Targeting homologous recombination using imatinib results in enhanced tumor cell chemosensitivity and radiosensitivity
Bibliographic record
Abstract
RAD51 is a key protein in the homologous recombination (HR) pathway of DNA double-strand break repair, and HR represents a novel target for cancer therapy. Because imatinib (Gleevec) has been reported to reduce RAD51 protein levels, we tested the clonogenic survival for RT112, H1299, PANC1, and PC3 tumor cell lines of varying p53 status and normal GM05757 normal fibroblasts after exposure to single agent imatinib (0-20 micromol/L; 0-72 hours). We also combined imatinib with DNA damaging agents that are toxic to RAD51-deficient cells, including ionizing radiation, gemcitabine, and mitomycin C. We observed decreased nuclear expression and chromatin binding of RAD51 protein following imatinib treatment. Imatinib also resulted in decreased error-free HR as determined by a flow cytometry-based integrated direct repeat-green fusion protein reporter system; this correlated to reduced RAD51 expression. Clonogenic survival experiments revealed increased cell kill for imatinib-treated cells in combination with ionizing radiation, gemcitabine, and mitomycin C, due in part to mitotic catastrophe. In experiments using imatinib and gemcitabine, tumor cell lines were sensitized to a greater extent than normal fibroblasts. This preservation of the therapeutic ratio was confirmed in vivo using PC3 xenograft growth delay and intestinal crypt cell clonogenic assays. HR inhibition may be an additional mechanism of action for the chemosensitization and radiosensitization of solid tumors with imatinib with preservation of the therapeutic ratio.
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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) | 0.000 | 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 | 0.000 |
| 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".