Double‐deleted vaccinia virus in virotherapy for refractory and metastatic pediatric solid tumors
Bibliographic record
Abstract
BACKGROUND: Previous studies have shown successful antitumor effects of systemically delivered double-deleted vaccinia virus (vvDD) against a number of adult tumor models, including glioma, colon and ovarian cancers. The purpose of this study was to investigate the oncolytic potential of vvDD against a panel of cell lines representative of pediatric solid tumors that are currently difficult to cure. METHODS: Cell lines derived from central nervous system atypical teratoid rhabdoid tumor (AT/RT) (BT12, BT16 and KCCF1), sarcoma (143B, HOS, RD and RH30), and neuroblastoma (SKNAS, SKNBE2, IMR-5 and IMR-32) were examined for vvDD mediated cytotoxicity defined by virus expansion followed by loss of tumor cell viability. The normal human fibroblast cell line HS68 was used as a control. Next, relevant orthotopic, subcutaneous and lung metastasis xenograft models were treated with intravenous doses of live vvDD or killed virus controls (DV). Tumor growth inhibition and viral replication were quantified and survival outcomes of these animals were assessed. RESULTS: vvDD was able to infect and kill nine of eleven of the pediatric tumor cells (81.8%) in vitro. In xenograft models, intravenous administration of a single dose of vvDD significantly inhibited the growth of tumors and prolonged the survival of intracranial and metastatic tumors. CONCLUSIONS: Oncolytic vvDD administered i.v. shows activity in preclinical models of pediatric malignancies that are resistant to many currently available treatments. Our data support further evaluation of vvDD virotherapy for refractory pediatric solid tumors.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".