Bifunctional nanomaterial enabled high-specific isolation of urinary exosomes for cervical cancer metabolomics analysis and biomarker discovery.

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.