Prostate cancer extracellular vesicle digital scoring assay – a rapid noninvasive approach for quantification of disease-relevant mRNAs. (February 2023)
- Record Type:
- Journal Article
- Title:
- Prostate cancer extracellular vesicle digital scoring assay – a rapid noninvasive approach for quantification of disease-relevant mRNAs. (February 2023)
- Main Title:
- Prostate cancer extracellular vesicle digital scoring assay – a rapid noninvasive approach for quantification of disease-relevant mRNAs
- Authors:
- Wang, Jasmine J.
Sun, Na
Lee, Yi-Te
Kim, Minhyung
Vagner, Tatyana
Rohena-Rivera, Krizia
Wang, Zhili
Chen, Zijing
Zhang, Ryan Y.
Lee, Junseok
Zhang, Ceng
Tang, Hubert
Widjaja, Josephine
Zhang, Tiffany X.
Qi, Dongping
Teng, Pai-Chi
Jan, Yu Jen
Hou, Kuan-Chu
Hamann, Candace
Sandler, Howard M.
Daskivich, Timothy J.
Luthringer, Daniel J.
Bhowmick, Neil A.
Pei, Renjun
You, Sungyong
Di Vizio, Dolores
Tseng, Hsian-Rong
Chen, Jie-Fu
Zhu, Yazhen
Posadas, Edwin M. - Abstract:
- Abstract: Optimizing outcomes in prostate cancer (PCa) requires precision in characterization of disease status. This effort was directed at developing a PCa extracellular vesicle (EV) Digital Scoring Assay (DSA) for detecting metastasis and monitoring progression of PCa. PCa EV DSA is comprised of an EV purification device (i.e., EV Click Chip) and reverse-transcription droplet digital PCR that quantifies 11 PCa-relevant mRNA in purified PCa-derived EVs. A Met score was computed for each plasma sample based on the expression of the 11-gene panel using the weighted Z score method. Under optimized conditions, the EV Click Chips outperformed the ultracentrifugation or precipitation method of purifying PCa-derived EVs from artificial plasma samples. Using PCa EV DSA, the Met score distinguished metastatic ( n = 20) from localized PCa ( n = 20) with an area under the receiver operating characteristic curve of 0.88 (95% CI:0.78–0.98). Furthermore, longitudinal analysis of three PCa patients showed the dynamics of the Met scores reflected clinical behavior even when disease was undetectable by imaging. Overall, a sensitive PCa EV DSA was developed to identify metastatic PCa and reveal dynamic disease states noninvasively. This assay may complement current imaging tools and blood-based tests for timely detection of metastatic progression that can improve care for PCa patients. Graphical Abstract: ga1 Highlights: Prostate Ca (PCa)-derived extracellular vesicles (EV) were isolatedAbstract: Optimizing outcomes in prostate cancer (PCa) requires precision in characterization of disease status. This effort was directed at developing a PCa extracellular vesicle (EV) Digital Scoring Assay (DSA) for detecting metastasis and monitoring progression of PCa. PCa EV DSA is comprised of an EV purification device (i.e., EV Click Chip) and reverse-transcription droplet digital PCR that quantifies 11 PCa-relevant mRNA in purified PCa-derived EVs. A Met score was computed for each plasma sample based on the expression of the 11-gene panel using the weighted Z score method. Under optimized conditions, the EV Click Chips outperformed the ultracentrifugation or precipitation method of purifying PCa-derived EVs from artificial plasma samples. Using PCa EV DSA, the Met score distinguished metastatic ( n = 20) from localized PCa ( n = 20) with an area under the receiver operating characteristic curve of 0.88 (95% CI:0.78–0.98). Furthermore, longitudinal analysis of three PCa patients showed the dynamics of the Met scores reflected clinical behavior even when disease was undetectable by imaging. Overall, a sensitive PCa EV DSA was developed to identify metastatic PCa and reveal dynamic disease states noninvasively. This assay may complement current imaging tools and blood-based tests for timely detection of metastatic progression that can improve care for PCa patients. Graphical Abstract: ga1 Highlights: Prostate Ca (PCa)-derived extracellular vesicles (EV) were isolated via nanosurface. This approach outperformed ultracentrifugation and precipitation. An EV-mRNA signature could distinguish metastatic from localized PCa patients. Changes in this mRNA signature reflected the dynamic clinical status of PCa patients. … (more)
- Is Part Of:
- Nano today. Volume 48(2023)
- Journal:
- Nano today
- Issue:
- Volume 48(2023)
- Issue Display:
- Volume 48, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 48
- Issue:
- 2023
- Issue Sort Value:
- 2023-0048-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-02
- Subjects:
- DSA Digital Scoring Assay -- EV extracellular vesicle -- PCa prostate cancer -- RT-ddPCR reverse transcription-droplet digital polymerase chain reaction
Prostate cancer -- Liquid biopsy -- Extracellular vesicle -- Metastatic biomarker -- Nanotechnology
Nanotechnology -- Periodicals
Nanosciences -- Périodiques
620.505 - Journal URLs:
- http://www.sciencedirect.com/science/journal/17480132 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.nantod.2022.101746 ↗
- Languages:
- English
- ISSNs:
- 1748-0132
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6015.335517
British Library DSC - BLDSS-3PM
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- 25674.xml