journal article·2025-09Open access

An MOF‐Enhanced Anti‐Fouling Immunoprobe Platform for Efficient Direct Screening of Pancreatic Cancer

Wenjuan Yang, Shujuan Mao, Hao Zhu, Handong Yao, Wei Jin, Lingyan Feng, Xinghua Gao, Xuefeng Wang, Wei Chen, Min Tu, Yuan Zhang

Advanced Science· Volume 12· Issue 36

Abstract

Abstract Monitoring biomarkers offers insights for early disease (e.g., cancer, chronic diseases) screening, treatment guidance and response evaluation. To tackle challenges in precise biomarker detection in complex blood samples, we propose a metal‐organic framework (MOF)‐enhanced anti‐fouling immunoprobe (MAIP). This sensing platform integrates several key features, including an anti‐fouling surface, fully oriented antibody immobilization, and an enhanced electron transfer layer. This platform demonstrates remarkable sensitivity and specificity, capable of detecting trace concentrations of cancer markers, ranging from pg/mL to ng/mL. Comprehensive analysis of clinical serum samples, combined with machine learning (ML) evaluations, underscores the platform's reliability and effectiveness in cancer biomarker detection. Using a combination of three biomarkers, the algorithm demonstrated satisfactory classification performance with an accuracy of 100% on the test set across 64 serum samples. Moreover, when evaluated using 10‐fold cross‐validation, the optimized model maintained a robust accuracy of 0.955 ± 0.09, reinforcing its strong stability and good generalization ability across different data partitions. The MAIP‐based platform developed here offers swift analysis, high accuracy, and a simplified testing process. This makes it a promising approach for directly profiling cancer markers from blood, thereby facilitating timely and effective patient care.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced biosensing and bioanalysis techniques · Biosensors and Analytical Detection · Nanopore and Nanochannel Transport Studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Materials Genome Institute Shanghai Engineering Research Center for Integrated Circuits and Advanced Display Materials Shanghai University Shanghai 200444 China

State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 China

Department of Emergency Tongji Hospital Tongji University School of Medicine Shanghai 200065 China

Funding

National Natural Science Foundation of China · Key Technologies Research and Development Program

References (41)

Show source-provided references
1. 10.1038/s44222-023-00032-w10.1038/s44222-023-00032-w ↗
2. 10.1038/s41551-022-00916-z10.1038/s41551-022-00916-z ↗
3. 10.1186/s12943-022-01509-910.1186/s12943-022-01509-9 ↗
4. 10.1002/advs.20240106910.1002/advs.202401069 ↗
5. 10.1002/adfm.20240527210.1002/adfm.202405272 ↗
6. 10.1021/acsnano.3c1226610.1021/acsnano.3c12266 ↗
7. 10.1002/smtd.20240123810.1002/smtd.202401238 ↗
8. 10.1039/c3cs60077g10.1039/c3cs60077g ↗
9. 10.1002/smtd.20240055110.1002/smtd.202400551 ↗
10. 10.1038/s41565-024-01611-710.1038/s41565-024-01611-7 ↗
11. 10.1038/s41565-023-01591-010.1038/s41565-023-01591-0 ↗
12. 10.1038/s41596-021-00511-710.1038/s41596-021-00511-7 ↗
13. 10.1002/advs.20230902710.1002/advs.202309027 ↗
14. 10.1038/s41467-023-36258-w10.1038/s41467-023-36258-w ↗
15. 10.1038/s41467-023-40873-y10.1038/s41467-023-40873-y ↗
16. 10.1039/C8SC00825F10.1039/C8SC00825F ↗
17. 10.1002/adma.20210660710.1002/adma.202106607 ↗
18. 10.1002/adma.20150364810.1002/adma.201503648 ↗
19. 10.1002/adma.20220822410.1002/adma.202208224 ↗
20. 10.1038/s41467-019-10622-110.1038/s41467-019-10622-1 ↗
21. 10.1021/acs.chemrev.9b0073910.1021/acs.chemrev.9b00739 ↗
22. 10.1002/adma.20230904610.1002/adma.202309046 ↗
23. 10.1002/advs.20230520410.1002/advs.202305204 ↗
24. 10.1038/ncomms1501610.1038/ncomms15016 ↗
25. 10.1038/nature1458110.1038/nature14581 ↗
26. 10.1038/nature1462610.1038/nature14626 ↗
27. 10.1038/ncb316910.1038/ncb3169 ↗
28. 10.1021/acsnano.0c0694610.1021/acsnano.0c06946 ↗
29. 10.1021/acssensors.9b0143010.1021/acssensors.9b01430 ↗
30. 10.1021/acsnano.3c0181210.1021/acsnano.3c01812 ↗
31. 10.1021/acssensors.2c0210510.1021/acssensors.2c02105 ↗
32. 10.1021/acs.analchem.3c0585810.1021/acs.analchem.3c05858 ↗
33. 10.1038/s41467-024-54215-z10.1038/s41467-024-54215-z ↗
34. 10.1107/S090904950501271910.1107/S0909049505012719 ↗
35. 10.1103/PhysRevB.71.09411010.1103/PhysRevB.71.094110 ↗
36. 10.1107/S090904950703190110.1107/S0909049507031901 ↗
37. 10.1103/PhysRevB.54.1116910.1103/PhysRevB.54.11169 ↗
38. 10.1103/PhysRevB.50.1795310.1103/PhysRevB.50.17953 ↗
39. 10.1103/PhysRevLett.77.386510.1103/PhysRevLett.77.3865 ↗
40. 10.1021/acs.chemmater.0c0330710.1021/acs.chemmater.0c03307 ↗
41. 10.1063/1.338234410.1063/1.3382344 ↗