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Abstract A024: <i>In vitro</i> efficacy of a novel dual PARP-HDAC inhibitor in ewing sarcoma

2022· article· en· W4296122547 on OpenAlexaffabout
Sarah Truong, Beibei Zhai, Fariba Ghaidi, Louise Ramos, Jay Joshi, Dennis Brown, Neil Sankar, John Langlands, Jeffrey Bacha, Shen Wang, Poul Sorensen, Mads Daugaard

Bibliographic record

VenueClinical Cancer Research · 2022
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOlaparibPARP1PARP inhibitorCancer researchPoly ADP ribose polymeraseHistone deacetylaseViability assayBiologyDNA damageDNA repairHistoneMolecular biologyPharmacologyIn vitroPolymeraseBiochemistryDNA

Abstract

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Abstract Introduction: Inhibition of poly-adenosine diphosphate-ribose polymerase (PARP) is an effective therapy against cancers with DNA damage repair (DDR) deficiencies, such as BRCA1 and BRCA2 defects. In preclinical studies, PARP inhibitors demonstrated potential therapeutic value in Ewing sarcoma (ES), though clinical trials with olaparib failed to show significant clinical benefit. While single agent therapy proved inefficacious in the clinical treatment of ES, combination therapies may show anti-tumour activity. A key regulatory event in DNA damage repair is acetylation and deacetylation of histones, controlled by histone acetyltransferases (HATs) and histone deacetylases (HDACs). Increased expression of HDACs have been correlated to more malignant phenotypes in sarcomas and inhibition of HDAC in ES has been shown to be effective in inhibiting tumor growth. HDAC inhibition combined with PARP inhibition has been shown to sensitize cells to treatment in vitro, however clinically, combination therapies often require sequential administration due to different pharmacokinetic profiles and overlapping toxicities, severely limiting clinical utility. Here, we evaluate the activity and efficacy of a novel bifunctional small-molecule compound designed to have both PARP and HDAC inhibiting activity. Methods: PARP1 activity was measured using the Trevigen Universal Colorimetric PARP Assay Kit and PARP2 activity was measured using the BPS Bioscience PARP2 Colorimetric PARP2 Assay Kit. HDAC activity was measured using HeLa nuclear extracts and a fluorogenic peptide-based biochemical assay. Cell survival EC50s were determined using live cell imaging with an Incucyte S3 system and the CellTiter Glo viability assay. Accumulation of phospho-histone H2AX (pH2AX) was detected by western blot using anti-phospho histone H2AX (Ser139) antibody from Cell Signaling Technologies. Results: A representative compound from the kt-3000 series showed potent inhibition of PARP1 and PARP2 with IC50 values in the low nM range, comparable to FDA-approved PARP inhibitors. The compound also showed inhibition of HDAC enzymes with IC50 values in the low µM range, slightly lower than the FDA-approved HDAC inhibitor, vorinostat. Cell survival EC50 values were superior to olaparib in ES cell lines in vitro. Treatment with the kt-3000 compound also resulted in the increased accumulation of pH2AX by western blot and increased S and G2/M cell cycle arrest compared to olaparib. Conclusion: Our kt-3000 compound shows potent inhibition of PARP1, PARP2, and HDAC, as well as induction of DNA damage and cell cycle arrest. Further development of these bifunctional single molecule inhibitors may result in a novel treatment opportunity for Ewing sarcoma. Citation Format: Sarah Truong, Beibei Zhai, Fariba Ghaidi, Louise Ramos, Jay Joshi, Dennis Brown, Neil Sankar, John Langlands, Jeffrey Bacha, Wang Shen, Poul Sorensen, Mads Daugaard. In vitro efficacy of a novel dual PARP-HDAC inhibitor in ewing sarcoma [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr A024.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.318
GPT teacher head0.542
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes2
Has abstractyes

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