Differential Regulation of Cancer Progression by CDK4/6 Plays a Central Role in DNA Replication and Repair Pathways
Bibliographic record
Abstract
Abstract Although the cyclin-dependent kinases CDK4 and CDK6 play fundamental roles in cancer, the specific pathways and downstream targets by which they exert their tumorigenic effects remain elusive. In this study, we uncover distinct and novel functions for these kinases in regulating tumor formation and metastatic colonization in various solid tumors, including those of the breast, prostate, and pancreas. Combining in vivo CRISPR-based CDK4 and CDK6 gene editing with pharmacologic inhibition approaches in orthotopic transplantation and patient-derived xenograft preclinical models, we defined clear functions for CDK4 and CDK6 in facilitating tumor growth and progression in metastatic cancers. Transcriptomic profiling of CDK4/6 CRISPR knockouts in breast cancer revealed these two kinases to regulate cancer progression through distinct mechanisms. CDK4 regulated prometastatic inflammatory cytokine signaling, whereas CDK6 mainly controlled DNA replication and repair processes. Inhibition of CDK6 but not CDK4 resulted in defective DNA repair and increased DNA damage. Multiple CDK6 DNA replication/repair genes were not only associated with cancer subtype, grades, and poor clinical outcomes, but also facilitated primary tumor growth and metastasis in vivo. CRISPR-based genomic deletion of CDK6 efficiently blocked tumor formation and progression in preestablished cell- and patient-derived xenograft preclinical models of breast cancer, providing a potential novel targeted therapy for these deadly tumors. Significance: In-depth transcriptomic analysis identifies cyclin-dependent kinases CDK4 and CDK6 as regulators of metastasis through distinct signaling pathways and reveals the DNA replication/repair pathway as central in promoting these effects.
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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 | 0.001 | 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".