Ultrasensitive Exosome Detection by Modularized SERS Labeling for Postoperative Recurrence Surveillance

Exosome-based liquid biopsy holds great potential in monitoring tumor progression. Current exosome detection biosensors rely on signal amplification strategies to improve sensitivity; however, these strategies pay little attention to manipulating the number of signal reporters, limiting the rational optimization of the biosensors. Here, we have developed a modularized surface-enhanced Raman spectroscopy (SERS) labeling strategy, where each Raman reporter is coupled with lysine as a signal-lysine module, and thus the number of Raman reporters can be precisely controlled by the modularized solid-phase peptide synthesis. Using this strategy, we screened out an optimum Raman biosensor for ultrasensitive exosome detection, with the limit of detection of 2.4 particles per microliter. This biosensor enables a successful detection of the tumor with an average diameter of approximately 3.55 mm, and thus enables successful surveillance of the postoperative tumor recurrence in mice models and distinguishing cancer patients from healthy subjects. Our work provides a de novo strategy to precisely amplify signals toward a myriad of biosensor-related medical applications.

Automated summary

The study developed a modularized surface-enhanced Raman spectroscopy (SERS) labeling strategy for ultrasensitive exosome detection, enabling successful tumor monitoring and differentiation between cancer patients and healthy subjects.