Bifidobacteria-derived exopolysaccharide promotes anti-tumor immunity
Bibliographic record
Abstract
While several phylogenetically distinct bacterial taxa can predict responses to or improve cancer immunotherapies, the underlying mechanisms remain poorly understood. The use of microbes for microbial therapeutics is currently under intense research, yet safety and regulatory hurdles remain challenging. Thus, non-replicative bacterial-derived molecules or extracts provide promising alternatives. We have identified exopolysaccharides (EPSs) from two bacterial species-Bifidobacterium pseudolongum and Bifidobacterium pseudocatenulatum-that promote anti-tumor immunity. EPS improved Th1 T cell immunity, which was further boosted by the metabolite inosine. Mechanistically, EPS was sensed by dendritic cells in a Tlr2-MyD88-dependent manner, which induced interleukin (IL)-12 and tumor necrosis factor (TNF)-α. Both cytokines were required for T cell-dependent killing of tumor cells in murine colon cancer models. EPS stimulated IL-12 production through Toll-like receptor 2 (TLR2) in human dendritic cells and promoted cell death in patient-derived colon cancer organoids through immune cells. Collectively, our study identifies microbe-derived EPS as an adjuvant immunotherapy in cancer.
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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 | 0.000 | 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) | 0.000 | 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".