Jews. N. Engl. J. Med. 336, 1401–1408 (1997).
Ford, D. et al. Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families. The Breast Cancer Linkage Consortium. Am. J. Hum. Genet. 62, 676–689 (1998).
Milne, R. L. & Antoniou, A. C. Modifiers of breast and ovarian cancer risks for BRCA1 and BRCA2 mutation carriers. Endocr. Relat. Cancer 23, T69–T84 (2016).
Hamdi, Y. et al. Association of breast cancer risk in BRCA1 and BRCA2 mutation carriers with genetic variants showing differential allelic expression: identification of a modifier of breast cancer risk at locus 11q22.3. Breast Cancer Res. Treat. 161, 117–134 (2016).
Lifsted, T. et al. Identification of inbred mouse strains harboring genetic modifiers of mammary tumor age of onset and metastatic progression. Int. J. Cancer 77, 640–644 (1998). This study is the first demonstration that inherited polymorphism is an important factor for metastatic progression.
Lancaster, M., Rouse, J. & Hunter, K. Modifiers for mammary tumor latency, progression and metastasis are present on mouse chromosomes 7, 9 and 17. Mamm. Genome 16, 120–126 (2005).
Park, Y. G. et al. Sipa1 is a candidate for underlying the metastasis efficiency modifier locus Mtes1. Nat. Genet. 37, 1055–1062 (2005). This study describes the identification of the first inherited metastasis susceptibility gene.
Crawford, N. P. et al. Rrp1b, a new candidate susceptibility gene for breast cancer progression and metastasis. PLOS Genet. 3, e214 (2007).
Faraji, F. et al. Cadm1 is a metastasis susceptibility gene that suppresses metastasis by modifying tumor interaction with the cell-mediated immunity. PLoS Genet. 8, e1002926 (2012).
Bai, L. et al. An integrated genome-wide systems genetics screen for breast cancer metastasis susceptibility genes. PLoS Genet. 12, e1005989 (2016).
Ha, N. H., Long, J., Cai, Q., Shu, X. O. & Hunter, K. W. The circadian rhythm gene Arntl2 is a metastasis susceptibility gene for estrogen receptor-negative breast cancer. PLoS Genet. 12, e1006267 (2016).
Guy, C. T., Cardiff, R. D. & Muller, W. J. Induction of mammary tumors by expression of polyomavirus middle T oncogene: a transgenic mouse model for metastatic disease. Mol. Cell. Biol. 12, 954–961 (1992).
Darvasi, A. Experimental strategies for the genetic dissection of complex traits in animal models. Nat. Genet. 18, 19–24 (1998).
Hunter, K. W. & Williams, R. W. Complexities of cancer research: mouse genetic models. ILAR J. 43, 80–88 (2002).
Hunter, K. W. et al. Predisposition to efficient mammary tumor metastatic progression is linked to the breast cancer metastasis suppressor gene Brms1. Cancer Res. 61, 8866–8872 (2001).
Park, Y. G., Clifford, R., Buetow, K. H. & Hunter, K. W. Multiple cross and inbred strain haplotype mapping of complex-trait candidate genes. Genome Res. 13, 118–121 (2003).
Crawford, N. P. et al. Bromodomain 4 activation predicts breast cancer survival. Proc. Natl Acad. Sci. USA 105, 6380–6385 (2008).
Crawford, N. P. et al. The diasporin pathway: a tumor progression-related transcriptional network that predicts breast cancer survival. Clin. Exp. Metastasis 25, 357–369 (2008).
Goldberger, N., Walker, R. C., Kim, C. H., Winter, S. & Hunter, K. W. Inherited variation in miR-290 expression suppresses breast cancer progression by targeting the metastasis susceptibility gene Arid4b. Cancer Res. 73, 2671–2681 (2013).
Winter, S. F., Lukes, L., Walker, R. C., Welch, D. R. & Hunter, K. W. Allelic variation and differential expression of the mSIN3A histone deacetylase complex gene Arid4b promote mammary tumor growth and metastasis. PLoS Genet. 8, e1002735 (2012).
Faraji, F. et al. Post-transcriptional control of tumor cell autonomous metastatic potential by CCR4-NOT deadenylase CNOT7. PLoS Genet. 12, e1005820 (2016).
Lee, M. et al. GNL3 and SKA3 are novel prostate cancer metastasis susceptibility genes. Clin. Exp. Metastasis 32, 769–782 (2015).
Ono, M. et al. WISP1/CCN4: a potential target for inhibiting prostate cancer growth and spread to bone. PLoS One 8, e71709 (2013).
Patel, S. J., Molinolo, A. A., Gutkind, S. & Crawford, N. P. Germline genetic variation modulates tumor progression and metastasis in a mouse model of neuroendocrine prostate carcinoma. PLoS One 8, e61848 (2013).
Winter, J. M. et al. Mapping complex traits in a diversity outbred F1 mouse population identifies germline modifiers of metastasis in human prostate cancer. Cell Syst. 4, 31–45.e6 (2017).
van der Weyden, L. et al. Genome-wide in vivo screen identifies novel host regulators of metastatic colonization. Nature 541, 233–236 (2017).
Alsarraj, J. et al. BRD4 short isoform interacts with RRP1B, SIPA1 and components of the LINC complex at the inner face of the nuclear membrane. PLoS One 8, e80746 (2013).
Faraji, F. et al. An integrated systems genetics screen reveals the transcriptional structure of inherited predisposition to metastatic disease. Genome Res. 24, 227–240 (2014).
Vivian, C. J. et al. Mitochondrial genomic backgrounds affect nuclear DNA methylation and gene expression. Cancer Res. 77, 6202–6214 (2017).
van ' t Veer, L. J. et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 415, 530–536 (2002).
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).
Crawford, N. P., Yang, H., Mattaini, K. R. & Hunter, K. W. The metastasis efficiency modifier Ribosomal RNA Processing 1 Homolog B (RRP1B) is a chromatin-associated factor. J. Biol. Chem. 284, 28660–28673 (2009).
Lukes, L., Crawford, N. P., Walker, R. & Hunter, K. W. The origins of breast cancer prognostic gene expression profiles. Cancer Res. 69, 310–318 (2009).
Yang, H. et al. Caffeine suppresses metastasis in a transgenic mouse model: a prototype molecule for prophylaxis of metastasis. Clin. Exp. Metastasis 21, 719–735 (2005).
Qamri, Z. et al. Synthetic cannabinoid receptor agonists inhibit tumor growth and metastasis of breast cancer. Mol. Cancer Ther. 8, 3117–3129 (2009).
Crawford, N. P. et al. Germline polymorphisms in SIPA1 are associated with metastasis and other indicators of poor prognosis in breast cancer. Breast Cancer Res. 8, R16 (2006).
Hsieh, S. M., Look, M. P., Sieuwerts, A. M., Foekens, J. A. & Hunter, K. W. Distinct inherited metastasis susceptibility exists for different breast cancer subtypes: a prognosis study. Breast Cancer Res. 11, R75 (2009).
Pei, R. et al. Association of SIPA1 545 C > T polymorphism with survival in Chinese women with metastatic breast cancer. Front. Med. 7, 138–142 (2013).
Gdowicz-Klosok, A., Giglok, M., Drosik, A., Suwinski, R. & Butkiewicz, D. The SIPA1 -313A>G polymorphism is associated with prognosis in inoperable non-small cell lung cancer. Tumour Biol. 36, 1273–1278 (2015).
Nanchari, S. R. et al. Rrp1B gene polymorphism (1307T>C) in metastatic progression of breast cancer. Tumour Biol. 36, 615–621 (2015).
Xie, C. et al. Sipa1 promoter polymorphism predicts risk and metastasis of lung cancer in Chinese. Mol. Carcinog. 52 (Suppl. 1), E110–E117 (2013).
Brooks, R. et al. Polymorphisms in MMP9 and SIPA1 are associated with increased risk of nodal metastases in early-stage cervical cancer. Gynecol. Oncol. 116, 539–543 (2010).
Ji, J., Forsti, A., Sundquist, J., Lenner, P. & Hemminki, K. Survival in familial pancreatic cancer. Pancreatology 8, 252–256 (2008).
Ji, J., Forsti, A., Sundquist, J., Lenner, P. & Hemminki, K. Survival in bladder and renal cell cancers is familial. J. Am. Soc. Nephrol. 19, 985–991 (2008).
Hemminki, K., Ji, J., Forsti, A., Sundquist, J. & Lenner, P. Survival in breast cancer is familial. Breast Cancer Res. Treat. 110, 177–182 (2008).
Hemminki, K., Ji, J., Forsti, A., Sundquist, J. & Lenner, P. Concordance of survival in family members with prostate cancer. J. Clin. Oncol. 26, 1705–1709 (2008).
Pirie, A. et al. Common germline polymorphisms associated with breast cancer-specific survival. Breast Cancer Res. 17, 58 (2015).
Gaudet, M. M. et al. Genetic variation in SIPA1 in relation to breast cancer risk and survival after breast cancer diagnosis. Int. J. Cancer 124, 1716–1720 (2009).
La Merrill, M., Gordon, R. R., Hunter, K. W., Threadgill, D. W. & Pomp, D. Dietary fat alters pulmonary metastasis of mammary cancers through cancer autonomous and non-autonomous changes in gene expression. Clin. Exp. Metastasis 27, 107–116 (2010).
Gordon, R. R. et al. Genotype X diet interactions in mice predisposed to mammary cancer: II. Tumors and metastasis. Mamm. Genome 19, 179–189 (2008).
Singh, A. K., Loscalzo, J. (eds) The Brigham Intensive Review of Internal Medicine (Oxford Univ. Press, 2012).
Michailidou, K. et al. Association analysis identifies 65 new breast cancer risk loci. Nature 551, 92–94 (2017).
Nam, J. S. et al. An anti-transforming growth factor beta antibody suppresses metastasis via cooperative effects on multiple cell compartments. Cancer Res. 68, 3835–3843 (2008).
Gartner, K. A third component causing random variability beside environment and genotype. A reason for the limited success of a 30 year long effort to standardize laboratory animals? Lab. Anim. 24, 71–77 (1990).
Wright, S. The relative importance of heredity and environment in determining the piebald pattern of guinea-pigs. Proc. Natl Acad. Sci. USA 6, 320–332 (1920).
Kirkwood, T. B. et al. What accounts for the wide variation in life span of genetically identical organisms reared in a constant environment? Mech. Ageing Dev. 126, 439–443 (2005).
Gartner, K. Commentary: random variability of quantitative characteristics, an intangible epigenomic product, supporting adaptation. Int. J. Epidemiol. 41, 342–346 (2012).
Blewitt, M. E., Chong, S. & Whitelaw, E. How the mouse got its spots. Trends Genet. 20, 550–554 (2004).
Campbell, P. J. et al. The patterns and dynamics of genomic instability in metastatic pancreatic cancer. Nature 467, 1109–1113 (2010).
Roe, J. S. et al. Enhancer reprogramming promotes pancreatic cancer metastasis. Cell 170, 875–888 (2017).
Alsaggar, M., Yao, Q., Cai, H. & Liu, D. Differential growth and responsiveness to cancer therapy of tumor cells in different environments. Clin. Exp. Metastasis 33, 115–124 (2015).
Zhang, L. et al. Microenvironment-induced PTEN loss by exosomal microRNA primes brain metastasis outgrowth. Nature 527, 100–104 (2015).
Aurilio, G. et al. Discordant hormone receptor and human epidermal growth factor receptor 2 status in bone metastases compared to primary breast cancer. Acta Oncol. 52, 1649–1656 (2013).
Hoefnagel, L. D. et al. Discordance in ERalpha, PR and HER2 receptor status across different distant breast cancer metastases within the same patient. Ann. Oncol. 24, 3017–3023 (2013).
Almendro, V. et al. Genetic and phenotypic diversity in breast tumor metastases. Cancer Res. 74, 1338–1348 (2014).
Navin, N. et al. Tumour evolution inferred by single-cell sequencing. Nature 472, 90–94 (2011).
Painter, C. et al. The metastatic breast cancer project: translational genomics through direct patient engagement [abstract P1-05-13]. San Antonio Breast Cancer Symposium https://www.sabcs.org/Portals/SABCS2016/Documents/SABCS-2016-Abstracts.pdf?v=1 (2016).
Condeelis, J. S., Wyckoff, J. & Segall, J. E. Imaging of cancer invasion and metastasis using green fluorescent protein. Eur. J. Cancer 36, 1671–1680 (2000).
Bravo-Cordero, J. J., Hodgson, L. & Condeelis, J. Directed cell invasion and migration during metastasis. Curr. Opin. Cell Biol. 24, 277–283 (2012).
Dovas, A., Patsialou, A., Harney, A. S., Condeelis, J. & Cox, D. Imaging interactions between macrophages and tumour cells that are involved in metastasis in vivo and in vitro. J. Microsc. 251, 261–269 (2013).
Sosa, M. S., Bragado, P. & Aguirre-Ghiso, J. A. Mechanisms of disseminated cancer cell dormancy: anawakening field. Nat. Rev. Cancer 14, 611–622 (2014).
Westcott, P. M. et al. The mutational landscapes of genetic and chemical models of Kras-driven lung cancer. Nature 517, 489–492 (2015).
O'Rourke, K. P. et al. Transplantation of engineered organoids enables rapid generation of metastatic mouse models of colorectal cancer. Nat. Biotechnol. 35, 577–582 (2017).
Roper, J. et al. In vivo genome editing and organoid transplantation models of colorectal cancer and metastasis. Nat. Biotechnol. 35, 569–576 (2017).
Acknowledgements
The authors wish to apologize to the many colleagues whose work may have been inadvertently omitted or not included owing to space constraints. This research was supported by the Intramural Research Program of the US National Institutes of Health (NIH), National Cancer Institute (K.W.H., L.W.).
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K.W.H. and L.W. researched the data for the article. K.W.H., L.W., R.A., S.D. and N.-H.H. provided substantial contributions to the discussions of the content. K.W.H. and L.W. contributed equally to writing and reviewing the article. R.A., S.D. and N.-H.H. also reviewed and edited the article before submission. S.D. and N.-H.H. created the figures for the article.
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Glossary
- Microcell-mediated chromosome transfer
-
A method of chromosomal transfer by fusion of membrane-encapsulated donor chromosomes with recipient cells.
- Polymorphisms
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Naturally occurring DNA variants that are passed down through different generations in populations.
- Modifier genes
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Genes that contribute to or affect the distribution of continuous traits, such as human height.
- Quantitative trait locus mapping
-
Genetic mapping to identify genomic intervals that contain genes that contribute to continuously distributed traits, such as human height.
- Genetic backcross mapping panels
-
A population of animals used for genetic mapping that are generated by breeding two strains to generate F1 progeny, which are then bred back to one of the parental strains.
- Recombinant inbred backcross
-
A genetic mapping study that results from breeding a panel of recombinant inbred strains to a mouse strain of interest.
- Haplotypes
-
Collections of specific DNA sequences of single nucleotide polymorphisms that are clustered and frequently inherited together.
- Warm autopsy programmes
-
Autopsies and tissue collection that occur as soon as possible after patient demise (also known as rapid autopsy programmes).
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Hunter, K., Amin, R., Deasy, S. et al. Genetic insights into the morass of metastatic heterogeneity. Nat Rev Cancer 18, 211–223 (2018). https://doi.org/10.1038/nrc.2017.126
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DOI: https://doi.org/10.1038/nrc.2017.126
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