Minimal Residual Disease Detection by Droplet Digital PCR in Multiple Myeloma, Mantle Cell Lymphoma, and Follicular Lymphoma: A Comparison with Real-Time PCR

J Mol Diagn. 2015 Nov;17(6):652-60. doi: 10.1016/j.jmoldx.2015.05.007. Epub 2015 Aug 28.

Abstract

Real-time quantitative PCR (qPCR) is a well-established tool for minimal residual disease (MRD) detection in mature lymphoid malignancies. Despite remarkable sensitivity and specificity, qPCR has some limitations, particularly in the need for a reference standard curve, based on target serial dilutions. In this study, we established droplet digital PCR (ddPCR) for MRD monitoring in multiple myeloma, mantle cell lymphoma, and follicular lymphoma and compared it head-to-head with qPCR. We observed that ddPCR has sensitivity, accuracy, and reproducibility comparable with qPCR. We then compared the two approaches in 69 patients with a documented molecular marker at diagnosis (18 multiple myelomas, 21 mantle cell lymphomas assessed with the immunoglobulin gene rearrangement, and 30 follicular lymphomas with the use of the BCL2/immunoglobulin gene major breakpoint region rearrangement). ddPCR was successful in 100% of cases, whereas qPCR failed to provide a reliable standard curve in three patients. Overall, 222 of 225 samples were evaluable by both methods. The comparison highlighted a good concordance (r = 0.94, P < 0.0001) with 189 of 222 samples (85.1%; 95% CI, 80.4%-89.8%) being fully concordant. We found that ddPCR is a reliable tool for MRD detection with greater applicability and reduced labor intensiveness than qPCR. It will be necessary to authorize ddPCR as an outcome predictor tool in controlled clinical settings and multilaboratory standardization programs.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Humans
  • Lymphoma, Follicular / diagnosis*
  • Lymphoma, Mantle-Cell / diagnosis*
  • Multiple Myeloma / diagnosis*
  • Neoplasm, Residual / diagnosis*
  • Real-Time Polymerase Chain Reaction / methods
  • Reference Standards
  • Reproducibility of Results
  • Sensitivity and Specificity