Zhu Hao-Tu, Liu Rong-Bin, Liang Ya-Yong, Hasan Abdulbaqi M E, Wang Hai-Yun, Shao Qiong, Zhang Zi-Chen, Wang Jing, He Cai-Yun, Wang Fang, Shao Jian-Yong
State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Department of Molecular Diagnostics, Sun Yat-sen University Cancer Center, Guangzhou, China.
Liver Int. 2017 Jun;37(6):888-896. doi: 10.1111/liv.13356. Epub 2017 Feb 3.
BACKGROUND & AIMS: The discovery of effective and reliable biomarkers to detect hepatitis B virus (HBV)-positive hepatocellular carcinoma (HCC) at an early stage may improve the survival of HCC. The aim of this study was to establish serum microRNA (miRNA) profiles as diagnostic biomarkers for HBV-positive HCC.
We used deep sequencing to screen serum miRNAs in a discovery cohort (n=100). Quantitative polymerase chain reaction (qPCR) assays were then applied to evaluate the expression of selected miRNAs. A diagnostic 2-miRNA panel was established by a logistic regression model using a training cohort (n=182). The predicted probability of being detected as HCC was used to construct the receiver operating characteristic (ROC) curve. Area under the ROC curve (AUC) was used to assess the diagnostic performance of the selected miRNA panel.
The predicted probability of being detected as HCC by the 2-miRNA panel was calculated by: logit P=-2.988 + 1.299 × miR-27b-3p + 1.245 × miR-192-5p. These results were further confirmed in a validation cohort (n=246).The miRNA panel provided a high diagnostic accuracy of HCC (AUC=0.842, P<.0001 for training set; AUC=0.836, P<.0001 for validation set respectively). In addition, the miRNA panel showed better prediction of HCC diagnosis than did alpha-foetoprotein (AFP). The miRNA panel also differentiated HCC from healthy (AUC=0.823, P<.0001), and cirrhosis patients (AUC=0.859, P<.0001) respectively.
Differentially expressed serum miRNAs may have considerable clinical value in HCC diagnosis, and be particularly helpful for AFP-negative HCC.
发现有效且可靠的生物标志物以早期检测乙型肝炎病毒（HBV）阳性肝细胞癌（HCC），可能会提高HCC患者的生存率。本研究旨在建立血清微小RNA（miRNA）谱作为HBV阳性HCC的诊断生物标志物。
我们在一个发现队列（n = 100）中使用深度测序筛选血清miRNA。然后应用定量聚合酶链反应（qPCR）分析来评估所选miRNA的表达。使用训练队列（n = 182）通过逻辑回归模型建立诊断性2-miRNA组合。被检测为HCC的预测概率用于构建受试者工作特征（ROC）曲线。ROC曲线下面积（AUC）用于评估所选miRNA组合的诊断性能。
通过2-miRNA组合被检测为HCC的预测概率通过以下公式计算：logit P = -2.988 + 1.299×miR-27b-3p + 1.245×miR-192-5p。这些结果在验证队列（n = 246）中得到进一步证实。该miRNA组合对HCC具有较高的诊断准确性（训练集AUC = 0.842，P <.0001；验证集AUC = 0.836，P <.0001）。此外，该miRNA组合对HCC诊断的预测能力优于甲胎蛋白（AFP）。该miRNA组合还分别将HCC与健康人（AUC = 0.823，P <.0001）和肝硬化患者（AUC = 0.859，P <.0001）区分开来。
差异表达的血清miRNA在HCC诊断中可能具有重要的临床价值，对AFP阴性的HCC尤其有帮助。
