The non-coding transcriptome as a dynamic regulator of cancer metastasis.

Since the discovery of microRNAs, non-coding RNAs (NC-RNAs) have increasingly attracted the attention of cancer investigators. Two classes of NC-RNAs are emerging as putative metastasis-related genes: long non-coding RNAs (lncRNAs) and small nucleolar RNAs (snoRNAs). LncRNAs orchestrate metastatic progression through several mechanisms, including the interaction with epigenetic effectors, splicing control and generation of microRNA-like molecules. In contrast, snoRNAs have been long considered "housekeeping" genes with no relevant function in cancer. However, recent evidence challenges this assumption, indicating that some snoRNAs are deregulated in cancer cells and may play a specific role in metastasis. Interestingly, snoRNAs and lncRNAs share several mechanisms of action, and might synergize with protein-coding genes to generate a specific cellular phenotype. This evidence suggests that the current paradigm of metastatic progression is incomplete. We propose that NC-RNAs are organized in complex interactive networks which orchestrate cellular phenotypic plasticity. Since plasticity is critical for cancer cell metastasis, we suggest that a molecular interactome composed by both NC-RNAs and proteins orchestrates cancer metastasis. Interestingly, expression of lncRNAs and snoRNAs can be detected in biological fluids, making them potentially useful biomarkers. NC-RNA expression profiles in human neoplasms have been associated with patients' prognosis. SnoRNA and lncRNA silencing in pre-clinical models leads to cancer cell death and/or metastasis prevention, suggesting they can be investigated as novel therapeutic targets. Based on the literature to date, we critically discuss how the NC-RNA interactome can be explored and manipulated to generate more effective diagnostic, prognostic, and therapeutic strategies for metastatic neoplasms

Surface-enhanced raman scattering (Sers) spectroscopy for sensing and characterization of exosomes in cancer diagnosis

28 pags., 14 figs. -- This article belongs to the Special Issue Exosomes in Cancers TherapyExosomes are emerging as one of the most intriguing cancer biomarkers in modern oncology for early cancer diagnosis, prognosis and treatment monitoring. Concurrently, several nano-plasmonic methods have been applied and developed to tackle the challenging task of enabling the rapid, sensitive, affordable analysis of exosomes. In this review, we specifically focus our attention on the application of plasmonic devices exploiting surface-enhanced Raman spectroscopy (SERS) as the optosensing technique for the structural interrogation and characterization of the heteroge-neous nature of exosomes. We summarized the current state-of-art of this field while illustrating the main strategic approaches and discuss their advantages and limitations.This research was supported by the Spanish Ministerio de Economia y Competitividad (CTQ2017-88648R and RYC-2016-20331), the Generalitat de Cataluña (2017SGR883), and the Universitat Rovira I Virgili (FR 2019-B2)

The Polycomb group protein CBX6 is an essential regulator of embryonic stem cell identity

Polycomb group proteins (PcG) are transcriptional repressors that control cell identity and development. In mammals, five different CBX proteins associate with the core Polycomb repressive complex 1 (PRC1). In mouse embryonic stem cells (ESCs), CBX6 and CBX7 are the most highly expressed CBX family members. CBX7 has been recently characterized, but little is known regarding the function of CBX6. Here, we show that CBX6 is essential for ESC identity. Its depletion destabilizes the pluripotency network and triggers differentiation. Mechanistically, we find that CBX6 is physically and functionally associated to both canonical PRC1 (cPRC1) and non-canonical PRC1 (ncPRC1) complexes. Notably, in contrast to CBX7, CBX6 is recruited to chromatin independently of H3K27me3. Taken together, our findings reveal that CBX6 is an essential component of ESC biology that contributes to the structural and functional complexity of the PRC1 complex.This work was supported by grants from the Spanish Ministry of Economy and Competitiveness (BFU2016-75008-P), Centro de Excelencia Severo Ochoa 2013-2017 (SEV-2012-0208), AGAUR, Fundació “La Marató de TV3,” CERCA Programme/Generalitat de Catalunya, and EU FP7 Programs 4DCellFate (277899) to L.D.C. This work aided by collaboration with the National Center for Dynamic Interactome Research and the National Resource for the Mass Spectrometric Analysis of Biological Macromolecules, supported in part by NIH grant P41 GM109824 to Michael P. Rout and grant P41 GM103314 to Brian T. Chait. This paper is subject to the NIH Public Access Policy