Guo Jiao, Jing Rui, Zhong Jian-Hong, Dong Xin, Li Yun-Xi, Liu Yin-Kun, Huang Tian-Ren, Zhang Chun-Yan
Experimental Department, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi, PR China.
Hematology Department, Affiliated Hospital of Binzhou Medical University, Yantai, Shandong, PR China.
Oncotarget. 2017 Jun 28;8(37):62011-62028. doi: 10.18632/oncotarget.18782. eCollection 2017 Sep 22.
Hepatocellular carcinoma (HCC) is one of the most common malignant tumors without effective diagnostic biomarkers. This study intended to dynamically analyze serum proteomics in different pathological stages of liver diseases, and discover potential diagnostic biomarkers for early HCC. Patients with hepatitis B virus (HBV) infection, liver cirrhosis (LC), or HCC together with healthy controls (HC) were enrolled. Proteins differentially expressed between groups were screened using isobaric tagging for relative and absolute quantitation (iTRAQ), and promising HCC biomarker candidates were subjected to bioinformatics analysis, including K-means clustering, gene ontology (GO) and string network analysis. Potential biomarkers were validated by Western blotting and enzyme-linked immunosorbent assay (ELISA), and their diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. Finally, 93 differentially expressed proteins were identified, of which 43 differed between HBV and HC, 70 between LC and HC, and 51 between HCC and HC. Expression levels of gelsolin (GELS) and sulfhydryl oxidase 1 (QSOX1) varied with disease state as follows: HC < HBV < LC < HCC. The reverse trend was observed with CD14. These iTRAQ results were confirmed by Western blotting and ELISA. Logistic regression and ROC curve analysis identified the optimal cut-off for alpha-fetoprotein (AFP), CD14 and AFP/CD14 was 191.4 ng/mL (AUC 0.646, 95%CI 0.467-0.825, sensitivity 31.6%, specificity 94.4%), 3.16 ng/mL (AUC 0.760, 95%CI 0.604-0.917, sensitivity 94.7%, specificity 50%) and 0.197 ng/mL (AUC 0.889, 95%CI 0.785-0.993, sensitivity 84.2%, specificity 83.3%) respectively. In conclusion, Assaying CD14 levels may complement AFP measurement for early detection of HCC.
肝细胞癌（HCC）是最常见的恶性肿瘤之一，目前尚无有效的诊断生物标志物。本研究旨在动态分析不同肝病病理阶段的血清蛋白质组学，寻找早期HCC潜在的诊断生物标志物。纳入乙型肝炎病毒（HBV）感染患者、肝硬化（LC）患者、HCC患者以及健康对照（HC）。采用相对和绝对定量的等压标签标记法（iTRAQ）筛选组间差异表达的蛋白质，并对有潜力的HCC生物标志物候选物进行生物信息学分析，包括K均值聚类、基因本体（GO）和STRING网络分析。通过蛋白质免疫印迹法和酶联免疫吸附测定（ELISA）验证潜在生物标志物，并使用受试者工作特征（ROC）曲线分析评估其诊断性能。最终，共鉴定出93种差异表达蛋白质，其中HBV组与HC组之间有43种，LC组与HC组之间有70种，HCC组与HC组之间有51种。凝溶胶蛋白（GELS）和巯基氧化酶1（QSOX1）的表达水平随疾病状态变化如下：HC < HBV < LC < HCC。CD14呈现相反趋势。蛋白质免疫印迹法和ELISA证实了这些iTRAQ结果。逻辑回归和ROC曲线分析确定甲胎蛋白（AFP）、CD14和AFP/CD14的最佳截断值分别为191.4 ng/mL（AUC 0.646，95%CI 0.467 - 0.825，灵敏度31.6%，特异性94.4%）、3.16 ng/mL（AUC 0.760，95%CI 0.604 - 0.917，灵敏度94.7%，特异性50%）和0.197 ng/mL（AUC 0.889，95%CI 0.785 - 0.993，灵敏度84.2%，特异性83.3%）。总之，检测CD14水平可能有助于补充AFP检测，用于早期HCC的诊断。
