Merging and imputation of flow cytometry data: A critical assessment.

Although most modern techniques and analysis methods in multiparameter flow cytometry (MFC) allow for increased dimensionality for the characterization and quantification of cell populations, most MFC applications depend on flow cytometers measuring relatively small (<16) numbers of parameters. When more markers than the available parameters need to be acquired, these are commonly distributed over multiple independent measurements that include a backbone of common markers. Several methods have been proposed to impute values for combinations of markers that were not measured simultaneously. These imputation methods are frequently used without proper validation and knowledge of their effects on data analysis. We evaluated the performance of existing imputation software (Infinicyt, CyTOFmerge, CytoBackBone, and cyCombine) in approximating known measured expression data in terms of similarity in visual appearance, cell expression, and gating in different datasets by splitting MFC samples into separate measurements with partially overlapping markers and re-calculating missing marker expression. Out of the assessed packages, CyTOFmerge showed the most accurate approximation of the known expression in terms of similar expression values and concordance with manual gating, with a mean F-score between 0.53 and 0.87 when retrieving cell populations in different datasets. Performance remained inadequate for all methods, with only limited similarity at the cell level. In conclusion, the use of imputed MFC data should take such limitations into account and include independent validation of results to justify conclusions.

Residual normal stem cells can be detected in newly diagnosed chronic myeloid leukemia patients by a new flow cytometric approach and predict for optimal response to imatinib.

Insensitivity of chronic myeloid leukemia (CML) hematopoietic stem cells to tyrosine kinase inhibitors (TKIs) prevents eradication of the disease and may be involved in clinical resistance. For improved treatment results more knowledge about CML stem cells is needed. We here present a new flow cytometric approach enabling prospective discrimination of CML stem cells from their normal counterparts within single-patient samples. In 24 of 40 newly diagnosed CML patients residual normal CD34(+)CD38(-) stem cells could be identified by lower CD34 and CD45 expression, lower forward/sideward light scatter and by differences of lineage marker expression (CD7, CD11b and CD56) and of CD90. fluorescent in situ hybridization (FISH) analysis on Fluorescence-activated cell sorting sorted cells proved that populations were BCR-ABL positive or negative and long-term liquid culture assays with subsequent colony forming unit assays and FISH analysis proved their stem cell character. Patients with residual non-leukemic stem cells had lower clinical risk scores (Sokal, Euro), lower hematological toxicity of imatinib (IM) and better molecular responses to IM than patients without. This new approach will expand our possibilities to separate CML and normal stem cells, present in a single bone marrow or peripheral blood sample, thereby offering opportunities to better identify new CML stem-cell-specific targets. Moreover, it may guide optimal clinical CML management.