Multiple mechanisms underlie resistance of leukemia cells to Apo2 Ligand/TRAIL
Bibliographic record
Abstract
Targeting death receptors with tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) has the remarkable potential to selectively kill malignant cells whereas normal cells are largely unaffected by this treatment. However, some tumor cells, including leukemia cells, exhibit resistance to this molecule. To investigate the basis for resistance of leukemia cells to the zinc-bound form of Apo2 ligand (Apo2L)/TRAIL, which is currently being evaluated in clinical trial, we isolated several resistant HL60 clones from parental HL60 cells by selection using the recombinant Apo2L/TRAIL. Differing resistance mechanisms were identified and characterized in these Apo2L/TRAIL-resistant clones. In one case, the level of the cell-surface death receptor DR4, but not DR5, was significantly decreased. However, these cells did undergo apoptosis in response to another form of recombinant TRAIL, histidine-tagged TRAIL, suggesting differing contributions of DR4 and DR5 in the response to these two forms of TRAIL. In the case of other clones, expression of procaspase-8 protein was lost and this was associated with a novel Leu(22)-->Phe(22) point mutation in CASP-8 gene. These results show that cells within a given tumor can have widely distinct mechanisms underlying resistance to Apo2L/TRAIL.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".