中国学者发现基因表达特征可预测曲妥珠单抗辅助治疗乳腺癌的疾病复发

　　2016年9月21日，英国《自然》旗下《科学报告》在线发表中国医学科学院北京协和医学院肿瘤医院、国家癌症中心、北京大学肿瘤医院杜丰、袁芃、Zhao ZT、Yang Z、Wang T、Zhao JD、罗杨、马飞、王佳玉、樊英、蔡锐刚、张频、李青、宋咏梅、徐兵河（通讯作者）的研究报告，发现通过微核糖核酸（miRNA、miR）表达特征可预测曲妥珠单抗辅助治疗HER2阳性乳腺癌后的疾病复发。

　　大约有20%的HER2阳性乳腺癌在曲妥珠单抗辅助治疗后疾病复发。该研究为了建立一种根据疾病复发风险对患者进行精准分层的分子预后模型，首先利用miRNA微阵列（芯片）确定复发和非复发患者的9种miRNA不同表达。随后，在演算组（101例）利用实时定量聚合酶链反应（qRT-PCR）验证这些miRNA的表达，并获得包括2种miRNA（miR-4734和miR-150-5p）的预后特征。最后，在内部测试组（57例）和外部独立测试组（53例）进一步证实该预后分类法的准确性。此外，通过比较受试者操作特征（ROC）曲线，发现该miRNA分类法结合TNM分期可提高TNM系统的预后作用。

　　结果表明，该双miRNA表达特征是HER2阳性乳腺癌患者的可靠预后指标。

　　该研究参与单位：复旦大学附属肿瘤医院、浙江省肿瘤医院、广东省人民医院、华中科技大学同济医学院附属同济医院、南方医科大学南方医院、中山大学肿瘤医院、四川大学华西医院、哈尔滨医科大学附属肿瘤医院、郑州大学附属肿瘤医院、中国医学科学院北京协和医学院北京协和医院。

Sci Rep. 2016 Sep 21;6:33825.

A miRNA-based signature predicts development of disease recurrence in HER2 positive breast cancer after adjuvant trastuzumab-based treatment.

Du F, Yuan P, Zhao ZT, Yang Z, Wang T, Zhao JD, Luo Y, Ma F, Wang JY, Fan Y, Cai RG, Zhang P, Li Q, Song YM, Xu BH.

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, Beijing, China; Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

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.

PMID: 27650797

DOI: 10.1038/srep33825