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In Cytometry. Part B, Clinical cytometry

INTRODUCTION : The diagnosis of CLL/SLL relies on flow cytometric immunophenotyping. Increasing emphasis is being placed on precise detection of the minimal residual disease. Following antigen recommendations of ERIC and ESCCA's Harmonization Project, we validated a 14-color assay for the characterization CD5+ lymphoproliferative neoplasms and CLL MRD with a sensitivity of at least 10-4 .

METHODS : The assay was designed based on ERIC/ESCCA recommended antigens with the addition of CD40 for alternate gating when CD19 expression is reduced. Lower limit of quantitation/lower limit of detection, assay procedural precision, linearity, and limit of blank were established. Then, 52 CD5+ B-cell lymphoproliferative neoplasms (41 CLL/11 non-CLL) and 29 normal samples were used for parallel evaluation. Automated cluster identification and quantitation of CLL clones in MRD setting was performed using Barned-Hutt SNE. Separation analysis between CLL and non-CLL phenotypes was performed by PCA and bh-SNE.

RESULTS : Separation ratios for each antigen exceeded ERIC/ESCCA guidelines. Precision was <20% at LLOQ (0.01%). The limit of blank was <10/500,000 cells. Concordance between the 14-color and legacy assay (Deming regression y = 1.01x, r2 = .99) was seen. All 20 samples with MRD levels 0.5%-0.006% (median 0.04%) showed an abnormal cell cluster by bh-SNE, with concordant results between manual and automated quantitation (y = x, r2 = 1). CLL cases clustered together and away from mantle cell lymphoma by bh-SNE and PCA with outlier atypical phenotype CLL cases posing diagnostic challenges by both manual and automated analysis.

CONCLUSION : The 14-color CD5+ LPD assay provides a robust standardization platform for MRD and disease characterization using both manual and automated analysis.

Goshaw Jennifer M, Gao Qi, Wardrope Jessica, Dogan Ahmet, Roshal Mikhail

2020-Sep-08

CLL, MRD, machine learning, mantle cell