Zhang Xiaonan, Chen Cuncun, Wu Min, Chen Liang, Zhang Jiming, Zhang Xinxin, Zhang Zhanqin, Wu Jingdi, Wang Jiefei, Chen Xiaorong, Huang Tao, Chen Lixiang, Yuan Zhenghong
Research Unit, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Antivir Ther. 2012;17(7):1243-53. doi: 10.3851/IMP2401. Epub 2012 Sep 21.
Interferon (IFN) and pegylated interferon (PEG-IFN) treatment of chronic hepatitis B leads to a sustained virological response in a limited proportion of patients and has considerable side effects. To find novel markers associated with prognosis of IFN therapy, we investigated whether a pretreatment plasma microRNA profile could be used to predict early virological response to IFN.
We performed microRNA microarray analysis of plasma samples from 94 patients with chronic hepatitis B who received IFN therapy. The microRNA profiles from 13 liver biopsy samples were also measured. The OneR feature ranking and incremental feature selection method were used to rank and optimize the number of features in the model. Support vector machine prediction engine and jack-knife cross-validation were used to generate and evaluate the prediction model.
The optimized model consisting of 11 microRNAs yielded a 74.2% overall accuracy in the training group and was independently confirmed in the test group (71.4% accuracy). Univariate and multivariate logistic regression analyses confirmed its independent association with early virological response (OR=7.35; P=2.12×10(-5)). Combining the microRNA profile with the alanine aminotransferase level improved the overall accuracy from 73.4% to 77.3%. Co-transfection of an HBV replicative construct with microRNA mimics revealed that let-7f, miR-939 and miR-638 were functionally associated with the HBV life cycle.
The 11 microRNA signatures in plasma, together with basic clinical variables, might provide an accurate method to assist in medication decisions and improve the overall sustained response to IFN treatment.
干扰素（IFN）和聚乙二醇化干扰素（PEG - IFN）治疗慢性乙型肝炎仅能使有限比例的患者获得持续病毒学应答，且存在相当多的副作用。为了寻找与干扰素治疗预后相关的新标志物，我们研究了治疗前血浆微小RNA谱是否可用于预测对干扰素的早期病毒学应答。
我们对94例接受干扰素治疗的慢性乙型肝炎患者的血浆样本进行了微小RNA微阵列分析。还检测了13份肝活检样本的微小RNA谱。使用OneR特征排名和增量特征选择方法对模型中的特征进行排名和优化。支持向量机预测引擎和留一法交叉验证用于生成和评估预测模型。
由11种微小RNA组成的优化模型在训练组中的总体准确率为74.2%，并在测试组中得到独立验证（准确率为71.4%）。单因素和多因素逻辑回归分析证实其与早期病毒学应答独立相关（OR = 7.35；P = 2.12×10⁻⁵）。将微小RNA谱与丙氨酸转氨酶水平相结合可将总体准确率从73.4%提高到77.3%。用微小RNA模拟物与乙肝病毒复制构建体共转染表明，let - 7f、miR - 939和miR - 638在功能上与乙肝病毒生命周期相关。
血浆中的11种微小RNA特征，连同基本临床变量，可能为辅助用药决策和提高干扰素治疗的总体持续应答提供一种准确的方法。
