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

Author:

Shen Guodong1,Jia Xiaohua23,Qi Tianyi4,Hu Zhenhua2,Xiao Anqi2,Liu Qiqi4,He Keyu1,Guo Weihong1,Zhang Dan5,Li Wanjun6,Cao Genmao7,Li Guoxin1,Tian Jie28,Huang Xinglu4ORCID,Hu Yanfeng1

Affiliation:

1. Department of General Surgery Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor Nanfang Hospital Southern Medical University Guangzhou 510515 China

2. Key Laboratory of Molecular Imaging of Chinese Academy of Sciences Institute of Automation Chinese Academy of Sciences Beijing 100190 China

3. Department of Ultrasound Shuozhou Grand Hospital of Shanxi Medical University Shuozhou 036000 China

4. State Key Laboratory of Medicinal Chemical Biology Key Laboratory of Bioactive Materials for the Ministry of Education College of Life Sciences Nankai University Tianjin 300071 China

5. Center of Biomedical Analysis Tsinghua University Beijing 100084 China

6. Department of Pathology Affiliated 3201 Hospital of Xi'an Jiaotong University Hanzhong 723000 China

7. Department of Vascular Surgery The Second Hospital of Shanxi Medical University Taiyuan 030000 China

8. Beijing Advanced Innovation Center for Big Data‐Based Precision Medicine School of Medicine and Engineering Beihang University Beijing 100191 China

Abstract

AbstractTargeted 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.

Funder

National Natural Science Foundation of China

Publisher

Wiley

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3