期刊
ONCOTARGET
卷 7, 期 37, 页码 59834-59844出版社
IMPACT JOURNALS LLC
DOI: 10.18632/oncotarget.10975
关键词
prognostic modeling; 3 ' untranslated region; alternative polyadenylation; triple-negative breast cancer; biomarker
资金
- Shanghai Committee of Science and Technology, China [12DZ2260100]
- National Natural Science Foundation of China [31271413, 81602316]
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据