Expression of interleukin-3 receptor subunits on defined subpopulations of acute myeloid leukemia blasts predicts the cytotoxicity of diphtheria toxin interleukin-3 fusion protein against malignant progenitors that engraft in immunodeficient mice
Bibliographic record
Abstract
The interleukin-3 receptor (IL-3R) subunits are overexpressed on acute myeloid leukemia (AML) blasts compared with normal hematopoietic cells and are thus potential targets for novel therapeutic agents. Both fluorescence-activated cell sorter (FACS) analysis and quantitative real-time reverse transcription-polymerase chain reaction (QRT-PCR) were used to quantify expression of the IL-3Ralpha and beta(c) subunits on AML cells. QRT-PCR for both subunits was most predictive of killing of AML colony-forming cells (AML-CFCs) by diphtheria toxin-IL-3 fusion protein (DT(388)IL3). Among 19 patient samples, the relative level of the IL-3Ralpha was higher than the IL-3Rbeta(c) and highest in CD34(+)CD38(-)CD71(-) cells, enriched for candidate leukemia stem cells, compared with cell fractions depleted of such progenitors. Overall, the amount of IL-3Rbeta(c) subunit did not vary among sorted subpopulations. However, expression of both subunits varied by more than 10-fold among different AML samples for all subpopulations studied. The level of IL-3Rbeta(c) expression versus glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (set at 1000) ranged from 0.14 to 13.56 in CD34(+)CD38(-)CD71(-) cells from different samples; this value was correlated (r = .76, P = .05) with the ability of DT(388)IL3 to kill AML progenitors that engraft in beta(2)-microglobin-deficient nonobese diabetic/severe combined immunodeficient (NOD/SCID) mice (n = 7). Thus, quantification of IL-3R subunit expression on AML blasts predicts the effectiveness IL-3R-targeted therapy in killing primitive leukemic progenitors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".