Concise Review: Targeting Cancer Stem Cells and Their Supporting Niche Using Oncolytic Viruses
Bibliographic record
Abstract
Cancer stem cells (CSCs) have the capacity to self-renew and differentiate to give rise to heterogenous cancer cell lineages in solid tumors. These CSC populations are associated with metastasis, tumor relapse, and resistance to conventional anticancer therapies. Here, we focus on the use of oncolytic viruses (OVs) to target CSCs as well as the OV-driven interferon production in the tumor microenvironment (TME) that can repress CSC properties. We explore the ability of OVs to deliver combinations of immune-modulating therapeutic transgenes, such as immune checkpoint inhibitor antibodies. In particular, we highlight the advantages of virally encoded bi-specific T cell engagers (BiTEs) to not only target cell-surface markers on CSCs, but also tumor-associated antigens on contributing components of the surrounding TME and other cancer cells. We also highlight the crucial role of combination anticancer treatments, evidenced by synergy of OV-delivered BiTEs and chimeric-antigen receptor T cell therapy. Stem Cells 2019;37:716-723.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".