The Chicken Chorioallantoic Membrane Tumor Assay as a Relevant In Vivo Model to Study the Impact of Hypoxia on Tumor Progression and Metastasis
Bibliographic record
Abstract
Hypoxia in the tumor microenvironment is a negative prognostic factor associated with tumor progression and metastasis, and therefore represents an attractive therapeutic target for anti-tumor therapy. To test the effectiveness of novel hypoxia-targeting drugs, appropriate preclinical models that recreate tumor hypoxia are essential. The chicken ChorioAllantoic Membrane (CAM) assay is increasingly used as a rapid cost-effective in vivo drug-testing platform that recapitulates many aspects of human cancers. However, it remains to be determined whether this model recreates the hypoxic microenvironment of solid tumors. To detect hypoxia in the CAM model, the hypoxic marker pimonidazole was injected into the vasculature of tumor-bearing CAM, and hypoxia-dependent gene expression was analyzed. We observed that the CAM model effectively supports the development of hypoxic zones in a variety of human tumor cell line-derived and patient's tumor fragment-derived xenografts. The treatment of both patient and cell line-derived CAM xenografts with modulators of angiogenesis significantly altered the formation of hypoxic zones within the xenografts. Furthermore, the changes in hypoxia translated into modulated levels of chick liver metastasis as measured by Alu-based assay. These findings demonstrate that the CAM xenograft model is a valuable in vivo platform for studying hypoxia that could facilitate the identification and testing of drugs targeting this tumor microenvironment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".