Accumulation of tolerogenic human 6-sulfo LacNAc dendritic cells in renal cell carcinoma is associated with poor prognosis
Bibliographic record
Abstract
Dendritic cells (DCs) essentially contribute to the induction and regulation of innate and adaptive immunity. Based on these important properties, DCs may profoundly influence tumor progression in patients. However, little is known about the role of distinct human DC subsets in primary tumors and their impact on clinical outcome. In the present study, we investigated the characteristics of human 6-sulfo LacNAc (slan) DCs in clear cell renal cell carcinoma (ccRCC). slanDCs have been shown to display various tumor-directed properties and to accumulate in tumor-draining lymph nodes from patients. When evaluating 263 ccRCC and 227 tumor-free tissue samples, we found increased frequencies of slanDCs in ccRCC tissues compared to tumor-free tissues. slanDCs were also detectable in the majority of 24 metastatic lymph nodes and 67 distant metastases from ccRCC patients. Remarkably, a higher density of slanDCs was significantly associated with a reduced progression-free, tumor-specific or overall survival of ccRCC patients. Tumor-infiltrating slanDCs displayed an immature phenotype expressing interleukin-10. ccRCC cells efficiently impaired slanDC-induced T-cell proliferation and programming as well as natural killer (NK) cell activation. In conclusion, these findings indicate that higher slanDC numbers in ccRCC tissues are associated with poor prognosis. The induction of a tolerogenic phenotype in slanDCs leading to an insufficient activation of innate and adaptive antitumor immunity may represent a novel immune escape mechanism of ccRCC. These observations may have implications for the design of therapeutic strategies that harness tumor-directed functional properties of DCs against ccRCC.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".