Rabbit VX2 lung tumor models can form early nodal metastases
Bibliographic record
Abstract
BACKGROUND: The rabbit squamous cell cancer line, VX2, has been used to generate various tumor models in rabbits. It is notable for its ability to generate nodal metastases. However, the timing and extent of nodal metastases vary by primary inoculation site and methodology. The development of metastases specifically in lung cancer models has not been well-described. We sought to characterize the generation of nodal metastases in rabbit transbronchial VX2 lung tumor models. METHODS: Rabbit VX2 lung tumor models were created in the right lung via transbronchial injection and serially imaged by computed tomography. Rabbits (n = 15) were sacrificed from between 5 and 24 days post-inoculation for collection of the ipsilateral and contralateral paratracheal lymph nodes. These underwent histopathological evaluation for metastases using hematoxylin and eosin as well as cytokeratin AE1/AE3 immunohistochemical staining. RESULTS: Nodal metastases were detectable as early as 1 week after inoculation but were more prevalent with longer inoculation; all rabbits at > 2 weeks post-inoculation had nodal metastases. Contralateral metastases were in general seen later than ipsilateral metastases. Lymph node volume did not predict the likelihood of nodal metastases (p = 0.4 and p = 0.07 for ipsilateral and contralateral nodal metastases, respectively), but primary tumor volume was significantly associated with the likelihood of nodal metastases (p = 0.001 and p = 0.005 for ipsilateral and contralateral nodal metastases, respectively). Ipsilateral metastases were detectable at a tumor diameter of 1 cm; contralateral metastases were more variable but in general required a tumor diameter of 2 cm. CONCLUSIONS: Rabbit transbronchial VX2 lung tumor models generate nodal metastases relatively early after inoculation. These results suggest such models may be valuable tools in the investigation of novel therapeutic modalities relevant for the treatment of both early-stage and locally advanced lung cancer.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".