Evidence map›Paper›PMID 40864319›Full record

ArticleDiscover oncology2025

Construction of a prognostic risk-scoring model based on SASP-related genes in patients with skin cutaneous melanoma.

Ming-Feng Li, Jing Du, Gang Wang, Wei Feng, Ju-Gao Chen, Chao Zhang

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Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Ming-Feng Li *Zhanjiang Institute of Clinical Medicine, Central People's Hospital of Zhanjiang, Guangdong Medical University Zhanjiang Central Hospital, Zhanjiang, 524045, People's Republic of China.
Jing Du *Department of Pathology, Central People's Hospital of Zhanjiang, Guangdong Medical University Zhanjiang Central Hospital, Zhanjiang, 524045, People's Republic of China.
Gang WangZhanjiang Institute of Clinical Medicine, Central People's Hospital of Zhanjiang, Guangdong Medical University Zhanjiang Central Hospital, Zhanjiang, 524045, People's Republic of China.
Wei FengZhanjiang Institute of Clinical Medicine, Central People's Hospital of Zhanjiang, Guangdong Medical University Zhanjiang Central Hospital, Zhanjiang, 524045, People's Republic of China.
Ju-Gao ChenDepartment of Oncology, Shenzhen People's Hospital, Second Clinical Medical College of Jinan University, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, 518020, People's Republic of China.
Chao ZhangZhanjiang Institute of Clinical Medicine, Central People's Hospital of Zhanjiang, Guangdong Medical University Zhanjiang Central Hospital, Zhanjiang, 524045, People's Republic of China. chaozhang_mail@foxmail.com.

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2024A1515010570
6 · The paper itself

Abstract

backgroundSkin 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.

methodsIn 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.

resultsThe 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.

conclusionsThis study presented a new prognostic model for assessing therapy in melanoma patients, providing a fresh perspective for combating melanoma.

Indexed as

ImmuneImmune checkpointMelanomaPrognosisSenescence-associated secretory phenotype (SASP)Tumor microenvironment (TME)

Identifiers

PMID40864319
PMCPMC12390897

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