Preclinical studies reveal MLN4924 is a promising new retinoblastoma therapy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract RB1 loss ( RB1 null ) or MYCN amplification ( MYCN amp ) in fetal human retina causes retinoblastoma. SKP2 loss kills RB1 null cells, but small molecule SKP2 inhibitors remain unexplored therapeutically. Whether SKP2 is synthetic lethal in MYCN amp retinoblastoma is unclear. SKP2 is the substrate recognition component of two Cullin-RING Ligase complexes (CRL1 SKP2 /SCF SKP2 , and CRL4 SKP2 ), a family of multiprotein E3 ubiquitin ligases. NEDD8 activating enzyme (NAE) is required for Cullin neddylation and thus CRL activation. Here, we show that the NAE inhibitor, Pevonedistat (MLN4924), potently inhibits RB1 null and MYCN amp tumors. Intravitreal MLN4924 suppressed multiple human xenografts with EC80s from 20 ng to 3.5 μg. Maximum tolerated dose (MTD) was 10–30 μg, highlighting a favorable therapeutic window. Inhibition of Cullin neddylation was similar in all cases, but cellular effects ranged from G1 arrest with apoptosis to G2/M arrest with endoreplication. However, even in less sensitive lines (EC50 ≈ 1 μM), prolonged exposure was lethal or induced persistent cytostasis. Mechanistically, depleting any single Cullin did not fully recapitulate drug phenotypes, but sensitivity to SKP2 loss correlated with that of drug. Thus, intravitreal MLN4924 is a promising new retinoblastoma therapy, mimicking the cancer-specific lethality of eliminating SKP2 complexes.
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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 it