Skip to main content

ORIGINAL RESEARCH article

Front. Genet.
Sec. Cancer Genetics and Oncogenomics
Volume 15 - 2024 | doi: 10.3389/fgene.2024.1509049
This article is part of the Research Topic Enhancing Precision Immunotherapy: Leveraging Deep Learning and Cancer Genomics for Molecular Innovations and Clinical Applications View all 3 articles

Exploring the Impact of Deubiquitination on Melanoma Prognosis Through Single-Cell RNA Sequencing

Provisionally accepted
Su Peng Su Peng 1Jiaheng Xie Jiaheng Xie 2Xiaohu He Xiaohu He 1*
  • 1 The Affiliated Friendship Plastic Surgery Hospital of Nanjing Medical University, Nanjing, China
  • 2 Xiangya Hospital, Central South University, Changsha, China

The final, formatted version of the article will be published soon.

    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.

    Keywords: Melanoma, Prognostic model, deubiquitination, single-cell RNA sequencing, immune microenvironment

    Received: 10 Oct 2024; Accepted: 19 Nov 2024.

    Copyright: © 2024 Peng, Xie and He. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Xiaohu He, The Affiliated Friendship Plastic Surgery Hospital of Nanjing Medical University, Nanjing, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.