Reuse & Permissions

It is not necessary to obtain permission to reuse this article or its components as it is available under the terms of the Creative Commons Attribution 4.0 International license. This license permits unrestricted use, distribution, and reproduction in any medium, provided attribution to the author(s) and the published article's title, journal citation, and DOI are maintained. Please note that some figures may have been included with permission from other third parties. It is your responsibility to obtain the proper permission from the rights holder directly for these figures.

Export citation

Export citation

Choose format for download:

Download Citation
  • Featured in Physics
  • Open Access

Brownian Bridging of Chromatin States in Leukemic Cells

M. Calero1,2,3,*, E. del Arco4,*, M. Amores-Sánchez4, D. Herráez-Aguilar5, E. García-Sánchez6, A. González-Murillo6, J. Lalchandani6, N. Caselli7, J. Fernández-Castillo7 et al.

A. Caamaño4, M. Ramírez-Orellana6,8,9,†, I. Mora-Jiménez4,‡, and F. Monroy1,7,§

  • *These authors contributed equally to this work.
  • †Contact author: manuel.ramirez@salud.madrid.org
  • ‡Contact author: inmaculada.mora@urjc.es
  • §Contact author: monroy@ucm.es

PRX Life 4, 033013 – Published 12 August, 2026

DOI: https://doi.org/10.1103/n2tk-q6gv

Abstract

Chromatin mobility in living interphase nuclei provides a dynamical readout of genome regulation. From time-resolved trajectories of chromatin granules in primary acute lymphoblastic leukemia (ALL) samples (one B-ALL, one T-ALL), leukemic cell lines (U266, Jurkat), and healthy donor T lymphocytes, we resolve rare but reproducible transitions between extreme mobility states. We quantify these events with Brownian-bridge ensembles, i.e., trajectories conditioned on crossings between low- and high-mobility quartiles. Despite their low frequency, crossings reveal strong polarity: activation (Q1→Q4) concentrates on a superlinear, ballistic-like ridge, whereas reconfinement (Q4→Q1) returns more slowly toward confinement. The scarcity of extreme events is comparable in magnitude to reported bursting fractions, motivating future joint live-imaging tests that directly link mobility bridges to transcriptional state. These asymmetric pathways yield a compact dynamical signature of disrupted confinement and lineage-dependent nuclear deregulation in ALL, and generate testable predictions for cohort-level validation.

View figure in article

Physics Subject Headings (PhySH)

synopsis

Cancer Sets DNA in Motion

Published 12 August, 2026

A microscope video analysis has provided new details about molecular motion inside the nuclei of cancer cells.

See more in Physics

Article Text

Supplemental Material

References (72)

  1. T. Cremer and M. Cremer, Chromosome territories, nuclear architecture and gene regulation in mammalian cells, Nat. Rev. Genet. 2, 292 (2001).
  2. J. Dixon, D. Gorkin, and B. Ren, Chromatin domains: The unit of chromosome organization, Mol. Cell 62, 668 (2016).
  3. A. Hafner and A. Boettiger, The spatial organization of transcriptional control, Nat. Rev. Genet. 24, 53 (2023).
  4. U. Seifert, Stochastic thermodynamics, fluctuation theorems and molecular machines, Rep. Prog. Phys. 75, 126001 (2012).
  5. C. Bechinger, R. Di Leonardo, H. Löwen, C. Reichhardt, G. Volpe, and G. Volpe, Active particles in complex and crowded environments, Rev. Mod. Phys. 88, 045006 (2016).
  6. W. Cho, J. Spille, M. Hecht, C. Lee, C. Li, V. Grube, and I. Cisse, Mediator and RNA polymerase II clusters associate in transcription-dependent condensates, Science 361, 412 (2018).
  7. B. Gu, T. Swigut, A. Spencley, M. R. Bauer, M. Chung, T. Meyer, and J. Wysocka, Transcription-coupled changes in nuclear mobility of mammalian cis-regulatory elements, Science 359, 1050 (2018).
  8. A. Coulon, Interphase chromatin biophysics and mechanics: New perspectives and open questions, Curr. Opin. Genet. Dev. 90, 102296 (2025).
  9. D. Herráez-Aguilar, F. Monroy, E. Madrazo, H. López-Menéndez, M. Ramírez, F. Monroy, and J. Redondo-Muñoz, Multiple particle tracking analysis in isolated nuclei reveals the mechanical phenotype of leukemia cells, Sci. Rep. 10, 6707 (2020).
  10. M. Zhang, C. Seitz, G. Chang, F. Iqbal, H. Lin, and J. Liu, A guide for single-particle chromatin tracking in live cell nuclei, Cell Biol. Int. 46, 683 (2022).
  11. J. van Staalduinen, T. van Staveren, F. Grosveld, and K. S. Wendt, Live-cell imaging of chromatin contacts opens a new window into chromatin dynamics, Epigenet. Chromatin 16, 27 (2023).
  12. D. Mazza, A. Abernathy, N. Golob, T. Morisaki, and J. McNally, A benchmark for chromatin binding measurements in live cells, Nucl. Acids Res. 40, e119 (2012).
  13. I. Bronshtein, E. Kepten, I. Kanter, S. Berezin, M. Lindner, A. Redwood, S. Mai, S. Gonzalo, R. Foisner, Y. Shav-Tal, et al., Loss of lamin A function increases chromatin dynamics in the nuclear interior, Nat. Commun. 6, 8044 (2015).
  14. M. E. Cates, in Active Matter and Nonequilibrium Statistical Physics: Lecture Notes of the Les Houches Summer School, edited by J. Tailleur, G. Gompper, M. C. Marchetti, J. M. Yeomans, and C. Salomon (Oxford University Press, Oxford, 2022), Vol. 12, pp. 180–216.
  15. S. C. Weber, A. J. Spakowitz, and J. A. Theriot, Nonthermal ATP-dependent fluctuations contribute to the in vivo motion of chromosomal loci, Proc. Natl. Acad. Sci. USA 109, 7338 (2012).
  16. G. Shi, S. Shin, and D. Thirumalai, Static three-dimensional structures determine fast dynamics between distal loci pairs in interphase chromosomes, Sci. Adv. 11, eadx1763 (2025).
  17. V. I. P. Keizer, S. Grosse-Holz, M. Woringer, et al., Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics, Science 377, 489 (2022).
  18. F. S. Gnesotto, F. Mura, J. Gladrow, and C. P. Broedersz, Broken detailed balance and non-equilibrium dynamics in living systems: A review, Rep. Prog. Phys. 81, 066601 (2018).
  19. G. J. Filion, J. G. van Bemmel, U. Braunschweig, et al., Systematic protein location mapping reveals five principal chromatin types in Drosophila cells, Cell 143, 212 (2010).
  20. J. D. Rowley, Chromosome translocations: Dangerous liaisons revisited, Nat. Rev. Cancer 1, 245 (2001).
  21. M. Greaves and C. C. Maley, Clonal evolution in cancer, Nature (London) 481, 306 (2012).
  22. M. Greaves, A causal mechanism for childhood acute lymphoblastic leukaemia, Nat. Rev. Cancer 18, 471 (2018).
  23. S. Hetzel, A. L. Mattei, H. Kretzmer, C. Qu, X. Chen, Y. Fan, et al., Acute lymphoblastic leukaemia displays a distinct highly methylated genome, Nat. Cancer 3, 768 (2022).
  24. S. E. A. Asrat, Trapnseq allows high‐throughput profiling of antigen‐specific antibody‐secreting cells, Cell Rep. Methods 3, 100522 (2023).
  25. S. M. Greenblatt and S. D. Nimer, Chromatin modifiers and the promise of epigenetic therapy in acute leukemia, Leukemia 28, 1396 (2014).
  26. L. Di Croce, Chromatin modifying activity of leukaemia associated fusion proteins, Human Molecular Genetics 14, R77 (2005), special Issue.
  27. T. B. Alexander, Z. Gu, I. Iacobucci, et al., The genetic basis and cell of origin of mixed phenotype acute leukaemia, Nature (London) 562, 373 (2018).
  28. R. Greenhalgh, W. Yang, S. W. Brady, D. A. Flasch, Y. Liu, K. A. Szlachta, L. Tian, P. Kolekar, J. Wang, X. Zhou, D. S. Gerhard, X. Ma, and J. Zhang, The landscape of structural variation in pediatric cancer, bioRxiv (2025).
  29. J. B. Koedijk, I. van der Werf, L. Penter, et al., A multidimensional analysis reveals distinct immune phenotypes and the composition of immune aggregates in pediatric acute myeloid leukemia, Leukemia 38, 2332 (2024).
  30. A. Agrawal, N. Ganai, S. Sengupta, and G. I. Menon, Nonequilibrium biophysical processes influence the large-scale architecture of the cell nucleus, Biophys. J. 118, 2229 (2020).
  31. H. Zhou, J. Huertas, M. J. Maristany, K. Russell, J. H. Hwang, R. Yao, J. Hutchings, M. Shiozaki, X. Zhao, L. K. Doolittle, B. A. Gibson, M. Riggi, J. R. Espinosa, Z. Yu, E. Villa, R. Collepardo-Guevara, and M. K. Rosen, Multi-scale structure of chromatin condensates rationalizes phase separation and material properties, bioRxiv (2025).
  32. G. Forte, C. A. Brackley, N. Gilbert, and D. Marenduzzo, Nonequilibrium polymer models for chromatin, Curr. Opin. Genet. Dev. 96, 102426 (2026).
  33. S. Chulián, Á. Molinos-Quintana, T. Caballero-Velázquez, J. A. Pérez-Simón, and M. Ramírez-Orellana, High-dimensional analysis of single-cell flow cytometry data predicts relapse in childhood acute lymphoblastic leukaemia, Cancers 13, 17 (2021).
  34. H. Bay, T. Tuytelaars, and L. Van Gool, in Computer Vision—ECCV 2006, Lecture Notes in Computer Science Vol. 3951 (Springer, Berlin, 2006), pp. 404–417.
  35. D. Revuz and M. Yor, Continuous Martingales and Brownian Motion, 3rd ed. (Springer, Berlin, 1999).
  36. J. L. Doob, Conditional Brownian motion and the boundary limits of harmonic functions, Bull. Am. Math. Soc. 63, 1 (1957).
  37. J. L. Jensen, On diffusion bridges, J. Appl. Probab. 56, 687 (2019).
  38. Y. Chen, T. T. Georgiou, and M. Pavon, Optimal transport in systems and control, Annu. Rev. Control Rob. Auton. Syst. 4, 89 (2021).
  39. G. E. Uhlenbeck and L. S. Ornstein, On the theory of the Brownian motion, Phys. Rev. 36, 823 (1930).
  40. C. W. Gardiner, Stochastic Methods: A Handbook for the Natural and Social Sciences, 4th ed., Springer Series in Synergetics (Springer, Berlin, Heidelberg, 2009).
  41. H. Risken, The Fokker–Planck Equation: Methods of Solution and Applications, 2nd ed., Springer Series in Synergetics (Springer, Berlin, 1996).
  42. A. Larson, D. Elnatan, M. Keenen, M. Trnka, J. Johnston, A. Burlingame, D. Agard, S. Redding, and G. Narlikar, Liquid droplet formation by HP1α suggests a role for phase separation in heterochromatin, Nature (London) 547, 236 (2017).
  43. See Supplemental Material at http://link.aps.org/supplemental/10.1103/n2tk-q6gv for additional methods, clinical and genomic characterization of primary ALL samples, two-state bridge-model derivations, statistical procedures, and supporting figures and tables.
  44. K. Rack, J. De Bie, G. Ameye, O. Gielen, S. Demeyer, J. Cools, K. De Keersmaecker, J. R. Vermeesch, J. Maertens, H. Segers, L. Michaux, and B. Dewaele, Optimizing the diagnostic workflow for acute lymphoblastic leukemia by optical genome mapping, Am. J. Hematol. 97, 548 (2022).
  45. S. Chan, E. Lam, M. Saghbini, S. Bocklandt, A. Hastie, H. Cao, E. Holmlin, and M. Borodkin, in Structural Variation: Methods and Protocols, Methods in Molecular Biology Vol. 1833 (Humana Press, Totowa, NJ, 2018), pp. 193–203.
  46. L. Wasserman, All of Statistics: A Concise Course in Statistical Inference (Springer, Berlin, 2004).
  47. B. W. Silverman, Density Estimation for Statistics and Data Analysis, Monographs on Statistics and Applied Probability (Chapman and Hall, London, UK, 1986).
  48. B. Delyon and Y. Hu, Simulation of conditioned diffusion and application to parameter estimation, Stoch. Process. Appl. 116, 1660 (2006).
  49. L. C. G. Rogers and D. Williams, Diffusions, Markov Processes and Martingales. Vol. 2: Itô Calculus, 2nd ed. (Cambridge University Press, Cambridge, UK, 2000).
  50. M. Hertzog and F. Erdel, The material properties of the cell nucleus: A matter of scale, Cells 12, 1958 (2023).
  51. L. H. Moura-Castro et al., The 3D genome of pediatric B-cell precursor acute lymphoblastic leukemia, BioRxiv (2025).
  52. A. P. Weng, A. A. Ferrando, W. C. Lee, J. P. Morris, L. B. Silverman, C. Sanchez-Irizarry, S. C. Blacklow, A. T. Look, and J. C. Aster, Activating mutations of NOTCH1 in human T cell acute lymphoblastic leukemia, Science 306, 269 (2004).
  53. M. Sanchez-Martin and A. Ferrando, The NOTCH1-MYC highway toward T-cell acute lymphoblastic leukemia, Blood 129, 1124 (2017).
  54. D. Herranz, A. Ambesi-Impiombato, J. Sudderth, M. Sánchez-Martín, L. Belver, V. Tosello, L. Xu, A. A. Wendorff, M. Castillo-Martín, et al., N-Me, a long range oncogenic enhancer in T-cell acute lymphoblastic leukemia, Nat. Med. 20, 1130 (2014).
  55. K. L. Bunting, T. D. Soong, R. Singh, Y. Jiang, L. Yu, A. Gérard, D. Lee, M. Régnier, Y. Liu, Z. Qin, G. Cattoretti, U. Klein, I. Aifantis, A. Melnick, and J. A. Skok, Multi-tiered reorganization of the genome during B cell affinity maturation anchored by a germinal center-specific locus control region, Immunity 45, 497 (2016).
  56. R. Vilarrasa-Blasi, P. Soler-Vila, N. Verdaguer-Dot, N. Russinol, M. Di Stefano, V. Chapaprieta, G. Clot, X. Farré, S. Xie, M. Sammeth, M. R. Branco, M. Beato, M. A. Martí-Renom, and J. I. Martín-Subero, Dynamics of genome architecture and chromatin function during human B cell differentiation and neoplastic transformation, Nat. Commun. 12, 651 (2021).
  57. C. Bruzeau, J. Drouet, and S. Le Noir, Contribution of immunoglobulin enhancers to B cell nuclear organization and gene regulation, Front. Immunol. 13, 877930 (2022).
  58. C. G. Mullighan, S. Goorha, I. Radtke, C. B. Miller, E. Coustan-Smith, J. T. Dalton, et al., Genome-wide analysis of genetic alterations in acute lymphoblastic leukaemia, Nature (London) 446, 758 (2007).
  59. Y. Song, Y. Huang, Z. Liu, Y. Liu, and W. Wang, Prognostic significance of copy number variation in B-cell acute lymphoblastic leukemia, Front. Oncol. 12, 981036 (2022).
  60. E. M. P. Steeghs, J. M. Boer, A. Q. Hoogkamer, A. Boeree, V. de Haas, H. A. de Groot-Kruseman, M. Horstmann, G. Escherich, R. Pieters, and M. L. den Boer, Copy number alterations in B-cell development genes, drug resistance, and clinical outcome in pediatric B-cell precursor acute lymphoblastic leukemia, Sci. Rep. 9, 4634 (2019).
  61. H. U. Schwenk and U. Schneider, Cell cycle dependency of a T-cell marker on lymphoblasts, Blut 31, 299 (1975).
  62. U. Schneider, H. U. Schwenk, and G. Bornkamm, Characterization of EBV-genome negative “null” and “T” cell lines derived from children with acute lymphoblastic leukemia and leukemic transformed non-Hodgkin lymphoma, Int. J. Cancer 19, 621 (1977).
  63. K. Nilsson, H. Bennich, S. G. Johansson, and J. Pontén, Established immunoglobulin producing myeloma (IgE) and lymphoblastoid (IgG) cell lines from an IgE myeloma patient, Clin. Exp. Immunol. 7, 477 (1970).
  64. I. Di Terlizzi, M. Gironella, D. Herráez-Aguilar, T. Betz, F. Monroy, M. Baiesi, and F. Ritort, Variance sum rule for entropy production, Science 383, 971 (2024).
  65. D. T. Teachey and C.-H. Pui, Comparative features and outcomes between paediatric T-cell and B-cell acute lymphoblastic leukaemia: A systematic review and meta-analysis, Lancet Oncol. 20, e142 (2019).
  66. S. P. Hunger and C. G. Mullighan, Acute lymphoblastic leukemia in children, N. Engl. J. Med. 373, 1541 (2015).
  67. A. D. Hughes, P. Pölönen, and D. T. Teachey, Relapsed childhood T-cell acute lymphoblastic leukemia and lymphoblastic lymphoma, Haematologica 110, 1934 (2025).
  68. L. Hellman and U. Pettersson, Immunoglobulin synthesis in the human myeloma cell line U-266, Eur. J. Immunol. 18, 905 (1988).
  69. A. L. Shaffer, M. Shapiro-Shelef, N. N. Iwakoshi, A. H. Lee, S. B. Qian, H. Zhao, X. Yu, L. Yang, B. K. Tan, A. Rosenwald, et al., XBP1, downstream of BLIMP-1, expands the secretory apparatus and other organelles, and increases protein synthesis in plasma cell differentiation, Immunity 21, 81 (2004).
  70. D. Ron and P. Walter, Signal integration in the endoplasmic reticulum unfolded protein response, Nat. Rev. Mol. Cell Biol. 8, 519 (2007).
  71. E. A. Obeng, L. M. Carlson, D. M. Gutman, W. J. Harrington, K. P. Lee, and L. H. Boise, Proteasome inhibitors induce a terminal unfolded protein response in multiple myeloma cells, Blood 107, 4907 (2006).
  72. M. Calero et al., Derived datasets for Brownian-bridge analysis of chromatin mobility states in leukemia [Data set], Zenodo, 2026, https://doi.org/10.5281/zenodo.20707128.

Outline

Information

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation