Vascular endothelial growth factor expression is independent of hypoxia in human malignant glioma spheroids and tumours
Bibliographic record
Abstract
We recently showed that severe hypoxia was not universally present adjacent to necrosis in human glioma xenografts and spheroids established from the M059K, M006, M006X, M006XLo and M010b cell lines. Using these glioma models, we wished to test whether oxygen serves as a regulator of cellular VEGF expression in situ. In situ hybridization (ISH) and immunohistochemistry (IHC) were used to detect vascular endothelial growth factor (VEGF) mRNA and protein expression in sections of glioma xenografts and spheroids in which hypoxic regions and regions with well-oxygenated necrosis were identified on contiguous sections by use of the hypoxia-specific marker, 3H-misonidazole. Independent validation of the presence of radiobiologically hypoxic cells in M006 xenografts was undertaken using the comet assay. Northern blotting analyses of monolayer cells demonstrated significant up-regulation of VEGF mRNA in the M006X line at oxygen concentrations of 6% and below. ISH analysis of VEGF mRNA showed unexpectedly strong staining for VEGF mRNA across the entire viable rim of M006X and M006XLo glioma spheroids. Similarly, in virtually all xenograft tumours of the M059K, M006 and M010b lines, VEGF ISH showed similar staining across all regions of healthy cells up to the border of necrosis. Only in one M006X tumour was there a suggestion of increased VEGF expression in cells adjacent to necrosis. IHC for VEGF showed good concordance with the ISH results. IHC analysis of the VEGF receptor flt-1 showed strong tumour cell staining in M006XLo glioma cells. In human glioma spheroids and xenograft tumours, regions of severe hypoxia do not correspond to areas of up-regulated VEGF expression; in fact, VEGF expression is quite uniform. Furthermore, this and our previous study demonstrate that levels of VEGF expression vary among sublines (M006, M006X and M006XLo) derived from a single human glioma specimen.
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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) | 0.001 | 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".