Harnessing virus flexibility to selectively capture and profile rare circulating target cells for precise cancer subtyping

Hui-Da Li, Yuan-Qiang Chen, Yan Li, Xing Wei, Si-Yi Wang, Ying Cao, Rui Wang, Cong Wang, Jing-Yue Li, Jian-Yi Li (), Hong-Ming Ding (), Ting Yang (), Jian-Hua Wang and Chuanbin Mao ()
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Hui-Da Li: Northeastern University
Yuan-Qiang Chen: Soochow University
Yan Li: Zhejiang University
Xing Wei: Northeastern University
Si-Yi Wang: Northeastern University
Ying Cao: Northeastern University
Rui Wang: Northeastern University
Cong Wang: Cancer Hospital of China Medical University
Jing-Yue Li: Cancer Hospital of China Medical University
Jian-Yi Li: Cancer Hospital of China Medical University
Hong-Ming Ding: Soochow University
Ting Yang: Northeastern University
Jian-Hua Wang: Northeastern University
Chuanbin Mao: The Chinese University of Hong Kong

Nature Communications, 2024, vol. 15, issue 1, 1-17

Abstract: Abstract The effective isolation of rare target cells, such as circulating tumor cells, from whole blood is still challenging due to the lack of a capturing surface with strong target-binding affinity and non-target-cell resistance. Here we present a solution leveraging the flexibility of bacterial virus (phage) nanofibers with their sidewalls displaying target circulating tumor cell-specific aptamers and their ends tethered to magnetic beads. Such flexible phages, with low stiffness and Young’s modulus, can twist and adapt to recognize the cell receptors, energetically enhancing target cell capturing and entropically discouraging non-target cells (white blood cells) adsorption. The magnetic beads with flexible phages can isolate and count target cells with significant increase in cell affinity and reduction in non-target cell absorption compared to magnetic beads having rigid phages. This differentiates breast cancer patients and healthy donors, with impressive area under the curve (0.991) at the optimal detection threshold (>4 target cells mL−1). Immunostaining of captured circulating tumor cells precisely determines breast cancer subtypes with a diagnostic accuracy of 91.07%. Our study reveals the power of viral mechanical attributes in designing surfaces with superior target binding and non-target anti-fouling.

Date: 2024
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DOI: 10.1038/s41467-024-50064-y

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