Different Mechanisms in Doxorubicin-Induced Neurotoxicity: Impact of BRCA Mutations
Bibliographic record
Abstract
The genotoxic drug doxorubicin (Dox) remains one of the most powerful chemotherapeutic options available for a wide range of cancers including breast, ovarian, and other cancers. However, emerging evidence links Dox treatment with chemotherapy-induced cognitive impairment, a condition that is popularly referred to as Dox-induced neurotoxicity or "chemobrain", which limits the use of the drug. There are no specific treatments for Dox-induced neurotoxicity, only interventions to mitigate the neurotoxic effects of the drug. Accumulating evidence indicates that DNA damage, oxidative stress, dysregulation of autophagy and neurogenesis, inflammation, and apoptosis play central roles in Dox-induced neurotoxicity. Additionally, germline mutations in the tumour suppressor genes breast cancer susceptibility genes 1 and 2 (BRCA1 and BRCA2) increase the risk of breast, ovarian, and related cancers. BRCA1 and BRCA2 are distinct proteins that play crucial, unique roles in homologous recombination-mediated double-stranded break repair. Furthermore, BRCA1 and 2 mitigate oxidative stress in both neural cells and brain microvascular endothelial cells, which suggests that they have a critical role as regulators of pathways central to the development of Dox-induced neurotoxicity. Despite research on the effects of Dox on cognitive function, there is a gap in knowledge about the role of BRCA1 and BRCA2 in Dox-induced neurotoxicity. In this review, we discuss existing findings about the role of different mechanisms and the role of BRCA1 and BRCA2 in Dox-induced neurotoxicity, along with future perspectives.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".