Delineation of target expression profiles in CD34+/CD38− and CD34+/CD38+ stem and progenitor cells in AML and CML
Bibliographic record
Abstract
In an attempt to identify novel markers and immunological targets in leukemic stem cells (LSCs) in acute myeloid leukemia (AML) and chronic myeloid leukemia (CML), we screened bone marrow (BM) samples from patients with AML (n = 274) or CML (n = 97) and controls (n = 288) for expression of cell membrane antigens on CD34+/CD38- and CD34+/CD38+ cells by multicolor flow cytometry. In addition, we established messenger RNA expression profiles in purified sorted CD34+/CD38- and CD34+/CD38+ cells using gene array and quantitative polymerase chain reaction. Aberrantly expressed markers were identified in all cohorts. In CML, CD34+/CD38- LSCs exhibited an almost invariable aberration profile, defined as CD25+/CD26+/CD56+/CD93+/IL-1RAP+. By contrast, in patients with AML, CD34+/CD38- cells variably expressed "aberrant" membrane antigens, including CD25 (48%), CD96 (40%), CD371 (CLL-1; 68%), and IL-1RAP (65%). With the exception of a subgroup of FLT3 internal tandem duplication-mutated patients, AML LSCs did not exhibit CD26. All other surface markers and target antigens detected on AML and/or CML LSCs, including CD33, CD44, CD47, CD52, CD105, CD114, CD117, CD133, CD135, CD184, and roundabout-4, were also found on normal BM stem cells. However, several of these surface targets, including CD25, CD33, and CD123, were expressed at higher levels on CD34+/CD38- LSCs compared with normal BM stem cells. Moreover, antibody-mediated immunological targeting through CD33 or CD52 resulted in LSC depletion in vitro and a substantially reduced LSC engraftment in NOD.Cg-PrkdcscidIl2rgtm1Wjl/SzJ (NSG) mice. Together, we have established surface marker and target expression profiles of AML LSCs and CML LSCs, which should facilitate LSC enrichment, diagnostic LSC phenotyping, and development of LSC-eradicating immunotherapies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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 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".