Activated ras regulates the proliferation/apoptosis balance and early survival of developing micrometastases.
Bibliographic record
Abstract
Mutant, activated ras oncogenes are found in many human cancers. Experimental studies have shown that Ras enhances metastatic ability in several cell types. However, the biological mechanisms by which Ras contributes to metastasis remain poorly understood. Our goal was to determine which steps in the formation of macroscopic metastases were affected by Ras. Green fluorescent protein-transfected NIH 3T3 and T24 H-ras-transformed (PAP2) fibroblasts were injected via mesenteric vein to target mouse liver. The proportion of cells that survived at each step of the metastatic process (at 60 min to 14 days after injection) were quantified. We found that Ras did not enhance the ability of cells to extravasate from liver sinusoids or to survive as solitary undivided cells in liver tissue. Furthermore, we found that a subset of cells from both cell lines initiated growth to form micrometastases by day 3. Only micrometastases formed by ras-transformed cells, however, persisted to form macroscopic metastases by day 14, whereas most NIH 3T3 micrometastases disappeared. We investigated this difference in maintenance of developing metastases by quantifying apoptosis and proliferation within the micrometastases. PAP2 metastases had a significantly higher proportion of proliferating cells as compared with apoptosing cells, whereas NIH 3T3 metastases had low proliferation and high apoptosis levels. Whereas the ability of Ras to induce vascular endothelial growth factor has suggested one way that Ras might affect metastatic ability (through induction of angiogenesis), our study provides in vivo evidence for a direct role for Ras in maintenance of metastatic growth via a shift in proliferation/apoptosis balance to favor metastatic growth.
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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) | 0.001 | 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".