Activation of Src and Src‐associated signaling pathways in relation to hypoxia in human cancer xenograft models
Bibliographic record
Abstract
The hypoxic response in vitro involves alterations in signaling proteins, including Src, STAT3 and AKT that are considered to be broadly pro-survival. The involvement of these signaling proteins in the hypoxic microenviroments that occur in solid tumors was investigated by the use of multicolor fluorescence image analysis to colocalize signaling proteins and regions of hypoxia in 4 human tumor xenografts, pancreatic carcinoma BxPC3 and PANC1 and cervical squamous cell carcinoma ME180 and SiHa. Expression levels of total Src protein (mean intensity x labeled region fraction) were higher in hypoxic regions, identified using the nitroimidazole probe EF5, relative to non-EF5 regions in all 4 tumor models. This was associated with higher levels of phosphorylated (p-) Y419p-Src and its substrate Y861p-FAK in EF5 positive regions of BxPC3 tumors. This effect was also seen in tumor-bearing mice continuously breathing 7% oxygen for 3 hr which markedly increased the extent of EF5 positive labeling. In contrast, the hypoxia treatment resulted in a significant decrease in S727p-STAT3 in BxPC3 xenografts and suggested that STAT3 activity is responsive to acute hypoxia, whereas Src-FAK signaling is associated with predominantly chronically hypoxic EF5 positive regions. Src activity in both hypoxic and nonhypoxic BxPC3 tumor regions was suppressed when mice were treated with the Src inhibitor AZD0530 (25 mg/kg/day, 5 days), suggesting that both hypoxic and normoxic tumor regions are accessible to pharmacological Src inhibition. These results show that signaling pathways are responsive to tumor hypoxia in vivo, although the effects appear to differ between individual tumor types.
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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".