Effect of radiation on cell proliferation and tumor hypoxia in HPV-positive head and neck cancer in vivo models.
Bibliographic record
Abstract
BACKGROUND/AIM: Human papilloma virus-associated head and neck squamous cell carcinomas (HNSCC) represent a distinct subgroup of HNSCC characterized by a favorable prognosis and a distinct molecular biology. There is a range of unresolved questions regarding the different biology and clinical outcome of HPV-positive HNSCC. The purpose of the present project was to obtain insight into the biology of treatment responsiveness of HPV-related HNSCC. MATERIALS AND METHODS: Tumor xenografts were established from HPV-negative (FaDuDD,) and HPV-positive (UD2 and UMSCC47) HNSCC cell lines. Tumors were treated with 10 Gy or 20 Gy and the effect on the tumor microenvironment was studied at different time points after treatment. Cryosections were imaged for cell proliferation, hypoxia, vessel density and vessel perfusion. RESULTS: In the HPV-positive tumor models the levels of cell proliferation decreased significantly following irradiation. This was not seen in the HPV-negative model (FaDuDD). Furthermore, it was found that the tumor hypoxic fraction decreased over time after treatment in irradiated HPV-positive tumors and not in the HPV-negative tumors. CONCLUSION: The radiosensitivity previously observed in vitro could be applied in vivo in respect to a radiation-induced decrease in proliferating cells. A decreasing hypoxic fraction following irradiation in the HPV-positive tumors could explain the lack of benefit from hypoxic modifiers observed in patients.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".