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Epigenetic evolution and lineage histories of chronic lymphocytic leukaemia
Open accessAbstract
Genetic and epigenetic intra-tumoral heterogeneity cooperate to shape the evolutionary course of cancer 1. Chronic lymphocytic leukaemia (CLL) is a highly informative model for cancer evolution as it undergoes substantial genetic diversification and evolution after therapy 2,3. The CLL epigenome is also an important disease-defining feature 4,5, and growing populations of cells in CLL diversify by stochastic changes in DNA methylation known as epimutations 6. However, previous studies using bulk sequencing methods to analyse the patterns of DNA methylation were unable to determine whether epimutations affect CLL populations homogeneously. Here, to measure the epimutation rate at single-cell resolution, we applied multiplexed single-cell reduced-representation bisulfite sequencing to B cells from healthy donors and patients with CLL. We observed that the common clonal origin of CLL results in a consistently increased epimutation rate, with low variability in the cell-to-cell epimutation rate. By contrast, variable epimutation rates across healthy B cells reflect diverse evolutionary ages across the trajectory of B cell differentiation, consistent with epimutations serving as a molecular clock. Heritable epimutation information allowed us to reconstruct lineages at high-resolution with single-cell data, and to apply this directly to patient samples. The CLL lineage tree shape revealed earlier branching and longer branch lengths than in normal B cells, reflecting rapid drift after the initial malignant transformation and a greater proliferative history. Integration of single-cell bisulfite sequencing analysis with single-cell transcriptomes and genotyping confirmed that genetic subclones mapped to distinct clades, as inferred solely on the basis of epimutation information. Finally, to examine potential lineage biases during therapy, we profiled serial samples during ibrutinib-associated lymphocytosis, and identified clades of cells that were preferentially expelled from the lymph node after treatment, marked by distinct transcriptional profiles. The single-cell integration of genetic, epigenetic and transcriptional information thus charts the lineage history of CLL and its evolution with therapy.
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“Another study combined single-cell transcriptome and DNA methylome data to construct a chronic lymphocytic leukaemia (CLL) lineage tree based on random DNA methylation changes, finding that certain CLL lineages were preferentially affected by drug treatment143.”
From The technological landscape and applications of single-cell multi-omics (2023) · cites this paper as [143]
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Citations
Cites
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies
Nguyen, L.-T., Schmidt, H. A., von Haeseler, A., & Minh, B. Q. (2015) · Molecular Biology and Evolution · doi:10.1093/molbev/msu300 · Cited by 26,046
ModelFinder: fast model selection for accurate phylogenetic estimates
Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A., & Jermiin, L. S. (2017) · Nature Methods · doi:10.1038/nmeth.4285 · Cited by 18,449
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
Self-citationUFBoot2: Improving the Ultrafast Bootstrap Approximation
Hoang, D. T., Chernomor, O., von Haeseler, A., Minh, B. Q., & Vinh, L. S. (2018) · Molecular Biology and Evolution · doi:10.1093/molbev/msx281 · Cited by 10,881
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Imran, K., Iqbal, M. J., Ahmed, M. M., Khalid, A., Cortés, H., Reyes‐Hernández, O. D., Figueroa‐González, G., Leyva‐Gómez, G., Falzone, L., Libra, M., et al. (2025) · Medical Oncology · doi:10.1007/s12032-025-02905-z · Cited by 26
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O’Neill, H., Lee, H. J., Gupta, I., Rodger, E. J., & Chatterjee, A. (2022) · Cancers · doi:10.3390/cancers14246171 · Cited by 19
Celebrating 20 Years of IGHV Mutation Analysis in CLL
Chiorazzi, N., & Stevenson, F. K. (2020) · HemaSphere · doi:10.1097/hs9.0000000000000334 · Cited by 20
Odell, S. C., Taki, F., Klein, S. L., Chen, R. J., Levine, O. B., Skelly, M. J., Nabila, A., Brindley, E., Toth, J. G., Dündar, F., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107789 · Cited by 17
Self-citationNucleosome repositioning in chronic lymphocytic leukemiaPreprint
Piroeva, K. V., McDonald, C., Xanthopoulos, C., Fox, C., Clarkson, C. T., Mallm, J., Vainshtein, Y., Ruje, L., Klett, L. C., Stilgenbauer, S., et al. (2023) · Genome Research · doi:10.1101/gr.277298.122 · Cited by 18
Cheng, T., Zhou, C., Bian, S., Sobeck, K., & Liu, Y. (2024) · Cancer Cell International · doi:10.1186/s12935-024-03288-3 · Cited by 19
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Gabbutt, C., Wright, N. A., Baker, A., Shibata, D. K., & Graham, T. A. (2022) · The Journal of Pathology · doi:10.1002/path.5911 · Cited by 16
The transcriptional legacy of developmental stochasticity
Ballouz, S., Kawaguchi, R. K., Peña, M. T., Fischer, S., Crow, M., French, L., Knight, F. M., Adams, L. B., & Gillis, J. (2023) · Nature Communications · doi:10.1038/s41467-023-43024-5 · Cited by 27
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Pfisterer, U., Bräunig, J., Brattås, P. L., Heidenblad, M., Karlsson, G., & Fioretos, T. (2021) · Genes Chromosomes and Cancer · doi:10.1002/gcc.22944 · Cited by 17
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Self-citationBennett, R., Thompson, E. R., & Tam, C. S. L. (2022) · Clinical Lymphoma Myeloma & Leukemia · doi:10.1016/j.clml.2022.07.013 · Cited by 18
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Bond, D. R., Uddipto, K., Enjeti, A. K., & Lee, H. J. (2020) · Epigenomics · doi:10.2217/epi-2020-0046 · Cited by 15
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Duran‐Ferrer, M., & Martín-Subero, J. I. (2023) · Annual Review of Pathology Mechanisms of Disease · doi:10.1146/annurev-pathmechdis-051122-100856 · Cited by 16
New insights into Human Hematopoietic Stem and Progenitor Cells via Single-Cell Omics
Zhang, Y., Huang, Y., Hu, L., & Cheng, T. (2022) · Stem Cell Reviews and Reports · doi:10.1007/s12015-022-10330-2 · Cited by 15
Microfluidics for Cancer Biomarker Discovery, Research, and Clinical Application
Žvirblytė, J., & Mažutis, L. (2022) · Advances in experimental medicine and biology · doi:10.1007/978-3-031-04039-9_20 · Cited by 13
Epigenetic cancer evolution, one cell at a time
Perdigoto, C. N. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0143-1 · Cited by 13
The LL-100 Cell Lines Panel: Tool for Molecular Leukemia–Lymphoma Research
Drexler, H. G., & Quentmeier, H. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21165800 · Cited by 15
The Crossroads of Clonal Evolution, Differentiation Hierarchy, and Ontogeny in Leukemia Development
Sturgeon, C. M., Wagenblast, E., Izzo, F., & Papapetrou, E. P. (2024) · Blood Cancer Discovery · doi:10.1158/2643-3230.bcd-24-0235 · Cited by 12
Ahuja, P., Yadav, R., Goyal, S., Yadav, C., Ranga, S., & Kadian, L. K. (2023) · Cell Biology and Toxicology · doi:10.1007/s10565-023-09818-5 · Cited by 12
Single-cell epigenomics and proteomics methods integrated in multiomics
Bi, H., & Weng, X. (2024) · Fundamental Research · doi:10.1016/j.fmre.2023.11.014 · Cited by 12
Fong, J., Gardner, J. R., Andrews, J. M., Cashen, A. F., Payton, J. E., Weinberger, K. Q., & Edwards, J. R. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab516 · Cited by 11
In Human Visualization of Ibrutinib-Induced CLL Compartment Shift
Mayerhoefer, M. E., Haug, A. R., Jaeger, U., Pichler, V., Pfaff, S., Wester, H., Hacker, M., Kazianka, L., & Staber, P. B. (2020) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-19-0880 · Cited by 12
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Xu, F., Dong, M.-M., Wang, Z., & Cao, L. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1083069 · Cited by 14
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Andreani, G., Carrà, G., Lingua, M. F., Maffeo, B., Brancaccio, M., Taulli, R., & Morotti, A. (2020) · Cancers · doi:10.3390/cancers12030629 · Cited by 11
Ng, A. K. Y., & Chiorazzi, N. (2021) · Hematology/Oncology Clinics of North America · doi:10.1016/j.hoc.2021.03.002 · Cited by 12
Domenico, A. D., Pipinikas, C., Maire, R., Bräutigam, K., Simillion, C., Dettmer, M. S., Vassella, E., Thirlwell, C., Perren, A. A., & Marinoni, I. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.08.029785 · Cited by 11
Charting single-cell lineages with synthetic and natural barcodes
Rodriguez-Fraticelli, A., & Parreno, V. (2026) · Nature Reviews Genetics · doi:10.1038/s41576-026-00943-5 · Cited by 11
The molecular map of CLL and Richter's syndrome
Sud, A., Parry, E. M., & Wu, C. J. (2024) · Seminars in Hematology · doi:10.1053/j.seminhematol.2024.01.009 · Cited by 10
Self-citationYe, B., Yang, L., Liu, B., Liu, N., Fan, D., Li, H., Sun, L., Du, Y., Wang, S., Tian, Y., et al. (2022) · Cellular and Molecular Immunology · doi:10.1038/s41423-022-00842-9 · Cited by 10
Can aggressive cancers be identified by the “aggressiveness” of their chromatin?
Gurova, K. V. (2022) · BioEssays · doi:10.1002/bies.202100212 · Cited by 9
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Tseng, C.-C., & Obeng, E. A. (2024) · Seminars in Hematology · doi:10.1053/j.seminhematol.2024.10.005 · Cited by 11
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Pearson, H. C. L., Hunt, K. V., Trahair, T. N., Lock, R. B., Lee, H. J., & de Bock, C. E. (2022) · HemaSphere · doi:10.1097/hs9.0000000000000734 · Cited by 9
Kulis, M., & Martín-Subero, J. I. (2022) · British Journal of Haematology · doi:10.1111/bjh.18465 · Cited by 11
Nam, A. S., Dusaj, N. N., Izzo, F., Murali, R., Myers, R. M., Mouhieddine, T. H., Sotelo, J., Benbarche, S., Waarts, M. R., Gaiti, F., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.01.14.476225 · Cited by 10
Self-citationGuo, W., Chen, W., Zhang, J., Li, M., Huang, H., Wang, Q., Fei, X., Huang, J., Zheng, T., Fan, H., et al. (2025) · BMC Cancer · doi:10.1186/s12885-024-13380-6 · Cited by 9
Self-citationThe end of the beginning: application of single-cell sequencing to chronic lymphocytic leukemia
Nagler, A., & Wu, C. J. (2022) · Blood · doi:10.1182/blood.2021014669 · Cited by 9
Self-citationCopy number-aware deconvolution of tumor-normal DNA methylation profilesPreprint
Cadieux, E. L., Mensah, N., Castignani, C., Tanić, M., Wilson, G. A., Dietzen, M., Dhami, P., Vaikkinen, H., Verfaillie, A., Cotobal, C., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.11.03.366252 · Cited by 9
Gaiti, F., Chamely, P., Hawkins, A. G., Cortés-López, M., Swett, A. D., Ganesan, S., Mouhieddine, T. H., Dai, X., Kluegel, L., Chen, C. Y., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.08.495292 · Cited by 9
Self-citationLiu, Y., Li, X. C., Mehrabadi, F. R., Schäffer, A. A., Pratt, D. W., Crawford, D. R., Malikić, S., Molloy, E. K., Gopalan, V., Mount, S. M., et al. (2023) · Genome Research · doi:10.1101/gr.277608.122 · Cited by 8
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Godfrey, L., & Rodríguez-Meira, A. (2022) · Cancers · doi:10.3390/cancers14235989 · Cited by 7
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Kabeer, F., Tran, H., Andronescu, M., Singh, G., Lee, H., Salehi, S., Wang, B., Biele, J., Brimhall, J., Gee, D., et al. (2024) · Genome biology · doi:10.1186/s13059-024-03318-3 · Cited by 9
Methylation patterns at the adjacent CpG sites within enhancers are a part of cell identity
Taryma‐Leśniak, O., Bińkowski, J., Przybylowicz, P. K., Sokolowska, K. E., Borowski, K., & Wojdacz, T. K. (2024) · Epigenetics & Chromatin · doi:10.1186/s13072-024-00555-5 · Cited by 8
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Pacholewska, A., Grimm, C., Herling, C., Lienhard, M., Königs, A., Timmermann, B., Altmüller, J., Mücke, O., Reinhardt, H. C., Plass, C., et al. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22179337 · Cited by 8
Saeed, W. H., Eissa, A. A., & Al-Doski, A. A. (2019) · Journal of Blood Medicine · doi:10.2147/jbm.s221707 · Cited by 8
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Kumar, S., Kats, L. M., & Gruber, E. (2025) · International Journal of Cancer · doi:10.1002/ijc.35426 · Cited by 8
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Paul, P., Stüssi, G., Bruscaggin, A., & Rossi, D. (2022) · Leukemia & lymphoma/Leukemia and lymphoma · doi:10.1080/10428194.2022.2153359 · Cited by 7
Radiomic features define risk and are linked to DNA methylation attributes in primary CNS lymphoma
Nenning, K., Gesperger, J., Furtner, J., Nemc, A., Roetzer-Pejrimovsky, T., Choi, S. W., Mitter, C., Leber, S. L., Hofmanninger, J., Klughammer, J., et al. (2023) · Neuro-Oncology Advances · doi:10.1093/noajnl/vdad136 · Cited by 7
Genomic Instability and Clonal Evolution in Chronic Lymphocytic Leukemia: Clinical Relevance
Condoluci, A., & Rossi, D. (2021) · Journal of the National Comprehensive Cancer Network · doi:10.6004/jnccn.2020.7623 · Cited by 7
Mircea, M., & Semrau, S. (2021) · Biochemical Society Transactions · doi:10.1042/bst20210135 · Cited by 9
Biancotti, R., Pozzo, C. A. D., Parente, P., Businello, G., Angerilli, V., Realdon, S., Savarino, E. V., Farinati, F., Milanetto, A. C., Pasquali, C., et al. (2022) · Digestive Diseases · doi:10.1159/000525421 · Cited by 7
Barozzi, I., Slaven, N., Canale, E., Lopes, R., Barbosa, I. A. M., Bleu, M., Ivanoiu, D., Pacini, C., Mensa’, E., Chambers, A., et al. (2024) · Cancer Discovery · doi:10.1158/2159-8290.cd-23-1157 · Cited by 7
Reid, J. C., Golubeva, D., Boyd, A. L., Hollands, C. G., Henly, C., Orlando, L., Leber, A., Hébert, J., Morabito, F., Cutrona, G., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.108845 · Cited by 7
Evolving strategies for lineage tracing: Genetic markers, synthetic barcodes, and natural variants
Kang, Z., Chen, H., Li, S., Wang, S., & Zhou, B. (2026) · Cell stem cell · doi:10.1016/j.stem.2026.05.001 · Cited by 6
Nomura, M., Raviram, R., Schiffman, J. S., Bussema, L., Lu, V., Wheeler, N., Lee, J. J. Y., Fan, Y., Zheng, M. H., Ruiz, F., et al. (2026) · Nature Genetics · doi:10.1038/s41588-026-02642-7 · Cited by 8
Self-citationGLP and G9a histone methyltransferases as potential therapeutic targets for lymphoid neoplasms
Silva-Carvalho, A. É., Filiú-Braga, L. D. D. C., Bogéa, G. M. R., de Assis, A. J. B., Pittella-Silva, F., & Saldanha‐Araújo, F. (2024) · Cancer Cell International · doi:10.1186/s12935-024-03441-y · Cited by 6
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Zhang, L., Yang, J., Tang, D., Zhang, H., Ding, J., & Xiao, H. (2022) · Scientia Sinica Chimica · doi:10.1360/ssc-2022-0158 · Cited by 6
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Oder, B., Chatzidimitriou, A., Langerak, A. W., Rosenquist, R., & Österholm, C. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1143811 · Cited by 5
Biological, prognostic, and therapeutic impact of the epigenome in CLL
Maiqués-Díaz, A., & Martín-Subero, J. I. (2023) · Seminars in Hematology · doi:10.1053/j.seminhematol.2023.11.005 · Cited by 5
Johnson, N. D., Cutler, D. J., & Conneely, K. N. (2024) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2024.02.009 · Cited by 5
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Pandkar, M. R., & Shukla, S. (2024) · Biochemical Journal · doi:10.1042/bcj20240221 · Cited by 6
DNA methylation dynamics in the shoot apical meristem
Yang, J., & Johannes, F. M. (2025) · Journal of Experimental Botany · doi:10.1093/jxb/eraf024 · Cited by 6
Single-cell lineage tracing techniques in hematology: unraveling the cellular narrative
Deng, L.-H., Li, M., Huang, X., & Zhao, X. (2025) · Journal of Translational Medicine · doi:10.1186/s12967-025-06318-4 · Cited by 5
A ternary-code DNA methylome atlas of mouse tissues
Lee, S. M., Goldberg, D. C., Cloud, C., Parker, J. B., Krapp, C. J., Loo, C. E., Kim, E., Zhao, I., Jin, C., Porecha, R., et al. (2025) · Genome biology · doi:10.1186/s13059-025-03808-y · Cited by 4
SOHO State of the Art Updates and Next Questions: Clonal Evolution in Chronic Lymphocytic Leukemia
Condoluci, A., & Rossi, D. (2020) · Clinical Lymphoma Myeloma & Leukemia · doi:10.1016/j.clml.2020.08.029 · Cited by 5
DNA methylation meets lineage tracing: History, recent progress, and future directions
Fu, R., Chen, M., & Wang, S. (2025) · Quantitative Biology · doi:10.1002/qub2.70017 · Cited by 4
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Song, P., Wu, Y., Zhang, C., Zhou, F., Bai, L., & Su, J. (2025) · Materials Today Bio · doi:10.1016/j.mtbio.2025.102539 · Cited by 5
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Agarwal, A. P., & Kumar, M. S. (2024) · Gene · doi:10.1016/j.gene.2024.149047 · Cited by 5
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Wang, K., He, X., & Hu, Z. (2026) · Nature Reviews Genetics · doi:10.1038/s41576-026-00969-9 · Cited by 7
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Lindroth, A. M., Park, Y. J., Matía, V., & Squatrito, M. (2020) · Human Molecular Genetics · doi:10.1093/hmg/ddaa143 · Cited by 4
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Klutstein, M. (2020) · BioEssays · doi:10.1002/bies.202000262 · Cited by 4
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Gutierrez, C., & Wu, C. J. (2019) · Hematology · doi:10.1182/hematology.2019000367 · Cited by 4
Self-citationSingle-cell technologies: a new lens into epigenetic regulation in development
Bolondi, A., Kretzmer, H., & Meissner, A. (2022) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2022.101947 · Cited by 4
Self-citationMai, L., Wen, Z., Zhang, Y., Gao, Y., Lin, G., Lian, Z., Yang, X., Zhou, J., Lin, X., Luo, C., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad892 · Cited by 4
Contributions of transcriptional noise to leukaemia evolution: KAT2A as a case-study
Pina, C. (2024) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2023.0052 · Cited by 6
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Leung, J. Y., Chia, K., Ong, D. S. T., & Taneja, R. (2019) · Antioxidants and Redox Signaling · doi:10.1089/ars.2019.7942 · Cited by 4
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Self-citationGregg, C. J. (2021) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2021.693781 · Cited by 4
Mimmi, S., Maisano, D., Dattilo, V., Gentile, M., Chiurazzi, F., d’Ambrosio, A., Zimbo, A. M., Nisticò, N., Aloisio, A., Vecchio, E., et al. (2022) · Biomedicines · doi:10.3390/biomedicines10030604 · Cited by 3
Kaufman, M. S., Yan, X., Li, W., Ghia, E. M., Langerak, A. W., Rassenti, L. Z., Belessi, C., Kay, N. E., Davi, F., Byrd, J. C., et al. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.897280 · Cited by 3
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Qin, S., Liu, S., & Weng, X. (2023) · Science China Chemistry · doi:10.1007/s11426-023-1793-7 · Cited by 2
Metadata
- Authors
- Gaiti, F., Chaligne, R., Gu, H., Brand, R. M., Kothen-Hill, S., Schulman, R. C., Grigorev, K., Risso, D., Kim, K.-T., Pastore, A., Huang, K. Y., Alonso, A., Sheridan, C., Omans, N. D., Biederstedt, E., Clement, K., Wang, L., Felsenfeld, J. A., Bhavsar, E. B., Aryee, M. J., Allan, J. N., Furman, R., Gnirke, A., Wu, C. J., Meissner, A., & Landau, D. A.
- Affiliations
- New York Genome Center (US)
- Broad Institute (US)
- Weill Cornell Medicine (US)
- University of Padua (IT)
- Memorial Sloan Kettering Cancer Center (US)
- City of Hope (US)
- Corresponding author
- Landau, Dan A.
- ORCID
- Venue
- Nature
- Published
- 2019-05-15
- Volume
- 569
- Issue
- 7757
- Pages
- 576-580
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC6533116
- OpenAlex
- W2946801856
- Cited by
- 262
- References
- 73
- Citations by year
- 2026: 18 · 2025: 27 · 2024: 34 · 2023: 37 · 2022: 51 · 2021: 51 · 2020: 35 · 2019: 9
- FWCI
- 20.01
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Padua Research Archive (University of Padova) (submittedVersion, other-oa)
- Funders
- National Institutes of Health (1dp2ca239065-01, 5r01ca229902-05)
- National Heart, Lung, and Blood Institute (R01HL145283)
- National Cancer Institute (R01CA240910, DP2-CA239065, R01-CA229902, R01CA216273, UG1CA233338, P30CA008748, P01CA206978, P30CA006516)
- National Institute of Environmental Health Sciences (K01ES025431)
- Topics
- Health Sciences › Medicine › Hematology › Chronic Lymphocytic Leukemia Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- chronic lymphocytic leukemia, epimutations, DNA methylation, epigenetic evolution, intratumoral heterogeneity, clonal evolution, lineage reconstruction, ibrutinib resistance, B cell differentiation, single-cell bisulfite sequencing, single-cell transcriptomics
- MeSH terms
- Epigenome, Base Sequence, Biological Clocks, Humans, Transcription, Genetic, Leukemia, Lymphocytic, Chronic, B-Cell, Gene Expression Regulation, Neoplastic, Sequence Analysis, RNA, Cell Lineage, Evolution, Molecular, DNA Methylation, Epigenesis, Genetic, Single-Cell Analysis, Mutation Rate
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