Exploring the impact of deubiquitination on melanoma prognosis through single-cell RNA sequencing
BackgroundCutaneous melanoma, characterized by the malignant proliferation of melanocytes, exhibits high invasiveness and metastatic potential. Thus, identifying novel prognostic biomarkers and therapeutic targets is essential.MethodsWe utilized single-cell RNA sequencing data (GSE215120) from the G...
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Frontiers Media S.A.
2024-12-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2024.1509049/full |
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| author | Su Peng Jiaheng Xie Xiaohu He |
| author_facet | Su Peng Jiaheng Xie Xiaohu He |
| author_sort | Su Peng |
| collection | DOAJ |
| description | BackgroundCutaneous melanoma, characterized by the malignant proliferation of melanocytes, exhibits high invasiveness and metastatic potential. Thus, identifying novel prognostic biomarkers and therapeutic targets is essential.MethodsWe 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.ResultsOur 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.ConclusionThis 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. |
| format | Article |
| id | doaj-art-fd5740208ef64537a23b5c3731453f81 |
| institution | Kabale University |
| issn | 1664-8021 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj-art-fd5740208ef64537a23b5c3731453f812024-12-06T08:50:37ZengFrontiers Media S.A.Frontiers in Genetics1664-80212024-12-011510.3389/fgene.2024.15090491509049Exploring the impact of deubiquitination on melanoma prognosis through single-cell RNA sequencingSu Peng0Jiaheng Xie1Xiaohu He2Department of Plastic Surgery, The Affiliated Friendship Plastic Surgery Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Plastic Surgery, The Affiliated Friendship Plastic Surgery Hospital of Nanjing Medical University, Nanjing, ChinaBackgroundCutaneous melanoma, characterized by the malignant proliferation of melanocytes, exhibits high invasiveness and metastatic potential. Thus, identifying novel prognostic biomarkers and therapeutic targets is essential.MethodsWe 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.ResultsOur 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.ConclusionThis 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.https://www.frontiersin.org/articles/10.3389/fgene.2024.1509049/fullmelanomaprognostic modeldeubiquitinationsingle-cell RNA sequencingimmune microenvironment |
| spellingShingle | Su Peng Jiaheng Xie Xiaohu He Exploring the impact of deubiquitination on melanoma prognosis through single-cell RNA sequencing Frontiers in Genetics melanoma prognostic model deubiquitination single-cell RNA sequencing immune microenvironment |
| title | Exploring the impact of deubiquitination on melanoma prognosis through single-cell RNA sequencing |
| title_full | Exploring the impact of deubiquitination on melanoma prognosis through single-cell RNA sequencing |
| title_fullStr | Exploring the impact of deubiquitination on melanoma prognosis through single-cell RNA sequencing |
| title_full_unstemmed | Exploring the impact of deubiquitination on melanoma prognosis through single-cell RNA sequencing |
| title_short | Exploring the impact of deubiquitination on melanoma prognosis through single-cell RNA sequencing |
| title_sort | exploring the impact of deubiquitination on melanoma prognosis through single cell rna sequencing |
| topic | melanoma prognostic model deubiquitination single-cell RNA sequencing immune microenvironment |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2024.1509049/full |
| work_keys_str_mv | AT supeng exploringtheimpactofdeubiquitinationonmelanomaprognosisthroughsinglecellrnasequencing AT jiahengxie exploringtheimpactofdeubiquitinationonmelanomaprognosisthroughsinglecellrnasequencing AT xiaohuhe exploringtheimpactofdeubiquitinationonmelanomaprognosisthroughsinglecellrnasequencing |