Breast cancer diagnosis by analysis of serum N-glycans using MALDI-TOF mass spectroscopy

Blood and serum N-glycans can be used as markers for cancer diagnosis, as alterations in protein glycosylation are associated with cancer pathogenesis and progression. We aimed to develop a platform for breast cancer (BrC) diagnosis based on serum N-glycan profiles using MALDI-TOF mass spectroscopy. Serum N-glycans from BrC patients and healthy volunteers were evaluated using NosQuest’s software “NosIDsys.” BrC-associated “NosID” N-glycan biomarkers were selected based on abundance and NosIDsys analysis, and their diagnostic potential was determined using NosIDsys and receiver operating characteristic curves. Results showed an efficient pattern recognition of invasive ductal carcinoma patients, with very high diagnostic performance [area under the curve (AUC): 0.93 and 95% confidence interval (CI): 0.917–0.947]. We achieved effective stage-specific differentiation of BrC patients from healthy controls with 82.3% specificity, 84.1% sensitivity, and 82.8% accuracy for stage 1 BrC and recognized hormone receptor-2 and lymph node invasion subtypes based on N-glycan profiles. Our novel technique supplements conventional diagnostic strategies for BrC detection and can be developed as an independent platform for BrC screening.

血液与血清N-聚糖（N-glycans）可作为癌症诊断的标志物，因为蛋白质糖基化的改变与癌症的发病机制及进展密切相关。本研究旨在基于血清N-聚糖谱图，利用基质辅助激光解吸电离飞行时间质谱（MALDI-TOF mass spectroscopy）开发一款用于乳腺癌（BrC）诊断的检测平台。本研究通过NosQuest公司的“NosIDsys”软件，对乳腺癌患者与健康志愿者的血清N-聚糖进行了分析评估。研究人员基于聚糖丰度与NosIDsys分析结果，筛选出与乳腺癌相关的“NosID”型N-聚糖生物标志物，并通过NosIDsys软件与受试者工作特征曲线（receiver operating characteristic curves，ROC）评估其诊断潜能。研究结果显示，该平台可有效识别浸润性导管癌患者，诊断性能极佳：曲线下面积（area under the curve, AUC）为0.93，95%置信区间（confidence interval, CI）为0.917~0.947。本研究可有效区分不同分期的乳腺癌患者与健康对照：针对Ⅰ期乳腺癌患者，其特异性达82.3%、敏感性达84.1%、准确率达82.8%；同时可基于N-聚糖谱图识别激素受体2型与淋巴结侵袭亚型。本研究提出的新型技术可作为现有乳腺癌检测常规诊断策略的补充手段，且有望开发为一款独立的乳腺癌筛查平台。