A Distinct Reactive Oxygen Species Profile Confers Chemoresistance in Glioma-Propagating Cells and Associates with Patient Survival Outcome
Bibliographic record
Abstract
AIMS: We explore the role of an elevated O2(-):H2O2 ratio as a prosurvival signal in glioma-propagating cells (GPCs). We hypothesize that depleting this ratio sensitizes GPCs to apoptotic triggers. RESULTS: We observed that an elevated O2(-):H2O2 ratio conferred enhanced resistance in GPCs, and depletion of this ratio by pharmacological and genetic methods sensitized cells to apoptotic triggers. We established the reactive oxygen species (ROS) Index as a quantitative measure of a normalized O2(-):H2O2 ratio and determined its utility in predicting chemosensitivity. Importantly, mice implanted with GPCs of a reduced ROS Index demonstrated extended survival. Analysis of tumor sections revealed effective targeting of complementarity determinant 133 (CD133)- and nestin-expressing neural precursors. Further, we established the Connectivity Map to interrogate a gene signature derived from a varied ROS Index for the patterns of association with individual patient gene expression in four clinical databases. We showed that patients with a reduced ROS Index demonstrate better survival. These data provide clinical evidence for the viability of our O2(-):H2O2-mediated chemosensitivity profiles. INNOVATION AND CONCLUSION: Gliomas are notoriously recurrent and highly infiltrative, and have been shown to arise from stem-like cells. We implicate an elevated O2(-):H2O2 ratio as a prosurvival signal in GPC self-renewal and proliferation. The ROS Index provides quantification of O2(-):H2O2-mediated chemosensitivity, an advancement in a previously qualitative field. Intriguingly, glioma patients with a reduced ROS Index correlate with longer survival and the Proneural molecular classification, a feature frequently associated with tumors of better prognosis. These data emphasize the feasibility of manipulating the O2(-):H2O2 ratio as a therapeutic strategy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".