Predicting overall survival of patients with hepatocellular carcinoma using a three-category method based on DNA methylation and machine learning.

In this study, we analyzed 450K methylation chip data from 377 HCC samples and 50 adjacent normal samples in the TCGA database. We screened 47,099 differentially methylated sites using Cox regression as well as SVM-RFE and FW-SVM algorithms, and constructed a model using three risk categories to predict the overall survival based on 134 methylation sites. The model showed a 10-fold cross-validation score of 0.95 and satisfactory predictive power, and correctly classified 26 of 33 samples in testing set obtained by stratified sampling from high, intermediate and low risk groups. PMID: 30784182 [PubMed - as supplied by publisher]

https://www.ncbi.nlm.nih.gov/pubmed/30784182?dopt=Abstract

Source: J Cell Mol Med - February 19, 2019 Category: Molecular Biology Authors: Dong RZ, Yang X, Zhang XY, Gao PT, Ke AW, Sun HC, Zhou J, Fan J, Cai JB, Shi GM Tags: J Cell Mol Med Source Type: research