Phosphorylated Histone H2AX in Spheroids, Tumors, and Tissues of Mice Exposed to Etoposide and 3-Amino-1,2,4-Benzotriazine-1,3-Dioxide
Bibliographic record
Abstract
We reported recently that exposure of hamster V79 fibroblasts to 6 drugs that varied in their ability to produce DNA double-strand breaks stimulated formation of phosphorylated histone H2AX (serine 139 phosphorylated histone H2AX; gammaH2AX). Using flow cytometry to analyze gammaH2AX antibody-stained cells 1 h after a 30-min drug treatment, the fraction of cells that showed the control levels of gammaH2AX correlated well with the fraction of cells that survived to form colonies. This observation is now extended to V79 and SiHa human cervical carcinoma cells grown as multicell spheroids and SiHa xenografts and SCCVII tumors in mice. Animals were injected with etoposide, a topoisomerase-II inhibitor that targets proliferating cells or 3-amino-1,2,4-benzotriazine-1,3-dioxide (tirapazamine), a bioreductive cytotoxin that targets hypoxic cells. For spheroids, gammaH2AX intensity predicted clonogenic cell survival for cells recovered 90 min after drug injection, regardless of position of the cells within the spheroid. Similar results were obtained for etoposide in tumors; however, the gammaH2AX signal for tirapazamine was smaller than expected for the observed amount of cell killing. Frozen sections of tumors confirmed the greater intensity of gammaH2AX staining in cells close to blood vessels of tumors soon after treatment with etoposide and the opposite pattern for tumors exposed to tirapazamine. Analysis of cells or frozen sections from mouse spleen and kidney suggests that information can also be obtained on initial damage in normal tissues. These results support the possibility of using gammaH2AX antibody staining as a method to aid in prediction of tumor and normal tissue response to treatment.
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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 | 0.001 |
| 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".