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Distinct Prostate Cancer-related MRNA Cargo in Extracellular Vesicle Subsets from Prostate Cell Lines

Overview
Journal BMC Cancer
Publisher Biomed Central
Specialty Oncology
Date 2017 Feb 2
PMID 28143451
Citations 38
Authors
Affiliations
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Abstract

Background: Multiple 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.

Methods: We 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.

Results: Based 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.

Conclusions: Our 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.

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