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Updated: May 12, 2025

Engineering Oncogenic Heterozygous Gain-of-Function Mutations in Human Hematopoietic Stem and Progenitor Cells
Published on: March 10, 2023
Utility of the Base Editing System for Introducing Drug-Resistant Gene Mutations Into Human Leukemia Cellular Models
Thao Nguyen1, Minori Tamai2, Shinichi Fujisawa3
1Pediatrics, University of Yamanashi, Chuo, JPN.
Abstract:
Background Recent genomic analyses of poor prognostic and relapsed leukemia have revealed the involvement of diverse gene mutations in treatment resistance. These gene mutations are classified into two groups: mutations involving resistance to specific agents such as the BCR::ABL1 fusion gene mutations (typically T315I mutation) in tyrosine kinase inhibitor (TKI) resistance and those involving the resistance to diverse therapeutic modalities such as the TP53 gene mutations. In the latter type, although their associations with drug resistance have been clinically demonstrated, the direct association with resistance to each therapeutic modality remains to be fully elucidated. To overcome treatment resistance induced by these gene mutations, appropriate leukemic cellular models are urgently required. Using the cytidine base editing (CBE) system, we introduced two types of mutations through C-to-T transition into human leukemia cell lines and evaluated their significance in the drug sensitivities. Methods We applied the CBE system to introduce the T315I (ACT to ATT) mutation of the BCR::ABL1 fusion gene in a human Philadelphia chromosome-positive leukemia cell line and to introduce the T125M (ACG to ATG) mutation of the TP53 gene in a human B-cell precursor acute lymphoblastic leukemia (BCP-ALL) cell line. Results We first confirmed an introduction of the T315I mutation in one of four BCR::ABL1 alleles as a result of base editing in the obtained TKI-resistant subline. We also identified the additional C-to-T transition at adjacent codon 314 (ATC), which resulted in a silent mutation, in the same allele. We next confirmed that the obtained subline acquired the T125M mutation of the TP53 gene without additional C-to-T transition. In the T125M subline, transcriptional activities of the p53 protein were disrupted and the sensitivities to diverse chemotherapeutic drugs and irradiation were reduced. Conclusion Our observations demonstrated the utility of the CBE system for introducing specific nucleotide transitions into human leukemia cell lines.
Insights
This study demonstrates cytidine base editing (CBE) can create leukemia cell models with specific gene mutations, aiding research into treatment resistance caused by BCR::ABL1 and TP53 mutations.
Area of Science:
- Genetics
- Molecular Biology
- Cancer Research
Background:
- Leukemia treatment resistance is linked to diverse gene mutations.
- Mutations in BCR::ABL1 and TP53 contribute to resistance against various therapies.
- Developing cellular models for these mutations is crucial for understanding and overcoming resistance.
Purpose of the Study:
- To utilize the cytidine base editing (CBE) system to engineer specific gene mutations in leukemia cell lines.
- To evaluate the impact of introduced mutations on drug sensitivities.
- To establish novel cellular models for studying treatment resistance in leukemia.
Main Methods:
- Applied the CBE system to introduce the T315I mutation in BCR::ABL1.
- Introduced the T125M mutation in TP53 using CBE in relevant leukemia cell lines.
- Assessed drug sensitivities and characterized mutation presence in engineered cell lines.
Main Results:
- Successfully introduced the T315I mutation in BCR::ABL1 and the T125M mutation in TP53.
- The TP53 T125M mutation disrupted p53 protein activity and reduced sensitivity to chemotherapy and irradiation.
- Confirmed the utility of CBE for precise gene editing in leukemia models.
Conclusions:
- Cytidine base editing is a viable tool for creating specific nucleotide transitions in leukemia cell lines.
- Engineered cell lines provide valuable models for investigating gene mutation-driven treatment resistance.
- Further research using these models can inform strategies to overcome leukemia drug resistance.

