posted on 2025-07-24, 02:07authored byChloe 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