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Annual Review of Cancer Biology

Volume 6, 2022

Single-Cell Epigenomics Reveals Mechanisms of Cancer Progression

Abstract

Cancer initiation is driven by the cooperation between genetic and epigenetic aberrations that disrupt gene regulatory programs critical to maintaining specialized cellular functions. After initiation, cells acquire additional genetic and epigenetic alterations influenced by tumor-intrinsic and -extrinsic mechanisms, which increase intratumoral heterogeneity, reshape the cell's underlying gene regulatory networks and promote cancer evolution. Furthermore, environmental or therapeutic insults drive the selection of heterogeneous cell states, with implications for cancer initiation, maintenance, and drug resistance. The advancement of single-cell genomics has begun to uncover the full repertoire of chromatin and gene expression states (cell states) that exist within individual tumors. These single-cell analyses suggest that cells diversify in their regulatory states upon transformation by co-opting damage-induced and nonlineage regulatory programs that can lead to epigenomic plasticity. Here, we review these recent studies related to regulatory state changes in cancer progression and highlight the growing single-cell epigenomics toolkit poised to address unresolved questions in the field.

Keyword(s): cancer evolution, DNA methylation, drug resistance, lineage infidelity, plasticity, single-cell epigenomics
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/content/journals/10.1146/annurev-cancerbio-070620-094453
2022-04-11
2024-04-19
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Literature Cited

  1. Affer M, Chesi M, Chen W-DG, Keats JJ, Demchenko YN et al. 2014. Promiscuous MYC locus rearrangements hijack enhancers but mostly super-enhancers to dysregulate MYC expression in multiple myeloma. Leukemia 28:81725–35
     [Google Scholar]
  2. Alonso-Curbelo D, Ho Y-J, Burdziak C, Maag JLV, Morris JP 4th et al. 2021. A gene-environment-induced epigenetic program initiates tumorigenesis. Nature 590:7847642–48
     [Google Scholar]
  3. Angermueller C, Clark SJ, Lee HJ, Macaulay IC, Teng MJ et al. 2016. Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity. Nat. Methods 13:3229–32
     [Google Scholar]
  4. Avsec Ž, Weilert M, Shrikumar A, Krueger S, Alexandari A et al. 2021. Base-resolution models of transcription-factor binding reveal soft motif syntax. Nat. Genet. 53:3354–66
     [Google Scholar]
  5. Bailey C, Black JRM, Reading JL, Litchfield K, Turajlic S et al. 2021. Tracking cancer evolution through the disease course. Cancer Discov 11:4916–32
     [Google Scholar]
  6. Bartosovic M, Kabbe M, Castelo-Branco G. 2021. Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues. Nat. Biotechnol. 39:825–35
     [Google Scholar]
  7. Bejjani F, Evanno E, Zibara K, Piechaczyk M, Jariel-Encontre I. 2019. The AP-1 transcriptional complex: local switch or remote command?. Biochim. Biophys. Acta Rev. Cancer 1872:111–23
     [Google Scholar]
  8. Biehs B, Dijkgraaf GJP, Piskol R, Alicke B, Boumahdi S et al. 2018. A cell identity switch allows residual BCC to survive Hedgehog pathway inhibition. Nature 562:7727429–33
     [Google Scholar]
  9. Black JRM, McGranahan N. 2021. Genetic and non-genetic clonal diversity in cancer evolution. Nat. Rev. Cancer 21:6379–92
     [Google Scholar]
  10. Blanpain C. 2013. Tracing the cellular origin of cancer. Nat. Cell Biol. 15:2126–34
     [Google Scholar]
  11. Boix CA, James BT, Park YP, Meuleman W, Kellis M 2021. Regulatory genomic circuitry of human disease loci by integrative epigenomics. Nature 590:7845300–7
     [Google Scholar]
  12. Bowling S, Sritharan D, Osorio FG, Nguyen M, Cheung P et al. 2020. An engineered CRISPR-Cas9 mouse line for simultaneous readout of lineage histories and gene expression profiles in single cells. Cell 181:61410–22.e27
     [Google Scholar]
  13. Bowman RL, Busque L, Levine RL. 2018. Clonal hematopoiesis and evolution to hematopoietic malignancies. Cell Stem Cell 22:2157–70
     [Google Scholar]
  14. Buenrostro JD, Corces MR, Lareau CA, Wu B, Schep AN et al. 2018. Integrated single-cell analysis maps the continuous regulatory landscape of human hematopoietic differentiation. Cell 173:61535–48.e16
     [Google Scholar]
  15. Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ 2013. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10:121213–18
     [Google Scholar]
  16. Buenrostro JD, Wu B, Litzenburger UM, Ruff D, Gonzales ML et al. 2015. Single-cell chromatin accessibility reveals principles of regulatory variation. Nature 523:7561486–90
     [Google Scholar]
  17. Cajuso T, Sulo P, Tanskanen T, Katainen R, Taira A et al. 2019. Retrotransposon insertions can initiate colorectal cancer and are associated with poor survival. Nat. Commun. 10:4022
     [Google Scholar]
  18. Cao J, Zhou W, Steemers F, Trapnell C, Shendure J. 2020. Sci-fate characterizes the dynamics of gene expression in single cells. Nat. Biotechnol. 38:8980–88
     [Google Scholar]
  19. Capper D, Jones DTW, Sill M, Hovestadt V, Schrimpf D et al. 2018. DNA methylation-based classification of central nervous system tumours. Nature 555:7697469–74
     [Google Scholar]
  20. Castro LNG, Tirosh I, Suvà ML 2021. Decoding cancer biology one cell at a time. Cancer Discov 11:4960–70
     [Google Scholar]
  21. Cejas P, Drier Y, Dreijerink KMA, Brosens LAA, Deshpande V et al. 2019. Enhancer signatures stratify and predict outcomes of non-functional pancreatic neuroendocrine tumors. Nat. Med. 25:81260–65
     [Google Scholar]
  22. Chen H, Li C, Peng X, Zhou Z, Weinstein JN et al. 2018. A pan-cancer analysis of enhancer expression in nearly 9000 patient samples. Cell 173:2386–99.e12
     [Google Scholar]
  23. Chen KH, Boettiger AN, Moffitt JR, Wang S, Zhuang X 2015. RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348:6233eaaa6090
     [Google Scholar]
  24. Chen S, Lake BB, Zhang K. 2019. High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell. Nat. Biotechnol. 37:121452–57
     [Google Scholar]
  25. Cheow LF, Courtois ET, Tan Y, Viswanathan R, Xing Q et al. 2016. Single-cell multimodal profiling reveals cellular epigenetic heterogeneity. Nat. Methods 13:10833–36
     [Google Scholar]
  26. Clark SJ, Argelaguet R, Kapourani C-A, Stubbs TM, Lee HJ et al. 2018. scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells. Nat. Commun. 9:781
     [Google Scholar]
  27. Corces MR, Buenrostro JD, Wu B, Greenside PG, Chan SM et al. 2016. Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution. Nat. Genet. 48:101193–203
     [Google Scholar]
  28. Corces MR, Granja JM, Shams S, Louie BH, Seoane JA et al. 2018. The chromatin accessibility landscape of primary human cancers. Science 362:6413eaav1898
     [Google Scholar]
  29. Cusanovich DA, Daza R, Adey A, Pliner HA, Christiansen L et al. 2015. Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing. Science 348:6237910–14
     [Google Scholar]
  30. Emert BL, Cote CJ, Torre EA, Dardani IP, Jiang CL et al. 2021. Variability within rare cell states enables multiple paths toward drug resistance. Nat. Biotechnol. 39:865–76
     [Google Scholar]
  31. ENCODE Proj. Consort., Moore JE, Purcaro MJ, Pratt HE, Epstein CB et al. 2020. Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature 583:7818699–710
     [Google Scholar]
  32. Essex A, Pineda J, Acharya G, Xin H, Evans JReprod. Proj. Cancer Biol 2019. Replication study: Wnt activity defines colon cancer stem cells and is regulated by the microenvironment. eLife 8:e45426
     [Google Scholar]
  33. Ewing AD, Smits N, Sanchez-Luque FJ, Faivre J, Brennan PM et al. 2020. Nanopore sequencing enables comprehensive transposable element epigenomic profiling. Mol. Cell 80:5915–28.e5
     [Google Scholar]
  34. Fearon ER, Vogelstein B. 1990. A genetic model for colorectal tumorigenesis. Cell 61:5759–67
     [Google Scholar]
  35. Ferone G, Lee MC, Sage J, Berns A 2020. Cells of origin of lung cancers: lessons from mouse studies. Genes Dev 34:15–161017–32
     [Google Scholar]
  36. Fiore VF, Krajnc M, Quiroz FG, Levorse J, Pasolli HA et al. 2020. Mechanics of a multilayer epithelium instruct tumour architecture and function. Nature 585:7825433–39
     [Google Scholar]
  37. Flavahan WA, Drier Y, Johnstone SE, Hemming ML, Tarjan DR et al. 2019. Altered chromosomal topology drives oncogenic programs in SDH-deficient GISTs. Nature 575:7781229–33
     [Google Scholar]
  38. Flavahan WA, Drier Y, Liau BB, Gillespie SM, Venteicher AS et al. 2016. Insulator dysfunction and oncogene activation in IDH mutant gliomas. Nature 529:7584110–14
     [Google Scholar]
  39. Gaiti F, Chaligne R, Gu H, Brand RM, Kothen-Hill S et al. 2019. Epigenetic evolution and lineage histories of chronic lymphocytic leukaemia. Nature 569:7757576–80
     [Google Scholar]
  40. Gasperini M, Hill AJ, McFaline-Figueroa JL, Martin B, Kim S et al. 2019. A genome-wide framework for mapping gene regulation via cellular genetic screens. Cell 176:6377–90.e19
     [Google Scholar]
  41. Ge Y, Gomez NC, Adam RC, Nikolova M, Yang H et al. 2017. Stem cell lineage infidelity drives wound repair and cancer. Cell 169:4636–50.e14
     [Google Scholar]
  42. George J, Uyar A, Young K, Kuffler L, Waldron-Francis K et al. 2016. Leukaemia cell of origin identified by chromatin landscape of bulk tumour cells. Nat. Commun. 7:12166
     [Google Scholar]
  43. Glass JL, Hassane D, Wouters BJ, Kunimoto H, Avellino R et al. 2017. Epigenetic identity in AML depends on disruption of nonpromoter regulatory elements and is affected by antagonistic effects of mutations in epigenetic modifiers. Cancer Discov 7:8868–83
     [Google Scholar]
  44. Gola A, Fuchs E. 2021. Environmental control of lineage plasticity and stem cell memory. Curr. Opin. Cell Biol. 69:88–95
     [Google Scholar]
  45. Goltsev Y, Samusik N, Kennedy-Darling J, Bhate S, Hale M et al. 2018. Deep profiling of mouse splenic architecture with CODEX multiplexed imaging. Cell 174:4968–81.e15
     [Google Scholar]
  46. Granja JM, Corces MR, Pierce SE, Bagdatli ST, Choudhry H et al. 2021. ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis. Nat. Genet. 53:3403–11
     [Google Scholar]
  47. Gravina S, Dong X, Yu B, Vijg J 2016. Single-cell genome-wide bisulfite sequencing uncovers extensive heterogeneity in the mouse liver methylome. Genome Biol 17:150
     [Google Scholar]
  48. Grosselin K, Durand A, Marsolier J, Poitou A, Marangoni E et al. 2019. High-throughput single-cell ChIP-seq identifies heterogeneity of chromatin states in breast cancer. Nat. Genet. 51:61060–66
     [Google Scholar]
  49. Gu Z, Liu Y, Zhang Y, Cao H, Lyu J et al. 2021. Silencing of LINE-1 retrotransposons is a selective dependency of myeloid leukemia. Nat. Genet. 53:5672–82
     [Google Scholar]
  50. Guerra C, Schuhmacher AJ, Cañamero M, Grippo PJ, Verdaguer L et al. 2007. Chronic pancreatitis is essential for induction of pancreatic ductal adenocarcinoma by K-Ras oncogenes in adult mice. Cancer Cell 11:3291–302
     [Google Scholar]
  51. Guo F, Li L, Li J, Wu X, Hu B et al. 2017. Single-cell multi-omics sequencing of mouse early embryos and embryonic stem cells. Cell Res 27:8967–88
     [Google Scholar]
  52. Gupta PB, Fillmore CM, Jiang G, Shapira SD, Tao K et al. 2011. Stochastic state transitions give rise to phenotypic equilibrium in populations of cancer cells. Cell 146:4633–44
     [Google Scholar]
  53. Haigis KM, Cichowski K, Elledge SJ 2019. Tissue-specificity in cancer: the rule, not the exception. Science 363:64321150–51
     [Google Scholar]
  54. Hendricks WPD, Sekulic A, Bryce AH, Murtaza M, Ramos P, Trent JM 2017. Cancer genomics and evolution. Holland-Frei Cancer Medicine RC Bast, WN Hait, DW Kufe, RR Weichselbaum, JF Holland et al., 9th ed.. https://doi.org/10.1002/9781119000822.hfcm007
    [Crossref] [Google Scholar]
  55. Hnisz D, Abraham BJ, Lee TI, Lau A, Saint-André V et al. 2013. Super-enhancers in the control of cell identity and disease. Cell 155:4934–47
     [Google Scholar]
  56. Hoadley KA, Yau C, Hinoue T, Wolf DM, Lazar AJ et al. 2018. Cell-of-origin patterns dominate the molecular classification of 10,000 tumors from 33 types of cancer. Cell 173:2291–304.e6
     [Google Scholar]
  57. Hou Y, Guo H, Cao C, Li X, Hu B et al. 2016. Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas. Cell Res 26:3304–19
     [Google Scholar]
  58. Hu Y, An Q, Guo Y, Zhong J, Fan S et al. 2019. Simultaneous profiling of mRNA transcriptome and DNA methylome from a single cell. Methods Mol. Biol. 1979:363–77
     [Google Scholar]
  59. Huang FW, Hodis E, Xu MJ, Kryukov GV, Chin L, Garraway LA 2013. Highly recurrent TERT promoter mutations in human melanoma. Science 339:6122957–59
     [Google Scholar]
  60. Ireland AS, Micinski AM, Kastner DW, Guo B, Wait SJ et al. 2020. MYC drives temporal evolution of small cell lung cancer subtypes by reprogramming neuroendocrine fate. Cancer Cell 38:160–78.e12
     [Google Scholar]
  61. Ishak CA, De Carvalho DD. 2020. Reactivation of endogenous retroelements in cancer development and therapy. Annu. Rev. Cancer Biol. 4:159–76
     [Google Scholar]
  62. Jaiswal S, Ebert BL 2019. Clonal hematopoiesis in human aging and disease. Science 366:6465eaan4673
     [Google Scholar]
  63. Jaiswal S, Fontanillas P, Flannick J, Manning A, Grauman PV et al. 2014. Age-related clonal hematopoiesis associated with adverse outcomes. N. Engl. J. Med. 371:262488–98
     [Google Scholar]
  64. Jerby-Arnon L, Shah P, Cuoco MS, Rodman C, Su M-J et al. 2018. A cancer cell program promotes T cell exclusion and resistance to checkpoint blockade. Cell 175:4984–97.e24
     [Google Scholar]
  65. Johnstone SE, Reyes A, Qi Y, Adriaens C, Hegazi E et al. 2020. Large-scale topological changes restrain malignant progression in colorectal cancer. Cell 182:61474–89.e23
     [Google Scholar]
  66. Kamimoto K, Hoffmann CM, Morris SA. 2020. CellOracle: dissecting cell identity via network inference and in silico gene perturbation. bioRxiv 2020.02.17.947416. https://doi.org/10.1101/2020.02.17.947416
    [Crossref]
  67. Karemaker ID, Vermeulen M. 2018. Single-cell DNA methylation profiling: technologies and biological applications. Trends Biotechnol 36:9952–65
     [Google Scholar]
  68. Kaur A, Ecker BL, Douglass SM, Kugel CH 3rd, Webster MR et al. 2019. Remodeling of the collagen matrix in aging skin promotes melanoma metastasis and affects immune cell motility. Cancer Discov 9:164–81
     [Google Scholar]
  69. Kaya-Okur HS, Wu SJ, Codomo CA, Pledger ES, Bryson TD et al. 2019. CUT&Tag for efficient epigenomic profiling of small samples and single cells. Nat. Commun. 10:1930
     [Google Scholar]
  70. Kelsey G, Stegle O, Reik W. 2017. Single-cell epigenomics: recording the past and predicting the future. Science 358:635969–75
     [Google Scholar]
  71. Klughammer J, Kiesel B, Roetzer T, Fortelny N, Nemc A et al. 2018. The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space. Nat. Med. 24:101611–24
     [Google Scholar]
  72. LaFave LM, Kartha VK, Ma S, Meli K, Del Priore I et al. 2020. Epigenomic state transitions characterize tumor progression in mouse lung adenocarcinoma. Cancer Cell 38:2212–28.e13
     [Google Scholar]
  73. Lal A, Chiang ZD, Yakovenko N, Duarte FM, Israeli J, Buenrostro JD. 2021. Deep learning-based enhancement of epigenomics data with AtacWorks. Nat. Commun. 12:1507
     [Google Scholar]
  74. Lambert SA, Jolma A, Campitelli LF, Das PK, Yin Y et al. 2018. The human transcription factors. Cell 175:2598–99
     [Google Scholar]
  75. Lareau CA, Duarte FM, Chew JG, Kartha VK, Burkett ZD et al. 2019. Droplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility. Nat. Biotechnol. 37:8916–24
     [Google Scholar]
  76. Laughney AM, Hu J, Campbell NR, Bakhoum SF, Setty M et al. 2020. Regenerative lineages and immune-mediated pruning in lung cancer metastasis. Nat. Med. 26:2259–69
     [Google Scholar]
  77. Li Y, He Y, Peng J, Su Z, Li Z et al. 2021. Mutant Kras co-opts a proto-oncogenic enhancer network in inflammation-induced metaplastic progenitor cells to initiate pancreatic cancer. Nat. Cancer 2:49–65
     [Google Scholar]
  78. Liau BB, Sievers C, Donohue LK, Gillespie SM, Flavahan WA et al. 2017. Adaptive chromatin remodeling drives glioblastoma stem cell plasticity and drug tolerance. Cell Stem Cell 20:2233–46.e7
     [Google Scholar]
  79. Ligorio M, Sil S, Malagon-Lopez J, Nieman LT, Misale S et al. 2019. Stromal microenvironment shapes the intratumoral architecture of pancreatic cancer. Cell 178:1160–75.e27
     [Google Scholar]
  80. Lim JS, Ibaseta A, Fischer MM, Cancilla B, O'Young G et al. 2017. Intratumoural heterogeneity generated by Notch signalling promotes small-cell lung cancer. Nature 545:7654360–64
     [Google Scholar]
  81. Liu XS, Wu H, Ji X, Stelzer Y, Wu X et al. 2016. Editing DNA methylation in the mammalian genome. Cell 167:1233–47.e17
     [Google Scholar]
  82. Long HK, Prescott SL, Wysocka J 2016. Ever-changing landscapes: transcriptional enhancers in development and evolution. Cell 167:51170–87
     [Google Scholar]
  83. Lopez R, Regier J, Cole MB, Jordan MI, Yosef N 2018. Deep generative modeling for single-cell transcriptomics. Nat. Methods 15:121053–58
     [Google Scholar]
  84. Ludwig LS, Lareau CA, Ulirsch JC, Christian E, Muus C et al. 2019. Lineage tracing in humans enabled by mitochondrial mutations and single-cell genomics. Cell 176:61325–39.e22
     [Google Scholar]
  85. Ma S, Zhang B, LaFave LM, Earl AS, Chiang Z et al. 2020. Chromatin potential identified by shared single-cell profiling of RNA and chromatin. Cell 183:41103–16.e20
     [Google Scholar]
  86. MacCarthy-Morrogh L, Martin P. 2020. The hallmarks of cancer are also the hallmarks of wound healing. Sci. Signal. 13:648eaay8690
     [Google Scholar]
  87. Mansour MR, Abraham BJ, Anders L, Berezovskaya A, Gutierrez A et al. 2014. An oncogenic super-enhancer formed through somatic mutation of a noncoding intergenic element. Science 346:62151373–77
     [Google Scholar]
  88. Marjanovic ND, Hofree M, Chan JE, Canner D, Wu K et al. 2020. Emergence of a high-plasticity cell state during lung cancer evolution. Cancer Cell 38:2229–46.e13
     [Google Scholar]
  89. Massagué J, Ganesh K. 2021. Metastasis-initiating cells and ecosystems. Cancer Discov 11:4971–94
     [Google Scholar]
  90. Moncada R, Barkley D, Wagner F, Chiodin M, Devlin JC et al. 2020. Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas. Nat. Biotechnol. 38:3333–42
     [Google Scholar]
  91. Nabhan AN, Brownfield DG, Harbury PB, Krasnow MA, Desai TJ. 2018. Single-cell Wnt signaling niches maintain stemness of alveolar type 2 cells. Science 359:63801118–23
     [Google Scholar]
  92. Nasser J, Bergman DT, Fulco CP, Guckelberger P, Doughty BR et al. 2021. Genome-wide enhancer maps link risk variants to disease genes. Nature 593:7858238–43
     [Google Scholar]
  93. Navin N, Kendall J, Troge J, Andrews P, Rodgers L et al. 2011. Tumour evolution inferred by single-cell sequencing. Nature 472:734190–94
     [Google Scholar]
  94. Nuñez JK, Chen J, Pommier GC, Cogan JZ, Replogle JM et al. 2021. Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing. Cell 184:92503–19.e17
     [Google Scholar]
  95. Oldridge DA, Wood AC, Weichert-Leahey N, Crimmins I, Sussman R et al. 2015. Genetic predisposition to neuroblastoma mediated by a LMO1 super-enhancer polymorphism. Nature 528:7582418–21
     [Google Scholar]
  96. Payne AC, Chiang ZD, Reginato PL, Mangiameli SM, Murray EM et al. 2021. In situ genome sequencing resolves DNA sequence and structure in intact biological samples. Science 371:6532eaay3446
     [Google Scholar]
  97. Pott S. 2017. Simultaneous measurement of chromatin accessibility, DNA methylation, and nucleosome phasing in single cells. eLife 6:e23203
     [Google Scholar]
  98. Puram SV, Tirosh I, Parikh AS, Patel AP, Yizhak K et al. 2017. Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in head and neck cancer. Cell 171:71611–24.e24
     [Google Scholar]
  99. Qiu Q, Hu P, Qiu X, Govek KW, Cámara PG, Wu H. 2020. Massively parallel and time-resolved RNA sequencing in single cells with scNT-seq. Nat. Methods 17:10991–1001
     [Google Scholar]
  100. Quinn JJ, Jones MG, Okimoto RA, Nanjo S, Chan MM et al. 2021. Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts. Science 371:6532eabc1944
     [Google Scholar]
  101. Rada-Iglesias A, Bajpai R, Swigut T, Brugmann SA, Flynn RA, Wysocka J 2011. A unique chromatin signature uncovers early developmental enhancers in humans. Nature 470:7333279–83
     [Google Scholar]
  102. Ramani V, Deng X, Qiu R, Lee C, Disteche CM et al. 2020. Sci-Hi-C: a single-cell Hi-C method for mapping 3D genome organization in large number of single cells. Methods 170:61–68
     [Google Scholar]
  103. Reiter JG, Baretti M, Gerold JM, Makohon-Moore AP, Daud A et al. 2019. An analysis of genetic heterogeneity in untreated cancers. Nat. Rev. Cancer 19:11639–50
     [Google Scholar]
  104. Rodriques SG, Stickels RR, Goeva A, Martin CA, Murray E et al. 2019. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 363:64341463–67
     [Google Scholar]
  105. Rotem A, Ram O, Shoresh N, Sperling RA, Goren A et al. 2015. Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state. Nat. Biotechnol. 33:111165–72
     [Google Scholar]
  106. Satija R, Farrell JA, Gennert D, Schier AF, Regev A. 2015. Spatial reconstruction of single-cell gene expression data. Nat. Biotechnol. 33:5495–502
     [Google Scholar]
  107. Satpathy AT, Granja JM, Yost KE, Qi Y, Meschi F et al. 2019. Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion. Nat. Biotechnol. 37:8925–36
     [Google Scholar]
  108. Schwenger E, Steidl U. 2021. An evolutionary approach to clonally complex hematologic disorders. Blood Cancer Discov 2:3201–15
     [Google Scholar]
  109. Shaffer SM, Dunagin MC, Torborg SR, Torre EA, Emert B et al. 2017. Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance. Nature 546:7658431–35
     [Google Scholar]
  110. Sharma SV, Lee DY, Li B, Quinlan MP, Takahashi F et al. 2010. A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations. Cell 141:169–80
     [Google Scholar]
  111. Shema E, Bernstein BE, Buenrostro JD. 2019. Single-cell and single-molecule epigenomics to uncover genome regulation at unprecedented resolution. Nat. Genet. 51:19–25
     [Google Scholar]
  112. Simeonov KP, Byrns CN, Clark ML, Norgard RJ, Martin B et al. 2021. Single-cell lineage tracing of metastatic cancer reveals selection of hybrid EMT states. Cancer Cell 39:81150–62.e9
     [Google Scholar]
  113. Sinha S, Satpathy AT, Zhou W, Ji H, Stratton JA et al. 2021. Profiling chromatin accessibility at single-cell resolution. Genom. Proteom. Bioinformat. 19:(2):172–90
     [Google Scholar]
  114. Skene PJ, Henikoff S 2017. An efficient targeted nuclease strategy for high-resolution mapping of DNA binding sites. eLife 6:e21856
     [Google Scholar]
  115. Smith EA, Hodges HC. 2019. The spatial and genomic hierarchy of tumor ecosystems revealed by single-cell technologies. Trends Cancer Res 5:7411–25
     [Google Scholar]
  116. Srivatsan SR, McFaline-Figueroa JL, Ramani V, Saunders L, Cao J et al. 2020. Massively multiplex chemical transcriptomics at single-cell resolution. Science 367:647345–51
     [Google Scholar]
  117. Stickels RR, Murray E, Kumar P, Li J, Marshall JL et al. 2021. Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2. Nat. Biotechnol. 39:3313–19
     [Google Scholar]
  118. Storz P. 2017. Acinar cell plasticity and development of pancreatic ductal adenocarcinoma. Nat. Rev. Gastroenterol. Hepatol. 14:5296–304
     [Google Scholar]
  119. Su J-H, Zheng P, Kinrot SS, Bintu B, Zhuang X. 2020. Genome-scale imaging of the 3D organization and transcriptional activity of chromatin. Cell 182:61641–59.e26
     [Google Scholar]
  120. Sud A, Kinnersley B, Houlston RS. 2017. Genome-wide association studies of cancer: current insights and future perspectives. Nat. Rev. Cancer 17:11692–704
     [Google Scholar]
  121. Sun X-X, Yu Q 2015. Intra-tumor heterogeneity of cancer cells and its implications for cancer treatment. Acta Pharmacol. Sin. 36:101219–27
     [Google Scholar]
  122. Taniguchi S, Elhance A, Van Duzer A, Kumar S, Leitenberger JJ, Oshimori N. 2020. Tumor-initiating cells establish an IL-33-TGF-β niche signaling loop to promote cancer progression. Science 369:6501eaay1813
     [Google Scholar]
  123. Tata PR, Chow RD, Saladi SV, Tata A, Konkimalla A et al. 2018. Developmental history provides a roadmap for the emergence of tumor plasticity. Dev. Cell 44:6679–93.e5
     [Google Scholar]
  124. Thornton CA, Mulqueen RM, Torkenczy KA, Nishida A, Lowenstein EG et al. 2021. Spatially mapped single-cell chromatin accessibility. Nat. Commun. 12:1274
     [Google Scholar]
  125. Timp W, Feinberg AP. 2013. Cancer as a dysregulated epigenome allowing cellular growth advantage at the expense of the host. Nat. Rev. Cancer 13:7497–510
     [Google Scholar]
  126. Valencia AM, Kadoch C. 2019. Chromatin regulatory mechanisms and therapeutic opportunities in cancer. Nat. Cell Biol. 21:2152–61
     [Google Scholar]
  127. Van Keymeulen A, Lee MY, Ousset M, Brohée S, Rorive S et al. 2015. Reactivation of multipotency by oncogenic PIK3CA induces breast tumour heterogeneity. Nature 525:7567119–23
     [Google Scholar]
  128. Visvader JE. 2011. Cells of origin in cancer. Nature 469:7330314–22
     [Google Scholar]
  129. Wagner DE, Klein AM. 2020. Lineage tracing meets single-cell omics: opportunities and challenges. Nat. Rev. Genet. 21:7410–27
     [Google Scholar]
  130. Wang X, Allen WE, Wright MA, Sylwestrak EL, Samusik N et al. 2018. Three-dimensional intact-tissue sequencing of single-cell transcriptional states. Science 361:6400eaat5691
     [Google Scholar]
  131. Weinreb C, Rodriguez-Fraticelli A, Camargo FD, Klein AM. 2020. Lineage tracing on transcriptional landscapes links state to fate during differentiation. Science 367:6479eaaw3381
     [Google Scholar]
  132. Weinstein JN, Cancer Genome Atlas Res. Netw., Collisson EA, Mills GB, Mills Shaw KR et al. 2013. The Cancer Genome Atlas Pan-Cancer analysis project. Nat. Genet. 45:101113–20
     [Google Scholar]
  133. Woodworth MB, Girskis KM, Walsh CA. 2017. Building a lineage from single cells: genetic techniques for cell lineage tracking. Nat. Rev. Genet. 18:4230–44
     [Google Scholar]
  134. Wu SJ, Furlan SN, Mihalas AB, Kaya-Okur HS, Feroze AH et al. 2021. Single-cell CUT&Tag analysis of chromatin modifications in differentiation and tumor progression. Nat. Biotechnol. 39:819–824
     [Google Scholar]
  135. Young MD, Mitchell TJ, Vieira Braga FA, Tran MGB, Stewart BJ et al. 2018. Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors. Science 361:6402594–99
     [Google Scholar]
  136. Zhao T, Chiang ZD, Morriss JW, LaFave LM, Murray EM et al. 2021. Spatial genomics enables multi-modal study of clonal heterogeneity in tissues. Nature 601:85–91
     [Google Scholar]
  137. Zhu Y, Gujar AD, Wong C-H, Tjong H, Ngan CY et al. 2021. Oncogenic extrachromosomal DNA functions as mobile enhancers to globally amplify chromosomal transcription. Cancer Cell 39:5694–707.e7
     [Google Scholar]
/content/journals/10.1146/annurev-cancerbio-070620-094453
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Single-Cell Epigenomics Reveals Mechanisms of Cancer Progression
Annual Review of Cancer Biology 6, 167 (2022); https://doi.org/10.1146/annurev-cancerbio-070620-094453
/content/journals/10.1146/annurev-cancerbio-070620-094453
/content/journals/10.1146/annurev-cancerbio-070620-094453
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  • Article Type: Review Article

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