Engineered measles virus as a novel oncolytic therapy against prostate cancer
Bibliographic record
Abstract
BACKGROUND: No curative therapy is currently available for locally advanced or metastatic prostate cancer. Oncolytic viruses represent a novel class of therapeutic agents that demonstrates no cross-resistance with existing approaches and can therefore be combined with conventional treatment modalities. Measles virus strains deriving from the Edmonston (MV-Edm) vaccine strain have shown considerable oncolytic activity against a variety of solid tumers and hematologic malignancies. In this study, we investigated the antitumor potential of recombinant MV-Edm derivatives as novel oncolytic agents against prostate cancer. METHODS: The susceptibility of prostate cancer cell lines (PC-3, DU-145, and LNCaP) to measles virus infection was demonstrated using an MV-Edm derivative expressing green fluorescent protein (GFP). MV-Edm replication in prostate cancer cell lines was assessed by one step viral growth curves. The oncolytic effect of an MV-Edm strain engineered to express the human carcinoembryonic antigen (CEA) was demonstrated in vitro by MTT assays and in vivo in subcutaneous PC-3 xenografts. CEA levels were quantitated in cell supernatants and mouse serum samples. RESULTS: Recombinant MV-Edm strains can effectively infect, replicate in and kill prostate cancer cells. Intratumoral administration of MV-CEA at a total dose of 6 x 10(6) TCID50 resulted in statistically significant tumor growth delay (P = 0.004) and prolongation of survival (P = 0.001) in a subcutaneous PC-3 xenograft model. Viral growth kinetics paralleled CEA production. CONCLUSIONS: MV-CEA has potent antitumor activity against prostate cancer cell lines and xenografts. Viral gene expression during treatment can be determined by monitoring of CEA levels in the serum; the latter could allow dose optimization and tailoring of individualized treatment protocols.
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.
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) | 0.000 | 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 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".