J Mol Diagn. 2022 Apr 4:S1525-1578(22)00075-7. doi: 10.1016/j.jmoldx.2022.03.004. Online ahead of print.
ABSTRACT
In minimal residual disease (MRD), where there are exceedingly low target copy numbers, droplet digital PCR (ddPCR) can improve the quantitation. However, we currently lack the standards for ddPCR data analysis and results for MRD interpretation in acute lymphoblastic leukemia (ALL). Here, for Ig/TCR-based MRD quantitation, we propose an objective, statistics-based analytic algorithm. In 161 post-induction samples from 79 children with ALL, we performed MRD quantitation by ddPCR and qPCR using the same markers and primer-probe sets. The ddPCR raw data were analysed using an automated algorithm. For assigning MRD positive/negative status, ddPCR and qPCR results were highly concordant (P<0.0001): 98% (50/51) of qPCR positive were positive by ddPCR, while 95% (61/64) of qPCR negative were also negative by ddPCR. For MRD quantitation, both qPCR and ddPCR were tightly correlated (R2=0.94). Using more DNA (1 μg ×7 vs 630 ng ×3), ddPCR improved the sensitivity of MRD quantitation by one-log10 (median MRD positive cut-off 1.6×10-5). With the improved sensitivity by ddPCR, 83% (29/35) of positive-not-quantifiable results by qPCR could be assigned with positive/negative MRD status. We also determined that 7 replicates of tested samples and negative controls were optimal for the assay. Compared to qPCR, for Ig/TCR-based MRD quantitation, ddPCR could improve MRD sensitivity by one log10. We proposed an automatable, statistics-based algorithm that minimized inter-operator variance for ddPCR MRD.
PMID:35390515 | DOI:10.1016/j.jmoldx.2022.03.004
