Ribavirin as an anti-cancer therapy: acute myeloid leukemia and beyond?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ribavirin was discovered nearly 40 years ago as a broad-spectrum antiviral drug. Recent data suggest that ribavirin may also be an effective cancer therapy. In this case, ribavirin targets an oncogene, the eukaryotic translation initiation factor eIF4E, elevated in approximately 30% of cancers including many leukemias and lymphomas. Specifically, ribavirin impedes eIF4E mediated oncogenic transformation by acting as an inhibitor of eIF4E. In a phase II clinical trial, ribavirin treatment led to substantial clinical benefit in patients with poor-prognosis acute myeloid leukemia (AML). Here molecular targeting of eIF4E correlated with clinical response. Ribavirin also targets a key enzyme in the guanosine biosynthetic pathway, inosine monophosphate dehydrogenase (IMPDH), and also modulates immunity. Parallels with known antiviral mechanisms could be informative; however, after 40 years, these are not entirely clear. The antiviral effects of ribavirin appear cell-type specific. This variation likely arises for many reasons, including cell specific variations in ribavirin metabolism as well as virus specific factors. Thus, it seems that the mechanisms for ribavirin action in cancer therapy may also vary in terms of the cancer/tissue under study. Here we review the anticancer activities of ribavirin and discuss the possible utility of incorporating ribavirin into diverse cancer therapeutic regimens.
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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) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.001 |
| 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 it