A Bifunctional PARP-HDAC Inhibitor with Activity in Ewing Sarcoma
Bibliographic record
Abstract
PURPOSE: Histone deacetylase (HDAC) inhibition has been shown to induce pharmacologic "BRCAness" in cancer cells with proficient DNA repair activity. This provides a rationale for exploring combination treatments with HDAC and PARP inhibition in cancer types that are insensitive to single-agent PARP inhibitors (PARPi). Here, we report the concept and characterization of a novel bifunctional PARPi (kt-3283) with dual activity toward PARP1/2 and HDAC enzymes in Ewing sarcoma cells. EXPERIMENTAL DESIGN: Inhibition of PARP1/2 and HDAC was measured using PARP1/2, HDAC activity, and PAR formation assays. Cytotoxicity was assessed by IncuCyte live cell imaging, CellTiter-Glo, and spheroid assays. Cell-cycle profiles were determined using propidium iodide staining and flow cytometry. DNA damage was examined by γH2AX expression and comet assay. Inhibition of metastatic potential by kt-3283 was evaluated via ex vivo pulmonary metastasis assay (PuMA). RESULTS: Compared with FDA-approved PARP (olaparib) and HDAC (vorinostat) inhibitors, kt-3283 displayed enhanced cytotoxicity in Ewing sarcoma models. The kt-3283-induced cytotoxicity was associated with strong S and G2-M cell-cycle arrest in nanomolar concentration range and elevated DNA damage as assessed by γH2AX tracking and comet assays. In three-dimensional spheroid models of Ewing sarcoma, kt-3283 showed efficacy in lower concentrations than olaparib and vorinostat, and kt-3283 inhibited colonization of Ewing sarcoma cells in the ex vivo PuMA model. CONCLUSIONS: Our data demonstrate the preclinical justification for studying the benefit of dual PARP and HDAC inhibition in the treatment of Ewing sarcoma in a clinical trial and provides proof-of-concept for a bifunctional single-molecule therapeutic strategy.
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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".