THE STABILIZATAION OF C-MYC BY THE NOVEL CELL CYCLE REGULATOR, SPY1, DECREASES EFFICACY OF BREAST CANCER TREATMENTS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Purpose c-Myc is frequently upregulated in breast cancers, however, targeting c-Myc has proven to be a challenge. Targeting of downstream mediators of c-Myc, such as the ‘cyclin-like’ cell cycle regulator Spy1, may be a viable therapeutic option in a subset of breast cancer subtypes. Methods Mouse mammary tumour cells isolated from MMTV-Myc mice and human breast cancer cell lines were used to manipulate Spy1 levels followed by tamoxifen or chemotherapeutic treatment with a variety of endpoints. Patient samples from TNBC patients were obtained and constructed into a TMA and stained for c-Myc and Spy1 protein levels. Results Over time, MMTV-Myc cells show a decreased response to tamoxifen treatment with increasing levels of Spy1 in the tamoxifen-resistant cells. shRNA against Spy1 re-establishes tamoxifen sensitivity. Spy1 was found to be highly elevated in human TNBC cell and patient samples, correlating to c-Myc protein levels. c-Myc was found to be stabilized by Spy1 and knocking down Spy1 in TNBC cells shows a significant increase in response to chemotherapy treatments. Conclusions Understanding the interplay between protein expression level and response to treatment is a critical factor in developing novel treatment options for breast cancer patients. These data have shown a connection between Spy1 and c-Myc protein levels in more aggressive breast cancer cells and patient samples. Furthermore, targeting c-Myc has proven difficult, these data suggest targeting Spy1 even when c-Myc is elevated can confer an advantage to current chemotherapies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it