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Long non-coding RNAs (lncRNAs) are the most heterogeneous class of non-protein-coding RNAs involved in a broad spectrum of molecular mechanisms controlling genome function, including the generation of complex networks of RNA-RNA competitive interactions. Accordingly, their dysregulation contributes to the onset of many tumors, including colorectal cancer (CRC). Through a combination of in silico approaches (statistical screening of expression datasets) and in vitro analyses (enforced expression, artificial inhibition, or activation of pathways), we identified LINC00483 as a potential tumor suppressor lncRNA in CRC. LINC00483 was downregulated in CRC biopsies and metastases and its decreased levels were associated with severe clinical features. Inhibition of the MAPK pathway and cell cycle arrest by starvation induced an upregulation of LINC00483, while the epithelial to mesenchymal transition activation by TGFβ-1 and IL-6 caused its down-modulation. Moreover, enforced expression of LINC00483 provoked a slowing down of cell migration rate without affecting cell proliferation. Since LINC00483 was predominantly cytoplasmic, we hypothesized a “miRNA sponge” role for it. Accordingly, we computationally reconstructed the LINC00483/miRNA/mRNA axes and evaluated the expression of mRNAs in different experimental conditions inducing LINC00483 alteration. By this approach, we identified a set of mRNAs sharing the miRNA response elements with LINC00483 and modulated in accordance with it. Moreover, we found that LINC00483 is potentially under negative control of transcription factor HNF4α. In conclusion, we propose that LINC00483 is a tumor suppressor in CRC that, through an RNA-RNA network, may control cell migration and participate in proliferation signaling.

Over the past few years, exosomes and their RNA cargo have been extensively studied because of the fascinating biological roles they play in cell-to-cell communication, including the signal exchange among cancer, stromal, and immune cells, leading to modifications of tumor microenvironment. RNAs, especially miRNAs, stored within exosomes, seem to be among the main determinants of such signaling: their sorting into exosomes appears to be cell-specific and related to cellular physiopathology. Accordingly, the identification of exosomal miRNAs in body fluids from pathological patients has become one of the most promising activity in the field of biomarker discovery. Several analyses on the qualitative and quantitative distribution of RNAs between cells and their secreted exosomes have given rise to questions on whether and how accurately exosomal RNAs would represent the transcriptomic snapshot of the physiological and pathological status of secreting cells. Although the exact molecular mechanisms of sorting remain quite elusive, many papers have reported an evident asymmetric quantitative distribution of RNAs between source cells and their exosomes. This phenomenon could depend both on passive and active sorting mechanisms related to: (a) RNA turnover; (b) maintaining the cytoplasmic miRNA:target equilibrium; (c) removal of RNAs not critical or even detrimental for normal or diseased cells. These observations represent very critical issues in the exploitation of exosomal miRNAs as cancer biomarkers. In this review, we will discuss how much the exosomal and corresponding donor cell transcriptomes match each other, to better understand the actual reliability of exosomal RNA molecules as pathological biomarkers reflecting a diseased status of the cells.

The mammalian ovarian follicle is the complex reproductive unit comprising germ cell, somatic cells (Cumulus and Granulosa cells), and follicular fluid (FF): paracrine communication among the different cell types through FF ensures the development of a mature oocyte ready for fertilization. This paper is focused on non-coding RNAs in ovarian follicles and their predicted role in the pathways involved in oocyte growth and maturation. We determined the expression profiles of microRNAs in human oocytes and FF by high-throughput analysis and identified 267 microRNAs in FF and 176 in oocytes. Most of these were FF microRNAs, while 9 were oocyte specific. By bioinformatic analysis, independently performed on FF and oocyte microRNAs, we identified the most significant Biological Processes and the pathways regulated by their validated targets. We found many pathways shared between the two compartments and some specific for oocyte microRNAs. Moreover, we found 41 long non-coding RNAs able to interact with oocyte microRNAs and potentially involved in the regulation of folliculogenesis. These data are important in basic reproductive research and could also be useful for clinical applications. In fact, the characterization of non-coding RNAs in ovarian follicles could improve reproductive disease diagnosis, provide biomarkers of oocyte quality in Assisted Reproductive Treatment, and allow the development of therapies for infertility disorders.