1. Additional file 1: of Large-scale analysis of DFNA5 methylation reveals its potential as biomarker for breast cancer
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Lieselot Croes, Beyens, Matthias, Fransen, Erik, Ibrahim, Joe, Berghe, Wim Vanden, Suls, Arvid, Peeters, Marc, Pauwels, Patrick, Camp, Guy Van, and Beeck, Ken Op De
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skin and connective tissue diseases - Abstract
Table S1. Mean difference in DFNA5 methylation between the paired tumor and normal breast sample in 79 patients for every of the 22 CpGs. Figure S1. DFNA5 methylation (in the gene promoter and in the gene body) and expression (microarray and RNA-seq) in paired tumor and normal breast samples. Figure S2. Correlation between microarray and RNA-seq expression data. Table S2. Stepwise linear regression models of DFNA5 microarray expression on DFNA5 methylation for both breast adenocarcinoma and normal breast samples. Table S3. Stepwise linear regression model of DFNA5 RNA-seq expression on DFNA5 methylation for the breast adenocarcinomas. Figure S3. DFNA5 expression as biomarker for breast adenocarcinomas. Table S4. Mean DFNA5 methylation for the ductal and the lobular breast adenocarcinomas for every of the 22 CpGs. Table S5. Mean DFNA5 methylation for ER status, PR status, and HER2 status for every of the 22 CpGs. Table S6. Mean DFNA5 expression for ER+ and ERâ breast adenocarcinomas. Table S7. Mean DFNA5 methylation for the four tumor stages for every of the 22 CpGs. Table S8.Vital status of the breast adenocarcinoma patients after 5Â years of follow-up. Table S9. False discovery rate (FDR) for 5-year OS analysis on all breast adenocarcinomas and ductal breast adenocarcinomas. Table S10. Concordance for 5-year OS analysis on all breast adenocarcinomas. Table S11. Concordance for 5-year OS analysis on ductal breast adenocarcinomas. Table S12. Similarities and differences between three studies investigating DFNA5 methylation in breast cancer. Table S13. Single nucleotide variants in the DFNA5 gene with corresponding changes in the amino acid sequence of DFNA5. Table S14. Three methylation datasets from the Gene Expression Omnibus (GEO) for validation of our model to predict the tumor status. (DOCX 629 kb)
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- 2018
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