Reovirus as a Viable Therapeutic Option for the Treatment of Multiple Myeloma
Bibliographic record
Abstract
PURPOSE: Despite the recent advances made in the treatment of multiple myeloma, the disease still remains incurable. The oncolytic potential of reovirus has previously been shown and is currently in phase III clinical trials for solid tumors. We tested the hypothesis that reovirus can successfully target human multiple myeloma in vitro, ex vivo, and in vivo without affecting human hematopoietic stem cell (HHSC) re-population/differentiation in a murine model that partially recapitulates human multiple myeloma. EXPERIMENTAL DESIGN: Human myeloma cell lines and ex vivo tumor specimens were exposed to reovirus and oncolysis and mechanisms of cell death were assessed. RPMI 8226(GFP+) cells were injected intravenously to non-obese diabetic/severe combined immune deficient (NOD/SCID) mice and treated with live reovirus (LV) or dead virus (DV). Multiple myeloma disease progression was evaluated via whole-body fluorescence and bone marrow infiltration. HHSCs exposed to LV/DV were injected to NOD/SCID mice and re-population/differentiation was monitored. RESULTS: A total of six of seven myeloma cell lines and five of seven patient tumor specimens exposed to reovirus showed significant in vitro sensitivity. Tumor response of multiple myeloma by LV, but not DV, was confirmed by comparison of total tumor weights (P = 0.05), and bone marrow infiltration (1/6, LV; 5/6, DV). Mice injected with LV- or DV-exposed HHSCs maintained in vivo re-population/lineage differentiation showing a lack of viral effect on the stem cell compartment. Reovirus oncolysis was mediated primarily by activation of the apoptotic pathways. CONCLUSIONS: The unique ability of reovirus to selectively kill multiple myeloma while sparing HHSCs places it as a promising systemic multiple myeloma therapeutic for clinical testing.
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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".