A Novel Promoter CpG-Based Signature for Long-Term Survival Prediction of Breast Cancer Patients

Frontiers in Oncology
Yang GuoFeng Jin

Abstract

DNA methylation has been reported as one of the most critical epigenetic aberrations during the tumorigenesis and development of breast cancer (BC). This study explored a novel promoter CpG-based signature for long-term survival prediction of BC patients. We used The Cancer Genome Atlas (TCGA) data as training set, and results were validated in an independent dataset from Gene Expression Omnibus (GEO). First, the differential methylation CpG sites were screened in TCGA dataset, of which the candidate promoter CpG sites were preliminarily identified with the univariate Cox regression analysis and the least absolute shrinkage and selection operator regression analysis. Second, the signature was constructed with stepwise regression analysis and multivariate Cox proportional hazards model, which was validated with the survival analysis of two cohorts each from TCGA and GEO databases. The 10-year receiver operating characteristic curves of risk score presented an area under the curve of over 0.7 for both cohorts. A nomogram was also constructed and released. Moreover, Gene Set Enrichment Analysis was performed to identify the more active pathways in high-risk patients. The CpG sites-target gene correlations and differential methylat...Continue Reading

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Citations

Sep 2, 2021·Biochemistry and Biophysics Reports·Zhishuai RenYuqi Guo

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Datasets Mentioned

BETA
GSE72308

Methods Mentioned

BETA
Chip
RNA-Seq

Software Mentioned

ChAMP R
glmnet
GSEA
ggpubr R package
Gene Set Enrichment Analysis ( GSEA )
LASSO
pheatmap R
metascape
R package
ChAMP R package

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