Yao Weirong, Wang Kaiyu, Jiang Yu, Huang Zhufeng, Huang Yiyun, Yan Huihui, Huang Suhong, Chen Min, Liao Jian
Institute for Laboratory Medicine, The First Hospital of Longhai, Zhangzhou, Fujian 363199, P.R. China.
Institute for Laboratory Medicine, Fuzhou General Hospital of Nanjing Command (The 900th Hospital of Joint Logistic Support Force People's Liberation Army), Fuzhou, Fujian 350003, P.R. China.
Oncol Lett. 2020 Aug;20(2):1597-1606. doi: 10.3892/ol.2020.11727. Epub 2020 Jun 11.
Our previous study reported a method of using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to analyze the association between abnormal fucosylation of serum glycoproteins and the progression of hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC). In the present study, the aforementioned method was improved by focusing on fucosylated glycoproteins <10 kD, classification models were established and blind tests were performed on an enlarged sample size (n=299). According to the present results, the classification models had a sensitivity and specificity of 74.31 and 76.32%, respectively, to identify HCC among all serum samples, 81.65 and 83.08%, respectively, to distinguish HCC from HBV-associated cirrhosis and chronic hepatitis Band 88.99 and 84.62%, respectively, to distinguish HCC from HBV-associated cirrhosis. When combined with α-fetoprotein (AFP) measurements (AFP >20 ng/ml), the sensitivity and specificity of the models were significantly elevated to 80.73 and 87.37%, 87.16 and 90.00%, and 92.66 and 93.84%, respectively. In addition, the HBV-HCC vs. HBV-cirrhosis classification model was used to analyze serum samples collected from 9 patients with cirrhosis 1 year before they were diagnosed with HCC, and from 6 patients who had cirrhosis but developed no signs of HCC for the following 3 years. The model identified 7 patients (77.78%) with no significant clinical symptoms of HCC, and gave no false positive results, demonstrating that the classification models established in the present study may be useful for the early diagnosis of HCC. After isolation and purification, two proteins with differential expression were identified as isoform 1 of inter-α-trypsin inhibitor heavy chain 4 precursor, and thymosin β-4-like protein 3. These may be used as candidate markers for HCC diagnosis. Additionally, the present study indicates that defucosylation of serum glycoproteins may occur during the development and progression of HCC.
我们之前的研究报道了一种使用基质辅助激光解吸/电离飞行时间质谱分析法来分析血清糖蛋白岩藻糖基化异常与乙型肝炎病毒(HBV)相关肝细胞癌(HCC)进展之间关联的方法。在本研究中,通过聚焦于分子量小于10 kD的岩藻糖化糖蛋白对上述方法进行了改进,建立了分类模型,并对扩大后的样本量(n = 299)进行了盲法测试。根据目前的结果,分类模型在所有血清样本中识别HCC的灵敏度和特异度分别为74.31%和76.32%,在区分HCC与HBV相关肝硬化和慢性乙型肝炎时的灵敏度和特异度分别为81.65%和83.08%,在区分HCC与HBV相关肝硬化时的灵敏度和特异度分别为88.99%和84.62%。当与甲胎蛋白(AFP)测量值(AFP>20 ng/ml)联合使用时,模型的灵敏度和特异度分别显著提高到80.73%和87.37%、87.16%和90.00%、92.66%和93.84%。此外,使用HBV-HCC与HBV-肝硬化分类模型分析了9例肝硬化患者在被诊断为HCC前1年以及6例肝硬化但在随后3年未出现HCC迹象的患者所采集的血清样本。该模型识别出7例(77.78%)无明显HCC临床症状的患者,且未给出假阳性结果,表明本研究中建立的分类模型可能有助于HCC的早期诊断。经过分离和纯化,鉴定出两种差异表达的蛋白质,分别为α-胰蛋白酶抑制剂重链4前体同工型1和胸腺素β-4样蛋白3。这些蛋白可作为HCC诊断的候选标志物。此外,本研究表明血清糖蛋白的去岩藻糖基化可能发生在HCC的发生和发展过程中。