ArticleExperimental hematology & oncology2025
Resolving intra-tumor heterogeneity and clonal evolution of core-binding factor acute myeloid leukemia patients with single-cell resolution.
Article in Experimental hematology & oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Review
- Characteristics of fusion genes in breast cancer.Cancer cell international · 2026Review
- Cancer Heterogeneity and Cancer Cell Plasticity: Molecular Mechanisms and Precision Therapy.MedComm · 2026Review
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14 authors.
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Abstract
Reconstructing and understanding intra-tumor heterogeneity, the coexistence of multiple genetically distinct subclones within the tumor of a patient, and tumor development is essential for resolving carcinogenesis and for identifying mechanisms of therapy resistance. While bulk sequencing can provide a broad view on tumoral complexity/heterogeneity of a patient, single-cell analysis remains essential to identify rare subclones that might drive chemotherapy resistance. In this study, we performed an integrated analysis of bulk and single-cell DNA sequencing data of core-binding factor acute myeloid leukemia patients, defined by the presence of a RUNX1::RUNX1T1 or CBFB::MYH11 fusion gene. By single-cell sequencing, we inferred tumor phylogenies for 8 patients at diagnosis including patient-specific somatic variants, somatic copy-number alterations and fusion genes, and studied clonal evolution under the pressure of chemotherapy for 3 patients. As a result, we developed an approach to reliably integrate subclonal somatic copy number alterations into phylogenetic trees and clonal evolution analysis, obtaining unprecedented resolution of intra-tumor heterogeneity in CBF AML. We were able to show that the fusion gene is among the earliest events of leukemogenesis at single-cell level. We identified remaining tumor clones in 6 patients with complete remission samples indicating incomplete eradication of the tumor clones. Here, we show that identifying the order of mutation acquisition can provide valuable insights into evolutionary history, offering a framework to improve drug selection in the era of targeted therapies.
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