Construction of Exosome SORL1 Detection Platform Based on 3D Porous Microfluidic Chip and its Application in Early Diagnosis of Colorectal Cancer

Author:

Li Peilong1,Chen Jiaci2,Chen Yuqing1,Song Shangling3,Huang Xiaowen2,Yang Yang4,Li Yanru1,Tong Yao1,Xie Yan1,Li Juan1,Li Shunxiang56,Wang Jiayi7,Qian Kun56ORCID,Wang Chuanxin1,Du Lutao1

Affiliation:

1. Department of Clinical Laboratory The Second Hospital of Shandong University Jinan 250033 China

2. State Key Laboratory of Biobased Material and Green Papermaking Department of Bioengineering Qilu University of Technology (Shandong Academy of Sciences) Jinan 250300 China

3. Department of medical engineering equipment The Second Hospital of Shandong University Jinan 250033 China

4. School of Information Science and Engineering Shandong University Jinan 250000 China

5. State Key Laboratory for Oncogenes and Related Genes School of Biomedical Engineering Institute of Medical Robotics and Med‐X Research Institute Shanghai Jiao Tong University Shanghai 200030 China

6. Department of Obstetrics and Gynecology Department of Cardiology Shanghai Key Laboratory of Gynecologic Oncology Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai 200127 China

7. Country Department of Clinical Laboratory Medicine Shanghai Chest Hospital Shanghai Jiao Tong University Shanghai 200030 China

Abstract

AbstractExosomes are promising new biomarkers for colorectal cancer (CRC) diagnosis, due to their rich biological fingerprints and high level of stability. However, the accurate detection of exosomes with specific surface receptors is limited to clinical application. Herein, an exosome enrichment platform on a 3D porous sponge microfluidic chip is constructed and the exosome capture efficiency of this chip is ≈90%. Also, deep mass spectrometry analysis followed by multi‐level expression screenings revealed a CRC‐specific exosome membrane protein (SORL1). A method of SORL1 detection by specific quantum dot labeling is further designed and the ensemble classification system is established by extracting features from 64‐patched fluorescence images. Importantly, the area under the curve (AUC) using this system is 0.99, which is significantly higher (p < 0.001) than that using a conventional biomarker (carcinoembryonic antigen (CEA), AUC of 0.71). The above system showed similar diagnostic performance, dealing with early‐stage CRC, young CRC, and CEA‐negative CRC patients.

Funder

National Natural Science Foundation of China

Key Technology Research and Development Program of Shandong

Natural Science Foundation of Shandong Province

Publisher

Wiley

Subject

Biomaterials,Biotechnology,General Materials Science,General Chemistry

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