Reversible p53 inhibition prevents cisplatin ototoxicity without blocking chemotherapeutic efficacy
Bibliographic record
Abstract
Cisplatin is a widely used chemotherapy drug, despite its significant ototoxic side effects. To date, the mechanism of cisplatin‐induced ototoxicity remains unclear, and hearing preservation during cisplatin‐based chemotherapy in patients is lacking. We found activation of the ATM‐Chk2‐p53 pathway to be a major determinant of cisplatin ototoxicity. However, prevention of cisplatin‐induced ototoxicity is hampered by opposite effects of ATM activation upon sensory hair cells: promoting both outer hair cell death and inner hair cell survival. Encouragingly, however, genetic or pharmacological ablation of p53 substantially attenuated cochlear cell apoptosis, thus preserving hearing. Importantly, systemic administration of a p53 inhibitor in mice bearing patient‐derived triple‐negative breast cancer protected auditory function, without compromising the anti‐tumor efficacy of cisplatin. Altogether, these findings highlight a novel and effective strategy for hearing protection in cisplatin‐based chemotherapy. The normal tissue injuries induced by the chemotherapeutic drug cisplatin remain a major clinical problem. Here, PFT‐α is shown to protect hearing without compromising the chemotherapeutic efficacy of cisplatin, and even sensitizes TP53‐mutant breast tumors to cisplatin. The normal tissue injuries induced by the chemotherapeutic drug cisplatin remain a major clinical problem. Here, PFT‐α is shown to protect hearing without compromising the chemotherapeutic efficacy of cisplatin and even sensitizes TP53‐mutant breast tumors to cisplatin.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".