Transcriptome and long noncoding RNA sequencing of three extracellular vesicle subtypes released from the human colon cancer LIM1863 cell line

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作者
Maoshan Chen
Rong Xu
Hong Ji
David W. Greening
Alin Rai
Keiichi Izumikawa
Hideaki Ishikawa
Nobuhiro Takahashi
Richard J. Simpson
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[1] La Trobe Institute for Molecular Science (LIMS),Department of Biochemistry and Genetics
[2] La Trobe University,Department of Applied Biological Science
[3] Graduate School of Agriculture,undefined
[4] Tokyo University of Agriculture and Technology,undefined
[5] Global Innovation Research Organisation,undefined
[6] Tokyo University of Agriculture and Technology,undefined
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Previously we reported that LIM1863 colorectal cancer (CRC) cells secrete three distinct extracellular vesicle subtypes – two subpopulations of exosomes (apical EpCAM-Exos and basolateral A33-Exos) and shed microvesicles (sMVs) – with distinct protein and miRNA signatures. Here, we extend our omics approach to understand the fundamental role of LIM1863-derived EVs by performing a comprehensive analysis of their mRNAs and long non-coding RNAs (lncRNAs) using RNA-Seq. We show that 2,389 mRNAs, 317 pseudogene transcripts, 1,028 lncRNAs and 206 short non-coding RNAs selectively distributed to (i.e., are enriched in) LIM1863 EVs, relative to the parent cell. An Ensembl/UniProtKB analysis revealed 1,937 mRNAs encode canonical proteins, 348 isoforms (including splice-variant proteins), and 119 ‘missing proteins’ (i.e., annotated in Ensembl but not UniProtKB). Further dissection of our protein/RNA data revealed that 6/151 observed RNA binding proteins have the potential to interact with ~75% of EV-enriched RNAs. Intriguingly, the co-existence of U1 and U2 ribonucleoproteins and their cognate snRNAs in LIM1863 EVs suggests a possible association of CRC EVs with recipient cell splicing events. Our data reveal several potential lncRNA CRC biomarkers and novel splicing/fusion genes that, collectively, will advance our understanding of EV biology in CRC and accelerate the development of EV-based diagnostics and therapeutics.
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