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Exploring the impact of deubiquitination on melanoma prognosis through single-cell RNA sequencing. | LitMetric

AI Article Synopsis

  • Cutaneous melanoma is an aggressive skin cancer with a strong tendency to spread, making the discovery of new biomarkers and treatment targets crucial.
  • The study utilized single-cell RNA sequencing to analyze melanoma cells, leading to the creation of a prognostic model that predicts patient risk by assessing genetic factors and immune environment differences.
  • The model showed high accuracy in predicting outcomes and underscores the importance of deubiquitination processes in melanoma, paving the way for future research on potential therapies.

Article Abstract

Background: Cutaneous melanoma, characterized by the malignant proliferation of melanocytes, exhibits high invasiveness and metastatic potential. Thus, identifying novel prognostic biomarkers and therapeutic targets is essential.

Methods: We utilized single-cell RNA sequencing data (GSE215120) from the Gene Expression Omnibus (GEO) database, preprocessing it with the Seurat package. Dimensionality reduction and clustering were executed through Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP). Cell types were annotated based on known marker genes, and the AUCell algorithm assessed the enrichment of deubiquitination-related genes. Cells were categorized into DUB_high and DUB_low groups based on AUCell scores, followed by differential expression analysis. Importantly, we constructed a robust prognostic model utilizing various genes, which was evaluated in the TCGA cohort and an external validation cohort.

Results: Our prognostic model, developed using Random Survival Forest (RSF) and Ridge Regression methods, demonstrated excellent predictive performance, evidenced by high C-index and AUC values across multiple cohorts. Furthermore, analyses of immune cell infiltration and tumor microenvironment scores revealed significant differences in immune cell distribution and microenvironment characteristics between high-risk and low-risk groups. Functional experiments indicated that TBC1D16 significantly impacts the migration and proliferation of melanoma cells.

Conclusion: This study highlights the critical role of deubiquitination in melanoma and presents a novel prognostic model that effectively stratifies patient risk. The model's strong predictive ability enhances clinical decision-making and provides a framework for future studies on the therapeutic potential of deubiquitination mechanisms in melanoma progression. Further validation and exploration of this model's applicability in clinical settings are warranted.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11659643PMC
http://dx.doi.org/10.3389/fgene.2024.1509049DOI Listing

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