Leukocyte Specific Protein 1 Deficiency Impairs Anti‐Melanoma Immunity by Disrupting <scp>DC</scp> and <scp>CD8</scp> <sup>+</sup> T Cell Function in Mice
Bibliographic record
Abstract
ABSTRACT Leukocyte‐specific protein 1 (LSP1) is an F‐actin‐binding protein involved in immune cell motility and cytoskeletal rearrangement. Although LSP1 has been extensively studied in neutrophils and macrophages, its role in dendritic cells and tumour surveillance remains poorly understood. Here, we demonstrate that LSP1 deficiency in mice leads to increased growth of B16‐OVA melanoma, accompanied by reduced survival. Flow cytometry and histological analysis revealed lower total leukocyte content in the tumour microenvironment (TME) in LSP1 knockout (KO) mice compared to wild‐type (WT) mice, and a significant reduction in CD8 + T cells and CD103 + dendritic cells (DCs), as well as in additional immune cell populations, in tumour‐draining lymph nodes of LSP1 KO mice. In vivo, DCs from LSP1 KO mice exhibited impaired antigen uptake and transportation to the tumour‐draining lymph node and a reduced in vitro capacity to activate naïve CD8 + T cells. These defects correlated with diminished in vitro and in vivo CD8 + T cell priming and activation in LSP1‐deficient mice. Cytokine profiling of tumour homogenates from LSP1 KO mice revealed a complex inflammatory milieu, with elevated levels of both pro‐ and anti‐tumoural cytokines, including IL‐1β, TNF‐α, IL‐10, IL‐17A, IFNβ IL‐23, IL‐27 and GM‐CSF. Our findings suggest that LSP1 plays a critical, cell‐intrinsic role in both DC and CD8 + T cell function, although we cannot exclude the possible role of other leukocyte populations. Its absence promotes tumour progression by disrupting key immune responses in the TME.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".