Evidence map›Paper›PMID 33580122›Full record

ArticleScientific reports2021

Analysis of extracellular vesicle mRNA derived from plasma using the nCounter platform.

Jillian W P Bracht, Ana Gimenez-Capitan, Chung-Ying Huang, Nicolas Potie, Carlos Pedraz-Valdunciel, Sarah Warren, Rafael Rosell, Miguel A Molina-Vila

Open access · goldAbstract readValidation Study
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
2.3field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 36 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Jillian W P BrachtPangaea Oncology, Laboratory of Oncology, Quirón Dexeus University Hospital, Sabino Arana 5-19, 08028, Barcelona, Spain. jill94bracht@gmail.com.
Ana Gimenez-CapitanPangaea Oncology, Laboratory of Oncology, Quirón Dexeus University Hospital, Sabino Arana 5-19, 08028, Barcelona, Spain.
Chung-Ying HuangNanoString Technologies, Seattle, WA, USA.
Nicolas PotieDepartment of Genetics, Faculty of Science, University of Granada, 18071, Granada, Spain.
Carlos Pedraz-ValduncielDepartment of Biochemistry, Molecular Biology and Biomedicine, Universitat Autónoma de Barcelona (UAB), 08193, Cerdanyola, Spain.
Sarah WarrenNanoString Technologies, Seattle, WA, USA.
Rafael RosellGermans Trias i Pujol Health Sciences Institute and Hospital (IGTP), Badalona, Barcelona, Spain.
Miguel A Molina-VilaPangaea Oncology, Laboratory of Oncology, Quirón Dexeus University Hospital, Sabino Arana 5-19, 08028, Barcelona, Spain. mamolina@panoncology.com.
Hospital Universitario Dexeus · ESInstitut d'Investigació en Ciències de la Salut Germans Trias i Pujol · ESNanostring Technologies (United States) · USUniversidad de Granada · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extracellular vesicles (EVs) are double-layered phospholipid membrane vesicles that are released by most cells and can mediate intercellular communication through their RNA cargo. In this study, we tested if the NanoString nCounter platform can be used for the analysis of EV-mRNA. We developed and optimized a methodology for EV enrichment, EV-RNA extraction and nCounter analysis. Then, we demonstrated the validity of our workflow by analyzing EV-RNA profiles from the plasma of 19 cancer patients and 10 controls and developing a gene signature to differentiate cancer versus control samples. TRI reagent outperformed automated RNA extraction and, although lower plasma input is feasible, 500 μL provided highest total counts and number of transcripts detected. A 10-cycle pre-amplification followed by DNase treatment yielded reproducible mRNA target detection. However, appropriate probe design to prevent genomic DNA binding is preferred. A gene signature, created using a bioinformatic algorithm, was able to distinguish between control and cancer EV-mRNA profiles with an area under the ROC curve of 0.99. Hence, the nCounter platform can be used to detect mRNA targets and develop gene signatures from plasma-derived EVs.

Indexed as

Blood Chemical AnalysisCase-Control StudiesExtracellular VesiclesHumansNeoplasmsProof of Concept StudyRNA, MessengerRNA, Messenger

Identifiers

PMID33580122
PMCPMC7881020
OpenAlexW3126329225

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.