Oncolytic Virotherapy for Multiple Myeloma.
Bibliographic record
Abstract
Abstract Oncolytic virotherapy for cancer employs viruses which specifically lyse tumour cells, leaving normal cells intact. Double-deleted vaccinia virus (vvDD) is tumour-specific due to mutations that restrict viral replication to dividing cells. This is the first use of vvDD to treat a hematologic malignancy. vvDD expressing enhanced green fluorescent protein (EGFP) was used to infect multiple myeloma (MM) cell lines. We used flow cytometry (FACS) analysis to quantify EGFP positive cells in parallel to colorimetric (MTT) and microscopic cell viability assays. FACS results indicated vvDD efficiently (27–73%) infected the MM cell lines RPMI8226, MY5, H929, U266 and LP1 by 72 hours post infection. MTT assays revealed a 7–8 fold decrease in cell viability of infected cells compared to controls. MM cell lines were grown as subcutaneous xenografts (My5) or systemically (RPMI8226) in non-obese diabetic/severe combined immunodeficient (NOD/SCID) mice, and tumour size/paralysis was monitored after systemic delivery of vvDD. My5 tumours responded to ip vvDD, resulting in a significant delay of tumour growth compared to controls, while 80% of mice treated with vvDD 3 days after iv RPMI8226 tumour injection were cured. Analysis of mouse tissues for viral biodistribution and pathogenicity showed that the ovary was the second highest viral containing tissue though it was 4 logs lower than tumour. Ovaries showed some evidence of follicular necrosis in treated tissues. All other tissues were unaffected. Primary human MM (CD138+) cells obtained from bone marrow aspiration were readily (50–60%) infected with vvDD while normal mononuclear cells from the same samples were not infected. At the same time primary human CD138+ cells were infected with vvDD at an MOI of 1 or mock infected and then plated in matrigel. vvDD treated cells showed significantly reduced colony formation compared to mock-infected controls. These results suggest that vvDD is a safe and effective treatment for multiple myeloma and should be considered for phase I testing in these patients.
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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 | 0.001 |
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".