Synthetic Lethal Targeting of PTEN-Deficient Cancer Cells Using Selective Disruption of Polynucleotide Kinase/Phosphatase
Bibliographic record
Abstract
A recent screen of 6,961 siRNAs to discover possible synthetic lethal partners of the DNA repair protein polynucleotide kinase/phosphatase (PNKP) led to the identification of the potent tumor suppressor phosphatase and tensin homolog deleted on chromosome 10 (PTEN). Here, we have confirmed the PNKP/PTEN synthetic lethal partnership in a variety of different cell lines including the PC3 prostate cancer cell line, which is naturally deficient in PTEN. We provide evidence that codepletion of PTEN and PNKP induces apoptosis. In HCT116 colon cancer cells, the loss of PTEN is accompanied by an increased background level of DNA double-strand breaks, which accumulate in the presence of an inhibitor of PNKP DNA 3'-phosphatase activity. Complementation of PC3 cells with several well-characterized mutated PTEN cDNAs indicated that the critical function of PTEN required to prevent toxicity induced by an inhibitor of PNKP is most likely associated with its cytoplasmic lipid phosphatase activity. Finally, we show that modest inhibition of PNKP in a PTEN knockout background enhances cellular radiosensitivity, suggesting that such a "synthetic sickness" approach involving the combination of PNKP inhibition with radiotherapy may be applicable to PTEN-deficient tumors.
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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) | 0.001 | 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 | 0.001 |
| 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".