Evidence map›Paper›PMID 28143451›Full record

ArticleBMC cancer2017

Distinct prostate cancer-related mRNA cargo in extracellular vesicle subsets from prostate cell lines.

Elisa Lázaro-Ibáñez, Taral R Lunavat, Su Chul Jang, Carmen Escobedo-Lucea, Jorge Oliver-De La Cruz, Pia Siljander, Jan Lötvall, Marjo Yliperttula

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
3.5field-weighted citation impact, top 7% 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

42 citing papers in PubMed, 69 citations in OpenAlex.

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  10. Cancer secretome: finding out hidden messages in extracellular secretions.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023
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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 3 institutions in 5 countries.

Elisa Lázaro-IbáñezDivision of Pharmaceutical Biosciences, Centre for Drug Research, Faculty of Pharmacy, University of Helsinki, Helsinki, 00014, Finland. elisa.lazaro-ibanez@helsinki.fi.
Taral R LunavatKrefting Research Center, Department of Internal Medicine and Clinical Nutrition, University of Gothenburg, Gothenburg, 40530, Sweden.
Su Chul JangKrefting Research Center, Department of Internal Medicine and Clinical Nutrition, University of Gothenburg, Gothenburg, 40530, Sweden.
Carmen Escobedo-LuceaDivision of Pharmaceutical Biosciences, Centre for Drug Research, Faculty of Pharmacy, University of Helsinki, Helsinki, 00014, Finland.
Jorge Oliver-De La CruzCenter for Translational Medicine, International Clinical Research Center, St. Anne's University Hospital, Brno, 65691, Czech Republic.
Pia SiljanderDivision of Pharmaceutical Biosciences, Centre for Drug Research, Faculty of Pharmacy, University of Helsinki, Helsinki, 00014, Finland.
Jan LötvallKrefting Research Center, Department of Internal Medicine and Clinical Nutrition, University of Gothenburg, Gothenburg, 40530, Sweden. jan.lotvall@gu.se.
Marjo YliperttulaDivision of Pharmaceutical Biosciences, Centre for Drug Research, Faculty of Pharmacy, University of Helsinki, Helsinki, 00014, Finland.
University of Helsinki · FIUniversity of Gothenburg · SESt. Anne's University Hospital Brno · CZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMultiple types of extracellular vesicles (EVs), including microvesicles (MVs) and exosomes (EXOs), are released by all cells constituting part of the cellular EV secretome. The bioactive cargo of EVs can be shuffled between cells and consists of lipids, metabolites, proteins, and nucleic acids, including multiple RNA species from non-coding RNAs to messenger RNAs (mRNAs). In this study, we hypothesized that the mRNA cargo of EVs could differ based on the EV cellular origin and subpopulation analyzed.

methodsWe isolated MVs and EXOs from PC-3 and LNCaP prostate cancer cells by differential centrifugation and compared them to EVs derived from the benign PNT2 prostate cells. The relative mRNA levels of 84 prostate cancer-related genes were investigated and validated using quantitative reverse transcription PCR arrays.

resultsBased on the mRNA abundance, MVs rather than EXOs were enriched in the analyzed transcripts, providing a snapshot of the tumor transcriptome. LNCaP MVs specifically contained significantly increased mRNA levels of NK3 Homeobox 1 (NKX3-1), transmembrane protease serine 2 (TMPRSS2), and tumor protein 53 (TP53) genes, whereas PC-3 MVs carried increased mRNA levels of several genes including, caveolin-2 (CAV2), glutathione S-transferase pi 1 (GSTP1), pescadillo ribosomal biogenesis factor 1 (PES1), calmodulin regulated spectrin associated protein 1 (CAMSAP1), zinc-finger protein 185 (ZNF185), and others compared to PNT2 MVs. Additionally, ETS variant 1 (ETV1) and fatty acid synthase (FASN) mRNAs identified in LNCaP- and PC-3- derived MVs highly correlated with prostate cancer progression.

conclusionsOur study provides new understandings of the variability of the mRNA cargo of MVs and EXOs from different cell lines despite same cancer origin, which is essential to better understand the the proportion of the cell transcriptome that can be detected within EVs and to evaluate their role in disease diagnosis.

Indexed as

Biomarkers, TumorCell Line, TumorExtracellular VesiclesHumansMaleProstateProstatic NeoplasmsRNA, MessengerTranscriptomeBiomarkers, TumorRNA, MessengerExosomesExtracellular vesiclesMicrovesiclesmRNAProstate cancer

Identifiers

PMID28143451
PMCPMC5286827
OpenAlexW2583743622

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.