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

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.