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Published on: October 17, 2025
Molecular genetic characteristics and clinical significance of childhood acute lymphoblastic leukemia
1Blood Donation Service Department, Wuhan Blood Center, Wuhan, China.
Objective:
To explore the molecular genetic characteristics of childhood acute lymphoblastic leukemia (ALL) and their relationships with clinical phenotypes, chromosomal abnormalities, and prognosis, so as to provide references for precise diagnosis and treatment.
Methods:
A total of 302 newly diagnosed children with ALL were included. Real-time fluorescent quantitative PCR, high-throughput sequencing and other technologies were used to detect common fusion genes, rare fusion genes and Ph-like ALL-related molecules. Combined with chromosomal karyotype analysis, immunophenotyping and minimal residual disease (MRD) monitoring, the associations between molecular genetic characteristics and clinical indicators as well as prognosis were analyzed.
Results:
Among the 302 children, the total positive rate of leukemia genes was 50.66%, and the gene detection rate in B-ALL children (52.90%) was significantly higher than that in T-ALL (37.21%). Common fusion genes were mainly ETV6/RUNX1 (19.54%), MLL (9.27%) and BCR/ABL (6.29%), with age- and immune subtype-specific distributions. Children with ETV6/RUNX1 positivity had the highest complete remission rate (93.2%) and the best 2-year event-free survival rate (89.8%), while those with BCR/ABL positivity had the worst prognosis (complete remission rate 57.9%, 2-year event-free survival rate 42.1%). There were differences in the consistency between fusion genes and chromosomal abnormalities: ETV6/RUNX1 and BCR/ABL showed 100% consistency with specific chromosomal translocations, while E2A/PBX1 and MLL showed about 50% consistency. The dynamic changes of MRD were closely related to gene types, with significantly higher MRD positive rates in children with high-risk genes.
Conclusion:
The molecular genetic characteristics of childhood ALL have clear clinical significance. Fusion gene detection can be used for disease classification, risk stratification and prognosis evaluation, providing an important basis for the formulation of individualized treatment strategies.
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