Reovirus in cancer therapy: an evidence-based review
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
Reovirus, a double-stranded ribonucleic acid virus and benign human pathogen, preferentially infects and kills cancer cells in its unmodified form, and is one of the leading oncolytic viruses currently undergoing clinical trials internationally. With 32 clinical trials completed or ongoing thus far, reovirus has demonstrated clinical therapeutic applicability against a multitude of cancers, including but not limited to breast cancer, prostate cancer, pancreatic cancer, malignant gliomas, advanced head and neck cancers, and metastatic ovarian cancers. Phase I trials have demonstrated that reovirus is safe to use via both intralesional/intratumoral and systemic routes of administration, with the most common adverse reactions being grade I/II toxicities, such as flu-like illness (fatigue, nausea, vomiting, headache, fever/chills, dizziness), diarrhea, and lymphopenia. In subsequent Phase II trials, reovirus administration was demonstrated to successfully decrease tumor size and promote tumor necrosis, thereby complementing compelling preclinical evidence of tumor destruction by the virus. Importantly, reovirus has been shown to be effective as a monotherapy, as well as in combination with other anticancer options, including radiation and chemotherapeutic agents, such as gemcitabine, docetaxel, paclitaxel, and carboplatin. Of note, the first Phase III clinical trial using reovirus in combination with paclitaxel and carboplatin for the treatment of head and neck cancers is under way. Based on the evidence from clinical trials, we comprehensively review the use of reovirus as an anticancer agent, acknowledge key obstacles, and suggest future directions to ultimately potentiate the efficacy of reovirus oncotherapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it