SERS-Nanozyme Cooperative Ag@Lacunary-POM Nanoclusters for Exosome Biosensing

The detection of cancer-related exosomes is of great significance for the early diagnosis of cancer and the prediction of prognosis. We developed a SERS-based nanozyme-linked immunosorbent assay (NELISA) utilizing lacunary polyoxometalate Na<sub>7</sub>PW<sub>11</sub>O<sub>39</sub>, whose vacancy-induced unsaturated coordination sites enhance Lewis/Brønsted acidity and modulate HOMO-LUMO levels. This electronic restructuring synergizes with Ag nanoparticles (NPs) synthesized via NaBH<sub>4</sub> reduction to form Ag@Na<sub>7</sub>PW<sub>11</sub>O<sub>39</sub>, integrating dual SERS enhancement (LOD: 1.66 × 10<sup>-8</sup> M for 4-MBA) and peroxidase-like catalysis via localized surface plasmon resonance (LSPR) and interfacial charge transfer (CT). CD<sub>9</sub> antibody-functionalized Ag@Na<sub>7</sub>PW<sub>11</sub>O<sub>39</sub> selectively captures the exosome through CD<sub>9</sub> transmembrane proteins on microplates. Clinical validation with ovarian/breast cancer patient sera revealed a linear correlation between SERS intensity and exosome concentration (9 × 10<sup>5</sup>-1.78 × 10<sup>8</sup> particles/mL, LOD: 7.73 × 10<sup>5</sup> particles/mL), with signals significantly elevated versus healthy controls. The lacunary POM architecture amplifies plasmon-catalytic synergy while enabling direct biointerface engineering. This NELISA-SERS platform achieves noninvasive, ultrasensitive cancer detection, advancing precision diagnostics and early screening paradigms.

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Journal
ACS Sensors
Published
2025-10-23
DOI
https://doi.org/10.1021/acssensors.5c02773
Citations
5
Primary Topic
Advanced Nanomaterials in Catalysis
Type
article
Field-Weighted Citation Impact
2.59
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article

SERS-Nanozyme Cooperative Ag@Lacunary-POM Nanoclusters for Exosome Biosensing

Qingnan Zhao, Wei Song, Saizhen Hu, Wang Fan et al.
5 citations
ACS Sensors
Advanced Nanomaterials in Catalysis
2.59
article

SERS-Nanozyme Cooperative Ag@Lacunary-POM Nanoclusters for Exosome Biosensing

Qingnan Zhao, Wei Song, Saizhen Hu, Wang Fan, Feng Lin
article en
5 citations

Abstract

The detection of cancer-related exosomes is of great significance for the early diagnosis of cancer and the prediction of prognosis. We developed a SERS-based nanozyme-linked immunosorbent assay (NELISA) utilizing lacunary polyoxometalate Na<sub>7</sub>PW<sub>11</sub>O<sub>39</sub>, whose vacancy-induced unsaturated coordination sites enhance Lewis/Brønsted acidity and modulate HOMO-LUMO levels. This electronic restructuring synergizes with Ag nanoparticles (NPs) synthesized via NaBH<sub>4</sub> reduction to form Ag@Na<sub>7</sub>PW<sub>11</sub>O<sub>39</sub>, integrating dual SERS enhancement (LOD: 1.66 × 10<sup>-8</sup> M for 4-MBA) and peroxidase-like catalysis via localized surface plasmon resonance (LSPR) and interfacial charge transfer (CT). CD<sub>9</sub> antibody-functionalized Ag@Na<sub>7</sub>PW<sub>11</sub>O<sub>39</sub> selectively captures the exosome through CD<sub>9</sub> transmembrane proteins on microplates. Clinical validation with ovarian/breast cancer patient sera revealed a linear correlation between SERS intensity and exosome concentration (9 × 10<sup>5</sup>-1.78 × 10<sup>8</sup> particles/mL, LOD: 7.73 × 10<sup>5</sup> particles/mL), with signals significantly elevated versus healthy controls. The lacunary POM architecture amplifies plasmon-catalytic synergy while enabling direct biointerface engineering. This NELISA-SERS platform achieves noninvasive, ultrasensitive cancer detection, advancing precision diagnostics and early screening paradigms.

ACS SensorsVol. 10(11)
Harbin Medical University (CN), The University of Texas at Dallas (US), Jilin University (CN), Second Affiliated Hospital of Harbin Medical University (CN), Jilin Medical University (CN), State Key Laboratory of Supramolecular Structure and Materials
Openalex Percentile: Top 10%
Advanced Nanomaterials in Catalysis
2.59
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SERS-Nanozyme Cooperative Ag@Lacunary-POM Nanoclusters for Exosome Biosensing — Qingnan Zhao, Wei Song, et al. · ACS Sensors (2025) | TGRS Research Map | TGRS