The ex vivo purge of cancer cells using oncolytic viruses: recent advances and clinical implications
Bibliographic record
Abstract
Jovian J Tsang,1,2 Harold L Atkins2,3 1Department of Biochemistry, University of Ottawa, 2Cancer Therapeutics, Ottawa Hospital Research Institute, 3Blood and Marrow Transplant Program, The Ottawa Hospital, Ottawa, ON, Canada Abstract: Hematological malignancies are treated with intensive high-dose chemotherapy, with or without radiation. This is followed by hematopoietic stem cell (HSC) transplantation (HSCT) to rescue or reconstitute hematopoiesis damaged by the anticancer therapy. Autologous HSC grafts may contain cancer cells and purging could further improve treatment outcomes. Similarly, allogeneic HSCT may be improved by selectively purging alloreactive effector cells from the graft rather than wholesale immune cell depletion. Viral agents that selectively replicate in specific cell populations are being studied in experimental models of cancer and immunological diseases and have potential applications in the context of HSC graft engineering. This review describes preclinical studies involving oncolytic virus strains of adenovirus, herpes simplex virus type 1, myxoma virus, and reovirus as ex vivo purging agents for HSC grafts, as well as in vitro and in vivo experimental studies using oncolytic coxsackievirus, measles virus, parvovirus, vaccinia virus, and vesicular stomatitis virus to eradicate hematopoietic malignancies. Alternative ex vivo oncolytic virus strategies are also outlined that aim to reduce the risk of relapse following autologous HSCT and mitigate morbidity and mortality due to graft-versus-host disease in allogeneic HSCT. Keywords: hematopoietic stem cells, oncolytic virus, hematopoietic stem cell transplantation, stem cell graft purging, hematopoietic malignancy, graft vs host disease
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".