Bladder Cancer (BC) presents one of the highest recurrence rates amongst solid tumours and constitutes the second deadliest disease of the genitourinary track. Non-invasive identification of patients facing disease recurrence and/or progression remains one of the most critical and challenging aspects in disease management. To contribute to this goal, we demonstrate the potential of glycan-affinity glycoproteomics nanoplatforms for urinary biomarkers discovery in bladder cancer. Briefly, magnetic nanoprobes (MNP) coated with three broad-spectrum lectins, namely Concanavalin A (ConA; [email protected]), Wheat Germ Agglutinin (WGA; [email protected]), and Sambucus nigra (SNA; [email protected]), were used to selectively capture glycoproteins from the urine of low-grade and high-grade non-muscle invasive as well as muscle-invasive BC patients. Proteins were identified by nano-LC MALDI-TOF/TOF and data was curated using bioinformatics tools (UniProt, NetOGlyc, NetNGlyc, ClueGO app for Cytoscape and Oncomine) to highlight clinically relevant species. Accordingly, 63 glycoproteins were exclusively identified in cancer samples compared with healthy controls matching in age and gender. Specific glycoprotein sets exclusively found in low-grade non-muscle invasive bladder tumours may aid early diagnosis, while those only found in high-grade non-invasive and muscle-invasive tumours hold potential for accessing progression. Amongst these proteins is bladder cancer stem-cell marker CD44, which has been associated with poor prognosis. Orthogonal validation studies by slot-blotting demonstrated an elevation in urine CD44 levels of high-grade patients, which became more pronounced upon muscle-invasion, in mimicry of the primary tumour. These observations demonstrate the potential of [email protected] for identification of clinically relevant glycoproteomics signatures in bladder cancer. Future clinical validation in a larger and well characterized patient subset is required envisaging clinical translation of the results.

膀胱癌（BC）是实体瘤中复发率最高的疾病之一，是泌尿生殖道疾病中第二致命的疾病。面对疾病复发和/或进展的患者的非侵入性识别仍然是疾病管理中最关键和最具挑战性的方面之一。为了实现这一目标，我们证明了聚糖亲和糖蛋白组学纳米平台在膀胱癌中发现尿液生物标志物的潜力。简而言之，涂有三种广谱凝集素的磁性纳米探针（MNP），即伴刀豆球蛋白A（ConA； [电子邮件保护]），小麦胚芽凝集素（WGA； [电子邮件保护]）和黑接骨木（SNA； [受电子邮件保护]），用于从低级和高级非肌肉侵入性以及肌肉侵入性BC患者的尿液中选择性捕获糖蛋白。通过nano-LC MALDI-TOF / TOF鉴定蛋白质，并使用生物信息学工具（UniProt，NetOGlyc，NetNGlyc，Cytoscape和Oncomine的ClueGO应用程序）整理数据，以突出临床相关物种。因此，与年龄和性别相匹配的健康对照相比，仅在癌症样品中鉴定出63种糖蛋白。仅在低度非肌肉浸润性膀胱肿瘤中发现的特定糖蛋白组可能有助于早期诊断，而仅在高度非浸润性和肌肉浸润性肿瘤中发现的特定糖蛋白具有进入进展的潜力。在这些蛋白质中，有膀胱癌干细胞标记CD44，这与预后不良有关。通过缝隙印迹进行的正交验证研究表明，在模仿原发性肿瘤的过程中，高级患者的尿液CD44水平升高，在肌肉侵入时变得更加明显。这些观察结果证明了[电子邮件保护]的潜力，可用于鉴定膀胱癌中临床相关的糖蛋白组学特征。考虑到结果的临床翻译，需要在更大且特征明确的患者子集中进行未来的临床验证。这些观察结果证明了[电子邮件保护]的潜力，可用于鉴定膀胱癌中临床相关的糖蛋白组学特征。考虑到结果的临床翻译，需要在更大且特征明确的患者子集中进行未来的临床验证。这些观察结果证明了[电子邮件保护]的潜力，可用于鉴定膀胱癌中临床相关的糖蛋白组学特征。考虑到结果的临床翻译，需要在更大且特征明确的患者子集中进行未来的临床验证。