REFERENCES
1. Jabbour E, Kantarjian H. Chronic myeloid leukemia: 2025 update on diagnosis, therapy, and monitoring. Am J Hematol. 2024;99:2191-212.
2. Rowley JD. A new consistent chromosomal abnormality in chronic myelogenous leukaemia identified by quinacrine fluorescence and giemsa staining. Nature. 1973;243:290-3.
3. Faderl S, Talpaz M, Estrov Z, O'brien S, Kurzrock R, Kantarjian HM. The biology of chronic myeloid leukemia. N Engl J Med. 1999;341:164-72.
4. Mandanas R, Leibowitz D, Gharehbaghi K, et al. Role of p21 RAS in p210 bcr-abl transformation of murine myeloid cells. Blood. 1993;82:1838-47.
5. Minciacchi VR, Kumar R, Krause DS. Chronic myeloid leukemia: a model disease of the past, present and future. Cells. 2021;10:117.
6. Raitano AB, Halpern JR, Hambuch TM, Sawyers CL. The Bcr-Abl leukemia oncogene activates Jun kinase and requires Jun for transformation. Proc Natl Acad Sci USA. 1995;92:11746-50.
7. Stein SJ, Baldwin AS. NF-κB suppresses ROS levels in BCR-ABL+ cells to prevent activation of JNK and cell death. Oncogene. 2011;30:4557-66.
8. Tam WF, Gu T, Chen J, et al. Id1 is a common downstream target of oncogenic tyrosine kinases in leukemic cells. Blood. 2008;112:1981-92.
9. He F, Lin S, Gao B, et al. A proteogenomic gene signature defines prognostic subgroups highlighting PI3K/AKT/mTOR signaling pathway as a therapeutic vulnerability in myeloid malignancies. Cell Commun Signal. 2025;24:61.
10. Mohammadhosseini M, Enright T, Duvall A, et al. Targeting the CD74 signaling axis suppresses inflammation and rescues defective hematopoiesis in RUNX1-familial platelet disorder. Sci Transl Med. 2025;17:eadn9832.
11. Huang X, Cortes J, Kantarjian H. Estimations of the increasing prevalence and plateau prevalence of chronic myeloid leukemia in the era of tyrosine kinase inhibitor therapy. Cancer. 2012;118:3123-7.
12. Weisberg E, Manley PW, Breitenstein W, et al. Characterization of AMN107, a selective inhibitor of native and mutant Bcr-Abl. Cancer Cell. 2005;7:129-41.
13. Shah NP, Tran C, Lee FY, Chen P, Norris D, Sawyers CL. Overriding imatinib resistance with a novel ABL kinase inhibitor. Science. 2004;305:399-401.
14. Druker BJ, Lydon NB. Lessons learned from the development of an Abl tyrosine kinase inhibitor for chronic myelogenous leukemia. J Clin Investig. 2000;105:3-7.
15. Jabbour E, Sasaki K, Haddad FG, et al. Low‐dose dasatinib 50 mg/day versus standard‐dose dasatinib 100 mg/day as frontline therapy in chronic myeloid leukemia in chronic phase: a propensity score analysis. Am J Hematol. 2022;97:1413-8.
16. Krishnan V, Schmidt F, Nawaz Z, et al. A single-cell atlas identifies pretreatment features of primary imatinib resistance in chronic myeloid leukemia. Blood. 2023;141:2738-55.
17. Zhang W, Yang B, Weng L, et al. Single cell sequencing reveals cell populations that predict primary resistance to imatinib in chronic myeloid leukemia. Aging. 2020;12:25337-55.
18. Komic H, Nilsson MS, Wennström L, et al. Single-cell proteo-transcriptomic profiling reveals altered characteristics of stem and progenitor cells in patients receiving cytoreductive hydroxyurea in early-phase chronic myeloid leukemia. Haematologica. 2025;110:117-28.
19. Stengel A, Hörst K, Kühn C, et al. Potential factors underlying the progression of RUNX1-mutated MDS to AML. Cancer Genet. 2025;294-5:181-3.
20. Li X, Zuo S, Zhang Y, et al. FBXO3-mediated DUSP9 ubiquitination promotes leukemia stem cell maintenance and tyrosine kinase inhibitor resistance in chronic myeloid leukemia. Cell Rep Med. 2026;7:102686.
21. Cui Y, Li Y, Ji J, et al. Dynamic single-Cell RNA-seq reveals mechanism of selinexor-resistance in chronic myeloid leukemia. Int Immunopharmacol. 2024;134:112212.
22. Liu H, Li Y, Karsidag M, Tu T, Wang P. Technical and biological biases in bulk transcriptomic data mining for cancer research. J Cancer. 2025;16:34-43.
23. Munje C, Copland M. Exploring stem cell heterogeneity in chronic myeloid leukemia. Trends Cancer. 2018;4:167-9.
24. Zheng Y, Yang X. Spatial RNA sequencing methods show high resolution of single cell in cancer metastasis and the formation of tumor microenvironment. Biosci Rep. 2023;43:BSR20221680.
25. Frankhouser DE, Zhao D, Fu YH, et al. Longitudinal single cell RNA-sequencing reveals evolution of micro- and macro-states in chronic myeloid leukemia. Syst Biol. 2025:2025.05.14.653262.
26. Cho J, Cao J, Hemberg M. Joint analysis of mutational and transcriptional landscapes in human cancer reveals key perturbations during cancer evolution. Genome Biol. 2024;25:65.
27. Zhu L, Yi K, Zhou J, et al. Concurrent NPM1::CCDC28A and BCR::ABL1 fusions in extramedullary blast crisis of chronic myeloid leukemia: A case report and literature review. Ann Hematol. 2025;104:6045-51.
28. Dawson A, Zarou MM, Prasad B, et al. Leukaemia exposure alters the transcriptional profile and function of BCR::ABL1 negative macrophages in the bone marrow niche. Nat Commun. 2024;15:1090.
29. Zhuo C, Dong X, Zhao X, et al. Single-cell sequencing reveals the expansion and diversity of T cell subsets in the bone marrow microenvironment of chronic myeloid leukemia. Genes Dis. 2025;12:101626.
30. Svensson V, Vento-Tormo R, Teichmann SA. Exponential scaling of single-cell RNA-seq in the past decade. Nat Protoc. 2018;13:599-604.
31. Hwang B, Lee JH, Bang D. Single-cell RNA sequencing technologies and bioinformaticspipelines. Exp Mol Med. 2018;50:1-14.
32. Shaffer SM, Dunagin MC, Torborg SR, et al. Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance. Nature. 2017;546:431-5.
33. Tang F, Barbacioru C, Wang Y, et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods. 2009;6:377-82.
34. Salmen F, De Jonghe J, Kaminski TS, et al. High-throughput total RNA sequencing in single cells using VASA-seq. Nat Biotechnol. 2022;40:1780-93.
35. Hagemann-Jensen M, Ziegenhain C, Chen P, et al. Single-cell RNA counting at allele and isoform resolution using Smart-seq3. Nat Biotechnol. 2020;38:708-14.
36. Gierahn TM, Wadsworth MH, Hughes TK, et al. Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput. Nat Methods. 2017;14:395-8.
37. Fan HC, Fu GK, Fodor SPA. Combinatorial labeling of single cells for gene expression cytometry. Science. 2015;347:1258367.
38. Wang X, He Y, Zhang Q, Ren X, Zhang Z. Direct comparative analyses of 10X genomics chromium and smart-Seq2. Genom Proteom Bioinform. 2021;19:253-66.
39. Warfvinge R, Geironson Ulfsson L, Dhapola P, et al. Single-cell multiomics analysis of chronic myeloid leukemia links cellular heterogeneity to therapy response. eLife. 2024;12:RP92074.
40. Li L, Rottmann I, Saeed BR, et al. High-dimensional spatiotemporal single-cell atlas and 3D imaging of the bone marrow microenvironment during CML progression. Blood. 2026;147:2648-65.
41. Mustjoki S, Richter J, Barbany G, et al. Impact of malignant stem cell burden on therapy outcome in newly diagnosed chronic myeloid leukemia patients. Leukemia. 2013;27:1520-6.
42. Sloma I, Beer PA, Saw KM, et al. Genotypic and functional diversity of phenotypically defined primitive hematopoietic cells in patients with chronic myeloid leukemia. Exp Hematol. 2013;41:837-47.
43. Giustacchini A, Thongjuea S, Barkas N, et al. Single-cell transcriptomics uncovers distinct molecular signatures of stem cells in chronic myeloid leukemia. Nat Med. 2017;23:692-702.
44. Warfvinge R, Geironson L, Sommarin MNE, et al. Single-cell molecular analysis defines therapy response and immunophenotype of stem cell subpopulations in CML. Blood. 2017;129:2384-94.
45. Ma J, Pettit N, Talburt J, Wang S, Weissman SM, Yang MQ. Integrating single-cell transcriptome and network analysis to characterize the therapeutic response of chronic myeloid leukemia. Int J Mol Sci. 2022;23:14335.
46. Yin Z, Su R, Ge L, et al. Single-cell resolution reveals RalA GTPase expanding hematopoietic stem cells and facilitating of BCR-ABL1-driven leukemogenesis in a CRISPR/Cas9 gene editing mouse model. Int J Biol Sci. 2023;19:1211-27.
47. Patterson SD, Copland M. The bone marrow immune microenvironment in CML: treatment responses, treatment-free remission, and therapeutic vulnerabilities. Curr Hematol Malig Rep. 2023;18:19-32.
48. Nievergall E, Reynolds J, Kok CH, et al. TGF-α and IL-6 plasma levels selectively identify CML patients who fail to achieve an early molecular response or progress in the first year of therapy. Leukemia. 2016;30:1263-72.
49. Reynaud D, Pietras E, Barry-Holson K, et al. IL-6 controls leukemic multipotent progenitor cell fate and contributes to chronic myelogenous leukemia development. Cancer Cell. 2011;20:661-73.
50. Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat Methods. 2013;10:1213-8.
51. Chimge N, Chen M, Nguyen C, et al. A deeply quiescent subset of CML LSC depend on FAO yet avoid deleterious ROS by suppressing mitochondrial complex I. Curr Mol Pharmacol. 2023;17:e060923220758.
52. Yu G, Lu W, Chen X, et al. Single-cell RNA sequencing to explore composition of peripheral blood NK cells in patients with chronic myeloid leukemia in treatment-free remission. Leukemia Lymphoma. 2022;63:2604-15.
53. Imeri J, Desterke C, Marcoux P, et al. Case report: long-term voluntary Tyrosine Kinase Inhibitor (TKI) discontinuation in chronic myeloid leukemia (CML): molecular evidence of an immune surveillance. Front Oncol. 2023;13:1117781.
54. Bertacchini J, Ketabchi N, Mediani L, Capitani S, Marmiroli S, Saki N. Inhibition of Ras-mediated signaling pathways in CML stem cells. Cell Oncol. 2015;38:407-18.
55. Zhou J, Zhao Y, Leng J, et al. DNA methylation-mediated differential expression of DLX4 isoforms has opposing roles in leukemogenesis. Cell Mol Biol Lett. 2022;27:59.
56. Holyoake TL, Vetrie D. The chronic myeloid leukemia stem cell: stemming the tide of persistence. Blood. 2017;129:1595-606.
57. Perry JM, Tao F, Roy A, et al. Overcoming Wnt-β-catenin dependent anticancer therapy resistance in leukaemia stem cells. Nat Cell Biol. 2020;22:689-700.
58. Desterke C, Hugues P, Hwang JW, Bennaceur-Griscelli A, Turhan AG. Embryonic program activated during blast crisis of chronic myelogenous leukemia (CML) implicates a TCF7L2 and MYC cooperative chromatin binding. Int J Mol Sci. 2020;21:4057.
59. Veenstra J, Dimitrion P, Yao Y, Zhou L, Ozog D, Mi Q. Research techniques made simple: use of imaging mass cytometry for dermatological research and clinical applications. J Investig Dermatol. 2021;141:705-12.e1.
60. Cheung TK, Lee C, Bayer FP, Mccoy A, Kuster B, Rose CM. Defining the carrier proteome limit for single-cell proteomics. Nat Methods. 2020;18:76-83.
61. Coorens THH, Oh JW, Choi YA, et al. The somatic mosaicism across human tissues network. Nature. 2025;643:47-59.
62. Rao A, Barkley D, França GS, Yanai I. Exploring tissue architecture using spatial transcriptomics. Nature. 2021;596:211-20.
63. Kuznetsova OA, Ivanov MV, Lebedeva AA, et al. Comprehensive molecular profiling in MOTION study. Cancer Genet. 2025;296-7:45-52.
64. Lopez R, Regier J, Cole MB, Jordan MI, Yosef N. Deep generative modeling for single-cell transcriptomics. Nat Methods. 2018;15:1053-8.
65. Cui H, Wang C, Maan H, et al. scGPT: toward building a foundation model for single-cell multi-omics using generative AI. Nat Methods. 2024;21:1470-80.
66. Borra S, Yan D, Welner RS, Yue Z. An AI-enabled single-cell transcriptomic analysis pipeline for gene signature discovery in natural killer cells linked to remission outcomes in chronic myeloid leukemia. Biology. 2026;15:588.
67. Huuhtanen J, Adnan-Awad S, Theodoropoulos J, et al. Single-cell analysis of immune recognition in chronic myeloid leukemia patients following tyrosine kinase inhibitor discontinuation. Leukemia. 2023;38:109-25.
68. Lei Y, Tang R, Xu J, et al. Applications of single-cell sequencing in cancer research: progress and perspectives. J Hematol Oncol. 2021;14:91.
69. Hu Y, An Q, Sheu K, Trejo B, Fan S, Guo Y. Single cell multi-omics technology: methodology and application. Front Cell Dev Biol. 2018;6:28.






