Newly Recruited CD11b+, GR-1+, Ly6Chigh Myeloid Cells Augment Tumor-Associated Immunosuppression Immediately following the Therapeutic Administration of Oncolytic Reovirus
Bibliographic record
Abstract
Tumor-associated immunosuppression aids cancer cells to escape immune-mediated attack and subsequent elimination. Recently, however, many oncolytic viruses, including reovirus, have been reported to overturn such immunosuppression and promote the development of a clinically desired antitumor immunity, which is known to promote favorable patient outcomes. Contrary to this existing paradigm, in this article we demonstrate that reovirus augments tumor-associated immunosuppression immediately following its therapeutic administration. Our data show that reovirus induces preferential differentiation of highly suppressive CD11b(+), Gr-1(+), Ly6C(high) myeloid cells from bone marrow hematopoietic progenitor cells. Furthermore, reovirus administration in tumor-bearing hosts drives time-dependent recruitment of CD11b(+), Gr-1(+), Ly6C(high) myeloid cells in the tumor milieu, which is further supported by virus-induced increased expression of numerous immune factors involved in myeloid-derived suppressor cell survival and trafficking. Most importantly, CD11b(+), Gr-1(+), Ly6C(high) myeloid cells specifically potentiate the suppression of T cell proliferation and are associated with the absence of IFN-γ response in the tumor microenvironment early during oncotherapy. Considering that the qualitative traits of a specific antitumor immunity are largely dictated by the immunological events that precede its development, our findings are of critical importance and must be considered while devising complementary interventions aimed at promoting the optimum efficacy of oncolytic virus-based anticancer immunotherapies.
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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".