Minute virus of mice is oncolytic for pancreatic cancer cells with mesenchymal phenotype
Bibliographic record
Abstract
Abstract Pancreatic cancer will soon become the second cause of death by cancer in Western countries. The main barrier to increase the survival of patients with this disease requires the development of novel and efficient therapeutic strategies, that better consider tumor biology. Oncolytic viruses are quickly moving toward the forefront of medicines for the management of cancer. Among them, the fibrotropic minute virus of mice prototype (MVMp) preferentially infects migrating and undifferentiated cells, that highly resemble poorly differentiated, basal-like, pancreatic tumors showing the worst clinical outcome. Thus, we hypothesized that MVMp may specifically target the most aggressive subtype of pancreatic cancer cells. We report here that MVMp specifically infects, replicates in and kills pancreatic cancer cells from murine and human origin with a mesenchymal, basal-like profile, while sparing cancer cells with an epithelial phenotype. In vivo , MVMp shows oncolytic activity in experimental tumors with mesenchymal phenotype only, and shows increased antitumoral efficacy in immune competent models. Collectively, we demonstrate herein for the first time that MVMp is specific and oncolytic for pancreatic tumors with mesenchymal, basal-like profile, paving the way for precision medicine opportunities for the management of the most aggressive and lethal form of this disease.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".