Reduced proliferation and enhanced migration: Two sides of the same coin? Molecular mechanisms of metastatic progression by YB-1
Bibliographic record
Abstract
Hyperproliferation induced by various oncogenic proteins, including activated Ras, is the most prominent and well characterized feature of cancerous cells. This property has been exploited in the development of the most successful anti-cancer treatments to target rapidly dividing cells. Here we argue that hyperproliferation may in fact be detrimental to survival during particular stages of cancer progression such as dissemination from primary tumor and establishing metastatic outgrowth. Our recent work has demonstrated that elevation of YB-1 protein levels, which is frequently observed in human cancers, is associated with reduced proliferation rates in disseminated mesenchymal-like breast carcinoma cells. In breast cancer cell lines with activated Ras-MAPK signaling, YB-1 inhibited cellular proliferation, while inducing an epithelial-to-mesenchymal transition (EMT). The underlying mechanism involves YB-1-mediated translational repression of pro-growth transcripts and activation of the messages encoding EMT-associated proteins, many of which are also known to inhibit proliferation. In addition to the lack of epithelial polarity, increased mobility and invasiveness, YB-1-overexpressing cells displayed a remarkable ability to shut down proliferation and survive in anchorage-independent conditions. These findings support the view that while an increase in proliferation is important for the initiation and maintenance of primary tumors, growth inhibition could ultimately be crucial for survival of carcinoma cells in the circulation and secondary organs, thereby leading to the development of a more malignant phenotype.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".