Investigation of effects of CFI-400945 and ionizing radiation on DNA damage response in triple-negative breast cancer
Bibliographic record
Abstract
Breast cancer is the leading cause of cancer-related morbidity and mortality in women. Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, often resistant to therapies including radiation treatment (RT). Developing new strategies for TNBC treatment is of paramount importance. In our previous studies, we have shown that a novel drug, Polo-like kinase 4 inhibitor CFI-400945, acts synergistically with RT to enhance antiproliferative effects in TNBC. Since one of the main anticancer mechanisms of RT is deoxyribonucleic acid (DNA) damage with ensuing DNA damage response (DDR) activation, in the current study, we aimed to investigate if and how CFI-400945 modulates DDR in response to RT. Using MDA-MB-231 and MDA-MB-468 TNBC cell lines, we investigated the levels and the foci formation of γ-H2AX, Ku70 and Rad51 proteins-the markers of DNA damage, non-homologous end joining (NHEJ) and homologous recombination (HR) repair pathways, respectively. We demonstrate that RT induces sustained DNA damage that is not further meaningfully enhanced or prolonged by CFI-400945. We also observed cell-line-dependent differences in the timing of activation of NHEJ and HR pathways in response to RT, and that CFI-400945 might lead to impeding RT-induced NHEJ pathway activation or result in earlier activation of the HR pathway. Notably, despite activation of the DDR responses, DNA damage persisted for 24 or more hours after RT. While some of these observations were cell-line dependent (emphasizing known molecular heterogeneity of TNBC), we highlight that canonical DDR pathways activity in response to RT might be inefficient and modulated by drugs, such as CFI-400945-a cancer cell vulnerability that warrants further investigations for better understanding the biology of TNBC, its responses to treatment and novel drug development.
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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".