CpG Methylation Signature Predicts Recurrence in Early-Stage Hepatocellular Carcinoma: Results From a Multicenter Study

被引:2
作者
Qiu, Jiliang [1 ,4 ,5 ,6 ]
Peng, Baogang [2 ]
Tang, Yunqiang [6 ]
Qian, Yeben [7 ]
Guo, Pi [3 ]
Li, Mengfeng [3 ]
Luo, Junhang [2 ]
Chen, Bin [2 ]
Tang, Hui [6 ]
Lu, Canliang [7 ]
Cai, Muyan [1 ,4 ,5 ]
Ke, Zunfu [2 ]
He, Wei [1 ,4 ,5 ]
Zheng, Yun [1 ,4 ,5 ]
Xie, Dan [1 ,4 ,5 ]
Li, Binkui [1 ,4 ,5 ]
Yuan, Yunfei [1 ,4 ,5 ]
机构
[1] Sun Yat Sen Univ, Ctr Canc, Guangzhou, Guangdong, Peoples R China
[2] Sun Yat Sen Univ, Affiliated Hosp 1, Guangzhou, Guangdong, Peoples R China
[3] Sun Yat Sen Univ, Guangzhou, Guangdong, Peoples R China
[4] Guangzhou Med Univ, Ctr Canc, State Key Lab Oncol South China, Guangzhou, Guangdong, Peoples R China
[5] Guangzhou Med Univ, Ctr Canc, Collaborat Innovat Ctr Canc Med, Guangzhou, Guangdong, Peoples R China
[6] Guangzhou Med Univ, Ctr Canc, Guangzhou, Guangdong, Peoples R China
[7] Anhui Med Univ, Affiliated Hosp 1, Hefei, Peoples R China
关键词
RADIOFREQUENCY ABLATION; SURGICAL RESECTION; TUMOR-SUPPRESSOR; CANCER; LIVER; CLASSIFICATION; EXPRESSION; HEPATITIS; DIAGNOSIS; BIOMARKER;
D O I
10.1200/JCO.2016.68.2153
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Purpose Early-stage hepatocellular carcinoma (E-HCC) is being diagnosed increasingly, and in one half of diagnosed patients, recurrence will develop. Thus, it is urgent to identify recurrence-related markers. We investigated the effectiveness of CpG methylation in predicting recurrence for patients with E-HCCs. Patients and Methods In total, 576 patients with E-HCC from four independent centers were sorted by three phases. In the discovery phase, 66 tumor samples were analyzed using the Illumina Methylation 450k Beadchip. Two algorithms, Least Absolute Shrinkage and Selector Operation and Support Vector Machine-Recursive Feature Elimination, were used to select significant CpGs. In the training phase, penalized Cox regression was used to further narrow CpGs into 140 samples. In the validation phase, candidate CpGs were validated using an internal cohort (n = 141) and two external cohorts (n = 191 and n = 104). Results After combining the 46 CpGs selected by the Least Absolute Shrinkage and Selector Operation and the Support Vector Machine-Recursive Feature Elimination algorithms, three CpGs corresponding to SCAN domain containing 3, Src homology 3-domain growth factor receptor-bound 2-like interacting protein 1, and peptidase inhibitor 3 were highlighted as candidate predictors in the training phase. On the basis of the three CpGs, a methylation signature for E-HCC (MSEH) was developed to classify patients into high-and low-risk recurrence groups in the training cohort (P < .001). The performance of MSEH was validated in the internal cohort (P < .001) and in the two external cohorts (P < .001; P = .002). Furthermore, a nomogram comprising MSEH, tumor differentiation, cirrhosis, hepatitis B virus surface antigen, and antivirus therapy was generated to predict the 5-year recurrence-free survival in the training cohort, and it performed well in the three validation cohorts (concordance index: 0.725, 0.697, and 0.693, respectively). Conclusion MSEH, a three-CpG-based signature, is useful in predicting recurrence for patients with E-HCC. (C) 2017 by American Society of Clinical Oncology
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页码:734 / +
页数:10
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