Loss of p27kip1 increases genomic instability and induces radio-resistance in luminal breast cancer cells
Bibliographic record
Abstract
Abstract Genomic instability represents a typical feature of aggressive cancers. Normal cells have evolved intricate responses to preserve genomic integrity in response to stress, such as DNA damage induced by γ-irradiation. Cyclin-dependent kinases (CDKs) take crucial part to these safeguard mechanisms, but involvement of CDK-inhibitors, such as p27Kip1, is less clear. We generated immortalized fibroblasts from p27kip1 knock-out (KO) mouse embryos and re-expressed p27kip1 WT, or its mutant forms, to identify the function of different domains. We γ-irradiated fibroblasts and observed that loss of p27Kip1 was associated to accumulation of residual DNA damage, increased number of mitotic aberration and, eventually, to survival advantage. Nuclear localization and cyclin/CDK-binding of p27Kip1 were critical to mediate proper response to DNA damage. In human luminal breast cancer (LBC) p27kip1 is frequently down-modulated and CDKN1B, p27Kip1 gene, sporadically mutated. We recapitulated results obtained in mouse fibroblasts in a LBC cell line genetically manipulated to be KO for CDKN1B gene. Following γ-irradiation, we confirmed that p27kip1 expression was necessary to preserve genomic integrity and to recognize and clear-out aberrant cells. Our study provides important insights into mechanisms underlying radio-resistance and unveils the possibility for novel treatment options exploiting DNA repair defects in LBC.
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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 | 0.001 |
| 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".