Immunotherapy in new pre-clinical models of HPV-associated oral cancers
Bibliographic record
Abstract
Cervical, anal, penile and a sub-set of head and neck (HN) tumors are critical health problems caused by high risk Human Papilloma Viruses (HPVs), like HPV type 16. No specific/effective pharmacological treatments exist. A valid preventive vaccination as well as the immunotherapy of persistent infections, pre-cancerous lesions or early-stage cancers could drive the HPV disease burden down. These treatments might be featured through low-cost platforms like those based on DNA and plant biotechnologies to produce tailored and enhanced formulations taking profit from the use of plants as bio-factories and as a source of immune-stimulators. Finally, and regardless of the formulation type, pre-clinical tests and models are crucial to foresee efficacy of immunotherapy before clinical trials. In this study, we created an orthotopic mouse model for HPV-related oral tumors, a subset of HN tumors for which no models have been generated before. The model was obtained by inducing the stable expression of the HPV16 E7 protein into the mouse oral squamous cell carcinoma (OSCC) AT-84 (AT-84 E7). The AT-84 E7 cells were injected into the mouth pavement of C3H mice via an extra-oral route to obtain orthotopic tumors. The model turned out to mimic the natural history of the human HPV oral cancer. From AT-84 E7, through engineering to express luciferase, the bioluminescent AT-84 E7-Luc cells were obtained for a fast and easy monitoring by imaging. The AT-84 E7 and the AT-84 E7-Luc tumors were used to test the efficacy of E7-based therapeutic vaccines that we had previously generated and that had been already proven to be active in mice against non-orthotopic E7-expressing tumors (TC-1 cells). In particular, we used genetic and plant-derived formulations based on attenuated HPV16 E7 variants either fused to plant virus genes with immunological activity or produced by tobacco plants. Mice were monitored by imaging allowing to test the size reduction of the mouth implanted experimental tumors in function of the different regimens used. The proposed tumor model is easy to handle and to reproduce and it is efficacious in monitoring immunotherapy. Furthermore, it is expected to be more predictive of clinical outcome of therapeutic vaccines than non-orthotopic models that are currently used. Finally, imaging offers unique opportunities to predict formulation efficacy through measuring tumor growth in vivo.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.017 | 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".