Skip to main content

Advertisement

Springer Nature Link
Log in

Unlocking the Complexity: Exploration of Acute Lymphoblastic Leukemia at the Single Cell Level

  • Current Opinion
  • Published:
Molecular Diagnosis & Therapy Aims and scope Submit manuscript

Abstract

Acute lymphoblastic leukemia (ALL) is the most common cancer in children. ALL originates from precursor lymphocytes that acquire multiple genomic changes over time, including chromosomal rearrangements and point mutations. While a large variety of genomic defects was identified and characterized in ALL over the past 30 years, it was only in recent years that the clonal heterogeneity was recognized. Thanks to the latest advancements in single-cell sequencing techniques, which have evolved from the analysis of a few hundred cells to the analysis of thousands of cells simultaneously, the study of tumor heterogeneity now becomes possible. Different modalities can be explored at the single-cell level: DNA, RNA, epigenetic modifications, and intracellular and cell surface proteins. In this review, we describe these techniques and highlight their advantages and limitations in the study of ALL biology. Moreover, multiomics technologies and the incorporation of the spatial dimension can provide insight into intercellular communication. We describe how the different single-cell sequencing technologies help to unravel the molecular complexity of ALL, shedding light on its development, its heterogeneity, its interaction with the leukemia microenvironment and possible relapse mechanisms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Adapted from Zhang et al. [94]

Fig. 5

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

References

  1. Ward E, DeSantis C, Robbins A, Kohler B, Jemal A. Childhood and adolescent cancer statistics, 2014. CA Cancer J Clin. 2014;64:83–103.

    Article  PubMed  Google Scholar 

  2. Bertuccio P, Bosetti C, Malvezzi M, Levi F, Chatenoud L, Negri E, et al. Trends in mortality from leukemia in Europe: An update to 2009 and a projection to 2012. Int J Cancer [Internet]. 2013 [cited 2021 Oct 14];132:427–36. Available from: https://onlinelibrary.wiley.com/doi/https://doi.org/10.1002/ijc.27624

  3. Parker C, Waters R, Leighton C, Hancock J, Sutton R, Moorman AV, et al. Effect of mitoxantrone on outcome of children with first relapse of acute lymphoblastic leukaemia (ALL R3): an open-label randomised trial. Lancet. 2010;376:2009–17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Eckert C, Henze G, Seeger K, Hagedorn N, Mann G, Panzer-Grümayer R, et al. Use of allogeneic hematopoietic stem-cell transplantation based on minimal residual disease response improves outcomes for children with relapsed acute lymphoblastic leukemia in the intermediate-risk group. J Clin Oncol. 2013;31:2736–42.

    Article  PubMed  Google Scholar 

  5. Vora A, Goulden N, Wade R, Mitchell C, Hancock J, Hough R, et al. Treatment reduction for children and young adults with low-risk acute lymphoblastic leukaemia defined by minimal residual disease (UKALL 2003): a randomised controlled trial. Lancet Oncol. 2013;14:199–209.

    Article  CAS  PubMed  Google Scholar 

  6. Pieters R, De Groot-Kruseman H, Van Der Velden V, Fiocco M, Van Den Berg H, De Bont E, et al. Successful therapy reduction and intensification for childhood acute lymphoblastic leukemia based on minimal residual disease monitoring: Study ALL10 from the Dutch Childhood Oncology Group. J Clin Oncol. 2016;34:2591–601.

    Article  PubMed  Google Scholar 

  7. Jensen KS, Oskarsson T, Lähteenmäki PM, Flaegstad T, Jónsson ÓG, Svenberg P, et al. Temporal changes in incidence of relapse and outcome after relapse of childhood acute lymphoblastic leukemia over three decades; a Nordic population-based cohort study. Leukemia 2022 36:5 [Internet]. 2022 [cited 2023 Mar 30];36:1274–82. Available from: https://www.nature.com/articles/s41375-022-01540-1

  8. Gjærde LK, Rank CU, Andersen MK, Jakobsen LH, Sengeløv H, Olesen G, et al. Improved survival after allogeneic transplantation for acute lymphoblastic leukemia in adults: a Danish population-based study. Leuk Lymphoma [Internet]. 2022 [cited 2024 Jan 29];63:416–25. Available from: https://www.tandfonline.com/doi/abs/https://doi.org/10.1080/10428194.2021.1992620

  9. Fredman D, Moshe Y, Wolach O, Heering G, Shichrur K, Goldberg I, et al. Evaluating outcomes of adult patients with acute lymphoblastic leukemia and lymphoblastic lymphoma treated on the GMALL 07/2003 protocol. Ann Hematol [Internet]. 2022 [cited 2024 Jan 29];101:581–93. Available from: https://link.springer.com/article/https://doi.org/10.1007/s00277-021-04738-y

  10. Lennmyr E, Karlsson K, Ahlberg L, Garelius H, Hulegårdh E, Izarra AS, et al. Survival in adult acute lymphoblastic leukaemia (ALL): A report from the Swedish ALL Registry. Eur J Haematol [Internet]. 2019 [cited 2024 Jan 29];103:88–98. Available from: https://onlinelibrary.wiley.com/doi/https://doi.org/10.1111/ejh.13247

  11. Aldoss I, Forman SJ, Pullarkat V. Acute lymphoblastic leukemia in the older adult. J Oncol Pract [Internet]. 2019 [cited 2024 Jan 29];15:67–75. Available from: https://ascopubs.org/doi/https://doi.org/10.1200/JOP.18.00271

  12. Aladag E, Aktimur SH, Aydın Ö, Demiroglu H, Buyukasik Y, Aksu S, et al. Allogeneic hematopoietic stem-cell transplantation improves disease-free survival compared to pediatric-inspired Berlin-Frankfurt-Münster chemotherapy in adult acute lymphoblastic leukemia. Clin Lymphoma Myeloma Leuk. 2021;21:147–53.

    Article  CAS  PubMed  Google Scholar 

  13. Iacobucci I, Mullighan CG. Genetic Basis of Acute Lymphoblastic Leukemia. Journal of Clinical Oncology [Internet]. 2017 [cited 2021 Oct 14];35:975–83. Available from: https://ascopubs.org/doi/https://doi.org/10.1200/JCO.2016.70.7836

  14. Roberts KG, Mullighan CG. The Biology of B-Progenitor Acute Lymphoblastic Leukemia. Cold Spring Harb Perspect Med [Internet]. 2020 [cited 2021 Oct 14];10:a034835. Available from: http://perspectivesinmedicine.cshlp.org/lookup/doi/https://doi.org/10.1101/cshperspect.a034835

  15. Girardi T, Vicente C, Cools J, De Keersmaecker K. The genetics and molecular biology of T-ALL. Blood [Internet]. 2017 [cited 2021 Oct 14];129:1113–23. Available from: https://ashpublications.org/blood/article/129/9/1113/36559/The-genetics-and-molecular-biology-of-TALL

  16. Iacobucci I, Kimura S, Mullighan CG. Biologic and Therapeutic Implications of Genomic Alterations in Acute Lymphoblastic Leukemia. J Clin Med [Internet]. 2021 [cited 2023 May 2];10:3792. Available from: /pmc/articles/PMC8432032/

  17. Brady SW, Roberts KG, Gu Z, Shi L, Pounds S, Pei D, et al. The genomic landscape of pediatric acute lymphoblastic leukemia. Nat Genet [Internet]. 2022 [cited 2022 Sep 2];54:1376–89. Available from: https://www.nature.com/articles/s41588-022-01159-z

  18. Brüggemann M, Kotrova M. Minimal residual disease in adult ALL: technical aspects and implications for correct clinical interpretation. Hematology [Internet]. 2017 [cited 2023 Mar 30];2017:13–21. Available from: https://ashpublications.org/hematology/article/2017/1/13/21072/Minimal-residual-disease-in-adult-ALL-technical

  19. Kruse A, Abdel-Azim N, Kim HN, Ruan Y, Phan V, Ogana H, et al. Minimal Residual Disease Detection in Acute Lymphoblastic Leukemia. Int J Mol Sci [Internet]. 2020 [cited 2022 Aug 22];21. Available from: https://pubmed.ncbi.nlm.nih.gov/32033444/

  20. Hunger SP, Mullighan CG. Acute Lymphoblastic Leukemia in Children. Longo DL, editor. New England Journal of Medicine [Internet]. 2015 [cited 2023 Mar 30];373:1541–52. Available from: http://www.nejm.org/doi/https://doi.org/10.1056/NEJMra1400972

  21. Pfisterer U, Bräunig J, Brattås P, Heidenblad M, Karlsson G, Fioretos T. Single‐cell sequencing in translational cancer research and challenges to meet clinical diagnostic needs. Genes Chromosomes Cancer [Internet]. 2021;60:504–24. Available from: https://onlinelibrary.wiley.com/doi/https://doi.org/10.1002/gcc.22944

  22. Lei Y, Tang R, Xu J, Wang W, Zhang B, Liu J, et al. Applications of single-cell sequencing in cancer research: progress and perspectives. J Hematol Oncol [Internet]. 2021 [cited 2023 Sep 22];14:91. Available from: https://jhoonline.biomedcentral.com/articles/https://doi.org/10.1186/s13045-021-01105-2

  23. Ellsworth DL, Blackburn HL, Shriver CD, Rabizadeh S, Soon-Shiong P, Ellsworth RE. Single-cell sequencing and tumorigenesis: improved understanding of tumor evolution and metastasis. Clin Transl Med. 2017;6:5.

    Article  Google Scholar 

  24. Alaggio R, Amador C, Anagnostopoulos I, Attygalle AD, Araujo IB de O, Berti E, et al. The 5th edition of the world health organization classification of haematolymphoid tumours: lymphoid neoplasms. Leukemia [Internet]. 2022 [cited 2023 Aug 16];36:1720. Available from: /pmc/articles/PMC9214472/

  25. Arber DA, Orazi A, Hasserjian RP, Borowitz MJ, Calvo KR, Kvasnicka HM, et al. International consensus classification of myeloid neoplasms and acute leukemias: integrating morphologic, clinical, and genomic data. Blood. 2022;140:1200–28.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Inaba H, Pui CH. Advances in the diagnosis and treatment of pediatric acute lymphoblastic leukemia. J Clin Med. 2021;10:5.

    Article  Google Scholar 

  27. Teachey DT, Pui CH. Comparative features and outcomes between paediatric T-cell and B-cell acute lymphoblastic leukaemia. Lancet Oncol. 2019;20:e142–54.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Papalexi E, Satija R. Single-cell RNA sequencing to explore immune cell heterogeneity. Nat Rev Immunol [Internet]. 2018 [cited 2023 May 8];18:35–45. Available from: https://www.nature.com/articles/nri.2017.76

  29. Zhu Y, Huang Y, Tan Y, Zhao W, Tian Q. Single‐Cell RNA Sequencing in Hematological Diseases. Proteomics [Internet]. 2020;20. Available from: https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/https://doi.org/10.1002/pmic.201900228

  30. Jovic D, Liang X, Zeng H, Lin L, Xu F, Luo Y. Single-cell RNA sequencing technologies and applications: a brief overview. Clin Transl Med. 2022;12:5.

    Article  Google Scholar 

  31. Wang S, Sun ST, Zhang XY, Ding HR, Yuan Y, He JJ, et al. The Evolution of Single-Cell RNA Sequencing Technology and Application: Progress and Perspectives. Int J Mol Sci [Internet]. 2023 [cited 2023 May 9];24. Available from: /pmc/articles/PMC9918030/

  32. Zhang Y, Xu S, Wen Z, Gao J, Li S, Weissman SM, et al. Sample-multiplexing approaches for single-cell sequencing. Cellular and Molecular Life Sciences [Internet]. 2022 [cited 2023 May 9];79:466. Available from: https://link.springer.com/https://doi.org/10.1007/s00018-022-04482-0

  33. Iacobucci I, Witkowski MT, Mullighan CG. Single-cell analysis of acute lymphoblastic and lineage-ambiguous leukemia: approaches and molecular insights. Blood [Internet]. 2023 [cited 2022 Aug 22];141:356–68. Available from: https://ashpublications.org/blood/article/141/4/356/486119/Single-cell-analysis-of-acute-lymphoblastic-and

  34. Evrony GD, Hinch AG, Luo C. Applications of Single-cell DNA Sequencing. Annu Rev Genom Hum Genet [Internet]. 2021 [cited 2023 Jun 6];22:171. Available from: /pmc/articles/PMC8410678/

  35. Gawad C, Koh W, Quake SR. Dissecting the clonal origins of childhood acute lymphoblastic leukemia by single-cell genomics. Proc Natl Acad Sci [Internet]. 2014 [cited 2021 Oct 14];111:17947–52. Available from: http://www.pnas.org/lookup/doi/https://doi.org/10.1073/pnas.1420822111

  36. Albertí-Servera L, Demeyer S, Govaerts I, Swings T, De Bie J, Gielen O, et al. Single-cell DNA amplicon sequencing reveals clonal heterogeneity and evolution in T-cell acute lymphoblastic leukemia. Blood [Internet]. 2021 [cited 2021 Oct 19];137:801–11. Available from: https://ashpublications.org/blood/article/137/6/801/463329/Single-cell-DNA-amplicon-sequencing-reveals-clonal

  37. Meyers S, Alberti-Servera L, Gielen O, Erard M, Swings T, Bie J De, et al. Monitoring of leukemia clones in B-cell acute lymphoblastic leukemia at diagnosis and during treatment by single-cell DNA amplicon sequencing. Hemasphere [Internet]. 2022 [cited 2022 Apr 28];6:e700. Available from: /pmc/articles/PMC8916209/

  38. Hanahan D. Hallmarks of Cancer: New Dimensions. Cancer Discov [Internet]. 2022 [cited 2023 Jun 6];12:31–46. Available from: https://pubmed.ncbi.nlm.nih.gov/35022204/

  39. Casado-Pelaez M, Bueno-Costa A, Esteller M. Single cell cancer epigenetics. Trends Cancer [Internet]. 2022;8:820–38. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2405803322001339

  40. Nakato R, Sakata T. Methods for ChIP-seq analysis: A practical workflow and advanced applications. Methods [Internet]. 2021;187:44–53. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1046202320300591

  41. Buccitelli C, Selbach M. mRNAs, proteins and the emerging principles of gene expression control. Nat Rev Genet [Internet]. 2020 [cited 2023 Jun 6];21:630–44. Available from: https://www.nature.com/articles/s41576-020-0258-4

  42. Bandura DR, Baranov VI, Ornatsky OI, Antonov A, Kinach R, Lou X, et al. Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry. Anal Chem. 2009;81:6813–22.

    Article  CAS  PubMed  Google Scholar 

  43. Bodenmiller B, Zunder ER, Finck R, Chen TJ, Savig ES, Bruggner R V, et al. Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators. Nat Biotechnol [Internet]. 2012 [cited 2023 Oct 13];30:858–67. Available from: https://www.nature.com/articles/nbt.2317

  44. Bennett HM, Stephenson W, Rose CM, Darmanis S. Single-cell proteomics enabled by next-generation sequencing or mass spectrometry. Nat Methods [Internet]. 2023 [cited 2024 Jan 25];20:363–74. Available from: http://www.ncbi.nlm.nih.gov/pubmed/36864196

  45. Mund A, Brunner A-D, Mann M. Unbiased spatial proteomics with single-cell resolution in tissues. Mol Cell [Internet]. 2022;82:2335–49. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1097276522004890

  46. Brunner A, Thielert M, Vasilopoulou C, Ammar C, Coscia F, Mund A, et al. Ultra‐high sensitivity mass spectrometry quantifies single‐cell proteome changes upon perturbation. Mol Syst Biol. 2022;18.

  47. Pai JA, Satpathy AT. High-throughput and single-cell T cell receptor sequencing technologies. Nat Methods [Internet]. 2021 [cited 2023 May 9];18:881. Available from: /pmc/articles/PMC9345561/

  48. Zheng B, Yang Y, Chen L, Wu M, Zhou S. B-cell receptor repertoire sequencing: Deeper digging into the mechanisms and clinical aspects of immune-mediated diseases. iScience [Internet]. 2022;25:105002. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2589004222012743

  49. Vandereyken K, Sifrim A, Thienpont B, Voet T. Methods and applications for single-cell and spatial multi-omics. Nat Rev Genet [Internet]. 2023 [cited 2023 May 15];24:494–515. Available from: https://www.nature.com/articles/s41576-023-00580-2

  50. Stoeckius M, Hafemeister C, Stephenson W, Houck-Loomis B, Chattopadhyay PK, Swerdlow H, et al. Simultaneous epitope and transcriptome measurement in single cells. Nature Methods 2017 14:9 [Internet]. 2017 [cited 2022 Feb 3];14:865–8. Available from: https://www.nature.com/articles/nmeth.4380

  51. Demaree B, Delley CL, Vasudevan HN, Peretz CAC, Ruff D, Smith CC, et al. Joint profiling of DNA and proteins in single cells to dissect genotype-phenotype associations in leukemia. Nat Commun. 2021;12.

  52. Macaulay IC, Haerty W, Kumar P, Li YI, Hu TX, Teng MJ, et al. G&T-seq: parallel sequencing of single-cell genomes and transcriptomes. Nat Methods [Internet]. 2015 [cited 2021 Oct 14];12:519–22. Available from: http://www.nature.com/articles/nmeth.3370

  53. Nam AS, Kim K-T, Chaligne R, Izzo F, Ang C, Taylor J, et al. Somatic mutations and cell identity linked by genotyping of transcriptomes. Nature [Internet]. 2019 [cited 2023 Oct 13];571:355–60. Available from: https://www.nature.com/articles/s41586-019-1367-0

  54. Moffitt JR, Lundberg E, Heyn H. The emerging landscape of spatial profiling technologies. Nat Rev Genet [Internet]. 2022 [cited 2023 May 15];23:741–59. Available from: https://www.nature.com/articles/s41576-022-00515-3

  55. Eisenstein M. Seven technologies to watch in 2022. Nature [Internet]. 2022;601:658–61. Available from: https://www.nature.com/articles/d41586-022-00163-x

  56. Anderson K, Lutz C, van Delft FW, Bateman CM, Guo Y, Colman SM, et al. Genetic variegation of clonal architecture and propagating cells in leukaemia. Nature [Internet]. 2011 [cited 2023 Jun 20];469:356–61. Available from: https://www.nature.com/articles/nature09650

  57. Furness CL, Mansur MB, Weston VJ, Ermini L, van Delft FW, Jenkinson S, et al. The subclonal complexity of STIL-TAL1+ T-cell acute lymphoblastic leukaemia. Leukemia [Internet]. 2018 [cited 2023 Jan 16];32:1984. Available from: /pmc/articles/PMC6127084/

  58. Bakhoum SF, Ngo B, Laughney AM, Cavallo J-A, Murphy CJ, Ly P, et al. Chromosomal instability drives metastasis through a cytosolic DNA response. Nature [Internet]. 2018 [cited 2024 Jan 12];553:467–72. Available from: https://www.nature.com/articles/nature25432

  59. Bakker B, Taudt A, Belderbos ME, Porubsky D, Spierings DCJ, de Jong TV, et al. Single-cell sequencing reveals karyotype heterogeneity in murine and human malignancies. Genome Biol. 2016;17:8.

    Article  Google Scholar 

  60. Woodward EL, Yang M, Moura-Castro LH, van den Bos H, Gunnarsson R, Olsson-Arvidsson L, et al. Clonal origin and development of high hyperdiploidy in childhood acute lymphoblastic leukaemia. Nat Commun [Internet]. 2023 [cited 2023 Oct 3];14. Available from: /pmc/articles/PMC10039905/

  61. Molina O, Ortega-Sabater C, Thampi N, Fernández-Fuentes N, Guerrero-Murillo M, Martínez-Moreno A, et al. Chromosomal instability in aneuploid acute lymphoblastic leukemia associates with disease progression. EMBO Mol Med [Internet]. 2023 [cited 2024 Jan 12];16:64–92. Available from: https://www.embopress.org/doi/full/https://doi.org/10.1038/s44321-023-00006-w

  62. De Bie J, Demeyer S, Alberti-Servera L, Geerdens E, Segers H, Broux M, et al. Single-cell sequencing reveals the origin and the order of mutation acquisition in T-cell acute lymphoblastic leukemia. Leukemia [Internet]. 2018 [cited 2021 Oct 14];32:1358. Available from: /pmc/articles/PMC5990522/

  63. Hanahan D. Hallmarks of cancer: new dimensions. Cancer Discov [Internet]. 2022 [cited 2024 Feb 22];12:31–46. Available from: /cancerdiscovery/article/12/1/31/675608/Hallmarks-of-Cancer-New-DimensionsHallmarks-of

  64. Caron M, St-Onge P, Sontag T, Wang YC, Richer C, Ragoussis I, et al. Single-cell analysis of childhood leukemia reveals a link between developmental states and ribosomal protein expression as a source of intra-individual heterogeneity. Sci Rep [Internet]. 2020 [cited 2022 Jan 7];10. Available from: https://pubmed.ncbi.nlm.nih.gov/32415257/

  65. Mehtonen J, Teppo S, Lahnalampi M, Kokko A, Kaukonen R, Oksa L, et al. Single cell characterization of B-lymphoid differentiation and leukemic cell states during chemotherapy in ETV6-RUNX1-positive pediatric leukemia identifies drug-targetable transcription factor activities. Genome Med [Internet]. 2020 [cited 2023 Feb 1];12. Available from: /pmc/articles/PMC7679990/

  66. Candelli T, Schneider P, Garrido Castro P, Jones LA, Bodewes E, Rockx-Brouwer D, et al. Identification and characterization of relapse-initiating cells in MLL-rearranged infant ALL by single-cell transcriptomics. Leukemia [Internet]. 2022;36:58–67. Available from: https://www.nature.com/articles/s41375-021-01341-y

  67. Muraro MJ, Dharmadhikari G, Grün D, Groen N, Dielen T, Jansen E, et al. A single-cell transcriptome atlas of the human pancreas. Cell Syst [Internet]. 2016 [cited 2023 Aug 18];3:385. Available from: /pmc/articles/PMC5092539/

  68. Khabirova E, Jardine L, Coorens THH, Webb S, Treger TD, Engelbert J, et al. Single-cell transcriptomics reveals a distinct developmental state of KMT2A-rearranged infant B-cell acute lymphoblastic leukemia. Nat Med [Internet]. 2022 [cited 2023 Jan 31];28:743. Available from: /pmc/articles/PMC9018413/

  69. Zhang X, Hou Z, Huang D, Wang F, Gao B, Zhang C, et al. Single-cell heterogeneity and dynamic evolution of Ph-like acute lymphoblastic leukemia patient with novel TPR-PDGFRB fusion gene. Exp Hematol Oncol [Internet]. 2023 [cited 2023 Oct 6];12. Available from: /pmc/articles/PMC9936632/

  70. Iacobucci I, Zeng AGX, Gao Q, Garcia-Prat L, Baviskar P, Shah S, et al. Single cell dissection of developmental origins and transcriptional heterogeneity in B-cell acute lymphoblastic leukemia. bioRxiv [Internet]. 2023 [cited 2024 Apr 18];2023.12.04.569954. Available from: https://www.biorxiv.org/content/https://doi.org/10.1101/2023.12.04.569954v1

  71. Anand P, Guillaumet-Adkins A, Dimitrova V, Yun H, Drier Y, Sotudeh N, et al. Single-cell RNA-seq reveals developmental plasticity with coexisting oncogenic states and immune evasion programs in ETP-ALL. Blood [Internet]. 2021 [cited 2021 Oct 14];137:2463–80. Available from: https://ashpublications.org/blood/article/137/18/2463/474247/Single-cell-RNA-seq-reveals-developmental

  72. Zamora AE, Crawford JC, Allen EK, Guo XZJ, Bakke J, Carter RA, et al. Pediatric patients with acute lymphoblastic leukemia generate abundant and functional neoantigen-specific CD8+ T cell responses. Sci Transl Med [Internet]. 2019 [cited 2023 Feb 1];11. Available from: /pmc/articles/PMC7020562/

  73. Cai Y, Chen X, Lu T, Yu Z, Hu S, Liu J, et al. Single-cell transcriptome analysis profiles the expression features of TMEM173 in BM cells of high-risk B-cell acute lymphoblastic leukemia. BMC Cancer [Internet]. 2023 [cited 2023 Oct 6];23. Available from: /pmc/articles/PMC10123968/

  74. Chen W, Shi H, Liu Z, Yang F, Liu J, Zhang L, et al. Single-cell transcriptomics reveals immune reconstitution in patients with R/R T-ALL/LBL treated with donor-derived CD7 CAR-T therapy. Clin Cancer Res [Internet]. 2023 [cited 2023 Oct 6];29:1484–95. Available from: https://doi.org/10.1158/1078-0432.CCR-22-2924

  75. Eberwine J, Sul J-Y, Bartfai T, Kim J. The promise of single-cell sequencing. Nat Methods [Internet]. 2014 [cited 2023 Oct 6];11:25–7. Available from: https://www.nature.com/articles/nmeth.2769

  76. Ostendorf BN, Patel MA, Bilanovic J, Hoffmann HH, Carrasco SE, Rice CM, et al. Common human genetic variants of APOE impact murine COVID-19 mortality. Nature 2022 611:7935 [Internet]. 2022 [cited 2024 Apr 15];611:346–51. Available from: https://www.nature.com/articles/s41586-022-05344-2

  77. Chen GM, Chen C, Das RK, Gao P, Chen CH, Bandyopadhyay S, et al. Integrative bulk and single-cell profiling of pre-manufacture T-cell populations reveals factors mediating long-term persistence of CAR T-cell therapy. Cancer Discov [Internet]. 2021 [cited 2023 Feb 1];11:2186. Available from: /pmc/articles/PMC8419030/

  78. Granja JM, Klemm S, McGinnis LM, Kathiria AS, Mezger A, Corces MR, et al. Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia. Nat Biotechnol [Internet]. 2019 [cited 2023 Sep 22];37:1458. Available from: /pmc/articles/PMC7258684/

  79. Chi Y, Shi J, Xing D, Tan L. Every gene everywhere all at once: High-precision measurement of 3D chromosome architecture with single-cell Hi-C. Front Mol Biosci [Internet]. 2022 [cited 2024 Jan 25];9. Available from: /pmc/articles/PMC9583135/

  80. Xing Z, Mai H, Liu X, Fu X, Zhang X, Xie L, et al. Single-cell diploid Hi-C reveals the role of spatial aggregations in complex rearrangements and KMT2A fusions in leukemia. Genome Biol [Internet]. 2022 [cited 2024 Jan 24];23. Available from: /pmc/articles/PMC9361544/

  81. Tan K, Xu J, Chen C, Vincent T, Pölönen St Jude P, Hu St Jude Children J, et al. Identification and targeting of treatment resistant progenitor populations in T-cell Acute Lymphoblastic Leukemia. 2023 [cited 2024 Apr 18]; Available from: https://www.researchsquare.com

  82. Iyer A, Hamers AAJ, Pillai AB. CyTOF® for the Masses. Front Immunol [Internet]. 2022 [cited 2024 Jul 15];13. Available from: /pmc/articles/PMC9047695/

  83. Robinson JP. Flow Cytometry: Past and Future. Biotechniques [Internet]. 2022 [cited 2024 Jul 15];72:159–69. Available from: https://www.tandfonline.com/doi/abs/https://doi.org/10.2144/btn-2022-0005

  84. Good Z, Sarno J, Jager A, Samusik N, Aghaeepour N, Simonds EF, et al. Single-cell developmental classification of b-cell precursor acute lymphoblastic leukemia at diagnosis reveals predictors of relapse. Nat Med [Internet]. 2018 [cited 2023 Feb 1];24:474. Available from: /pmc/articles/PMC5953207/

  85. Masih KE, Gardner RA, Chou HC, Abdelmaksoud A, Song YK, Mariani L, et al. A stem cell epigenome is associated with primary nonresponse to CD19 CAR T cells in pediatric acute lymphoblastic leukemia. Blood Adv. 2023;7:4218–32. https://doi.org/10.1182/bloodadvances.2022008977.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Bailur JK, McCachren SS, Pendleton K, Vasquez JC, Lim HS, Duffy A, et al. Risk-associated alterations in marrow T cells in pediatric leukemia. JCI Insight. 2020;5:5.

    Article  Google Scholar 

  87. Mikami T, Kato I, Wing JB, Ueno H, Tasaka K, Tanaka K, et al. Alteration of the immune environment in bone marrow from children with recurrent B cell precursor acute lymphoblastic leukemia. Cancer Sci. 2022;113:41–52.

    Article  CAS  PubMed  Google Scholar 

  88. Kim R, Bergugnat H, Larcher L, Duchmann M, Passet M, Gachet S, et al. Adult Low-Hypodiploid Acute Lymphoblastic Leukemia Emerges from Preleukemic TP53-Mutant Clonal Hematopoiesis. Blood Cancer Discov [Internet]. 2023;4:134–49. Available from: https://aacrjournals.org/bloodcancerdiscov/article/4/2/134/718389/Adult-Low-Hypodiploid-Acute-Lymphoblastic-Leukemia

  89. Witkowski MT, Dolgalev I, Evensen NA, Ma C, Chambers T, Roberts KG, et al. Extensive Remodeling of the Immune Microenvironment in B-cell Acute Lymphoblastic Leukemia. Cancer Cell [Internet]. 2020 [cited 2023 Jan 16];37:867. Available from: /pmc/articles/PMC7341535/

  90. Wang X, Chen Y, Li Z, Huang B, Xu L, Lai J, et al. Single-cell RNA-seq of T cells in B-ALL patients reveals an exhausted subset with remarkable heterogeneity. Adv Sci. 2021;8:5.

    Google Scholar 

  91. Lai W, Wang X, Liu L, Xu L, Mao L, Tan J, et al. Single-cell profiling of T cells uncovers a tissue-resident memory-like T-cell subset associated with bidirectional prognosis for B-cell acute lymphoblastic leukemia. Front Immunol [Internet]. 2022 [cited 2023 Oct 6];13. Available from: /pmc/articles/PMC9757161/

  92. Zhang Y, Wang S, Zhang J, Liu C, Li X, Guo W, et al. Elucidating minimal residual disease of paediatric B-cell acute lymphoblastic leukaemia by single-cell analysis. Nat Cell Biol [Internet]. 2022 [cited 2022 Mar 24];24:242–52. Available from: https://www.nature.com/articles/s41556-021-00814-7

  93. Zhao Y, Aldoss I, Qu C, Crawford JC, Gu Z, Allen EK, et al. Tumor-intrinsic and -extrinsic determinants of response to blinatumomab in adults with B-ALL. Blood [Internet]. 2021 [cited 2023 Feb 1];137:471–84. Available from: https://ashpublications.org/blood/article/137/4/471/463621/Tumor-intrinsic-and-extrinsic-determinants-of

  94. Zhang J, Duan Y, Wu P, Chang Y, Wang Y, Hu T, et al. Clonal evolution dissection reveals that a high MSI2 level promotes chemoresistance in T-cell acute lymphoblastic leukemia. Blood. 2024;143:320–35.

    Article  CAS  PubMed  Google Scholar 

  95. Clark IC, Fontanez KM, Meltzer RH, Xue Y, Hayford C, May-Zhang A, et al. Microfluidics-free single-cell genomics with templated emulsification. Nat Biotechnol [Internet]. 2023 [cited 2024 Jan 29];41:1557. Available from: /pmc/articles/PMC10635830/

  96. Baccin C, Al-Sabah J, Velten L, Helbling PM, Grünschläger F, Hernández-Malmierca P, et al. Combined single-cell and spatial transcriptomics reveal the molecular, cellular and spatial bone marrow niche organization. Nat Cell Biol [Internet]. 2020 [cited 2024 Jan 24];22:38–48. Available from: https://www.nature.com/articles/s41556-019-0439-6

  97. Tilburg J, Stone AP, Billingsley JM, Scoville DK, Pavenko A, Liang Y, et al. Spatial transcriptomics of murine bone marrow megakaryocytes at single-cell resolution. Res Pract Thromb Haemost [Internet]. 2023 [cited 2024 Jan 24];7:100158. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2475037923001310

  98. Xiao X, Juan C, Drennon T, Uytingco CR, Vishlaghi N, Sokolowskei D, et al. Spatial transcriptomic interrogation of the murine bone marrow signaling landscape. Bone Res [Internet]. 2023 [cited 2024 Jan 26];11:59. Available from: https://www.nature.com/articles/s41413-023-00298-1

  99. Ediriwickrema A, Aleshin A, Reiter JG, Corces MR, Kohnke T, Stafford M, et al. Single-cell mutational profiling enhances the clinical evaluation of AML MRD. Blood Adv [Internet]. 2020 [cited 2024 Jan 30];4:943–52. Available from: https://doi.org/10.1182/bloodadvances.2019001181

Download references

Acknowledgments

We thank somersault18:24 for designing the figures in this paper.

Author information

Authors and Affiliations

  1. Department of Oncology, KU Leuven, Leuven, Belgium

    Margo Aertgeerts & Heidi Segers

  2. Department of Human Genetics, KU Leuven, Leuven, Belgium

    Sarah Meyers, Sofie Demeyer & Jan Cools

  3. Center for Cancer Biology, VIB, Leuven, Belgium

    Margo Aertgeerts, Sarah Meyers, Sofie Demeyer & Jan Cools

  4. Leuvens Kanker Instituut (LKI), KU Leuven—UZ Leuven, Leuven, Belgium

    Margo Aertgeerts, Sarah Meyers, Sofie Demeyer, Heidi Segers & Jan Cools

  5. Department of Pediatric Hematology and Oncology, UZ Leuven, Leuven, Belgium

    Heidi Segers

Authors
  1. Margo Aertgeerts
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Sarah Meyers
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Sofie Demeyer
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Heidi Segers
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Jan Cools
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding authors

Correspondence to Heidi Segers or Jan Cools.

Ethics declarations

Funding

M.A. is funded by a research grant from KU Leuven (C14/18/104); S.M. is funded by a doctoral fellowship by FWO-Vlaanderen (11L9124N); S.D. is funded by a postdoctoral fellowship from Stichting Tegen Kanker; H.S. and J.C. obtained funding from Kom op Tegen Kanker, FWO-Vlaanderen and KU Leuven (C14/18/104); and H.S. also obtained funding from Stichting tegen Kanker (Clinical Mandates 2023).

Conflicts of Interest

There are no conflicts of interest for all authors (M.A., S.M., S.D., H.S., J.C.).

Availability of data and material

Not applicable.

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Code availability

Not applicable.

Author contributions

M.A., S.M., S.D., and J.C. wrote the manuscript. H.S. critically proofread the manuscript. M.A. performed the literature search and generated all tables and drafts of the figures.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aertgeerts, M., Meyers, S., Demeyer, S. et al. Unlocking the Complexity: Exploration of Acute Lymphoblastic Leukemia at the Single Cell Level. Mol Diagn Ther 28, 727–744 (2024). https://doi.org/10.1007/s40291-024-00739-5

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40291-024-00739-5

Profiles

  1. Jan Cools View author profile