A cellular hierarchy in melanoma uncouples growth and metastasis.

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
  • Additional Information
    • Source:
      Publisher: Nature Publishing Group Country of Publication: England NLM ID: 0410462 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1476-4687 (Electronic) Linking ISSN: 00280836 NLM ISO Abbreviation: Nature Subsets: MEDLINE
    • Publication Information:
      Publication: Basingstoke : Nature Publishing Group
      Original Publication: London, Macmillan Journals ltd.
    • Subject Terms:
    • Abstract:
      Although melanoma is notorious for its high degree of heterogeneity and plasticity 1,2 , the origin and magnitude of cell-state diversity remains poorly understood. Equally, it is unclear whether growth and metastatic dissemination are supported by overlapping or distinct melanoma subpopulations. Here, by combining mouse genetics, single-cell and spatial transcriptomics, lineage tracing and quantitative modelling, we provide evidence of a hierarchical model of tumour growth that mirrors the cellular and molecular logic underlying the cell-fate specification and differentiation of the embryonic neural crest. We show that tumorigenic competence is associated with a spatially localized perivascular niche, a phenotype acquired through an intercellular communication pathway established by endothelial cells. Consistent with a model in which only a fraction of cells are fated to fuel growth, temporal single-cell tracing of a population of melanoma cells with a mesenchymal-like state revealed that these cells do not contribute to primary tumour growth but, instead, constitute a pool of metastatic initiating cells that switch cell identity while disseminating to secondary organs. Our data provide a spatially and temporally resolved map of the diversity and trajectories of melanoma cell states and suggest that the ability to support growth and metastasis are limited to distinct pools of cells. The observation that these phenotypic competencies can be dynamically acquired after exposure to specific niche signals warrant the development of therapeutic strategies that interfere with the cancer cell reprogramming activity of such microenvironmental cues.
      (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)
    • Comments:
      Erratum in: Nature. 2022 Nov;611(7934):E4. (PMID: 36261534)
      Comment in: Nat Rev Cancer. 2022 Dec;22(12):658. (PMID: 36319698)
    • References:
      Rambow, F., Marine, J. C. & Goding, C. R. Melanoma plasticity and phenotypic diversity: therapeutic barriers and opportunities. Genes Dev. 33, 1295–1318 (2019).
      Arozarena, I. & Wellbrock, C. Phenotype plasticity as enabler of melanoma progression and therapy resistance. Nat. Rev. Cancer 19, 377–391 (2019).
      Gulati, G. S. et al. Single-cell transcriptional diversity is a hallmark of developmental potential. Science 367, 405–411 (2020). (PMID: 31974247769487310.1126/science.aax0249)
      Rambow, F. et al. Toward minimal residual disease-directed therapy in melanoma. Cell 174, 843–855 (2018). (PMID: 3001724510.1016/j.cell.2018.06.025)
      Tirosh, I. et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352, 189–196 (2016). (PMID: 27124452494452810.1126/science.aad0501)
      Wouters, J. et al. Robust gene expression programs underlie recurrent cell states and phenotype switching in melanoma. Nat. Cell Biol. 22, 986–998 (2020). (PMID: 3275367110.1038/s41556-020-0547-3)
      Patton, E. E. et al. Melanoma models for the next generation of therapies. Cancer Cell 39, 610–631 (2021).
      Ackermann, J. et al. Metastasizing melanoma formation caused by expression of activated N-Ras Q61K on an INK4a-deficient background. Cancer Res. 65, 4005–4011 (2005). (PMID: 1589978910.1158/0008-5472.CAN-04-2970)
      Serrano, M. et al. Role of the INK4a locus in tumor suppression and cell mortality. Cell 85, 27–37 (1996). (PMID: 862053410.1016/S0092-8674(00)81079-X)
      Tirosh, I. et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352, 189–196 (2016). (PMID: 27124452494452810.1126/science.aad0501)
      Jerby-Arnon, L. et al. A cancer cell program promotes T cell exclusion and resistance to checkpoint blockade. Cell 175, 984–997 (2018). (PMID: 30388455641037710.1016/j.cell.2018.09.006)
      Rambow, F. et al. New functional signatures for understanding melanoma biology from tumor cell lineage-specific analysis. Cell Rep. 13, 840–853 (2015). (PMID: 26489459597054210.1016/j.celrep.2015.09.037)
      Sade-Feldman, M. et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 175, 998–1013 (2018). (PMID: 30388456664198410.1016/j.cell.2018.10.038)
      Fan, J. et al. Linking transcriptional and genetic tumor heterogeneity through allele analysis of single-cell RNA-seq data. Genome Research 28, 1217–1227 (2018). (PMID: 29898899607164010.1101/gr.228080.117)
      Goding, C. R. & Arnheiter, H. MITF—the first 25 years. Genes Dev. 33, 983–1007 (2019).
      Hoek, K. S. & Goding, C. R. Cancer stem cells versus phenotype-switching in melanoma. Pigment Cell Melanoma Res. 23, 746–759 (2010).
      Aibar, S. et al. SCENIC: single-cell regulatory network inference and clustering. Nat. Methods 14, 1083–1086 (2017). (PMID: 28991892593767610.1038/nmeth.4463)
      Soldatov, R. et al. Spatiotemporal structure of cell fate decisions in murine neural crest. Science 364, eaas9536 (2019). (PMID: 3117166610.1126/science.aas9536)
      Kerosuo, L. & Bronner, M. E. cMyc regulates the size of the premigratory neural crest stem cell pool. Cell Rep. 17, 2648–2659 (2016). (PMID: 27926868572651510.1016/j.celrep.2016.11.025)
      Tsoi, J. et al. Multi-stage differentiation defines melanoma subtypes with differential vulnerability to drug-induced iron-dependent oxidative stress. Cancer Cell 33, 890–904 (2018). (PMID: 29657129595383410.1016/j.ccell.2018.03.017)
      Köhler, C. et al. Mouse cutaneous melanoma induced by mutant BRaf arises from expansion and dedifferentiation of mature pigmented melanocytes. Cell Stem Cell 21, 679–693 (2017). (PMID: 2903335110.1016/j.stem.2017.08.003)
      Pozniak, J. et al. A TCF4/BRD4-dependent regulatory network confers cross-resistance to targeted and immune checkpoint therapy in melanoma. Preprint at bioRxiv https://doi.org/10.1101/2022.08.11.502598 (2022).
      Snippert, H. J. et al. Intestinal crypt homeostasis results from neutral competition between symmetrically dividing Lgr5 stem cells. Cell 143, 134–144 (2010). (PMID: 2088789810.1016/j.cell.2010.09.016)
      Reeves, M. Q., Kandyba, E., Harris, S., Del Rosario, R. & Balmain, A. Multicolour lineage tracing reveals clonal dynamics of squamous carcinoma evolution from initiation to metastasis. Nat. Cell Biol. 20, 699–709 (2018). (PMID: 29802408640058710.1038/s41556-018-0109-0)
      Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 (2019). (PMID: 31178118668739810.1016/j.cell.2019.05.031)
      Chen, A. et al. Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays. Cell 185, 1777–1792 (2022). (PMID: 3551270510.1016/j.cell.2022.04.003)
      Calabrese, C. et al. A perivascular niche for brain tumor stem cells. Cancer Cell 11, 69–82 (2007). (PMID: 1722279110.1016/j.ccr.2006.11.020)
      Browaeys, R., Saelens, W. & Saeys, Y. NicheNet: modeling intercellular communication by linking ligands to target genes. Nat. Methods 17, 159–162 (2020). (PMID: 3181926410.1038/s41592-019-0667-5)
      Jin, S. et al. Inference and analysis of cell-cell communication using CellChat. Nat. Commun. 12, 1088 (2021). (PMID: 33597522788987110.1038/s41467-021-21246-9)
      Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005). (PMID: 16199517123989610.1073/pnas.0506580102)
      Wei, K. et al. Notch signalling drives synovial fibroblast identity and arthritis pathology. Nature 582, 259–264 (2020). (PMID: 32499639784171610.1038/s41586-020-2222-z)
      Takano, S. et al. Prrx1 isoform switching regulates pancreatic cancer invasion and metastatic colonization. Genes Dev. 30, 233–247 (2016). (PMID: 26773005471931210.1101/gad.263327.115)
      Ocaña, O. H. et al. Metastatic colonization requires the repression of the epithelial-mesenchymal transition inducer Prrx1. Cancer Cell 22, 709–724 (2012). (PMID: 2320116310.1016/j.ccr.2012.10.012)
      Hoek, K. S. et al. In vivo switching of human melanoma cells between proliferative and invasive states. Cancer Res. 68, 650–656 (2008). (PMID: 1824546310.1158/0008-5472.CAN-07-2491)
      Verfaillie, A. et al. Decoding the regulatory landscape of melanoma reveals TEADS as regulators of the invasive cell state. Nat. Commun. https://doi.org/10.1038/ncomms7683 (2015).
      Widmer, D. S. et al. Systematic classification of melanoma cells by phenotype-specific gene expression mapping. Pigment Cell Melanoma Res. 25, 343–353 (2012). (PMID: 2233614610.1111/j.1755-148X.2012.00986.x)
      Kawanami, A., Matsushita, T., Chan, Y. Y. & Murakami, S. Mice expressing GFP and CreER in osteochondro progenitor cells in the periosteum. Biochem. Biophys. Res. Commun. 386, 477–482 (2009). (PMID: 19538944274235010.1016/j.bbrc.2009.06.059)
      Boiko, A. D. et al. Human melanoma-initiating cells express neural crest nerve growth factor receptor CD271. Nature 466, 133–137 (2010). (PMID: 20596026289875110.1038/nature09161)
      Roesch, A. et al. A temporarily distinct subpopulation of slow-cycling melanoma cells is required for continuous tumor growth. Cell 141, 583–594 (2010). (PMID: 20478252288269310.1016/j.cell.2010.04.020)
      Schatton, T. et al. Identification of cells initiating human melanomas. Nature 451, 345–349 (2008). (PMID: 18202660366070510.1038/nature06489)
      Quintana, E. et al. Efficient tumour formation by single human melanoma cells. Nature 456, 593–598 (2008). (PMID: 19052619259738010.1038/nature07567)
      Stemmler, M. P., Eccles, R. L., Brabletz, S. & Brabletz, T. Non-redundant functions of EMT transcription factors. Nat. Cell Biol. 21, 102–112 (2019).
      Bosenberg, M. et al. Characterization of melanocyte-specific inducible Cre recombinase transgenic mice. Genesis 44, 262–267 (2006). (PMID: 1667632210.1002/dvg.20205)
      Krimpenfort, P., Quon, K. C., Mooi, W. J., Loonstra, A. & Berns, A. Loss of p16Ink4a confers susceptibility to metastatic melanoma in mice. Nature 413, 83–86 (2001). (PMID: 1154453010.1038/35092584)
      Dankort, D. et al. Braf V600E cooperates with Pten loss to induce metastatic melanoma. Nat. Genet. 41, 544–552 (2009). (PMID: 19282848270591810.1038/ng.356)
      Maria Bosisio, F. et al. Functional heterogeneity of lymphocytic patterns in primary melanoma dissected through single-cell multiplexing. eLife https://doi.org/10.7554/eLife.53008 (2020).
      Susaki, E. A. et al. Whole-brain imaging with single-cell resolution using chemical cocktails and computational analysis. Cell 157, 726–739 (2014). (PMID: 2474679110.1016/j.cell.2014.03.042)
      Frankish, A. et al. GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Res. 47, D766–D773 (2019). (PMID: 3035739310.1093/nar/gky955)
      Yates, A. D. et al. Ensembl 2020. Nucleic Acids Res. 48, D682–D688 (2020). (PMID: 31691826)
      Marçais, G. & Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27, 764–770 (2011). (PMID: 21217122305131910.1093/bioinformatics/btr011)
      Gans, J. D. & Wolinsky, M. Improved assay-dependent searching of nucleic acid sequence databases. Nucleic Acids Res. 36, e74 (2008). (PMID: 18515842247561010.1093/nar/gkn301)
      Rodriguez, J. M. et al. APPRIS 2017: principal isoforms for multiple gene sets. Nucleic Acids Res. 46, D213–D217 (2018). (PMID: 2906947510.1093/nar/gkx997)
      Bankhead, P. et al. QuPath: open source software for digital pathology image analysis. Sci. Rep. 7, 16878 (2017). (PMID: 29203879571511010.1038/s41598-017-17204-5)
      Schmidt, U., Weigert, M., Broaddus, C. & Myers, G. Cell detection with star-convex polygons. In Proc. Medical Image Computing and Computer Assisted Intervention—MICCAI 2018 (eds Frangi, A. et al.) Vol. 11071, 265–273 (Springer, 2018).
      McGinnis, C. S., Murrow, L. M. & Gartner, Z. J. DoubletFinder: doublet detection in single-cell RNA sequencing data using artificial nearest neighbors. Cell Syst. 8, 329–337 (2019). (PMID: 30954475685361210.1016/j.cels.2019.03.003)
      Korsunsky, I. et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 16, 1289–1296 (2019). (PMID: 31740819688469310.1038/s41592-019-0619-0)
      Rousseeuw, P. J. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20, 53–65 (1987). (PMID: 10.1016/0377-0427(87)90125-7)
      Oren, Y. et al. Cycling cancer persister cells arise from lineages with distinct programs. Nature 596, 576–582 (2021). (PMID: 34381210920984610.1038/s41586-021-03796-6)
      Guzmán, C., Bagga, M., Kaur, A., Westermarck, J. & Abankwa, D. ColonyArea: an ImageJ plugin to automatically quantify colony formation in clonogenic assays. PLoS ONE 9, e92444 (2014). (PMID: 24647355396024710.1371/journal.pone.0092444)
    • Grant Information:
      MC_PC_17230 United Kingdom MRC_ Medical Research Council; R01 DK056645 United States DK NIDDK NIH HHS; 219478/Z/19/Z United Kingdom WT_ Wellcome Trust; P30 CA013696 United States CA NCI NIH HHS; United Kingdom WT_ Wellcome Trust
    • Publication Date:
      Date Created: 20220921 Date Completed: 20221007 Latest Revision: 20231011
    • Publication Date:
      20240829
    • Accession Number:
      PMC10439739
    • Accession Number:
      10.1038/s41586-022-05242-7
    • Accession Number:
      36131018