Investigating AhR as a mechanism of CD8+ T cell modulation by microbial-derived metabolites in PDAC 2802
Bibliographic record
Abstract
Abstract Description Pancreatic ductal adenocarcinoma (PDAC) has the lowest five-year-survival of common solid cancer types and responds poorly to immunotherapy despite an abundant intra-tumour immune infiltrate. The microbiota has been reported to impact tumour characteristics and survival, at least partially by limiting CD8+ T cell function. The microbiota can potentially influence immune function through metabolites, including indole production as a result of microbial tryptophan metabolization. The aryl hydrocarbon receptor (AhR) is a key cellular response pathway in the host-microbiota axis that may play an immunosuppressive role in CD8+ T cells. Since AhR can be activated by microbial-derived indoles, we tested the hypothesis that microbiota-produced indoles suppress intratumoural CD8+ T cell function via AhR activation, thus promoting disease progression. Using an orthotopic model of PDAC, we found that tumour burden was reduced in CD8-specific AhR knockout mice compared to the littermate controls. Further, murine PDAC tumours have a greater concentration of indole compounds compared to healthy pancreases. Moreover, exposure to these indole compounds activated AhR in CD8+ T cells, significantly suppressing their acquisition of an inflammatory phenotype. In summary, our data suggest that microbial-derived metabolites can suppress CD8+ T cell function in PDAC through activation of AhR Funding Sources NIH, CIHR, and TFRI Topic Categories Tumor Immunology: Cellular Responses and Tumor Microevironment (TIME)
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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) | 0.003 | 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".