The Cyclin-Like Protein Spy1 Mediates Tumourigenic Potential of Triple Negative Breast Cancer
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 Triple negative breast cancer is an aggressive subtype of breast cancer that relies on systemic chemotherapy as its primary means of treatment. Cell cycle regulators are enriched in drug resistant forms of the disease supporting the potential of targeting cell cycle checkpoints as a therapeutic direction to re-sensitize patients to treatment. Spy1 is an atypical cyclin-like protein that can override cell cycle checkpoints and is elevated in triple negative breast cancer. We report for the first time the effects of CRISPR-Cas9 mediated knockout of Spy1 on functional characteristics of triple negative breast cancer cells and perform unbiased analysis of protein expression to assess global changes in expression which correlate with functional changes in cell properties. Loss of Spy1 reduced rates of proliferation, decreased metastatic potential, and led to a reduction in stemness properties of triple negative breast cancer cells. Importantly, knockout of Spy1 delayed tumour onset in an in vivo model and significantly increased response to chemotherapy, pushing cells towards a senescent state. This data reveals that changes in expression of proteins that are not essential for proliferation and only transiently expressed can have significant impacts on cell dynamics and provides support for targeting the Spy1-CDK2 complex as a new therapeutic avenue in triple negative breast cancer. Statement of Significance Targeting the atypical cell cycle regulator Spy1 induces senescence and increases responsiveness of triple negative breast cancer to standard of care chemotherapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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