Comparison between the comet assay and pimonidazole binding for measuring tumour hypoxia
Bibliographic record
Abstract
Pimonidazole is finding increasing use in histochemical analyses of hypoxia in tumours. Whether it can identify every hypoxic cell in a tumour, and whether the usual subjective criteria used to define 'positive' cells are optimal, are less certain. Therefore, our aim was to develop an objective flow cytometry procedure for quantifying pimonidazole binding in tumours, and to validate this method by using a more direct indicator of radiobiologic hypoxia, the comet assay. SCCVII tumours in C3H mice were analysed for pimonidazole binding using flow cytometry and an iterative curve-fitting procedure, and the results were compared to the comet assay for the same cell suspensions. On average, cells defined as anoxic by flow analysis (n = 43 tumours) bound 10.8 +/- 0.95 times more antibody than aerobic cells. In samples containing known mixtures of aerobic and anoxic cells, hypoxic fractions as low as 0.5% could easily be detected. To assess the flow cytometry assay under a wider range of tumour oxygen contents, mice were injected with hydralazine to reduce tumour blood flow, or allowed to breathe various gas mixtures during the 90 min exposure to pimonidazole. Hypoxic fraction estimated by the pimonidazole binding method agreed well with the hypoxic fraction measured using the comet assay in SCCVII tumours (r2 = 0.87, slope = 0.98), with similar results in human U87 glioma cells and SiHa cervical carcinoma xenografts. We therefore conclude that this objective analysis of pimonidazole labelling by flow cytometry gives a convenient and accurate estimate of radiobiological hypoxia. Preliminary analyses of biopsies from 3 patients given 0.5 g m-2 pimonidazole also suggest the suitability of this approach for human tumours.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".