Multimodal DNA Nanostructure Barcodes for Single-Cell Protein Profiling and Tumor Subtyping

Molecular classification of diseases that accurately reflects clinical behavior is fundamental to the realization of precision medicine. Single-cell protein analysis combined with coding technology offers a promising approach for constructing robust molecular classifiers. However, the low abundance of disease-related cells and the technical challenges in parallel profiling of multiple proteins remain major obstacles. Herein, we present a DNA nanostructure-based multicomponent coding strategy that enables multiprotein analysis at the single-cell level by precisely controlling the stoichiometry, orientation, and modularity of the magnetized tags and multicolor fluorescent tags. Compared with conventional linear DNA barcoding methods, our approach allows for the simultaneous magnetic separation of heterogeneous cell populations and multicolor fluorescence-based phenotypic encoding. By integrating single-cell trapping techniques, we demonstrate the accurate molecular subtyping of breast cancer based on fluorescence-encoded phenotypic features. This strategy expands the scope of applications in cell sorting, proteomic profiling, and genomic analysis, thus advancing the frontiers of precision medicine.

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Publication Details

Journal
ACS Nano
Published
2026-02-12
DOI
https://doi.org/10.1021/acsnano.5c18968
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Multimodal DNA Nanostructure Barcodes for Single-Cell Protein Profiling and Tumor Subtyping

Chenxu Hu, Jiahan Dong, Chunhai Fan, Linlin Wang et al.
ACS Nano
Single-cell and spatial transcriptomics
article

Multimodal DNA Nanostructure Barcodes for Single-Cell Protein Profiling and Tumor Subtyping

Chenxu Hu, Jiahan Dong, Chunhai Fan, Linlin Wang, Jie Chao, Bicheng Sun, Meirong Cui
article en

Abstract

Molecular classification of diseases that accurately reflects clinical behavior is fundamental to the realization of precision medicine. Single-cell protein analysis combined with coding technology offers a promising approach for constructing robust molecular classifiers. However, the low abundance of disease-related cells and the technical challenges in parallel profiling of multiple proteins remain major obstacles. Herein, we present a DNA nanostructure-based multicomponent coding strategy that enables multiprotein analysis at the single-cell level by precisely controlling the stoichiometry, orientation, and modularity of the magnetized tags and multicolor fluorescent tags. Compared with conventional linear DNA barcoding methods, our approach allows for the simultaneous magnetic separation of heterogeneous cell populations and multicolor fluorescence-based phenotypic encoding. By integrating single-cell trapping techniques, we demonstrate the accurate molecular subtyping of breast cancer based on fluorescence-encoded phenotypic features. This strategy expands the scope of applications in cell sorting, proteomic profiling, and genomic analysis, thus advancing the frontiers of precision medicine.

ACS NanoVol. 20(7)
Shanghai Jiao Tong University (CN), Nanjing University of Posts and Telecommunications (CN), Flex (Mauritius) (MU), Theranostics (New Zealand) (NZ), Division of Materials Science and Engineering (AU), Center for Translational Molecular Medicine (NL), Institute for Advanced Study (DE)
Good health and well-being
Openalex Percentile: Top 59%
Single-cell and spatial transcriptomics
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