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Immunoglobulin NGS enhance residual disease detection and prognosis in pediatric Ph+ acute lymphoblastic leukemia
Lixian Chang1,2, Jiao Chang1,2, Beibei Zhao1,2
1State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Abstract:
In pediatric Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph+ B-ALL), the clinical value of highly sensitive minimal residual disease (MRD) detection by immunoglobulin next-generation sequencing (Ig-NGS), and its role for tracking clonal evolution, remains inadequately characterized. In this study, we evaluated MRD in a cohort of pediatric Ph+ B-ALL patients using Ig-NGS in parallel with conventional methods, including flow cytometry (FCM) and BCR-ABL reverse transcription polymerase chain reaction (RT-PCR). Malignant clonal burden at diagnosis, MRD kinetics, and immunoglobulin heavy chain (IGH) clonal evolution were analyzed for their prognostic relevance. We observed that a lower percentage of malignant clonal cells detected by Ig-NGS at diagnosis was associated with improved relapse-free survival (RFS) (p < 0.01). Ig-NGS-derived pre-treatment malignant clone burden showed stronger association with relapse risk compared with FCM or RT-PCR. Furthermore, Ig-NGS MRD negativity at the end of induction (EOI) was associated with superior two-yeas RFS (p = 0.01), and Ig-NGS detected molecular relapse earlier than FCM or RT-PCR in some patients. Specific IGHV and IGHJ gene usage patterns and the extent of V-replacement clonal evolution at diagnosis were also correlated with prognosis. In summary, these findings suggested that Ig-NGS based MRD assessment may provide enhanced prognostic stratification and enable dynamic monitoring of clonal evolution in pediatric Ph+ B-ALL. Its integration into routine clinical practice may enhance early relapse prediction and support more precise risk-adapted therapeutic decisions.
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