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Abstract P081: <i>In vitro</i> activity and efficacy of novel dual PARP-HDAC inhibitors

2021· article· en· W4200167174 on OpenAlexaff
Sarah Truong, Fariba Ghaidi, Louise Ramos, Jay Joshi, Dennis Brown, Neil Sankar, John Langlands, Jeffrey Bacha, Shen Wang, Mads Daugaard

Bibliographic record

VenueMolecular Cancer Therapeutics · 2021
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsAcuitas Therapeutics (Canada)
Fundersnot available
KeywordsPARP inhibitorPoly ADP ribose polymeraseDNA repairCancer researchMolecular biologySynthetic lethalityChemistryHistoneBiologyPolymeraseDNABiochemistry

Abstract

fetched live from OpenAlex

Abstract Introduction: Inhibition of poly adenosine diphosphate-ribose polymerase (PARP) is an effective treatment strategy against tumors with homologous recombination (HR) DNA repair deficiencies. Combination treatments utilizing PARP inhibitors (PARPi) in concert with inhibitors of key DNA repair or PARPi-resistance pathways, may expand the utility of PARPi beyond cancers harboring germ-line HR deficiencies. Acetylation and deacetylation of histones is an important regulatory event in the DNA damage response. Combining histone deacetylation inhibitors (HDACi) and PARPi have sensitized PARPi-resistant cells to treatment; however, combination regimens often require sequential administration to manage overlapping toxicities and accommodate diverse pharmacokinetics, constituting a significant limitation of these strategies in a clinical setting. Here, we test the activity of kt-3000 series, a novel bi-functional class of small molecules with dual PARP and HDAC inhibitor activity in HR-proficient cancer cells where PARPi have historically lacked single-agent activity. Methods: PARP enzyme activity was measured using the Trevigen Universal Colorimetric PARP Assay Kit. HDAC activity was measured using nuclear extracts of treated cells and the HDAC Fluorometric Activity Assay Kit from Cayman Chemical, as per the manufacturer’s protocol. PARP activity was measured by fluorescence in C41 cells following compound treatment for 2 hours and PARP-activation with 1M H2O2 by staining cells with an anti-PARP Ab followed by a FITC-coupled secondary antibodies. Cell survival EC50 values were obtained by treating cells with a range of inhibitor concentrations, then quantifying cell confluency after 72-hours of treatment based on images taken with an Incucyte S3 system. Results: kt-3000 series compounds are potent inhibitors of PARP and HDAC with IC50 values for PARP enzyme activity in the low nM range, comparable to those of FDA-approved PARP inhibitors (olaparib, rucaparib, niraparib, and talazoparib) and IC50 values for the inhibition of HDAC activity comparable to FDA-approved HDAC inhibitors (panabinostat, belinostat, and vorinostat). Fluorescent assays of PARP activity in C41 cells also resulted in IC50 values in the nM range and cell survival EC50 values of the dual inhibitors are comparable to FDA-approved PARP inhibitors alone and in similar range with FDA-approved HDAC inhibitors alone. Conclusion: Our novel dual PARP-HDAC inhibitors show potent inhibition of PARP activity in vitro comparable to FDA-approved PARP inhibitors and also show potent inhibition of HDAC activity. The potency and activity of kt-3000 series compounds exhibit potential superiority to FDA-approved PARP inhibitors and HDAC inhibitors, in formulation as a single molecule. Development of these multi-target inhibitors will target unmet medical needs in the treatment of HR-proficient cancer types with dysregulation of histone deacetylation. Citation Format: Sarah Truong, Fariba Ghaidi, Louise Ramos, Jay Joshi, Dennis Brown, Neil Sankar, John Langlands, Jeffrey Bacha, Wang Shen, Mads Daugaard. In vitro activity and efficacy of novel dual PARP-HDAC inhibitors [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P081.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.037
GPT teacher head0.327
Teacher spread0.290 · 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 teacher head, not a consensus.

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

Citations1
Published2021
Admission routes1
Has abstractyes

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