Characterization of Early Metastatic Subpopulations in Uveal Melanoma: Single-Cell Insights Into SPP1 <sup>+</sup> Cells and Their Interactions With Macrophages
Bibliographic record
Abstract
Purpose: To identify highly invasive subpopulations of tumor cells that may be responsible for early uveal melanoma (UM) metastasis at the single-cell level and to analyze their interactions with immune cells. Methods: Single-cell RNA sequencing was conducted on 11 samples from 11 UM patients who underwent primary enucleation. The patients were categorized into metastasis (M+) and nonmetastasis (M-) groups based on whether metastasis occurred during the 3-year follow-up. The results were validated using bulk RNA sequencing data from 133 patients from our cohort (n = 53) and The Cancer Genome Atlas human UM database (n = 80). The clustering was confirmed by immunofluorescence. Cell proliferation and invasiveness were evaluated using CCK8 and transwell assays. Apoptosis was analyzed using flow cytometry after Annexin V-fluorescein isothiocyanate/propidium iodide staining. The relative expression levels of genes were assessed using RT-qPCR. Results: A secreted phosphoprotein 1 (SPP1)+ cluster that may be related to early metastasis and high invasiveness was identified by comprehensive bioinformatics analysis and confirmed by immunofluorescence in UM sections. In vitro experiments supported that SPP1 regulates UM cell proliferation, migration, and invasion. Moreover, C-C motif chemokine ligand 3+ (CCL3+) macrophages were associated with poor prognosis, and the high mobility group box 1/T cell immunoglobulin and mucin domain-containing protein 3 (HMGB1/TIM-3) axis may serve as a potential immune checkpoint target. Consequently, SPP1+ melanoma cell populations will likely interact with CCL3+ macrophages, highlighting their possible role in the metastatic process. Conclusions: Our study reveals early metastatic mechanisms in UM by identifying highly invasive SPP1+ melanoma cells and their interaction with macrophages, providing potential therapeutic targets for the metastatic process.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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".