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Digital PCR for Minimal Residual Disease Quantitation Using Immunoglobulin/T-Cell Receptor Gene Rearrangements in Acute Lymphoblastic Leukemia: A Proposed Analytic Algorithm.
Lu, Yi; Li, Zhenhua; Lim, Evelyn Huizi; Huan, Pei Tee; Kham, Shirley Kow Yin; Yeoh, Allen Eng-Juh.
Afiliación
  • Lu Y; VIVA-NUS Centre for Translational Research in Acute Leukemia, Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Li Z; VIVA-NUS Centre for Translational Research in Acute Leukemia, Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Lim EH; VIVA-NUS Centre for Translational Research in Acute Leukemia, Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Huan PT; VIVA-NUS Centre for Translational Research in Acute Leukemia, Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Kham SKY; VIVA-NUS Centre for Translational Research in Acute Leukemia, Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Yeoh AE; VIVA-NUS Centre for Translational Research in Acute Leukemia, Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; VIVA-University Children's Cancer Centre, Khoo Teck Puat-National University Children's Medical Institute, National University Hospit
J Mol Diagn ; 24(6): 655-665, 2022 06.
Article en En | MEDLINE | ID: mdl-35390515
ABSTRACT
In minimal residual disease (MRD), where there are exceedingly low target copy numbers, digital PCR (dPCR) can improve MRD quantitation. However, standards for dPCR MRD interpretation in acute lymphoblastic leukemia are lacking. Here, for immunoglobulin/T-cell receptor-based MRD, we propose an objective, statistics-based analytic algorithm. In 161 postinduction samples from 79 children with acute lymphoblastic leukemia, MRD was performed by dPCR and real-time quantitative PCR (qPCR) using the same markers and primer-probe sets. The dPCR raw data were analyzed by using an automated algorithm. dPCR and qPCR results were highly concordant (P < 0.0001) 98% (50 of 51) of qPCR positive were positive by dPCR, whereas 95% (61 of 64) of qPCR negative results were also negative by dPCR. For MRD quantitation, both qPCR and dPCR were tightly correlated (R2 = 0.94). Using more DNA (1 µg × 7 versus 630 ng × 3), dPCR improved sensitivity of MRD quantitation by one log10 (median MRD positive cutoff 1.6 × 10-5). With dPCR, 83% (29 of 35) of positive-not-quantifiable results by qPCR could be assigned positive/negative MRD status. Seven replicates of tested samples and negative controls were optimal. Compared with qPCR, dPCR could improve MRD sensitivity by one log10. We proposed an automatable, statistics-based algorithm that minimized interoperator variance for dPCR MRD.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Leucemia-Linfoma Linfoblástico de Células Precursoras Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Child / Humans Idioma: En Revista: J Mol Diagn Asunto de la revista: BIOLOGIA MOLECULAR Año: 2022 Tipo del documento: Article País de afiliación: Singapur

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Leucemia-Linfoma Linfoblástico de Células Precursoras Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Child / Humans Idioma: En Revista: J Mol Diagn Asunto de la revista: BIOLOGIA MOLECULAR Año: 2022 Tipo del documento: Article País de afiliación: Singapur