A cellular hierarchy in melanoma uncouples growth and metastasis.
Animals
Cell Communication
Cell Differentiation
Cell Lineage
Cell Proliferation
Cell Tracking
Cellular Reprogramming
Endothelial Cells
Melanoma
/ genetics
Mesoderm
/ pathology
Mice
Neoplasm Metastasis
/ pathology
Neural Crest
/ embryology
Phenotype
Single-Cell Analysis
Transcriptome
Tumor Microenvironment
Journal
Nature
ISSN: 1476-4687
Titre abrégé: Nature
Pays: England
ID NLM: 0410462
Informations de publication
Date de publication:
10 2022
10 2022
Historique:
received:
01
07
2020
accepted:
17
08
2022
pubmed:
22
9
2022
medline:
12
10
2022
entrez:
21
9
2022
Statut:
ppublish
Résumé
Although melanoma is notorious for its high degree of heterogeneity and plasticity
Identifiants
pubmed: 36131018
doi: 10.1038/s41586-022-05242-7
pii: 10.1038/s41586-022-05242-7
pmc: PMC10439739
mid: NIHMS1922523
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
190-198Subventions
Organisme : Medical Research Council
ID : MC_PC_17230
Pays : United Kingdom
Organisme : NIDDK NIH HHS
ID : R01 DK056645
Pays : United States
Organisme : Wellcome Trust
ID : 219478/Z/19/Z
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : P30 CA013696
Pays : United States
Organisme : Wellcome Trust
Pays : United Kingdom
Commentaires et corrections
Type : ErratumIn
Type : CommentIn
Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Nature Limited.
Références
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).
pubmed: 31974247
pmcid: 7694873
doi: 10.1126/science.aax0249
Rambow, F. et al. Toward minimal residual disease-directed therapy in melanoma. Cell 174, 843–855 (2018).
pubmed: 30017245
doi: 10.1016/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).
pubmed: 27124452
pmcid: 4944528
doi: 10.1126/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).
pubmed: 32753671
doi: 10.1038/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
pubmed: 15899789
doi: 10.1158/0008-5472.CAN-04-2970
Serrano, M. et al. Role of the INK4a locus in tumor suppression and cell mortality. Cell 85, 27–37 (1996).
pubmed: 8620534
doi: 10.1016/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).
pubmed: 27124452
pmcid: 4944528
doi: 10.1126/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).
pubmed: 30388455
pmcid: 6410377
doi: 10.1016/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).
pubmed: 26489459
pmcid: 5970542
doi: 10.1016/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).
pubmed: 30388456
pmcid: 6641984
doi: 10.1016/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).
pubmed: 29898899
pmcid: 6071640
doi: 10.1101/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).
pubmed: 28991892
pmcid: 5937676
doi: 10.1038/nmeth.4463
Soldatov, R. et al. Spatiotemporal structure of cell fate decisions in murine neural crest. Science 364, eaas9536 (2019).
pubmed: 31171666
doi: 10.1126/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).
pubmed: 27926868
pmcid: 5726515
doi: 10.1016/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).
pubmed: 29657129
pmcid: 5953834
doi: 10.1016/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).
pubmed: 29033351
doi: 10.1016/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).
pubmed: 20887898
doi: 10.1016/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).
pubmed: 29802408
pmcid: 6400587
doi: 10.1038/s41556-018-0109-0
Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 (2019).
pubmed: 31178118
pmcid: 6687398
doi: 10.1016/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).
pubmed: 35512705
doi: 10.1016/j.cell.2022.04.003
Calabrese, C. et al. A perivascular niche for brain tumor stem cells. Cancer Cell 11, 69–82 (2007).
pubmed: 17222791
doi: 10.1016/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).
pubmed: 31819264
doi: 10.1038/s41592-019-0667-5
Jin, S. et al. Inference and analysis of cell-cell communication using CellChat. Nat. Commun. 12, 1088 (2021).
pubmed: 33597522
pmcid: 7889871
doi: 10.1038/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).
pubmed: 16199517
pmcid: 1239896
doi: 10.1073/pnas.0506580102
Wei, K. et al. Notch signalling drives synovial fibroblast identity and arthritis pathology. Nature 582, 259–264 (2020).
pubmed: 32499639
pmcid: 7841716
doi: 10.1038/s41586-020-2222-z
Takano, S. et al. Prrx1 isoform switching regulates pancreatic cancer invasion and metastatic colonization. Genes Dev. 30, 233–247 (2016).
pubmed: 26773005
pmcid: 4719312
doi: 10.1101/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).
pubmed: 23201163
doi: 10.1016/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).
pubmed: 18245463
doi: 10.1158/0008-5472.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).
pubmed: 22336146
doi: 10.1111/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).
pubmed: 19538944
pmcid: 2742350
doi: 10.1016/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).
pubmed: 20596026
pmcid: 2898751
doi: 10.1038/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).
pubmed: 20478252
pmcid: 2882693
doi: 10.1016/j.cell.2010.04.020
Schatton, T. et al. Identification of cells initiating human melanomas. Nature 451, 345–349 (2008).
pubmed: 18202660
pmcid: 3660705
doi: 10.1038/nature06489
Quintana, E. et al. Efficient tumour formation by single human melanoma cells. Nature 456, 593–598 (2008).
pubmed: 19052619
pmcid: 2597380
doi: 10.1038/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).
pubmed: 16676322
doi: 10.1002/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).
pubmed: 11544530
doi: 10.1038/35092584
Dankort, D. et al. Braf
pubmed: 19282848
pmcid: 2705918
doi: 10.1038/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).
pubmed: 24746791
doi: 10.1016/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).
pubmed: 30357393
doi: 10.1093/nar/gky955
Yates, A. D. et al. Ensembl 2020. Nucleic Acids Res. 48, D682–D688 (2020).
pubmed: 31691826
Marçais, G. & Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27, 764–770 (2011).
pubmed: 21217122
pmcid: 3051319
doi: 10.1093/bioinformatics/btr011
Gans, J. D. & Wolinsky, M. Improved assay-dependent searching of nucleic acid sequence databases. Nucleic Acids Res. 36, e74 (2008).
pubmed: 18515842
pmcid: 2475610
doi: 10.1093/nar/gkn301
Rodriguez, J. M. et al. APPRIS 2017: principal isoforms for multiple gene sets. Nucleic Acids Res. 46, D213–D217 (2018).
pubmed: 29069475
doi: 10.1093/nar/gkx997
Bankhead, P. et al. QuPath: open source software for digital pathology image analysis. Sci. Rep. 7, 16878 (2017).
pubmed: 29203879
pmcid: 5715110
doi: 10.1038/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).
pubmed: 30954475
pmcid: 6853612
doi: 10.1016/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).
pubmed: 31740819
pmcid: 6884693
doi: 10.1038/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).
doi: 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).
pubmed: 34381210
pmcid: 9209846
doi: 10.1038/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).
pubmed: 24647355
pmcid: 3960247
doi: 10.1371/journal.pone.0092444