Systemic versus localized <scp>Bacillus Calmette Guérin</scp> immunotherapy of bladder cancer promotes an anti‐tumoral microenvironment: Novel role of trained immunity
Bibliographic record
Abstract
Treatment for higher-risk non-muscle invasive bladder cancer (NMIBC) involves intravesical immunotherapy with Bacillus Calmette Guérin (BCG); however, disease recurrence and progression occur frequently. Systemic immunity is critical for successful cancer immunotherapy; thus, recurrence of NMIBC may be due to suboptimal systemic activation of anti-tumor immunity after local immunotherapy. We previously reported that systemically acquired trained immunity (a form of innate immune memory) in circulating monocytes is associated with increased time-to-recurrence in patients with NMIBC treated with BCG. Herein, we used a mouse model of NMIBC to compare the effects of intravesical versus intravenous (systemic) BCG immunotherapy on the local and peripheral immune microenvironments. We also assessed whether BCG-induced trained immunity modulates anti-tumor immune responses. Compared with intravesical BCG, which led to a tumor-promoting immune microenvironment, intravenous BCG resulted in an anti-tumoral bladder microenvironment characterized by increased proportions of cytotoxic T lymphocytes (CTLs), and decreased proportions of myeloid-derived suppressor cells. Polarization toward anti-tumoral immunity occurred in draining lymph nodes, spleen, and bone marrow following intravenous versus intravesical BCG treatment. Pre-treatment with intravesical BCG was associated with increased rate of tumor growth compared with intravenous BCG pre-treatment. Trained immunity contributed to remodeling of the tumor immune microenvironment, as co-instillation of BCG-trained macrophages with ovalbumin-expressing bladder tumor cells increased the proportion of tumor-specific CTLs. Furthermore, BCG-trained dendritic cells exhibited enhanced antigen uptake and presentation and promoted CTL proliferation. Our data support the concept that systemic immune activation promotes anti-tumor responses, and that BCG-induced trained immunity is important in driving anti-tumor adaptive immunity.
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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 | 0.000 |
| 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".