c-Myc regulates expression of NKG2D ligands ULBP1/2/3 in AML and modulates their susceptibility to NK-mediated lysis
Bibliographic record
Abstract
Cytarabine (cytosine arabinoside) is one of the most effective drugs for the treatment of patients diagnosed with acute myeloid leukemia (AML). Despite its efficiency against AML cells, the emergence of drug resistance due to prolonged chemotherapy in most patients is still a major obstacle. Several studies have shown that drug resistance mechanisms alter the sensitivity of leukemia cells to immune system effector cells. To investigate this phenomenon, parental acute myeloid cell lines, HL-60 and KG-1, were continuously exposed to increasing doses of cytarabine in order to establish equivalent resistant cell lines, HL-60(R) and KG-1(R). Our data indicate that cytarabine-resistant cells are more susceptible to natural killer (NK)-mediated cell lysis as compared with parental cytarabine-sensitive cells. The increased susceptibility correlates with the induction of UL-16 binding proteins (ULBP) 1/2/3 and NK group 2, member D (NKG2D) ligands on target cells by a mechanism involving c-Myc induction. More importantly, chromatin immunoprecipitation assay revealed that ULBP1/3 are direct targets of c-Myc. Using drug-resistant primary AML blasts as target cells, inhibition of c-Myc resulted in decreased expression of NKG2D ligands and the subsequent impairment of NK cell lysis. This study provides for the first time, the c-Myc dependent regulation of NKG2D ligands in AML.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".