PersonALL: a genetic scoring guide for personalized risk assessment in pediatric B-cell precursor acute lymphoblastic leukemia.
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Bedics Gábor, Egyed Bálint, Kotmayer Lili, Benard-Slagter Anne, de Groot Karel, Bekő Anna, Hegyi Lajos László, Bátai Bence, Krizsán Szilvia, Kriván Gergely, Erdélyi Dániel J, Müller Judit, Haltrich Irén, Kajtár Béla, Pajor László, Vojcek Ágnes, Ottóffy Gábor, Ujfalusi Anikó, Szegedi István, Tiszlavicz Lilla Györgyi, Bartyik Katalin, Csanádi Krisztina, Péter György, Simon Réka, Hauser Péter, Kelemen Ágnes, Sebestyén Endre, Jakab Zsuzsanna, Matolcsy András, Kiss Csongor, Kovács Gábor, Savola Suvi, Bödör Csaba, Alpár Donát
Аннотация
METHODS: Disease-relevant copy number aberrations (CNAs) were screened genome-wide in 260 children with B-cell precursor ALL. Results were integrated with cytogenetic data to improve risk assessment.
RESULTS: CNAs were detected in 93.8% (n = 244) of the patients. First, cytogenetic profiles were combined with IKZF1 status (IKZF1normal, IKZF1del and IKZF1plus) and three prognostic subgroups were distinguished with significantly different 5-year event-free survival (EFS) rates, IKAROS-low (n = 215): 86.3%, IKAROS-medium (n = 27): 57.4% and IKAROS-high (n = 18): 37.5%. Second, contribution of genetic aberrations to the clinical outcome was assessed and an aberration-specific score was assigned to each prognostically relevant alteration. By aggregating the scores of aberrations emerging in individual patients, personalized cumulative values were calculated and used for defining four prognostic subgroups with distinct clinical outcomes. Two favorable subgroups included 60% of patients (n = 157) with a 5-year EFS of 96.3% (excellent risk, n = 105) and 87.2% (good risk, n = 52), respectively; while 40% of patients (n = 103) showed high (n = 74) or ultra-poor (n = 29) risk profile (5-year EFS: 67.4% and 39.0%, respectively).
CONCLUSIONS: PersonALL, our conceptually novel prognostic classifier considers all combinations of co-segregating genetic alterations, providing a highly personalized patient stratification.