Personalized Cancer-Specific Protein-Aptamer Corona for Orthogonal Multiplex Cancer Diagnosis

Aptamers are powerful synthetic recognition elements for biosensing, yet their application in complex biofluids, such as human serum, is critically limited by enzymatic degradation. To overcome this fundamental challenge, we introduce a novel analytical platform centered on the concept of a personalized protein-aptamer corona (PAC). This strategy leverages the spontaneous formation of a disease-specific protein corona on magnetic nanoparticles, which not only enriches low-abundance biomarkers but also creates a stabilized, nuclease-free nanobio interface for subsequent aptamer recognition. The integration of this PAC concept with an 8-channel orthogonal multiplexed electrochemical (OMEC) chip enables sensitive, amplification-free (PCR-free) signal transduction via alternating current voltammetry. By coupling this platform with machine learning algorithms, we translate complex, multiplexed aptamer binding signatures into a robust diagnostic output. Clinical validation on two independent cancer cohorts demonstrated outstanding performance, achieving an area under the curve of 99.50% for ovarian cancer (<i>n</i> = 121) and 96.54% for non-small cell lung cancer (<i>n</i> = 107). This work establishes the PAC-OMEC platform as a versatile and powerful strategy for high-throughput clinical diagnostics, fundamentally addressing the instability of aptamers in native biological samples.

Authors

Institutions

Publication Details

Journal
Journal of the American Chemical Society
Published
2025-10-23
DOI
https://doi.org/10.1021/jacs.5c12860
Citations
3
Primary Topic
Nanoplatforms for cancer theranostics
Type
article
Field-Weighted Citation Impact
2.02
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Personalized Cancer-Specific Protein-Aptamer Corona for Orthogonal Multiplex Cancer Diagnosis

Guangyi Jiang, Jianqing Zhu, Lu Sun, Weihong Tan et al.
3 citations
Journal of the American Chemical Society
Nanoplatforms for cancer theranostics
2.02
article

Personalized Cancer-Specific Protein-Aptamer Corona for Orthogonal Multiplex Cancer Diagnosis

Guangyi Jiang, Jianqing Zhu, Lu Sun, Weihong Tan, Baichuan Jin, Weishan Lu, Jinlong Fan, Yang Liu, Yuan Liu, Xin Dai, Qixun Chen, Ting Fu
article en
3 citations

Abstract

Aptamers are powerful synthetic recognition elements for biosensing, yet their application in complex biofluids, such as human serum, is critically limited by enzymatic degradation. To overcome this fundamental challenge, we introduce a novel analytical platform centered on the concept of a personalized protein-aptamer corona (PAC). This strategy leverages the spontaneous formation of a disease-specific protein corona on magnetic nanoparticles, which not only enriches low-abundance biomarkers but also creates a stabilized, nuclease-free nanobio interface for subsequent aptamer recognition. The integration of this PAC concept with an 8-channel orthogonal multiplexed electrochemical (OMEC) chip enables sensitive, amplification-free (PCR-free) signal transduction via alternating current voltammetry. By coupling this platform with machine learning algorithms, we translate complex, multiplexed aptamer binding signatures into a robust diagnostic output. Clinical validation on two independent cancer cohorts demonstrated outstanding performance, achieving an area under the curve of 99.50% for ovarian cancer (<i>n</i> = 121) and 96.54% for non-small cell lung cancer (<i>n</i> = 107). This work establishes the PAC-OMEC platform as a versatile and powerful strategy for high-throughput clinical diagnostics, fundamentally addressing the instability of aptamers in native biological samples.

Journal of the American Chemical SocietyVol. 147(44)
Shanghai Jiao Tong University (CN), Xiamen University (CN), Chinese Academy of Sciences (CN), Renji Hospital (CN), Zhejiang Cancer Hospital (CN), Institute for Advanced Study (DE), Institute of Molecular Medicine (IN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 12%
Nanoplatforms for cancer theranostics
2.02
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.