Influence of Oxygen on the Radiosensitivity of Human Glioma Cell Lines
Bibliographic record
Abstract
We have investigated the influence of hypoxia on the radiosensitivity of 4 early-passage tumor cell lines that were established from malignant glioma patients at our Institute. These cell lines were M006, M059J (a highly radiosensitive line), M059K (a radioresistant line derived from the same biopsy as M059J), and M010b. The GM637 human fibroblast cell line was used as a normal control. The oxygen enhancement ratios (OERs) for these cell lines, determined using a clonogenic survival assay, were approximately 3.6 (GM637), approximately 3.7 (M006), approximately 2.5 (M010b), approximately 2.1 (M059K), and approximately 3.5 (M059J). The broad range of OERs for these glioma lines was not related to cellular glutathione levels or to differences in intrinsic cellular radiosensitivity. Because studies with rodent cell lines indicate that defects in certain DNA repair genes, including ERCC1, can greatly influence cellular OERs, and because several such repair genes, including ERCC1, localize to a region of chromosome 19q that is close to a common deletion in human glioma, we reasoned that such deletions might contribute to the diverse OERs of these tumor cell lines. However, measurements of ERCC1 protein levels using immunofluorescence staining or Western blotting, of ERCC1 mRNA levels using Northern blotting, and of functional nucleotide excision repair capability using the UV/adenovirus reactivation assay, failed to indicate any deficit in these activities. Thus, although the effect of hypoxia on the radiosensitivity of different human glioma cell lines can vary widely, the mechanism of this effect remains unknown. The potential implications of this finding for radiation therapy, and especially for hypoxia imaging-guided intensity-modulated radiation therapy (IMRT) treatment planning, are discussed.
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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".