Cut-like homeobox 1 (CUX1) tumor suppressor gene haploinsufficiency induces apoptosis evasion to sustain myeloid leukemia
Bibliographic record
Abstract
While oncogenes promote tumorigenesis, they also induce deleterious cellular stresses, such as apoptosis, that cancer cells must combat by coopting adaptive responses. Whether tumor suppressor gene haploinsufficiency leads to such phenomena and their mechanistic basis is unclear. Here, we demonstrate that elevated levels of the anti-apoptotic factor, CASP8 and FADD-like apoptosis regulator (CFLAR), promotes apoptosis evasion in acute myeloid leukemia (AML) cells haploinsufficient for the cut-like homeobox 1 (CUX1) transcription factor, whose loss is associated with dismal clinical prognosis. Genome-wide CRISPR/Cas9 screening identifies CFLAR as a selective, acquired vulnerability in CUX1-deficient AML, which can be mimicked therapeutically using inhibitor of apoptosis (IAP) antagonists in murine and human AML cells. Mechanistically, CUX1 deficiency directly alleviates CUX1 repression of the CFLAR promoter to drive CFLAR expression and leukemia survival. These data establish how haploinsufficiency of a tumor suppressor is sufficient to induce advantageous anti-apoptosis cell survival pathways and concurrently nominate CFLAR as potential therapeutic target in these poor-prognosis leukemias.
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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 | 0.000 |
| 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".