中国学者发现一种预测三阴性乳腺癌高转移亚组结局的新模型

　　三阴性乳腺癌（TNBC）是一种具有高度异质性的侵袭性疾病，因此需要潜在患者结局的预测模型。

　　2016年8月1日，美国《肿瘤标靶》在线发表复旦大学附属肿瘤医院、复旦大学上海医学院、中国科学院上海高等研究院、上海科技大学生命科学与技术学院、复旦大学生物医学研究院的研究报告，采用替代性3'非翻译区（UTR）特征标记模式提高术后风险分层。

　　该研究收集了327个可公开获得的微阵列芯片，并根据替代性3'UTR表达率生成3'UTR全图，过滤初始特征后，采用弹性网模型建立17-3'UTR分类法。时间依赖性受试者操作特征（ROC）曲线比较和卡普兰-迈耶生存曲线分析证实该三阴性乳腺癌患者预后模型的优秀识别能力。在实施队列中，低风险组5年无事件生存（EFS）为78.6%（95%置信区间：71.2～86.0），高风险组为16.3%（95%置信区间：2.3～30.4）（对数秩p＜0.0001，风险比为8.29，95%置信区间：4.78～14.4）；在验证队列中，低风险组5年EFS为75.6%（95%置信区间：68.0～83.2），高风险组为33.2%（95%置信区间：17.1～49.3）（对数秩p＜0.0001，风险比[HR]为3.17，95%置信区间：1.66～5.42）。

　　因此，17-3'UTR分类法为估计TNBC患者疾病复发和转移提供了优越的预后性能，并使个体化管理策略成为可能。

Oncotarget. 2016 Aug 1. [Epub ahead of print]

The 3'UTR signature defines a highly metastatic subgroup of triple-negative breast cancer.

Wang L, Hu X, Wang P, Shao ZM.

Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China; Shanghai Medical College, Fudan University, Shanghai, China; Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China; School of Life Science and Technology, ShanghaiTech University, Shanghai, China; Institutes of Biomedical Sciences, Fudan University, Shanghai, China.

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.

KEYWORDS: 3' untranslated region; alternative polyadenylation; biomarker; prognostic modeling; triple-negative breast cancer

PMID: 27494850

DOI: 10.18632/oncotarget.10975