Proximity-Guaranteed DNA Machine for Accurate Identification of Breast Cancer Extracellular Vesicles.

Breast cancer is one of the most diagnosed cancers worldwide. Precise diagnosis and subtyping have important significance for targeted therapy and prognosis prediction of breast cancer. Herein, we design a proximity-guaranteed DNA machine for accurate identification of breast cancer extracellular vesicles (EVs), which is beneficial to explore the subtype features of breast cancer. In our design, two proximity probes are located close on the same EV through specific recognition of coexisting surface biomarkers, thus being ligated with the help of click chemistry. Then, the ligated product initiates the operation of a DNA machine involving catalytic hairpin assembly and clusters of regularly interspaced short palindromic repeats (CRISPR)-Cas12a-mediated trans-cleavage, which finally generates a significant response that enables the identification of EVs expressing both biomarkers. Principle-of-proof studies are performed using EVs derived from the breast cancer cell line BT474 as the models, confirming the high sensitivity and specificity of the DNA machine. When further applied to clinical samples, the DNA machine is shown to be capable of not only distinguishing breast cancer patients with special subtypes but also realizing the tumor staging regarding the disease progression. Therefore, our work may provide new insights into the subtype-based diagnosis of breast cancer as well as identification of more potential therapeutic targets in the future.

Proximity labeling-assisted click conjugation for electrochemical analysis of specific subpopulations in circulating extracellular vesicles.

Sensitive and accurate analysis of specific subpopulations in circulating extracellular vesicles (EVs) can provide a wealth of information for cancer diagnosis and management. Thus, we propose herein a new electrochemical biosensing method based on a proximity labeling-assisted click conjugation strategy. The method's core design is use of antibody-guided proximity labeling to equip target EVs with a large amount of alkyne groups, so that azide-tagged silver nanoparticles can be accurately loaded onto target EV surfaces, via click conjugation, to generate significant electrochemical responses. Adopting CD44-positive EVs as the model, the electrochemical method was demonstrated by analyzing target EVs across a wide linear range (103-109 particles/mL) with acceptable sensitivity and specificity. Satisfactory utility in clinical blood samples, and versatility with human epidermal growth factor receptor-2-positive EVs as alternative targets, were also shown. This method may thus provide a novel approach to specific subgroup analyses of circulating EVs, and is expected to offer reliable guidance for cancer diagnoses and management strategies.