Non-malignant and Tumor-derived Cells Differ in Their Requirement for p27Kip1 in Transforming Growth Factor-β-mediated G1 Arrest
Bibliographic record
Abstract
Transforming growth factor beta (TGF-beta) induces G(1) arrest in susceptible cells by multiple mechanisms that inhibit the G(1) cyclin-dependent kinases (Cdks), including Cdk2, Cdk4, and Cdk6. TGF-beta treatment of early passage finite lifespan human mammary epithelial cells (HMECs) led to an accumulation of p27(Kip1) in cyclin E1-Cdk2 complexes and kinase inhibition. The requirement for p27 in the G(1) arrest by TGF-beta was assessed by transfection of antisense p27 (ASp27) oligonucleotides into TGF-beta-treated HMECs. Despite a reduction in total and cyclin E-Cdk2 bound p27 after ASp27 transfection, HMECs remained arrested in the G(1) phase. Maintenance of the G(1) arrest was accompanied by increased association of the Cdk inhibitor p21(WAF-1/Cip-1) and the retinoblastoma family member p130(Rb2) in cyclin E1-Cdk2 complexes along with kinase inhibition. In contrast to the findings in HMECs, p27 was essential for G(1) arrest by TGF-beta in two tumor-derived lines. ASp27 transfection into two TGF-beta-responsive, cancer-derived lines was not associated with increased compensatory binding of p21 and p130 to cyclin E1-Cdk2, and these cell lines failed to maintain G(1) arrest despite the continued presence of TGF-beta. Progressive cell cycle deregulation leading to impaired checkpoint controls during malignant tumor progression may alter the role of p27 from a redundant to an essential inhibitor of G(1)-to-S phase progression.
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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 | 0.001 |
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".