Differential expression gene screening and prognostic biomarkers of skin cutaneous melanoma based on GEPIA database

[Objective] To explore the differential gene expression profiles between skin cutaneous melanoma (SKCM) and normal tissues using bioinformatics methods, and to evaluate their predictive value for patient survival and prognosis. [Methods] Differentially expressed genes (DEGs) between tumor and normal tissues were identified using the GEPIA database. The correlation between key gene expression and overall survival was analyzed.[Results] A total of 6,457 significantly upregulated genes (FDR < 0.05) were identified. The top 10 genes with the highest expression levels included PRAME, RP11-40C6.2, SERPINE2, SDC3, UBE2SP2, ETV5, PLOD3, EIF5AP4, UBE2S, and HNRNPCP2. Survival analysis revealed that the expression levels of EIF5AP4, UBE2S, and SERPINE2 were significantly associated with clinical prognosis. Specifically, high EIF5AP4 expression was significantly associated with shortened disease-free survival (DFS), while high UBE2S expression was significantly associated with reduced overall survival (OS) and DFS. In contrast, high SERPINE2 expression was significantly associated with prolonged OS and DFS.[Conclusion] This study suggests that UBE2S and EIF5AP4 may function as oncogenic factors promoting SKCM progression, whereas SERPINE2 may play a protective role. The combined expression of these three genes may serve as a novel molecular signature for prognostic evaluation in SKCM.

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Publication Details

Journal
Medical Research
Published
2025-06-13
DOI
https://doi.org/10.6913/mrhk.070204
Primary Topic
Melanoma and MAPK Pathways
Type
article
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0.00
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article

Differential expression gene screening and prognostic biomarkers of skin cutaneous melanoma based on GEPIA database

Jessica Qi, Yu Zhang, Gang Nie, Peijie Yan
Medical Research
Melanoma and MAPK Pathways
article

Differential expression gene screening and prognostic biomarkers of skin cutaneous melanoma based on GEPIA database

Jessica Qi, Yu Zhang, Gang Nie, Peijie Yan
article en

Abstract

[Objective] To explore the differential gene expression profiles between skin cutaneous melanoma (SKCM) and normal tissues using bioinformatics methods, and to evaluate their predictive value for patient survival and prognosis. [Methods] Differentially expressed genes (DEGs) between tumor and normal tissues were identified using the GEPIA database. The correlation between key gene expression and overall survival was analyzed.[Results] A total of 6,457 significantly upregulated genes (FDR < 0.05) were identified. The top 10 genes with the highest expression levels included PRAME, RP11-40C6.2, SERPINE2, SDC3, UBE2SP2, ETV5, PLOD3, EIF5AP4, UBE2S, and HNRNPCP2. Survival analysis revealed that the expression levels of EIF5AP4, UBE2S, and SERPINE2 were significantly associated with clinical prognosis. Specifically, high EIF5AP4 expression was significantly associated with shortened disease-free survival (DFS), while high UBE2S expression was significantly associated with reduced overall survival (OS) and DFS. In contrast, high SERPINE2 expression was significantly associated with prolonged OS and DFS.[Conclusion] This study suggests that UBE2S and EIF5AP4 may function as oncogenic factors promoting SKCM progression, whereas SERPINE2 may play a protective role. The combined expression of these three genes may serve as a novel molecular signature for prognostic evaluation in SKCM.

Medical ResearchVol. 7(2)
Openalex Percentile: Top 88%
Melanoma and MAPK Pathways
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Differential expression gene screening and prognostic biomarkers of skin cutaneous melanoma based on GEPIA database — Jessica Qi, Yu Zhang, et al. · Medical Research (2025) | TGRS Research Map | TGRS