A CpG-methylation-based assay to predict survival in clear cell renal cell carcinoma

Jin-Huan Wei, Ahmed Haddad, Kai-Jie Wu, Hong-Wei Zhao, Payal Kapur, Zhi-Ling Zhang, Liang-Yun Zhao, Zhen-Hua Chen, Yun-Yun Zhou, Jian-Cheng Zhou, Bin Wang, Yan-Hong Yu, Mu-Yan Cai, Dan Xie, Bing Liao, Cai-Xia Li, Pei-Xing Li, Zong-Ren Wang, Fang-Jian Zhou, Lei Shi, Qing-Zuo Liu, Zhen-Li Gao, Da-Lin He, Wei Chen, Jer-Tsong Hsieh, Quan-Zhen Li, Vitaly Margulis and Jun-Hang Luo ()
Additional contact information
Jin-Huan Wei: First Affiliated Hospital, Sun Yat-sen University
Ahmed Haddad: University of Texas Southwestern Medical Center at Dallas
Kai-Jie Wu: First Affiliated Hospital of Xi’an Jiaotong University
Hong-Wei Zhao: Affiliated Yantai Yuhuangding Hospital, Qingdao University Medical College
Payal Kapur: University of Texas Southwestern Medical Center at Dallas
Zhi-Ling Zhang: Cancer Center, Sun Yat-sen University
Liang-Yun Zhao: Affiliated Hospital of Kunming University of Science and Technology
Zhen-Hua Chen: First Affiliated Hospital, Sun Yat-sen University
Yun-Yun Zhou: Quantitive Biomedical Research Center, University of Texas Southwestern Medical Center at Dallas
Jian-Cheng Zhou: University of Texas Southwestern Medical Center at Dallas
Bin Wang: University of Texas Southwestern Medical Center at Dallas
Yan-Hong Yu: Affiliated Hospital of Kunming University of Science and Technology
Mu-Yan Cai: Cancer Center, Sun Yat-sen University
Dan Xie: Cancer Center, Sun Yat-sen University
Bing Liao: First Affiliated Hospital, Sun Yat-sen University
Cai-Xia Li: School of Mathematics and Computational Science, Sun Yat-sen University
Pei-Xing Li: School of Mathematics and Computational Science, Sun Yat-sen University
Zong-Ren Wang: First Affiliated Hospital, Sun Yat-sen University
Fang-Jian Zhou: Cancer Center, Sun Yat-sen University
Lei Shi: Affiliated Yantai Yuhuangding Hospital, Qingdao University Medical College
Qing-Zuo Liu: Affiliated Yantai Yuhuangding Hospital, Qingdao University Medical College
Zhen-Li Gao: Affiliated Yantai Yuhuangding Hospital, Qingdao University Medical College
Da-Lin He: First Affiliated Hospital of Xi’an Jiaotong University
Wei Chen: First Affiliated Hospital, Sun Yat-sen University
Jer-Tsong Hsieh: University of Texas Southwestern Medical Center at Dallas
Quan-Zhen Li: University of Texas Southwestern Medical Center at Dallas
Vitaly Margulis: University of Texas Southwestern Medical Center at Dallas
Jun-Hang Luo: First Affiliated Hospital, Sun Yat-sen University

Nature Communications, 2015, vol. 6, issue 1, 1-11

Abstract: Abstract Clear cell renal cell carcinomas (ccRCCs) display divergent clinical behaviours. Molecular markers might improve risk stratification of ccRCC. Here we use, based on genome-wide CpG methylation profiling, a LASSO model to develop a five-CpG-based assay for ccRCC prognosis that can be used with formalin-fixed paraffin-embedded specimens. The five-CpG-based classifier was validated in three independent sets from China, United States and the Cancer Genome Atlas data set. The classifier predicts the overall survival of ccRCC patients (hazard ratio=2.96−4.82; P=3.9 × 10−6−2.2 × 10−9), independent of standard clinical prognostic factors. The five-CpG-based classifier successfully categorizes patients into high-risk and low-risk groups, with significant differences of clinical outcome in respective clinical stages and individual ‘stage, size, grade and necrosis’ scores. Moreover, methylation at the five CpGs correlates with expression of five genes: PITX1, FOXE3, TWF2, EHBP1L1 and RIN1. Our five-CpG-based classifier is a practical and reliable prognostic tool for ccRCC that can add prognostic value to the staging system.

Date: 2015
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DOI: 10.1038/ncomms9699

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