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

被引:30
作者
Li, Peilong [1 ]
Chen, Jiaci [2 ]
Chen, Yuqing [1 ]
Song, Shangling [3 ]
Huang, Xiaowen [2 ]
Yang, Yang [4 ]
Li, Yanru [1 ]
Tong, Yao [1 ]
Xie, Yan [1 ]
Li, Juan [1 ]
Li, Shunxiang [5 ,6 ]
Wang, Jiayi [7 ]
Qian, Kun [5 ,6 ]
Wang, Chuanxin [1 ]
Du, Lutao [1 ]
机构
[1] Shandong Univ, Hosp 2, Dept Clin Lab, Jinan 250033, Peoples R China
[2] Qilu Univ Technol, Shandong Acad Sci, Dept Bioengn, State Key Lab Biobased Mat & Green Papermaking, Jinan 250300, Peoples R China
[3] Shandong Univ, Hosp 2, Dept Med Engn Equipment, Jinan 250033, Peoples R China
[4] Shandong Univ, Sch Informat Sci & Engn, Jinan 250000, Peoples R China
[5] Shanghai Jiao Tong Univ, Sch Biomed Engn Inst Med Robot, Medx Res Inst, State Key Lab Oncogenes & Related Genes,Inst Med R, Shanghai 200030, Peoples R China
[6] Shanghai Jiao Tong Univ, Renji Hosp, Dept Obstet & Gynecol, Dept Cardiol,Sch Med,Shanghai Key Lab Gynecol Onco, Shanghai 200127, Peoples R China
[7] Shanghai Jiao Tong Univ, Shanghai Chest Hosp, Country Dept Clin Lab Med, Shanghai 200030, Peoples R China
关键词
artificial intelligence; biomarkers; cancer; exosomes; microfluidic chips; ARTIFICIAL-INTELLIGENCE; BIOMARKERS;
D O I
10.1002/smll.202207381
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Exosomes 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 approximate to 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.
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页数:13
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