CDK4 regulates cancer stemness and is a novel therapeutic target for triple-negative breast cancer
Bibliographic record
Abstract
Triple negative breast cancers exhibit very aggressive features and poor patient outcomes. These tumors are enriched in cancer stem cells and exhibit resistance to most treatments and chemotherapy. In this study, we found the cyclin-dependent kinase (CDK4) to act as a cancer stem cell regulator and novel prognostic marker in triple negative breast cancers. We found CDK4 to be highly expressed in these tumors and its expression to correlate with poor overall and relapse free survival outcomes, high tumor grade and poor prognostic features of triple negative breast cancer patients. Moreover, we found that blocking CDK4 expression or kinase activity, using a pharmacological inhibitor prevented breast cancer stem cell self-renewal. Interestingly, suppression of CDK4 expression or kinase activity reversed the basal-B TNBC mesenchymal phenotype to an epithelial- and luminal-like phenotype which correlates with better clinical prognosis. Finally, blocking CDK4 activity efficiently eliminated both normal and chemotherapy-resistant cancer cells in triple negative breast cancers, highlighting CDK4 as a promising novel therapeutic target for these aggressive breast tumors.
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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) | 0.001 | 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".