OC-0055 Zebrafish model to study the use of nanoparticles as a radiosensitizer in low Z target beams
Bibliographic record
Abstract
Several clinical studies have shown the possibilities to give a higher dose to certain hypothetically more radioresistant tumour sub-volumes, typically with high accumulation of FDG or a hypoxia tracer.We have tested the therapeutic efficacy of dose-painting (DP) strategies, i.e. targeted dose escalation and dose redistribution, in a rat syngeneic rhabdomyosarcoma model based on FDG uptake [1].Our data indicate that, while dose escalation to high FDG uptake sub-volume was not superior to the same dose increase in low FDG uptake areas, dose redistribution was even detrimental, consistent with the hypothesis that tumor response is dependent on the minimum intratumoral dose.Interestingly, in the same tumour model dose escalation to the hypoxic sub-volume, as determined by the highest uptake of HX4 hypoxia tracer, resulted in worse tumour response than the same dose increment to the non-hypoxic sub-volume [2].This data suggests that dose to the tumour bulk should be sufficient to inactivate non-hypoxic cells.It might be difficult to achieve clinically sufficient dose escalation to eradicate tumour cells in hypoxic tumor subvolume.Therefore, we moved beyond the traditional DP approaches combining hypoxia-targeted drugs with inverse dose-painting of hypoxic sub-volume and thus offering, in our view, more efficient utilization of radiation, i.e. radiation boost to non-hypoxic tumour areas with simultaneous inactivation of hypoxic tumour cells by a HAP.Indeed, our results support targeted dose escalation to non-hypoxic sub-volume with no/low activity of HAPs.This strategy applies on average a lower radiation dose and is as effective as uniform dose escalation to the entire tumour.Routine implementation particularly of hypoxia PET imaging in the clinic is problematic because it is expensive, labor intensive, not attractive for the patient, or even not accessible.Therefore, partial non-targeted tumour irradiation with high dose in combination with immunotherapy might be a new alternative approach to dose-painting, which is currently being tested in our laboratory.It is expected that partial tumour irradiation enables delivery of high doses to tumor sub-volumes reducing normal tissue injury, causes less total damage to intratumoral vasculature permitting immune cells infiltration and provides stronger induction of immunogenic cell death releasing antigens and stimulants to immune system, while immunotherapy boosts antitumour immune response with systemic therapeutic potential.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".