An 11-gene-based prognostic signature for uveal melanoma metastasis based on gene expression and DNA methylation profile.
J Cell Biochem
; 120(5): 8630-8639, 2019 May.
Article
em En
| MEDLINE
| ID: mdl-30556166
ABSTRACT
Uveal melanoma (UM) is the most common intraocular tumor worldwide. We proposed to identify a vital gene signature that has prognostic value for UM metastasis. For this purpose, we obtained a published DNA methylation and gene expression data set associated with UM from the Gene Expression Omnibus. The genes whose aberrant expression significantly associated with UM patients' metastasis-free survival (MFS) were identified by applying a univariate Cox proportional hazards model to the gene expression data set followed by a robust likelihood-based survival analysis to screen the optimal prognostic gene signatures (PGS). A formula for calculating the risk score that represents UM metastasis risk was constructed by including the PGSs' expression values weighted by their regression coefficients, which were obtained by a multivariate Cox regression analysis. As a result, aberrant expression of 2884 genes were found to be significantly associated with UM patients' MFS, which were referred to as MFSGs, and 11 out of those MFSGs, GJC1, TCEA1, MFSD3, FAF2, TLCD1, GPAA1, CYC1, ASAP1, JPH1, LDB3, and KDELR3, were identified as PGSs through which we could accurately separate UM samples with shorter MFS from those with longer MFS. By combining the DNA methylation data set and MFSGs, we further identified 265 MFSGs, which contained CpG sites that significantly hyper- or hypo-methylated in UM samples compared with control samples. Functional enrichment analysis and pathway crosstalk analysis of those genes indicated significant enrichment of cancer-related pathways. In conclusion, we identified an 11-gene-based prognostic signature and several gene biomarkers for UM metastasis, which should be helpful for selecting an appropriate treatment method for specific patients with UM.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article