Dataset Information

Cancer-Derived Extracellular Vesicle-Associated MicroRNAs in Intercellular Communication: One Cell's Trash Is Another Cell's Treasure.

ABSTRACT: Several non-protein-coding genomic regions, previously marked as "junk DNA", have been reported to be transcriptionally active, giving rise to non-coding RNA species implicated in fundamental biological and pathological processes. In particular, microRNAs (miRNAs), a class of small non-coding RNAs mediating post-transcriptional gene silencing, are causally involved in several human diseases, including various cancer types. Extracellular vesicles (EVs) are membranous structures physiologically released by most cell types. Initially, they were considered a "waste-removal" mechanism, through which cells could dispose unnecessary material and organelles. It is now widely demonstrated that EVs also play a critical role in intercellular communication, mediating the horizontal transfer of lipids, proteins, and genetic material. A paradigm shift in the biology of miRNAs was represented by the discovery that EVs, especially from cancer cells, contain miRs. EV-associated miRs act as autocrine, paracrine and endocrine factors, participating in cancer pathogenesis by modulating intercellular communication. Noteworthy, these formerly neglected molecules are now considered the next generation of cancer "theranostic" tools, with strong clinical relevance. In this review, we aim to summarize the most recent findings regarding EV-associated miRs in cancer pathogenesis and in the development of novel anti-neoplastic diagnostic and therapeutic approaches.

SUBMITTER: Mills J

PROVIDER: S-EPMC6940802 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Publications

Cancer-Derived Extracellular Vesicle-Associated MicroRNAs in Intercellular Communication: One Cell's Trash Is Another Cell's Treasure.

Mills Joseph J Capece Marina M Cocucci Emanuele E Tessari Anna A Palmieri Dario D

International journal of molecular sciences 20191204 24

Several non-protein-coding genomic regions, previously marked as "junk DNA", have been reported to be transcriptionally active, giving rise to non-coding RNA species implicated in fundamental biological and pathological processes. In particular, microRNAs (miRNAs), a class of small non-coding RNAs mediating post-transcriptional gene silencing, are causally involved in several human diseases, including various cancer types. Extracellular vesicles (EVs) are membranous structures physiologically re ...[more]

PMID: 31817101

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Project description:BackgroundNext Generation Sequencing (NGS) experiments produce millions of short sequences that, mapped to a reference genome, provide biological insights at genomic, transcriptomic and epigenomic level. Typically the amount of reads that correctly maps to the reference genome ranges between 70% and 90%, leaving in some cases a consistent fraction of unmapped sequences. This 'misalignment' can be ascribed to low quality bases or sequence differences between the sample reads and the reference genome. Investigating the source of the unmapped reads is definitely important to better assess the quality of the whole experiment and to check for possible downstream or upstream 'contamination' from exogenous nucleic acids.ResultsHere we propose DecontaMiner, a tool to unravel the presence of contaminating sequences among the unmapped reads. It uses a subtraction approach to identify bacteria, fungi and viruses genome contamination. DecontaMiner generates several output files to track all the processed reads, and to provide a complete report of their characteristics. The good quality matches on microorganism genomes are counted and compared among samples. DecontaMiner builds an offline HTML page containing summary statistics and plots. The latter are obtained using the state-of-the-art D3 javascript libraries. DecontaMiner has been mainly used to detect contamination in human RNA-Seq data. The software is freely available at http://www-labgtp.na.icar.cnr.it/decontaminer .ConclusionsDecontaMiner is a tool designed and developed to investigate the presence of contaminating sequences in unmapped NGS data. It can suggest the presence of contaminating organisms in sequenced samples, that might derive either from laboratory contamination or from their biological source, and in both cases can be considered as worthy of further investigation and experimental validation. The novelty of DecontaMiner is mainly represented by its easy integration with the standard procedures of NGS data analysis, while providing a complete, reliable, and automatic pipeline.

Dataset Information

Cancer-Derived Extracellular Vesicle-Associated MicroRNAs in Intercellular Communication: One Cell's Trash Is Another Cell's Treasure.

Publications

Cancer-Derived Extracellular Vesicle-Associated MicroRNAs in Intercellular Communication: One Cell's Trash Is Another Cell's Treasure.

Similar Datasets

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