Journal
ADVANCED FUNCTIONAL MATERIALS
Volume 32, Issue 3, Pages -Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/adfm.202010296
Keywords
early melanoma detection; extracellular vesicles; liquid biopsy; microfluidic device; surface-enhanced Raman spectroscopy
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Funding
- National Breast Cancer Foundation of Australia [CG-12-07]
- Australian Research Council (ARC) [DP160102836, DP210103151]
- ARC [DE200100345]
- National Health and Medical Research Council (NHMRC) [APP1173669]
- NHMRC Centre of Research Excellence scheme [APP1099021]
- NHMRC Peter Doherty Fellowships [APP1111216, APP1106491]
- NHMRC Medical Research Future Fund Next Generation Clinical Researchers Program Practitioner Fellowship [APP1137127]
- Merchant Charitable Foundation
- Australian Research Council [DE200100345] Funding Source: Australian Research Council
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Sensitive nanotechnology is used to profile serum extracellular vesicles for early melanoma detection, and the combination of microfluidic device and SERS technology can accurately differentiate melanoma patients from healthy individuals.
Precise detection of early melanomas is essential as the stage of disease guides treatment options. One growing field that may facilitate the advancement of early melanoma detection, is achieved through profiling serum extracellular vesicles (EVs) using sensitive nanotechnology. As a proof of principle, using a detection platform that combines a microfluidic device and surface-enhanced Raman spectroscopy (SERS), the expression profiles of 4 protein biomarkers in serum EVs (termed as EV SERS signatures) derived from 20 early stage melanoma patients (including in situ melanoma) and 21 healthy participants are multiplexed. Significantly higher signal intensities of selected protein biomarkers are observed in serum EVs from melanoma patients compared with healthy participants, with mean fold-changes ranging from 3.7 to 4.2. It is demonstrated that the EV SERS signatures can accurately separate melanoma patients and healthy individuals, with an area under the curve of 0.95. Thus, with further development, this ultra-sensitive detection platform, combined with the panel of melanoma-associated biomarkers, has the ability to differentiate early stage melanoma patients from healthy participants.
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