TLR4 downregulation protects against cisplatin-induced ototoxicity in adult and pediatric patients with cancer
Bibliographic record
Abstract
Cisplatin causes permanent hearing loss or cisplatin-induced ototoxicity in over 50% of treated patients with cancer, leading to significant social and functional limitations. Interindividual variability in developing hearing loss suggests the role of genetic predispositions to cisplatin-induced hearing loss. We investigated genetic associations between cisplatin-induced ototoxicity and toll-like receptor 4 (TLR4), an immune receptor known to mediate inflammatory responses to cisplatin. Using a case-control candidate gene approach, we identified 20 single nucleotide polymorphisms at the TLR4 locus with significant protection against ototoxicity in a cohort of 213 adult patients, followed by an independent pediatric patient cohort (n = 357). Combined cohort analysis demonstrated a significant association between cisplatin-induced ototoxicity protection and a single variant in the TLR4 promoter, rs10759932. We showed that rs10759932 downregulated TLR4 expression that is normally induced by cisplatin. This work provides pharmacogenetic and functional evidence to implicate TLR4 with cisplatin-induced hearing loss in patients. SIGNIFICANCE STATEMENT: Adult and pediatric patients carrying toll-like receptor 4 (TLR4) genetic variants were protected against developing cisplatin-induced hearing loss following cisplatin treatment. Important variants in the TLR4 promoter disrupted a drug-gene interaction between cisplatin and TLR4, mirroring the protective effect conferred by genetic inhibition of TLR4. These variants have the potential to improve the prediction of cisplatin toxicity, allowing for more precise chemotherapy treatment.
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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".