Background Minimal residual disease (MRD) assessment of hematopoietic neoplasia below 10−4 requires more leukocytes than is usually attainable by post‐lysis preparation. However, not all laboratories are resourced for consensus Euroflow pre‐lysis methodology. Our study aim was to validate a modified pre‐lysis protocol against our standard post‐lysis method for MRD detection of multiple myeloma (MM), chronic lymphocytic leukemia (CLL), and B‐non Hodgkin lymphoma (B‐NHL), to meet demand for deeper MRD assessment by flow cytometry. Method Clinical samples for MRD assessment of MM, CLL, and B‐NHL (50, 30, and 30 cases, respectively) were prepared in parallel by pre and post‐lysis methods for the initial validation. Total leukocytes, MRD, and median fluorescence intensity of antigen expression were compared as measures of sensitivity and antigen stability. Lymphocyte and granulocyte composition were compared, assessing relative sample processing stability. Sensitivity of the pre‐lysis assay was monitored post validation for a further 18 months. Results Pre‐lysis achieved at least 10−4 sensitivity in 85% MM, 81% CLL, and 90% B‐NHL samples versus 24%, 48%, and 26% by post‐lysis, respectively, with stable antigen expression and leukocyte composition. Post validation over 18 months with technical expertise improving, pre‐lysis permitted 10−5 MRD assessment in 69%, 86%, and 82% of the respective patient groups. Conclusion This modified pre‐lysis procedure provides a sensitive, robust, time efficient, and relatively cost‐effective alternative for MRD testing by MFC at 10−5, facilitating clinically meaningful deeper response assessment for MM, CLL, and B‐NHL. This method adaptation may facilitate more widespread adoption of highly sensitive flow cytometry‐based MRD assessment.
SummaryUndetectable measurable residual disease (MRD) is associated with favourable clinical outcomes in chronic lymphocytic leukaemia (CLL). While assessment is commonly performed using multiparameter flow cytometry (MFC), this approach is associated with limitations including user bias and expertise that may not be widely available. Implementation of unsupervised clustering algorithms in the laboratory can address these limitations and have not been previously reported in a systematic quantitative manner. We developed a computational pipeline to assess CLL MRD using FlowSOM. In the training step, a self‐organising map was generated with nodes representing the full breadth of normal immature and mature B cells along with disease immunophenotypes. This map was used to detect MRD in multiple validation cohorts containing a total of 456 samples. This included an evaluation of atypical CLL cases and samples collected from two different laboratories. Computational MRD showed high correlation with expert analysis (Pearson's r > 0.99 for typical CLL). Binary classification of typical CLL samples as either MRD positive or negative demonstrated high concordance (>98%). Interestingly, computational MRD detected disease in a small number of atypical CLL cases in which MRD was not detected by expert analysis. These results demonstrate the feasibility and value of automated MFC analysis in a diagnostic laboratory.
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