Computational Detection of Breast Cancer Invasiveness with DNA Methylation Biomarkers.

ABSTRACT: Breast cancer is the most common female malignancy. It has high mortality, primarily due to metastasis and recurrence. Patients with invasive and noninvasive breast cancer require different treatments, so there is an urgent need for predictive tools to guide clinical decision making and avoid overtreatment of noninvasive breast cancer and undertreatment of invasive cases. Here, we divided the sample set based on the genome-wide methylation distance to make full use of metastatic cancer data. Specifically, we implemented two differential methylation analysis methods to identify specific CpG sites. After effective dimensionality reduction, we constructed a methylation-based classifier using the Random Forest algorithm to categorize the primary breast cancer. We took advantage of breast cance

SUBMITTER: Wang C 

PROVIDER: S-EPMC7072524 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature