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Lateral flow assay for detection of breast cancer derived small extracellular vesicles

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posted on 2025-07-24, 02:07 authored by Chloe Anne Duffield
<p dir="ltr">Cancer cell derived small extracellular vesicles (sEVs) have emerged as promising biomarkers for cancer diagnosis and monitoring, however their heterogeneity remains a challenge for accurate capture and detection. To address this challenge, we have developed a colorimetric and surface-enhanced Raman scattering (SERS) based lateral flow Immunoassay (LFIA) for detection and subtyping of cancer-derived sEVs from breast cancer patient plasma samples. This novel approach combines rapid detection, high sensitivity, and multiplexing capabilities of SERS nanotag technology, with the simplicity of a LFIA design for end-users. SERS nanotags utilise strong plasmonic nanoparticles with functionalised antibodies for specific detection of EpCAM (a cancer biomarker) expressed on breast cancer sEVs. The LFIA incorporates three test lines with common sEV markers known as tetraspanins, enabling accurate capture and subtyping of sEV populations. Using this design, we obtained the overall EpCAM expression and tetraspanin subtyping in breast cancer cell line-derived sEVs through both colorimetric and SERS measurements. The overall colorimetric intensity of EpCAM expression was confirmed to be consistent regardless of tetraspanin order on the assay (p=0.0757). To validate clinical relevance, we analysed breast cancer patient plasma samples, determining overall EpCAM expression and unique tetraspanin subtyping. With further development, the SERS LFIA shows promising potential as a clinical aid for multiplexed sEV analysis and cancer detection, offering a powerful tool in breast cancer diagnostics.</p>

History

Table of Contents

Chapter 1. Introduction -- Chapter 2. Recent Advances in SERS Multiplex Assays of Cancer-derived Small Extracellular Vesicles -- Chapter 3. Materials and Methods -- Chapter 4. Results and Discussion -- Chapter 5. Conclusion and Future perspectives -- References

Awarding Institution

Macquarie University

Degree Type

Thesis MRes

Degree

Master of Research

Department, Centre or School

School of Natural Sciences

Year of Award

2024

Principal Supervisor

Yuling Wang

Additional Supervisor 1

Sebastian Schlücker

Additional Supervisor 2

David Inglis

Rights

Copyright: The Author Copyright disclaimer: https://www.mq.edu.au/copyright-disclaimer

Language

English

Extent

80 pages

Former Identifiers

AMIS ID: 410803

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