Characterization of the Tumor-Microenvironment in Patient-Derived Cervix Xenografts (OCICx)
Bibliographic record
Abstract
RATIONALE: The tumor microenvironment (TME) is heterogeneous including both malignant and host cell components as well as regions of hypoxia, elevated interstitial fluid pressure (IFP) and poor nutrient supply. The quantitative extent to which the microenvironmental properties of primary tumors are recapitulated in xenograft models is not well characterized. METHODS: Xenografts were generated by implanting tumor biopsies directly into the cervix of mice to create a panel of orthotopically-passaged xenografts (OCICx). Tumors were grown to ~1 cm (diameter) and IFP measurements recorded prior to sacrifice. Enlarged para-aortic lymph nodes (>1-2 mm) were excised for histologic confirmation of metastatic disease. Quantitative histological analysis was used to evaluate hypoxia, proliferation, lymphatic and blood vessels in the epithelial and stromal regions of the xenografts and original patient tumour. RESULTS: IFP and nodal disease were not correlated with tumor engraftment. IFP measurements in the xenografts were generally lower than those in the patient's tumor. Lymphatic metastasis increased with passage number as did levels of hypoxia in the epithelial component of the xenografts. The blood vessel density in the stromal component of the xenografts increased in parallel. When all the markers were compared between the biopsy and the respective 3rd generation xenograft 10 of 11 tumors showed a good correlation. CONCLUSIONS: This ongoing study provides characterization about tumoral and stromal heterogeneity in a unique orthotopic xenograft model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".