Shimazaki Hiroko, Uojima Haruki, Yamasaki Kazumi, Obayashi Tomomi, Fuseya Sayaka, Sato Takashi, Mizokami Masashi, Kuno Atsushi
Molecular & Cellular Glycoproteomics Research Group, Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science & Technology, Tsukuba 305-8565, Japan.
Precision System Science Co., Ltd., Matsudo 271-0064, Japan.
Molecules. 2024 Nov 28;29(23):5640. doi: 10.3390/molecules29235640.
Regular monitoring of patients with a history of hepatitis C virus (HCV) infection is critical for the detection and management of hepatocellular carcinoma (HCC). Mac-2 binding protein glycosylation isomer (M2BPGi) has been used to monitor fibrosis progression and predict HCC. However, HCC prediction based on M2BPGi has not been optimized. Here, we identified HCC risk-related glycan signatures of M2BP using a newly developed automated bead array with multiplexed lectins. Among 955 patients with HCV who achieved sustained virological response following direct-acting antiviral treatment, we compared M2BP glycosylation from sera of 42 patients diagnosed with HCC during follow-up and 43 without HCC (control) by the lectin microarray. At the HCC observation point, we found significant differences in 17 lectins. Using an automated bead array with 12 of 17 lectins, a principal component analysis (PCA) biplot differentiated HCC from control, along the PC1 axis, explaining 75.2% of variance. Based on PC1, we generated a scoring formula for an HCC-related glycosylation signature on M2BP (M2BPgs-HCC), showing good diagnostic performance for HCC ( = 2.92 × 10, AUC = 0.829). This automated multilectin bead array improved the ability of M2BP to detect HCC, providing a candidate test for HCC surveillance in combination with other HCC markers.
对丙型肝炎病毒(HCV)感染病史患者进行定期监测对于肝细胞癌(HCC)的检测和管理至关重要。Mac-2结合蛋白糖基化异构体(M2BPGi)已用于监测纤维化进展和预测HCC。然而,基于M2BPGi的HCC预测尚未得到优化。在此,我们使用新开发的带有多重凝集素的自动化磁珠阵列鉴定了M2BP的HCC风险相关聚糖特征。在955例接受直接抗病毒治疗后实现持续病毒学应答的HCV患者中,我们通过凝集素微阵列比较了随访期间诊断为HCC的42例患者和未患HCC的43例患者(对照组)血清中的M2BP糖基化情况。在HCC观察点,我们发现17种凝集素存在显著差异。使用包含17种凝集素中的12种的自动化磁珠阵列,主成分分析(PCA)双标图沿PC1轴将HCC与对照组区分开来,解释了75.2%的方差。基于PC1,我们生成了一个针对M2BP上HCC相关糖基化特征的评分公式(M2BPgs-HCC),其对HCC具有良好的诊断性能( = 2.92 × 10,AUC = 0.829)。这种自动化多凝集素磁珠阵列提高了M2BP检测HCC的能力,为结合其他HCC标志物进行HCC监测提供了一种候选检测方法。