A synthetically lethal nanomedicine delivering novel inhibitors of polynucleotide kinase 3′-phosphatase (PNKP) for targeted therapy of PTEN-deficient colorectal cancer
Bibliographic record
Abstract
Phosphatase and TENsin homolog deleted on chromosome 10 (PTEN) is a major tumor-suppressor protein that is lost in up to 75% of aggressive colorectal cancers (CRC). The co-depletion of PTEN and a DNA repair protein, polynucleotide kinase 3′-phosphatase (PNKP), has been shown to lead to synthetic lethality in several cancer types including CRC. This finding inspired the development of novel PNKP inhibitors as potential new drugs against PTEN-deficient CRC. Here, we report on the in vitro and in vivo evaluation of a nano-encapsulated potent, but poorly water-soluble lead PNKP inhibitor, A83B4C63, as a new targeted therapeutic for PTEN-deficient CRC. Our data confirmed the binding of A83B4C63, as free or nanoparticle (NP) formulation, to intracellular PNKP using the cellular thermal shift assay (CETSA), in vitro and in vivo. Dose escalating toxicity studies in healthy CD-1 mice, based on measurement of animal weight changes and biochemical blood analysis, revealed the safety of both free and nano-encapsulated A83B4C63, at assessed doses of ≤50 mg/kg. Nano-carriers of A83B4C63 effectively inhibited the growth of HCT116/PTEN−/− xenografts in NIH-III nude mice following intravenous (IV) administration, but not that of wild-type HCT116/PTEN+/+ xenografts. This was in contrast to IV administration of A83B4C63 solubilized with the aid of Cremophor EL: Ethanol (CE), which led to similar tumor growth to that of formulation excipients (NP or CE without drug) or 5% dextrose. This observation was attributed to the higher levels of A83B4C63 delivered to tumor tissue by its NP formulation. Our data provide evidence for the success of NPs of A83B4C63, as novel synthetically lethal nano-therapeutics in the treatment of PTEN-deficient CRC. This research also highlights the potential of successful application of nanomedicine in the drug development process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".