Du F, Yuan P, Zhao Z T, Yang Z, Wang T, Zhao J D, Luo Y, Ma F, Wang J Y, Fan Y, Cai R G, Zhang P, Li Q, Song Y M, Xu B H
Department of Medical Oncology, Cancer Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, National Cancer Center, Beijing, China.
The VIPII Gastrointestinal Cancer Division of Medical Department, Peking University Cancer Hospital and Institute, 52 Fucheng Road, Haidian District, Beijing, China.
Sci Rep. 2016 Sep 21;6:33825. doi: 10.1038/srep33825.
Approximately 20% of HER2 positive breast cancer develops disease recurrence after adjuvant trastuzumab treatment. This study aimed to develop a molecular prognostic model that can reliably stratify patients by risk of developing disease recurrence. Using miRNA microarrays, nine miRNAs that differentially expressed between the recurrent and non-recurrent patients were identified. Then, we validated the expression of these miRNAs using qRT-PCR in training set (n = 101), and generated a 2-miRNA (miR-4734 and miR-150-5p) based prognostic signature. The prognostic accuracy of this classifier was further confirmed in an internal testing set (n = 57), and an external independent testing set (n = 53). Besides, by comparing the ROC curves, we found the incorporation of this miRNA based classifier into TNM stage could improve the prognostic performance of TNM system. The results indicated the 2-miRNA based signature was a reliable prognostic biomarker for patients with HER2 positive breast cancer.
约20%的HER2阳性乳腺癌患者在辅助曲妥珠单抗治疗后会出现疾病复发。本研究旨在开发一种分子预后模型,该模型能够可靠地根据疾病复发风险对患者进行分层。通过miRNA微阵列,我们鉴定出9种在复发患者和未复发患者之间差异表达的miRNA。然后,我们在训练集(n = 101)中使用qRT-PCR验证了这些miRNA的表达,并生成了基于2种miRNA(miR-4734和miR-150-5p)的预后特征。该分类器的预后准确性在内部测试集(n = 57)和外部独立测试集(n = 53)中得到进一步证实。此外,通过比较ROC曲线,我们发现将基于这种miRNA的分类器纳入TNM分期可以提高TNM系统的预后性能。结果表明,基于2种miRNA的特征是HER2阳性乳腺癌患者可靠的预后生物标志物。