Improved Systemic Delivery of Oncolytic Reovirus to Established Tumors Using Preconditioning with Cyclophosphamide-Mediated Treg Modulation and Interleukin-2
Bibliographic record
Abstract
PURPOSE: The goals of this study were (a) to investigate whether preconditioning of immunocompetent mice with PC-61-mediated regulatory T-cell (Treg) depletion and interleukin-2 (IL-2) would enhance systemic delivery of reovirus into subcutaneous tumors and (b) to test whether cyclophosphamide (CPA), which is clinically approved, could mimic PC-61 for modification of Treg activity for translation into the next generation of clinical trials for intravenous delivery of reovirus. EXPERIMENTAL DESIGN: C57Bl/6 mice bearing subcutaneous B16 tumors were treated with CPA or PC-61 followed by 10 injections of low-dose IL-2. Mice were then treated with intravenous reovirus. Virus localization to tumor and other organs was measured along with tumor growth and systemic toxicity. RESULTS: Preconditioning with PC-61 and IL-2 enhanced localization of intravenous oncolytic reovirus to tumors with significantly increased antitumor therapy compared with controls (P < 0.01). However, with the maximal achievable dose of reovirus, Treg modification + IL-2 was also associated with systemic toxicity. CPA (100 mg/kg) did not deplete, but did functionally inhibit, Treg. CPA also mimicked PC-61, in combination with IL-2, by inducing "hyperactivated" NK cells. Consistent with this, preconditioning with CPA + IL-2 enhanced therapy of intravenously delivered, intermediate-dose reovirus to a level indistinguishable from that induced by PC-61 + IL-2, without any detectable toxicity. CONCLUSION: With careful reference to ongoing clinical trials with dose escalation of reovirus alone and in combination with CPA, we propose that future clinical trials of CPA + IL-2 + reovirus will allow for both improved levels of virus delivery and increased antitumor efficacy.
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 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 | 0.002 | 0.001 |
| 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 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".