Data-Driven Design of Triple-Targeted Protein Nanoprobes for Multiplexed Imaging of Cancer Lymphatic Metastasis.

Abstract

Targeted imaging of cancer lymphatic metastasis remains challenging due to its highly heterogeneous molecular and phenotypic diversity. Herein, triple-targeted protein nanoprobes capable of specifically binding to three targets for imaging cancer lymphatic metastasis, through a data-driven design approach combined with a synthetic biology-based assembly strategy, are introduced. Specifically, to address the diversity of metastatic lymph nodes (LNs), a combination of three targets, including C-X-C motif chemokine receptor 4 (CXCR4), transferrin receptor protein 1 (TfR1), and vascular endothelial growth factor receptor 3 (VEGFR3) is identified, leveraging machine leaning-based bioinformatics analysis and examination of LN tissues from patients with gastric cancer. Using this identified target combination, ferritin nanocage-based nanoprobes capable of specifically binding to all three targets are designed through the self-assembly of genetically engineered ferritin subunits using a synthetic biology approach. Using these nanoprobes, multiplexed imaging of heterogeneous metastatic LNs is successfully achieved in a polyclonal lymphatic metastasis animal model. In 19 freshly resected human gastric specimens, the signal from the triple-targeted nanoprobes significantly differentiates metastatic LNs from benign LNs. This study not only provides an effective nanoprobe for imaging highly heterogeneous lymphatic metastasis but also proposes a potential strategy for guiding the design of targeted nanomedicines for cancer lymphatic metastasis.