ArticleClinical and experimental medicine2025
Identification of a Treg-related gene signature for predicting prognosis and immunosuppression in skin cutaneous melanoma.
Article in Clinical and experimental medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Integrative bioinformatic and experimental analysis reveals prognostic and immunological roles of psychological stress-related genes in skin cutaneous melanoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Skin cutaneous melanoma (SKCM) is an aggressive malignancy where regulatory T cells (Tregs) drive an immunosuppressive tumor microenvironment, resulting in poor prognosis. Thus, there was an urgent need to identify Treg-related molecular biomarkers to optimize SKCM's prognostic assessment and therapeutic strategies. In this study, SKCM-related datasets were acquired from public databases. First, gene modules associated with Tregs screened using Weighted Correlation Network Analysis were intersected with differentially expressed genes to obtain Treg-DEGs. Subsequently, univariate Cox proportional hazards regression, LASSO regression, and multivariate Cox proportional hazards regression were employed to construct a prognostic biomarker signature. Furthermore, the biological functions of the prognostic biomarkers were explored by integrating functional enrichment analysis, molecular regulatory network construction, and drug prediction analysis. Finally, in cellular experiments, the mRNA and protein expression levels of the biomarkers were validated using qRT-PCR and Western blot. The risk model constructed based on the 10 prognostic biomarkers (PTPRF, ULK1, TGM3, CRABP2, SV2A, HLA-DQB2, KHDRBS3, VWA5A, CRIP1, and TFAP2C) could well predict the overall survival of SKCM patients. Functional enrichment analyses indicated that high-risk patients were enriched in keratinization pathways, whereas low-risk patients showed activation of autoimmune and infection-related pathways. NEAT1 might have regulated CRABP2 via miR-375. Additionally, 54 potential drugs, including resveratrol and metronidazole, were predicted for targeted therapy. qRT-PCR and Western blot confirmed PTPRF, ULK1, TGM3, and CRABP2 were upregulated at both the mRNA and protein levels. These findings indicate that the Treg-related signature serves as robust prognostic biomarkers and may guide personalized immunotherapy in SCKM.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.