Monocytes mediate <i>Salmonella Typhimurium</i> ‐induced tumor growth inhibition in a mouse melanoma model
Bibliographic record
Abstract
Abstract The use of bacteria as an alternative cancer therapy has been reinvestigated in recent years. SL7207: an auxotrophic Salmonella enterica serovar Typhimurium aroA mutant with immune‐stimulatory potential has proven a promising strain for this purpose. Here, we show that systemic administration of SL7207 induces melanoma tumor growth arrest in vivo, with greater survival of the SL7207‐treated group compared to control PBS‐treated mice. Administration of SL7207 is accompanied by a change in the immune phenotype of the tumor‐infiltrating cells toward pro‐inflammatory, with expression of the T H 1 cytokines IFN‐γ, TNF‐α, and IL‐12 significantly increased. Interestingly, Ly6C + MHCII + monocytes were recruited to the tumors following SL7207 treatment and were pro‐inflammatory. Accordingly, the abrogation of these infiltrating monocytes using clodronate liposomes prevented SL7207‐induced tumor growth inhibition. These data demonstrate a previously unappreciated role for infiltrating inflammatory monocytes underlying bacterial‐mediated tumor growth inhibition. This information highlights a possible novel role for monocytes in controlling tumor growth, contributing to our understanding of the immune responses required for successful immunotherapy of cancer.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".