Cao Yiqing, Qin Yulin, Cheng Qunxian, Zhong Jialiang, Han Bing, Li Yan
Department of Pharmaceutical Analysis, School of Pharmacy, Fudan University, Shanghai, 201203, China.
Department of Pharmacy, Minhang Hospital, Fudan University, Shanghai, 201100, China.
Talanta. 2025 Apr 1;285:127280. doi: 10.1016/j.talanta.2024.127280. Epub 2024 Nov 23.
Cervical cancer (CC) remains a critical public health issue, highlighting the importance of early detection. However, current methods such as cytological and HPV testing face challenges of invasiveness and low patient compliance. Exosomes, emerging as crucial in cancer diagnosis, offer promise due to their noninvasive, highly specificity, and abundant biomarkers. However, isolating exosomes efficiently remains challenging. In this study, we designed and synthesized a bifunctional affinity nanomaterial FeO @CD63-CLIKKPF, based on the synergistic interaction between its modified aptamer CD63 and peptide CLIKKPF, and CD63 protein and PS of exosomes which can achieve high specificity and high yield separation of urinary exosomes. Notably, the co-modified aptamer CD63 and peptide CLIKKPF not only enable efficient exosome isolation by leveraging dual-affinity mechanisms through a synergistic "AND" logic analysis, but also could be achieved on the FeO in one-step reaction at room temperature via Fe-S bonding. Combined with LC-MS/MS, we conducted exosome metabolomics analysis in healthy individuals and CC patients across various stages, and machine learning models demonstrated accurate classification (accuracy >0.822) and prediction capabilities for CC. Furthermore, six key metabolites indicative of CC progression were identified and validated in additional patient samples, highlighting their potential as biomarkers. Overall, this study establishes a novel method for exosome metabolomics in CC, offering insights for non-invasive early diagnosis and progression prediction on a large scale.
宫颈癌（CC）仍然是一个关键的公共卫生问题，凸显了早期检测的重要性。然而，目前的细胞学和HPV检测等方法面临着侵入性和患者依从性低的挑战。外泌体在癌症诊断中变得至关重要，因其具有非侵入性、高特异性和丰富的生物标志物而展现出前景。然而，高效分离外泌体仍然具有挑战性。在本研究中，我们基于修饰的适配体CD63与肽CLIKKPF之间的协同相互作用，设计并合成了一种双功能亲和纳米材料FeO@CD63-CLIKKPF，其CD63蛋白与外泌体的磷脂酰丝氨酸（PS）结合，可实现尿液外泌体的高特异性和高产率分离。值得注意的是，共修饰的适配体CD63和肽CLIKKPF不仅通过协同的“与”逻辑分析利用双亲和机制实现了外泌体的高效分离，而且还可以在室温下通过Fe-S键合在一步反应中在FeO上实现。结合液相色谱-串联质谱（LC-MS/MS），我们对不同阶段的健康个体和CC患者进行了外泌体代谢组学分析，机器学习模型显示出对CC的准确分类（准确率>0.822）和预测能力。此外，在另外的患者样本中鉴定并验证了六种指示CC进展的关键代谢物，突出了它们作为生物标志物的潜力。总体而言，本研究建立了一种用于CC外泌体代谢组学的新方法，为大规模非侵入性早期诊断和进展预测提供了见解。
