A dual mechanism of sensitivity to PLK4 inhibition by RP-1664 in neuroblastoma
Bibliographic record
Abstract
ABSTRACT A novel therapeutic strategy was recently proposed for high-risk neuroblastoma carrying copy number gain of the TRIM37 gene: centriole loss upon inhibition of polo-like kinase 4 (PLK4), while tolerated by normal cells, induces aberrant mitotic spindle formation and p53-dependent cell death in TRIM37 -overexpressing cells. Interestingly, while full PLK4 inhibition causes centriole loss, partial inhibition is known to elevate centriole numbers. Here we show using a novel selective PLK4 inhibitor RP-1664 that both centriole loss and amplification contribute to hypersensitivity of neuroblastoma cells. Whereas inactivation of TRIM37 and TP53 rescues neuroblastoma cell death at higher concentrations of RP-1664, at lower doses cell death is TRIM37/TP53 -independent. With CRISPR screens and live cell imaging we demonstrate that upon centriole amplification, neuroblastoma cells succumb to multipolar mitoses due to inability to cluster or inactivate supernumerary centrosomes. In vivo , RP-1664 shows robust efficacy in neuroblastoma xenografts at doses consistent with centriole amplification. STATEMENT OF SIGNIFICANCE High-risk neuroblastoma is associated with poor outcomes in pediatric patients and novel therapies need to be developed. We show that neuroblastoma cells are remarkably sensitive to PLK4 inhibitors due to a combination of two complementary mechanisms, supporting the evaluation of PLK4 inhibitors in clinical trials of high-risk neuroblastoma.
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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".