Single Particle Automated Raman Trapping Analysis of Breast Cancer Cell-Derived Extracellular Vesicles as Cancer Biomarkers


Posted: 2021-11-04 19:00:00
. 2021 Nov 4. doi: 10.1021/acsnano.1c07075. Online ahead of print. Affiliations Expand Affiliations 1 Department of Materials, Imperial College London, London SW7 2AZ, United Kingdom. 2 Department of Bioengineering, Imperial College London, London SW7 2AZ, United Kingdom. 3 Institute of Biomedical Engineering, Imperial College London, London SW7 2AZ, United Kingdom. 4 Department of Surgery and Cancer, Hammersmith Hospital, Imperial College, London W120HS, United Kingdom. Item in Clipboard Jelle Penders et al. ACS Nano. 2021. Show details Display options Display options Format . 2021 Nov 4. doi: 10.1021/acsnano.1c07075. Online ahead of print. Affiliations 1 Department of Materials, Imperial College London, London SW7 2AZ, United Kingdom. 2 Department of Bioengineering, Imperial College London, London SW7 2AZ, United Kingdom. 3 Institute of Biomedical Engineering, Imperial College London, London SW7 2AZ, United Kingdom. 4 Department of Surgery and Cancer, Hammersmith Hospital, Imperial College, London W120HS, United Kingdom. Item in Clipboard CiteDisplay options Display options Format Abstract Extracellular vesicles (EVs) secreted by cancer cells provide an important insight into cancer biology and could be leveraged to enhance diagnostics and disease monitoring. This paper details a high-throughput label-free extracellular vesicle analysis approach to study fundamental EV biology, toward diagnosis and monitoring of cancer in a minimally invasive manner and with the elimination of interpreter bias. We present the next generation of our single particle automated Raman trapping analysis─SPARTA─system through the development of a dedicated standalone device optimized for single particle analysis of EVs. Our visualization approach, dubbed dimensional reduction analysis (DRA), presents a convenient and comprehensive method of comparing multiple EV spectra. We demonstrate that the dedicated SPARTA system can differentiate between cancer and noncancer EVs with a high degree of sensitivity and specificity (>95% for both). We further show that the predictive ability of our approach is consistent across multiple EV isolations from the same cell types. Detailed modeling reveals accurate classification between EVs derived from various closely related breast cancer subtypes, further supporting the utility of our SPARTA-based approach for detailed EV profiling. Keywords: cancer; confocal; diagnostics; exosomes; extracellular vesicles; spectroscopic; spectroscopy.

参考サイト PubMed: exsome



バイオクイックニュース日本語版:エクソソーム特集

バイオクイックニュース日本語版
8月 31, 2020 バイオアソシエイツ

MicroRNA-218-5pを含む皮膚エクソソームが毛髪の再生を促進することが判明

ノースカロライナ州立大学の研究者は、毛髪の再生を促進する可能性のあるマイクロRNA(miRNA)を特定した。 このmiRNA(miR-218-5p)は、毛包の再生に関与するパスウェイの調節に重要な役割を果たしており、将来の薬剤開発の候補となる可能性がある。毛髪の成長は、毛包の成長サイクルを調節する真皮乳頭(dermal papillae)細胞の健康に依存する。 脱毛のための現在の治療は、侵襲的な手術から望ましい結果をもたらさない化学的治療に至るまで、費用がかかり、効果的でない場合がある。…

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