| Autor: |
Nareg Ohannesian, Mohammad Sadman Mallick, Jianzhong He, Yawei Qiao, Nan Li, Simona F. Shaitelman, Chad Tang, Eileen H. Shinn, Wayne L. Hofstetter, Alexei Goltsov, Manal M. Hassan, Kelly K. Hunt, Steven H. Lin, Wei-Chuan Shih |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Communications Medicine, Vol 4, Iss 1, Pp 1-10 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2730-664X |
| DOI: |
10.1038/s43856-024-00514-x |
| Popis: |
Abstract Background Small extracellular vesicle (sEV) analysis can potentially improve cancer detection and diagnostics. However, this potential has been constrained by insufficient sensitivity, dynamic range, and the need for complex labeling. Methods In this study, we demonstrate the combination of PANORAMA and fluorescence imaging for single sEV analysis. The co-acquisition of PANORAMA and fluorescence images enables label-free visualization, enumeration, size determination, and enables detection of cargo microRNAs (miRs). Results An increased sEV count is observed in human plasma samples from patients with cancer, regardless of cancer type. The cargo miR-21 provides molecular specificity within the same sEV population at the single unit level, which pinpoints the sEVs subset of cancer origin. Using cancer cells-implanted animals, cancer-specific sEVs from 20 µl of plasma can be detected before tumors were palpable. The level plateaus between 5–15 absolute sEV count (ASC) per µl with tumors ≥8 mm3. In healthy human individuals (N = 106), the levels are on average 1.5 ASC/µl (+/− 0.95) without miR-21 expression. However, for stage I–III cancer patients (N = 205), nearly all (204 out of 205) have levels exceeding 3.5 ASC/µl with an average of 12.2 ASC/µl (±9.6), and a variable proportion of miR-21 labeling among different tumor types with 100% cancer specificity. Using a threshold of 3.5 ASC/µl to test a separate sample set in a blinded fashion yields accurate classification of healthy individuals from cancer patients. Conclusions Our techniques and findings can impact the understanding of cancer biology and the development of new cancer detection and diagnostic technologies. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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