p66ShcA potentiates the cytotoxic response of triple-negative breast cancers to PARP inhibitors
Bibliographic record
Abstract
Triple-negative breast cancers (TNBCs) lack effective targeted therapies, and cytotoxic chemotherapies remain the standard of care for this subtype. Owing to their increased genomic instability, poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi) are being tested against TNBCs. In particular, clinical trials are now interrogating the efficacy of PARPi combined with chemotherapies. Intriguingly, while response rates are low, cohort of patients do respond to PARPi in combination with chemotherapies. Moreover, recent studies suggest that an increase in levels of ROS may sensitize cells to PARPi. This represents a therapeutic opportunity, as several chemotherapies, including doxorubicin, function in part by producing ROS. We previously demonstrated that the p66ShcA adaptor protein is variably expressed in TNBCs. We now show that, in response to therapy-induced stress, p66ShcA stimulated ROS production, which, in turn, potentiated the synergy of PARPi in combination with doxorubicin in TNBCs. This p66ShcA-induced sensitivity relied on the accumulation of oxidative damage in TNBCs, rather than genomic instability, to potentiate cell death. These findings suggest that increasing the expression of p66ShcA protein levels in TNBCs represents a rational approach to bolster the synergy between PARPi and doxorubicin.
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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".