Evidence map›Paper›PMID 41247132›Full record

ArticleInvestigative ophthalmology & visual science2025

Characterization of Early Metastatic Subpopulations in Uveal Melanoma: Single-Cell Insights Into SPP1+ Cells and Their Interactions With Macrophages.

Jingting Luo, Jingyao Zeng, Heng Wang, Qiheng Qian, Haowen Li, Yuning Chen, Jingying Xiu, Rui Fang, Qiong Yang, Zhaoxun Feng and 3 more

Abstract read
In one paragraph

Article in Investigative ophthalmology & visual science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Jingting LuoBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Jingyao ZengNational Genomics Data Center, China National Center for Bioinformation, Beijing, China.
Heng WangBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Qiheng QianNational Genomics Data Center, China National Center for Bioinformation, Beijing, China.
Haowen LiBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Yuning ChenBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Jingying XiuBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Rui FangBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Qiong YangBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Zhaoxun FengDepartment of Ophthalmology, University of Ottawa, Ottawa, Ontario, Canada.
Yang LiBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Jingfa XiaoNational Genomics Data Center, China National Center for Bioinformation, Beijing, China.
Wenbin WeiBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

MacrophagesMelanomaOsteopontinUveal NeoplasmsAgedApoptosisBiomarkers, TumorCell MovementCell ProliferationFemaleFlow CytometryHumansMaleMiddle AgedNeoplasm InvasivenessNeoplasm MetastasisBiomarkers, TumorOsteopontinSPP1 protein, human

Identifiers

PMID41247132
PMCPMC12633778

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.