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Synergistic Nanomedicine Delivering Topoisomerase I Toxin (SN-38) and Inhibitors of Polynucleotide Kinase 3′-Phosphatase (PNKP) for Enhanced Treatment of Colorectal Cancer

2024· article· en· W4398777972 on OpenAlexafffund
Sams M. A. Sadat, Mohammad Reza Vakili, Sara Hafeez, Marco Paladino, Dennis G. Hall, Michael Weinfeld, Afsaneh Lavasanifar

Bibliographic record

VenueMolecular Pharmaceutics · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer therapeutics and mechanisms
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchAlberta Cancer FoundationMinistry of Higher Education and Scientific ResearchNanoMedicines Innovation Network
KeywordsCytotoxicityChemistryStereochemistryTopoisomeraseEnzymeMicelleNuclear chemistryBiochemistryOrganic chemistryIn vitro

Abstract

fetched live from OpenAlex

Inhibitors of a DNA repair enzyme known as polynucleotide kinase 3′-phosphatase (PNKP) are expected to show synergistic cytotoxicity in combination with topoisomerase I (TOP1) inhibitors in cancer. In this study, the synergistic cytotoxicity of a novel inhibitor of PNKP, i.e., A83B4C63, with a potent TOP1 inhibitor, i.e., SN-38, against colorectal cancer cells was investigated. Polymeric micelles (PMs) for preferred tumor delivery of A83B4C63, developed through physical encapsulation of this compound in methoxy poly(ethylene oxide)-poly(α-benzyl carboxylate-ε-caprolactone) (mPEO- b -PBCL) micelles, were combined with SN-38 in free or PM form. The PM form of SN-38 was prepared through chemical conjugation of SN-38 to the functional end group of mPEO- b -PBCL and further assembly of mPEO- b -PBCL-SN-38 in water. Moreover, mixed micelles composed of mPEO- b -PBCL and mPEO- b -PBCL-SN-38 were used to co-load A83B4C63 and SN-38 in the same nanoformulation. The loading content (% w/w) of the SN-38 and A83B4C63 to mPEO- b -PBCL in the co-loaded formulation was 7.91 ± 0.66 and 16.13 ± 0.11% (w/w), respectively, compared to 15.67 ± 0.34 (% w/w) and 23.06 ± 0.63 (% w/w) for mPEO- b -PBCL micelles loading individual drugs. Notably, the average diameter of PMs co-encapsulating both SN-38 and A83B4C63 was larger than that of PMs encapsulating either of these compounds alone but still lower than 60 nm. The release of A83B4C63 from PMs co-encapsulating both drugs was 76.36 ± 1.41% within 24 h, which was significantly higher than that of A83B4C63-encapsulated micelles (42.70 ± 0.72%). In contrast, the release of SN-38 from PMs co-encapsulating both drugs was 44.15 ± 2.61% at 24 h, which was significantly lower than that of SN-38-conjugated PMs (74.16 ± 3.65%). Cytotoxicity evaluations by the MTS assay as analyzed by the Combenefit software suggested a clear synergy between PM/A83B4C63 (at a concentration range of 10–40 μM) and free SN-38 (at a concentration range of 0.001–1 μM). The synergistic cytotoxic concentration range for SN-38 was narrowed down to 0.1–1 or 0.01–1 μM when combined with PM/A83B4C63 at 10 or 20–40 μM, respectively. In general, PMs co-encapsulating A83B4C63 and SN-38 at drug concentrations within the synergistic range (10 μM for A83B4C63 and 0.05–1 μM for SN-38) showed slightly less enhancement of SN-38 anticancer activity than a combination of individual micelles, i.e., A83B4C63 PMs + SN-38 PMs at the same molar concentrations. This was attributed to the slower release of SN-38 from the SN-38 and A83B4C63 co-encapsulated PMs compared to PMs only encapsulating SN-38. Cotreatment of cells with TOP1 inhibitors and A83B4C63 formulation enhanced the expression level of γ-HA2X, cleaved PARP, caspase-3, and caspase-7 in most cases. This trend was more consistent and notable for PMs co-encapsulating both A83B4C63 and SN-38. The overall result from the study shows a synergy between PMs of SN-38 and A83B4C63 as a mixture of two PMs for individual drugs or PMs co-encapsulating both drugs.

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 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 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 score0.055
Threshold uncertainty score0.853

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 head0.015
GPT teacher head0.316
Teacher spread0.301 · 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.

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".

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Citations1
Published2024
Admission routes2
Has abstractyes

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