Restoration of chemosensitivity to drug resistant breast cancer cells through peptide activation of Anaphase Promoting Complex
Bibliographic record
Abstract
Abstract The primary care of cancer patients involves improving their outcomes, resulting in longer remission periods and, in some cases, cures. However, many cancers eventually return to a state that is too resistant to therapy. Once cancers become multidrug resistant (MDR) and aggressive, palliative care or more toxic therapies are the remaining options for this growing population of cancer survivors. New approaches to resensitize MDR malignancies to nontoxic therapies are critically important to improve patient outcomes. Previously, we reported that activation of the Anaphase Promoting Complex (APC) resensitized recurrent MDR malignancies in vitro , independent of cancer type, chemotherapy exposure, or species. Specifically, the indirect APC chemical activator, M2I-1, resensitized MDR canine lymphoma cells and human breast cancer cells to first-line therapy. In this study, we applied small peptides that were discovered via a yeast 2-hybrid screen for peptides that interact with the Apc10 APC subunit as direct activators of the APC. The tested peptides indeed increased APC activity, as indicated by reduced APC protein substrate levels, increased (activating) phosphorylation of APC1 S355 , and increased E3 ligase activity, as determined via in vitro ubiquitination assays. One peptide significantly restored chemosensitivity to the MDA-MB-231 breast cancer cell line in vitro and in an in vivo mouse model. The peptides induced mitotic catastrophe, increased DNA damage, and activated apoptotic pathways. Taken together, our results demonstrate that direct activation of the APC via a small APC-activating peptide has anticancer effects both in vitro and in vivo in MDR breast cancer cells, suggesting the potential for targeted treatment to improve patient outcomes.
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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) | 0.002 | 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".