In vitro screen of a small molecule inhibitor drug library identifies multiple compounds that synergize with oncolytic myxoma virus against human brain tumor-initiating cells
Bibliographic record
Abstract
BACKGROUND: Brain tumor-initiating cells (BTICs) are stem-like cells hypothesized to form a disease reservoir that mediates tumor recurrence in high-grade gliomas. Oncolytic virotherapy uses replication-competent viruses to target and kill malignant cells and has been evaluated in clinic for glioma therapy with limited results. Myxoma virus (MyxV) is a safe and highly effective oncolytic virus (OV) in conventional glioma models but, as seen with other OVs, is only modestly effective for patient-derived BTICs. The objective of this study was to determine whether MyxV treatment against human BTICs could be improved by combining chemotherapeutics and virotherapy. METHODS: A 73-compound library of drug candidates in clinical use or preclinical development was screened to identify compounds that sensitize human BTICs to MyxV treatment in vitro, and synergy was evaluated mathematically in lead compounds using Chou-Talalay analyses. The effects of combination therapy on viral gene expression and viral replication were also assessed. RESULTS: Eleven compounds that enhance MyxV efficacy were identified, and 6 were shown to synergize with the virus using Chou-Talalay analyses. Four of the synergistic compounds were shown to significantly increase viral gene expression, indicating a potential mechanism for synergy. Three highly synergistic compounds (axitinib, a VEGFR inhibitor; rofecoxib, a cyclooxygenase-2 inhibitor; and pemetrexed, a folate anti-metabolite) belong to classes of compounds that have not been previously shown to synergize with oncolytic viruses in vitro. CONCLUSIONS: This study has identified multiple novel drug candidates that synergistically improve MyxV efficacy in a preclinical BTIC glioma model.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".