Bifunctional bowl-shaped organosilica for efficient exosome capture and metabolites panel based hepatocellular carcinoma diagnosis

• Innovative Nanoplatform: a novel bifunctional bowl-shaped organosilica-based nanoplatform (SA@Pt-MONB) is proposed. • Efficient Exosome Capture and Metabolite Analysis: the distinctive morphology and specific chemical structure enables excellent exosome capture and provides inherent matrix effect for the metabolite analysis using LDI-MS. • Metabolites Panel and Hepatocellular carcinoma (HCC) Diagnosis: four metabolite panel from serum exosome is proposed using machine learning algorithms for the diagnosis of HCC with AUC value from 0.985 to 0.987, promising in noninvasive liquid biopsy of diseases diagnosis and precision medicine. Efficient purifying and analyzing exosomes remain challenging in noninvasive liquid biopsy diagnostics. Nanomaterials-assisted laser desorption/ionization mass spectrometry (LDI-MS) provides a powerful approach for screening exosome metabolites. Herein, we developed a novel bifunctional bowl-shaped organosilica-based nanoplatform, the streptavidin-functionalized Pt-deposited mesoporous organosilica nanobowl (SA@Pt-MONB), as an exosome capture vessel and inherent LDI-MS matrix for sequential exosome capture and metabolite analysis. We established a simple, rapid, efficient, and cost-effective serum exosome diagnostic platform with low sample consumption. The unique bowl-shaped morphology provides excellent exosome capture efficiency through more interaction sites (with a maximum value of 97.35%) and improves light trapping for downstream LDI-MS. The aromatic ring in the framework and deposited Pt NPs facilitate hot carrier production and charge transfer, improving the ionization efficiency of metabolites in LDI-MS analysis. As the inherent matrix, SA@Pt-MONB synergistically enhanced the high-throughput LDI-MS analysis of exosome metabolites. Machine learning algorithms were applied to effectively distinguish hepatocellular carcinoma (HCC) from healthy donors (HD) using serum exosome metabolic profile. A metabolite biomarker panel comprising four key metabolites was proposed for the diagnosis of HCC with AUC value from 0.985 to 0.987. This work demonstrates the significant potential of efficient exosome purification and metabolite analysis based on nanomaterials, promising in noninvasive liquid biopsy of diseases diagnosis and precision medicine.