Activation of concurrent apoptosis and necroptosis by SMAC mimetics for the treatment of refractory and relapsed ALL
Bibliographic record
Abstract
More precise treatment strategies are urgently needed to decrease toxicity and improve outcomes for treatment-refractory leukemia. We used ex vivo drug response profiling of high-risk, relapsed, or refractory acute lymphoblastic leukemia (ALL) cases and identified a subset with exquisite sensitivity to small-molecule mimetics of the second mitochondria-derived activator of caspases (SMAC) protein. Potent ex vivo activity of the SMAC mimetic (SM) birinapant correlated with marked in vivo antileukemic effects, as indicated by delayed engraftment, decreased leukemia burden, and prolonged survival of xenografted mice. Antileukemic activity was dependent on simultaneous execution of apoptosis and necroptosis, as demonstrated by functional genomic dissection with a multicolored lentiCRISPR approach to simultaneously disrupt multiple genes in patient-derived ALL. SM specifically targeted receptor-interacting protein kinase 1 (RIP1)-dependent death, and CRISPR-mediated disruption of RIP1 completely blocked SM-induced death yet had no impact on the response to standard antileukemic agents. Thus, SM compounds such as birinapant circumvent escape from apoptosis in leukemia by activating a potent dual RIP1-dependent apoptotic and necroptotic cell death, which is not exploited by current therapy. Ex vivo drug activity profiling could provide important functional diagnostic information to identify patients who may benefit from targeted treatment with birinapant in early clinical trials.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".