An optimized whole blood method for flow cytometric measurement of ZAP‐70 protein expression in chronic lymphocytic leukemia
Bibliographic record
Abstract
BACKGROUND: ZAP-70 protein expression has been proposed as a marker for immunoglobulin heavy chain mutational status, which some studies have correlated with disease course in B-cell chronic lymphocytic leukemia (CLL). Studies published to date measuring levels of expression of ZAP-70 intracellular protein using flow cytometry have demonstrated poor performance, as defined by the difference in signal in known positive and negative lymphocyte populations. METHODS: A recently published method (Chow S, Hedley DW, Grom P, Magari R, Jacobberger JW, Shankey TV, Cytometry A 2005;67:4-17) to measure intracellular phospho-epitopes was optimized using a design of experiments (DOE) approach to provide the best separation of ZAP-70 expression in positive T- or NK-cells as compared to negative B-cells in peripheral blood samples. A number of commercially available anti-ZAP-70 antibody-conjugates were screened using this methodology, and the antibody-conjugate showing the best performance was chosen to develop a four-color, five antibody assays to measure ZAP-70 levels in whole blood specimens. RESULTS: Using the optimized fixation and permeabilization method, improvement in assay performance (signal-to-noise, S/N) was seen in most of the antibodies tested. The custom SBZAP conjugate gave the best S/N when used in conjunction with this optimized fixation /permeabilization method. In conjunction with carefully standardized instrument set-up protocols, we obtained both intra- and interlaboratory reproducibility in the analysis of ZAP-70 expression in whole blood samples from normal and CLL patients. CONCLUSIONS: The development of a sensitive, specific and highly reproducible ZAP-70 assay represents only the first essential step for any clinical assay. The universal implementation of a validated data analysis method and the establishment of methodology-based cutoff points for clinical outcomes must next be established before ZAP-70 protein analysis can be routinely implemented in the clinical laboratory.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".