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

2019; Wiley; Volume: 23; Issue: 5 Linguagem: Inglês

10.1111/jcmm.14231

1582-4934

Rui‐Zhao Dong, Xuan Yang, Xinyu Zhang, Pingting Gao, Ai‐Wu Ke, Hui‐Chuan Sun, Jian Zhou, Jia Fan, Jia‐Bin Cai, Guo‐Ming Shi,

Ferroptosis and cancer prognosis

Abstract Hepatocellular carcinoma (HCC) is closely associated with abnormal DNA methylation. 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.