Quantification of fluorescence properties of lymphocytes in peripheral blood mononuclear cell suspensions using a latent class model

Abstract

Lymphocytes, monocytes, granulocytes, and other blood cells can be distinguished on the basis of their forward (FSC) and sideward (SSC) light scatter properties and their expression of CD45 and CD14. A FSC,SSC gate can be set to include >95% of the lymphocytes using a "back gating" procedure on the CD45 + , CD14-cells. However, nonlymphoid cells such as monocytes have light scattering properties similar to lymphocytes. This problem occurs particularly in patient populations where the light scattering properties of lymphocyte subsets have changed (e.g., due to activation) and are similar to those of the monocytes. Thus, immunophenotyping using antibodies specific for other markers than CD45 and CD14 does not allow a direct assessment of the percentage of all lymphocytes positive for those markers. In order to optimize immunophenotyping we have developed an analytic model in which the FSC,SSC dot plot is partitioned into six nonoverlapping light scatter regions. Each light scatter region containsThe identification and quantitative analysis of lymphocyte subsets are an important application of flow cytometry. Lymphocytes can be distinguished from other types of blood cells on the basis of their forward (FSC) and sideward (SSC) light scattering properties (8,lO). Recently, the technique of setting a light scatter gate around the lymphocytes has been optimized by including the expression of CD45 and CD14 in the definition of lymphocytes (5). With this technique, termed a mixture population of different cell types, i.e., lymphocytes, monocytes, granulocytes, and other cells. The proportions of each cell type are known from the CD45,CD14 expression within each light scatter region. Under the assumption of independence of fluorescence and scatter properties conditional on cell type, the expression of markers other than CD45 or CD14 are derived from the cell type composition and the fluorescence properties on the other markers of each light scatter region. The underlying statistical model is a latent class model, and maximum likelihood estimates are computed using the expectation-maximization (EM) algorithm. The application of the model for immunophenotyping of lymphocytes of healthy individuals and cancer patients receiving immunotherapy is shown.

Analysis of factors contributing to the formation of mononuclear cell aggregates (?escapees?) in flow cytometric immunophenotyping

“…This automated ''no-gating'' analytical method for lymphocyte immunophenotyping also assumes that the type of staining does not influence cellular light scatter characteristics. However, while evaluating the LCM software for routine lymphocyte immunophenotyping, we noticed FSC and SSC signals of lymphocytes to alter with certain mAb cocktails (24), in agreement with observations by others (7,8,11,17). Specifically, the use of certain fluorescein isothiocyanate (FITC)-labeled mAb was reported to induce aggregate formation between lymphocytes, activated platelets, and monocytes or granulocytes.…”

“…Official guidelines for lymphocyte immunophenotyping (1,2) recommend FSC-SSC-based selection of lymphocytes to be made on the basis of staining with CD45 and CD14 monoclonal antibodies (mAbs), which allows distinction between lymphocytes, monocytes, and granulocytes on the basis of 4-parameter definitions (12). The so-called latent class model (LCM) software developed by our group is also based on the FSC, SSC, CD45, and CD14 definition of leukocyte subsets (24). This automated ''no-gating'' analytical method for lymphocyte immunophenotyping also assumes that the type of staining does not influence cellular light scatter characteristics.…”

Three‐marker phenotypic analysis of lymphocytes based on two‐color immunofluorescence using a multinomial model for flow cytometric counts and maximum likelihood estimation

“…A similar approach, i.e., a multinomial model and maximum likelihood estimation, has been applied previously by us for the quantification of fluorescence properties of lymphocytes (13). The general advantage of this model over the published subtraction methods (10,11,14) is that the information in the data is being used optimally.…”

Modulation of immune parameters in patients with metastatic renal-cell cancer receiving combination immunotherapy (IL-2, IFNα and autologous IL-2-activated lymphocytes)

“…List mode data of 10,000 nucleated cells per sample were analyzed using SimulSET software (BDIS) featuring semi-automated selection of lymphocytes by CD45, CD14 "backgating" (Loken et a/., 1990). Cytolytic activities were determined in standard 3-hr %r-release assays as described (Gratama et al, 1993). From the percentages of specific lysis derived from 4 effector:target ratios (i.e., 50:1, 25:1, 12.5:l and 6.3:1), the weighed mean of specific lysis (WMSL) was calculated as…”

“…The DAKO-CD8/PE MAb was obtained from Dakopatts (Glostrup, Denmark); all other MAbs were supplied by Becton Dickinson Immunocytometry Systems (BDIS, San Jose, CA). Staining of the PBMC and flow cytometry was performed as described (Van Putten et al, 1993). List mode data of 10,000 nucleated cells per sample were analyzed using SimulSET software (BDIS) featuring semi-automated selection of lymphocytes by CD45, CD14 "backgating" (Loken et a/., 1990).…”