Literature DB >> 28068175

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

Jiliang Qiu1, Baogang Peng1, Yunqiang Tang1, Yeben Qian1, Pi Guo1, Mengfeng Li1, Junhang Luo1, Bin Chen1, Hui Tang1, Canliang Lu1, Muyan Cai1, Zunfu Ke1, Wei He1, Yun Zheng1, Dan Xie1, Binkui Li1, Yunfei Yuan1.   

Abstract

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.

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Year:  2017        PMID: 28068175     DOI: 10.1200/JCO.2016.68.2153

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  46 in total

1.  Myeloid signature reveals immune contexture and predicts the prognosis of hepatocellular carcinoma.

Authors:  Chong Wu; Jie Lin; Yulan Weng; Dan-Ni Zeng; Jing Xu; Shufeng Luo; Li Xu; Mingyu Liu; Qiaomin Hua; Chao-Qun Liu; Jin-Qing Li; Jing Liao; Cheng Sun; Jian Zhou; Min-Shan Chen; Chao Liu; Zhenhong Guo; Shi-Mei Zhuang; Jin-Hua Huang; Limin Zheng
Journal:  J Clin Invest       Date:  2020-09-01       Impact factor: 14.808

2.  Promoter aberrant methylation status of ADRA1A is associated with hepatocellular carcinoma.

Authors:  Guoqiao Chen; Xiaoxiao Fan; Yirun Li; Lifeng He; Shanjuan Wang; Yili Dai; Cui Bin; Daizhan Zhou; Hui Lin
Journal:  Epigenetics       Date:  2020-01-14       Impact factor: 4.528

3.  Machine Learning to Improve Prognosis Prediction of Early Hepatocellular Carcinoma After Surgical Resection.

Authors:  Gu-Wei Ji; Ye Fan; Dong-Wei Sun; Ming-Yu Wu; Ke Wang; Xiang-Cheng Li; Xue-Hao Wang
Journal:  J Hepatocell Carcinoma       Date:  2021-08-10

4.  Evaluation of the effect of ultrasound interventional injection of cisplatin in the treatment of liver cancer.

Authors:  Tao Zhang; Shengkai Cheng; Jianbo Li; Yangyang Shang; Mingyou Zheng
Journal:  Am J Transl Res       Date:  2021-05-15       Impact factor: 4.060

5.  A Gene-Expression Predictor for Efficacy of Induction Chemotherapy in Locoregionally Advanced Nasopharyngeal Carcinoma.

Authors:  Yuan Lei; Ying-Qin Li; Wei Jiang; Xiao-Hong Hong; Wen-Xiu Ge; Yuan Zhang; Wei-Han Hu; Ya-Qin Wang; Ye-Lin Liang; Jun-Yan Li; William C S Cho; Jing-Ping Yun; Jing Zeng; Jie-Wei Chen; Li-Zhi Liu; Li Li; Lei Chen; Fang-Yun Xie; Wen-Fei Li; Yan-Ping Mao; Xu Liu; Yu-Pei Chen; Ling-Long Tang; Ying Sun; Na Liu; Jun Ma
Journal:  J Natl Cancer Inst       Date:  2021-04-06       Impact factor: 13.506

6.  Development and validation of survival nomograms in colorectal cancer patients with synchronous liver metastases underwent simultaneous surgical treatment of primary and metastatic lesions.

Authors:  Xiao Guo; Yang Liu; Lu-Jia Liu; Jun Li; Lei Zhao; Xiang-Ren Jin; Wei Yan; Bai-Qiang Lin; Shang Shi; Zhi-Yong Li; Shuang Wang; Xin Wu; Hong-Ye Chen; Yang Shen; Yun-Wei Wei
Journal:  Am J Cancer Res       Date:  2021-06-15       Impact factor: 6.166

7.  A Nomogram Based on a Collagen Feature Support Vector Machine for Predicting the Treatment Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients.

Authors:  Wei Jiang; Min Li; Jie Tan; Mingyuan Feng; Jixiang Zheng; Dexin Chen; Zhangyuanzhu Liu; Botao Yan; Guangxing Wang; Shuoyu Xu; Weiwei Xiao; Yuanhong Gao; Shuangmu Zhuo; Jun Yan
Journal:  Ann Surg Oncol       Date:  2021-06-19       Impact factor: 5.344

8.  SNRPC promotes hepatocellular carcinoma cell motility by inducing epithelial-mesenchymal transition.

Authors:  Yuanping Zhang; Jiliang Qiu; Dinglan Zuo; Yichuan Yuan; Yuxiong Qiu; Liang Qiao; Wei He; Binkui Li; Yunfei Yuan
Journal:  FEBS Open Bio       Date:  2021-05-12       Impact factor: 2.693

9.  Genomewide transcriptomic profiling identifies a gene signature for predicting recurrence in early-stage hepatocellular carcinoma.

Authors:  Tatsuhiko Kakisaka; Moto Fukai; Jasjit K Banwait; Toshiya Kamiyama; Tatsuya Orimo; Tomoko Mitsuhashi; Kensuke Yamamura; Takeo Toshima; Hideo Baba; Akinobu Taketomi; Ajay Goel
Journal:  Clin Transl Med       Date:  2021-06

10.  Down-regulation of EGFL8 regulates migration, invasion and apoptosis of hepatocellular carcinoma through activating Notch signaling pathway.

Authors:  Fan Wu; Fang-Yong Zhang; Guo-Qian Tan; Wei-Jia Chen; Biao Huang; Lun Yan; Hao-Lu Zhang; Shi Chen; Yang Jiao; Bai-Lin Wang
Journal:  BMC Cancer       Date:  2021-06-15       Impact factor: 4.430

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