NLRP1 Shapes Immune and Inflammatory Signatures in Human Melanoma but Not in Mouse Models
Bibliographic record
Abstract
Abstract Inflammasomes are multiprotein complexes that activate pro-caspase-1, leading to the maturation of the pro-inflammatory cytokines IL-1β and IL-18. Nlrp1 , the first receptor identified with inflammasome-forming capacity, is highly expressed in both the skin and immune cells. Despite its prominent role in these tissues, the function of Nlrp1 in melanoma remains poorly characterized. In this study, we investigated the impact of Nlrp1 on melanoma patient survival and found that its expression is associated with improved prognosis and with a co-expression network enriched for pro-inflammatory genes. However, in murine models, neither Nlrp1 expression nor activation significantly affected melanoma development or progression. Similarly, pharmacological activation of Nlrp1 using Val-Boro-Pro (VbP) did not alter tumor growth or the local inflammatory profile in mice but directly influenced CD25 + cell generation and glucose uptake in in vitro models. Finally, we demonstrated that a melanoma risk score can be constructed based on genes specific to inflammasome and pyroptosis pathways. Collectively, our findings reveal species-specific differences in NLRP1 function between humans and mice and support the potential of inflammasome-related pathways as prognostic biomarkers and therapeutic targets in human cancers.
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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 | 0.001 | 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 | 0.001 |
| 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".