Chronic Myeloid Leukemia: Predicting the Effectiveness of Anticancer Drug Treatment Now Possible

It is expected that the effectiveness of anticancer drug treatment can be predicted in patients with chronic myeloid leukemia.

On November 25, a research team led by Professor Kim Hyungbum and Dr. Jung Yoosang and Dr. Yoo Goosang from the Department of Pharmacology at Yonsei University College of Medicine announced that they had identified all patterns of drug resistance associated with ABL1 gene mutations in chronic myeloid leukemia cells using prime editing technology.

Yonsei Medical Center

The results of this study were published in the international journal Nature Biomedical Engineering (IF 26.7).

Chronic myeloid leukemia is a representative type of blood cancer caused by the BCR-ABL1 fusion gene. This gene abnormally activates the ABL1 enzyme in cells, causing cancer cells to continue growing. Four generations of anticancer drugs have been developed for chronic myeloid leukemia, and many patients have shown positive treatment outcomes.

However, as the treatment period continues, mutations can occur in the ABL1 gene, frequently leading to drug resistance. When gene mutations arise, it becomes difficult to determine which drugs the patient will be resistant or responsive to, making it challenging to select the appropriate anticancer drug for each patient in clinical practice.

The research team used the latest gene editing technology called "prime editor" to analyze the degree of drug resistance for 98% (1,954 out of 1,998) of all possible single amino acid mutations in the ABL1 gene.

Yonsei Medical Center

By utilizing prime editing technology, the team created 1,954 types of single amino acid mutations in the ABL1 gene within a human-derived chronic myeloid leukemia cell line (K562). They then evaluated the degree of resistance for each mutation to a total of five drugs: the first- to fourth-generation anticancer agents imatinib, nilotinib, bosutinib, ponatinib, and asciminib.

As a result, the team newly identified 361 pairs of drug resistance mutations that had not been previously reported. Notably, many new resistance mutations not included in existing clinical guidelines were discovered, and mutation patterns were found that either responded to only specific drugs or showed resistance to multiple drugs simultaneously.

Additionally, the team conducted the same analysis using another human-derived chronic myeloid leukemia cell line (KCL22) and a mouse model, and confirmed consistent results upon revalidation.

Professor Kim Hyungbum stated, "Through this study, we were able to identify comprehensive information on anticancer drug resistance associated with ABL1 gene mutations," and added, "Even if gene mutations are detected in chronic myeloid leukemia patients in the future, we expect that this research data can be used to provide personalized precision medicine for each patient."

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