Inhibition of Aberrantly Overexpressed Polo-like Kinase 4 Is a Potential Effective Treatment for DNA Damage Repair–Deficient Uterine Leiomyosarcoma
Bibliographic record
Abstract
PURPOSE: Uterine leiomyosarcoma (LMS) is an aggressive sarcoma and a subset of which exhibits DNA repair defects. Polo-like kinase 4 (PLK4) precisely modulates mitosis, and its inhibition causes chromosome missegregation and increased DNA damage. We hypothesize that PLK4 inhibition is an effective LMS treatment. EXPERIMENTAL DESIGN: Genomic profiling of clinical uterine LMS samples was performed, and homologous recombination (HR) deficiency scores were calculated. A PLK4 inhibitor (CFI-400945) with and without an ataxia telangiectasia mutated (ATM) inhibitor (AZD0156) was tested in vitro on gynecologic sarcoma cell lines SK-UT-1, SKN, and SK-LMS-1. Findings were validated in vivo using the SK-UT-1 xenograft model in the Balb/c nude mouse model. The effects of CFI-400945 were also evaluated in a BRCA2-knockout SK-UT-1 cell line. The mechanisms of DNA repair were analyzed using a DNA damage reporter assay. RESULTS: Uterine LMS had a high HR deficiency score, overexpressed PLK4 mRNA, and displayed mutations in genes responsible for DNA repair. CFI-400945 demonstrated effective antitumor activity in vitro and in vivo. The addition of AZD0156 resulted in drug synergism, largely due to a preference for nonhomologous end-joining DNA repair. Compared with wild-type cells, BRCA2 knockouts were more sensitive to PLK4 inhibition when both HR and nonhomologous end-joining repairs were impaired. CONCLUSIONS: Uterine LMS with DNA repair defects is sensitive to PLK4 inhibition because of the effects of chromosome missegregation and increased DNA damage. Loss-of-function BRCA2 alterations or pharmacologic inhibition of ATM enhanced the efficacy of the PLK4 inhibitor. Genomic profiling of an advanced-stage or recurrent uterine LMS may guide therapy.
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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".