Screening and identification of potential prognostic biomarkers in metastatic skin cutaneous melanoma by bioinformatics analysis.

ABSTRACT: Skin cutaneous melanoma (SKCM) is a multifactorial disease that presents a poor prognosis due to its rapid progression towards metastasis. This study focused on the identification of prognostic differentially expressed genes (DEGs) between primary and metastatic SKCM. DEGs were obtained using three chip data sets from the Gene Expression Omnibus database. The protein-protein interaction network was described by STRING and Cytoscape. Kaplan-Meier curves were implemented to evaluate survival benefits within distinct groups. A total of 258 DEGs were distinguished as possible candidate biomarkers. Besides, survival curves indicated that DSG3, DSC3, PKP1, EVPL, IVL, FLG, SPRR1A and SPRR1B were of significant value to predict the metastatic transformation of melanoma. To further validate our hyp

SUBMITTER: Sheng Z 

PROVIDER: S-EPMC7576265 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature