Screening of differentially methylated genes in breast cancer and risk model construction based on TCGA database

Differentially methylated genes in breast cancer were screened out and a prognostic risk model of breast cancer was constructed. RNA-seq data and methylation data for breast cancer-related level 3 were downloaded from The Cancer Genome Atlas (TCGA), and MethylMix R package was used to screen out differentially methylated genes in cancer tissues and normal tissues. DAVID was used to analyze the GO enrichment of differentially methylated genes, ConsensusPathDB to analyze the PATHWAY pathways of differentially methylated genes, the single factor, multivariate Cox analysis and Akaike Information Criterion (AIC) to construct the prognostic risk model of breast cancer, and the ROC curve to judge the clinical application value of the risk model. Two hundred and fifty-seven differentially methylated genes were successfully screened out in cancer tissues and normal tissues; 39 related to GO enrichments and 19 related to PATHWAY pathways were found; the best prognostic risk model was obtained, risk score = QRFP (degree of methylation) × (−3.657) + S100A16 × (−3.378) + TDRD1 × (−4.001) + SMO × (3.548); it was determined from each sample that the median value of the risk score was 0.936; using it as the cut-off value, the five-year survival rate in high-risk group of patients was 72.4% (95% CI, 62.7–83.6%), and that in low-risk group of patients was 86.6% (95% CI, 78.6–95.3%). The difference in the survival rate between the high-risk and low-risk groups was significant (P<0.001). The AUC of ROC curve was 0.791, so the model had a good clinical application value. This study successfully found multiple breast cancer-related methylation genes, the relationship between them and the course and prognosis of breast cancer was analyzed. Moreover, a prognostic risk model was constructed, which facilitated the expansion of the current study on the role of methylation in the occurrence and development of breast cancer.