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• W2480709584 abstract "// Lei Wang 1, 2, 3 , Xin Hu 1, 2, 3 , Peng Wang 4, 5 , Zhi-Ming Shao 1, 2, 3, 6 1 Department of Breast Surgery, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China 2 Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China 3 Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China 4 Key Laboratory of Systems Biology, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China 5 School of Life Science and Technology, ShanghaiTech University, Shanghai, China 6 Institutes of Biomedical Sciences, Fudan University, Shanghai, China Corresponding to: Zhi-Ming Shao, email: zhimingshao@yahoo.com Peng Wang, email: wangpeng@sari.ac.cn Xin Hu, email: xinhu@fudan.edu.cn Keywords: prognostic modeling, 3′ untranslated region, alternative polyadenylation, triple-negative breast cancer, biomarker Received: February 6, 2016     Accepted: July 18, 2016     Published: August 01, 2016 ABSTRACT Triple-negative breast cancer (TNBC) is a highly heterogeneous disease with an aggressive clinical course. Prognostic models are needed to chart potential patient outcomes. To address this, we used alternative 3′UTR patterns to improve postoperative risk stratification. We collected 327 publicly available microarrays and generated the 3′UTR landscape based on expression ratios of alternative 3′UTR. After initial feature filtering, we built a 17-3′UTR-based classifier using an elastic net model. Time-dependent ROC comparisons and Kaplan–Meier analyses confirmed an outstanding discriminating power of our prognostic model for TNBC patients. In the training cohort, 5-year event-free survival (EFS) was 78.6% (95% CI 71.2–86.0) for the low-risk group, and 16.3% (95% CI 2.3–30.4) for the high-risk group (log-rank p <0.0001; hazard ratio [HR] 8.29, 95% CI 4.78–14.4), In the validation set, 5-year EFS was 75.6% (95% CI 68.0–83.2) for the low-risk group, and 33.2% (95% CI 17.1–49.3) for the high-risk group (log-rank p <0.0001; HR 3.17, 95% CI 1.66–5.42). In conclusion, the 17-3′UTR-based classifier provides a superior prognostic performance for estimating disease recurrence and metastasis in TNBC patients and it may permit personalized management strategies." @default.
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• W2480709584 date "2016-08-01" @default.
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• W2480709584 title "The 3′UTR signature defines a highly metastatic subgroup of triple-negative breast cancer" @default.
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• W2480709584 doi "https://doi.org/10.18632/oncotarget.10975" @default.
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