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Article Abstract
Background: Skin cutaneous melanoma (SKCM) is a highly aggressive and deadly subtype of skin cancer. Lack of efficient biomarkers for prognosis has limited the improvement of survival outcome for patients with SKCM.
Methods: In this study, we obtained RNA-seq data from TCGA and GTEx databases, followed by identification of differential expressed genes, univariate Cox regression, and LASSO regression to identify prognostic SASP-related genes in the TCGA datasets and constructed a prognostic risk-scoring model.
Results: The establishment of prognostic model was based on the expression levels of 14 SASP-related genes, including ASPRV1, ICAM1, IL2RA, ABCC2, HLA-B, TPMT, ATM, CD59, KIR2DL4, CTLA4, ITGB3, FOXM1, NOX4, and TRIM21. Patients with melanoma who were in the high-risk group had a shorter overall survival (OS), indicating that the model served as an independent prognostic index. Furthermore, we found that the risk score was potentially linked to immune scores, estimate score, immune cell infiltration level, and immunotherapy efficacy.
Conclusions: This study presented a new prognostic model for assessing therapy in melanoma patients, providing a fresh perspective for combating melanoma.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12390897 | PMC |
| http://dx.doi.org/10.1007/s12672-025-02935-z | DOI Listing |
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