Oncolytic reovirus-mediated recruitment of early innate immune responses reverses immunotherapy resistance in prostate tumors
Bibliographic record
Abstract
Prostate cancers are considered "cold" tumors characterized by minimal T cell infiltrates, absence of a type I interferon (IFN) signature, and the presence of immunosuppressive cells. This non-inflamed phenotype is likely responsible for the lack of sensitivity of prostate cancer patients to immune checkpoint blockade (ICB) therapy. Oncolytic virus therapy can potentially overcome this resistance to immunotherapy in prostate cancers by transforming cold tumors into "hot," immune cell-infiltrated tumors. We investigated whether the combination of intratumoral oncolytic reovirus, followed by targeted blockade of Programmed cell death protein 1 (PD-1) checkpoint inhibition and/or the immunomodulatory CD73/Adenosine system can enhance anti-tumor immunity. Treatment of subcutaneous TRAMP-C2 prostate tumors with combined intratumoral reovirus and anti-PD-1 or anti-CD73 antibody significantly enhanced survival of mice compared with reovirus or either antibody therapy alone. Only combination therapy led to rejection of pre-established tumors and protection from tumor re-challenge. This therapeutic effect was dependent on CD4 + T cells and natural killer (NK) cells. NanoString immune profiling of tumors confirmed that reovirus increased tumor immune cell infiltration and revealed an upregulation of the immune-regulatory receptor, B- and T-lymphocyte attenuator (BTLA). This expression of BTLA on innate antigen-presenting cells (APCs) and its ligand, Herpesvirus entry mediator (HVEM), on T cells from reovirus-infected tumors was in keeping with a role for the HVEM-BTLA pathway in promoting the potent anti-tumor memory response observed.
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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) | 0.000 | 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) | 0.001 | 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".