Orthogonal DNA self-assembly technology enables rapid and accurate analysis of circulating tumor cells in breast cancer.

Background: As a non-invasive liquid biopsy technology, the detection of circulating tumor cells (CTCs) overcomes the limitations of traditional tissue biopsy methods, enabling continuous sample collection and long-term dynamic monitoring. However, current CTCs analysis methods typically rely on cell size to separate and identify tumor cells, which fails to effectively distinguish tumor cells from different sources. In addition, existing methods are often constrained by limited antibody species, typically detecting only 2-3 molecular phenotypes. This narrow detection scope does not fully capture the heterogeneity of CTCs at the single-cell level, thus limiting its utility in precision diagnosis and personalized treatment. To address these challenges, it is urgent to develop CTCs detection methods that can simultaneously integrate comprehensive target and cell morphology information.

Results: Using breast cancer as a research model, we developed a computer-aided design-based hybridization chain reaction (CAD-HCR) by combining DNA encoding and antibody coupling technologies with orthogonal DNA self-assembly to achieve multiple detection and heterogeneity analysis of breast cancer mimic samples. This technology overcomes the limitation of antibody species in traditional CTCs detection and utilizes antibody-trigger strand coupling to convert target protein signals into DNA signals, thereby circumventing throughput limitation of existing detection methods. By utilizing the signal amplification effect of DNA self-assembly, this technology enhances sensitivity significantly, allowing for accurate single-cell level detection of CTCs.

Significance: This technology provides spatial positioning and cell morphological characteristics information for CTCs analysis of breast cancer, which is expected to provide a more accurate basis for diagnosis and treatment decision-making for in-depth understanding of tumor heterogeneity and clinical applications.