Chronic hypoxia promotes an aggressive phenotype in rat prostate cancer cells
Bibliographic record
Abstract
In general, tumors cells that are resistant to apoptosis and increase angiogenesis are a result of the hypoxic responses contributing to the malignant phenotype. In this study, we developed a chronic hypoxic cell model (HMLL), by incubating the prostate cancer MatLyLu cells in a hypoxic chamber (1% O(2)) over 3 weeks. Surviving cells were selected through each cell passage and were grown in the hypoxic condition up to 8 weeks. This strategy resulted in survival of only 5% of the cells. The surviving hypoxic cells displayed a greater stimulation on hypoxic adaptive response, including a greater expression of glucose transporter1 (Glut1) and VEGF secretion. In addition, higher invasion activity was observed in the chronic hypoxic HMLL cells as compared to MatLyLu cells exposed to acute hypoxia (1% O(2), 5 h) using the matrigel assay. To further examine the role of HIF-1alpha in tumor progression, both MatLyLu and HMLL cells were transfected with dominant-negative form of HIF-1alpha (DNHIF-1alpha). The Matrigel invasion activity induced by chronic hypoxia was significantly attenuated by DNHIF-1alpha. These results suggest that signaling pathways leading to hypoxic response may be differentially regulated in chronic hypoxic cells and acute hypoxic cells. Chronic hypoxia may play a greater role than acute hypoxia in promoting the aggressive phenotype of tumor cells. This observation mimics the clinical scenario where tumor cells following treatment with radiation are subjected to hypoxic conditions. The reemergence of tumor following treatment usually results in tumor cells that are more aggressive and metastatic.
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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) | 0.002 | 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".