Identification of a Putative Tdp1 Inhibitor (CD00509) by in Vitro and Cell-Based Assays
Bibliographic record
Abstract
Mutations of DNA repair pathways contribute to tumorigenesis and provide a therapeutic target for synthetic lethal interactions in tumor cells. Given that tyrosyl-DNA phosphodiesterase 1 (Tdp1) repairs stalled topoisomerase-I DNA complexes, we hypothesized that inhibition of Tdp1 has synthetic lethal effects in some cancers. To test this, we screened tumor arrays for Tdp1 expression and observed that Tdp1 is expressed in many tumors, including more than 90% of human breast tumors. Subsequent chemical screening identified putative Tdp1 inhibitors. Treatment of control human mammary epithelial cells and the breast cancer cell line MCF-7 with compound CD00509 preferentially sensitized MCF-7 cells to camptothecin and decreased cell proliferation 25% more than camptothecin treatment alone. This suggests that CD00509 specifically targeted Tdp1 in vitro, and CD00509 increased the sensitivity of wild-type murine embryonic fibroblasts (MEFs) to camptothecin to a degree comparable to that of Tdp1(-/-) MEFs. In addition, consistent with poly ADP-ribose polymerase-1 (PARP-1) collaborating with Tdp1 in DNA repair, combined Tdp1 and PARP-1 inhibition was more detrimental to MCF-7 cells than either treatment alone, whereas the combination was not additively harmful to control mammary cells. We conclude that targeting Tdp1 in anticancer therapy preferentially enhances the sensitivity of some breast cancer cells to camptothecin and may be an effective adjuvant for breast cancer therapy.
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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".