Figure 1.
Data analysis strategy used to optimize the antibody panel for distinguishing between BCP-ALL cells and their nearest normal/reactive BCP counterpart. First, multiple normal/reactive BM samples and/or regenerating BM samples were merged (phase 1: n = 7; phase 2: n = 11; phase 3: n = 14; phase 4: n = 10) and CD19-positive B cells were selected. These were subdivided into 4 B-cell subsets, based on the backbone markers (CD19/CD10/CD20/CD34/CD45): CD34+ pre–B-I cells (light green), CD34−/CD10+/CD20− to dim pre–B-II/immature cells (dark blue), CD34−/CD10+/CD20+ immature/transitional B cells (light blue), and CD34−/CD10−/CD20+ mature B cells (dark green). Dot plots of CD34 vs CD10 (A) and CD10 vs CD20 (B) are shown. The 1 standard deviation (SD) (dashed line) and 2 SD lines (solid line) of the 2 most immature BCP subsets (pre–B-I [light green] and pre–B-II/immature [dark blue]) were displayed in an APS view, which was subsequently fixed (supervised; C). Each individual BCP-ALL case was added to the fixed APS plot, and the normal BCP population nearest to each of the BCP-ALL populations was defined (D). The BCP-ALL cells and nearest normal BCP subset were then visualized in a separate (nonfixed and balanced) APS plot, 1 using the backbone markers only (E) and 1 using all 8 markers (F), by plotting the 1 SD curve and 2 SD curves of the 2 populations. To prevent an influence of the number of cells on the principal component analysis (PCA), we opted to use a balanced PCA, implying a fixed ratio between normal and pathological events. Finally, the separation between the 2 populations was scored based on: no overlap between 2 SD curves: 3 points; overlap of the 2 SD curves: 2 points; overlap of the 2 SD and the 1 SD curve: 1 point; overlap of both 1 SD curves: 0 points. An example of this scoring is shown in supplemental Figure 1. It should be noted that the above described strategy was only used for optimizing the antibody panel for the BCP-ALL MRD tubes and not for actual MRD analyses.

Data analysis strategy used to optimize the antibody panel for distinguishing between BCP-ALL cells and their nearest normal/reactive BCP counterpart. First, multiple normal/reactive BM samples and/or regenerating BM samples were merged (phase 1: n = 7; phase 2: n = 11; phase 3: n = 14; phase 4: n = 10) and CD19-positive B cells were selected. These were subdivided into 4 B-cell subsets, based on the backbone markers (CD19/CD10/CD20/CD34/CD45): CD34+ pre–B-I cells (light green), CD34/CD10+/CD20 to dim pre–B-II/immature cells (dark blue), CD34/CD10+/CD20+ immature/transitional B cells (light blue), and CD34/CD10/CD20+ mature B cells (dark green). Dot plots of CD34 vs CD10 (A) and CD10 vs CD20 (B) are shown. The 1 standard deviation (SD) (dashed line) and 2 SD lines (solid line) of the 2 most immature BCP subsets (pre–B-I [light green] and pre–B-II/immature [dark blue]) were displayed in an APS view, which was subsequently fixed (supervised; C). Each individual BCP-ALL case was added to the fixed APS plot, and the normal BCP population nearest to each of the BCP-ALL populations was defined (D). The BCP-ALL cells and nearest normal BCP subset were then visualized in a separate (nonfixed and balanced) APS plot, 1 using the backbone markers only (E) and 1 using all 8 markers (F), by plotting the 1 SD curve and 2 SD curves of the 2 populations. To prevent an influence of the number of cells on the principal component analysis (PCA), we opted to use a balanced PCA, implying a fixed ratio between normal and pathological events. Finally, the separation between the 2 populations was scored based on: no overlap between 2 SD curves: 3 points; overlap of the 2 SD curves: 2 points; overlap of the 2 SD and the 1 SD curve: 1 point; overlap of both 1 SD curves: 0 points. An example of this scoring is shown in supplemental Figure 1. It should be noted that the above described strategy was only used for optimizing the antibody panel for the BCP-ALL MRD tubes and not for actual MRD analyses.

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