KDM6B protects T-ALL cells from NOTCH1-induced oncogenic stress
Bibliographic record
Abstract
Abstract T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematopoietic neoplasm resulting from the malignant transformation of T-cell progenitors. While activating NOTCH1 mutations are the dominant genetic drivers of T-ALL, epigenetic dysfunction plays a central role in the pathology of T-ALL and can provide alternative mechanisms to oncogenesis in lieu of or in combination with genetic mutations. The histone demethylase enzyme KDM6A (UTX) is also recurrently mutated in T-ALL patients and functions as a tumor suppressor. However, its gene paralog, KDM6B (JMJD3), is never mutated and can be significantly overexpressed, suggesting it may be necessary for sustaining the disease. Here, we used mouse and human T-ALL models to show that KDM6B is required for T-ALL development and maintenance. Using NOTCH1 gain-of-function retroviral models, mouse cells genetically deficient for Kdm6b were unable to propagate T-ALL. Inactivating KDM6B in human T-ALL patient cells by CRISPR/Cas9 showed KDM6B-targeted cells were significantly outcompeted over time. The dependence of T-ALL cells on KDM6B was proportional to the oncogenic strength of NOTCH1 mutation, with KDM6B required to prevent stress-induced apoptosis from strong NOTCH1 signaling. These studies identify a crucial role for KDM6B in sustaining NOTCH1-driven T-ALL and implicate KDM6B as a novel therapeutic target in these patients.
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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) | 0.002 | 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".