The RNA helicase/transcriptional co-regulator, p68 (DDX5), stimulates expression of oncogenic protein kinase, Polo-like kinase-1 (PLK1), and is associated with elevated PLK1 levels in human breast cancers
Bibliographic record
Abstract
p68 (DDX5) acts both as an ATP-dependent RNA helicase and as a transcriptional co-activator of several cancer-associated transcription factors, including the p53 tumor suppressor. p68 is aberrantly expressed in a high proportion of cancers, but the oncogenic drive for, or the consequences of, these expression changes remain unclear. Here we show that elevated p68 expression in a cohort of human breast cancers is associated significantly with elevated levels of the oncogenic protein kinase, Polo-like kinase-1 (PLK1). Patients expressing detectable levels of both p68 and PLK1 have a poor prognosis, but only if they also have mutation in the TP53 gene (encoding p53), suggesting that p68 can regulate PLK1 levels in a manner that is suppressed by p53. In support of this hypothesis, we show that p68 stimulates expression from the PLK1 promoter, and that silencing of endogenous p68 expression downregulates endogenous PLK1 gene expression. In the absence of functional p53, p68 stimulates the expression of PLK1 both at basal levels and in response to the clinically relevant drug, etoposide. In keeping with a role as a transcriptional activator/co-activator, chromatin immuno-precipitation analysis shows that p68 is associated with the PLK1 promoter, irrespective of the p53 status. However, its recruitment is stimulated by etoposide in cells lacking p53, suggesting that p53 can oppose association of p68 with the PLK1 promoter. These data provide a model in which p68 and p53 interplay regulates PLK1 expression, and which describes the behavior of these molecules, and the outcome of their interaction, in human breast cancer.
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.
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".