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      The small GTPase RhoU lays downstream of JAK/STAT signaling and mediates cell migration in multiple myeloma

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          Abstract

          Multiple myeloma is a post-germinal center B-cell neoplasm, characterized by the proliferation of malignant bone marrow plasma cells, whose survival and proliferation is sustained by growth factors and cytokines present in the bone marrow microenvironment. Among them, IL-6 triggers the signal downstream of its receptor, leading to the activation of the JAK/STAT pathway. The atypical GTPase RhoU lays downstream of STAT3 transcription factor and could be responsible for mediating its effects on cytoskeleton dynamics. Here we demonstrate that RHOU is heterogeneously expressed in primary multiple myeloma cells and significantly modulated with disease progression. At the mRNA level, RHOU expression in myeloma patients correlated with the expression of STAT3 and its targets MIR21 and SOCS3. Also, IL-6 stimulation of human myeloma cell lines up-regulated RHOU through STAT3 activation. On the other hand, RhoU silencing led to a decrease in cell migration with the accumulation of actin stress fibers, together with a decrease in cyclin D2 expression and in cell cycle progression. Furthermore, we found that even though lenalidomide positively regulated RhoU expression leading to higher cell migration rates, it actually led to cell cycle arrest probably through a p21 dependent mechanism. Lenalidomide treatment in combination with RhoU silencing determined a loss of cytoskeletal organization inhibiting cell migration, and a further increase in the percentage of cells in a resting phase. These results unravel a role for RhoU not only in regulating the migratory features of malignant plasma cells, but also in controlling cell cycle progression.

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          In silico prediction of protein-protein interactions in human macrophages

          Background: Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. Results: We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. Conclusion: Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level.
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            The molecular classification of multiple myeloma.

            To better define the molecular basis of multiple myeloma (MM), we performed unsupervised hierarchic clustering of mRNA expression profiles in CD138-enriched plasma cells from 414 newly diagnosed patients who went on to receive high-dose therapy and tandem stem cell transplants. Seven disease subtypes were validated that were strongly influenced by known genetic lesions, such as c-MAF- and MAFB-, CCND1- and CCND3-, and MMSET-activating translocations and hyperdiploidy. Indicative of the deregulation of common pathways by gene orthologs, common gene signatures were observed in cases with c-MAF and MAFB activation and CCND1 and CCND3 activation, the latter consisting of 2 subgroups, one characterized by expression of the early B-cell markers CD20 and PAX5. A low incidence of focal bone disease distinguished one and increased expression of proliferation-associated genes of another novel subgroup. Comprising varying fractions of each of the other 6 subgroups, the proliferation subgroup dominated at relapse, suggesting that this signature is linked to disease progression. Proliferation and MMSET-spike groups were characterized by significant overexpression of genes mapping to chromosome 1q, and both exhibited a poor prognosis relative to the other groups. A subset of cases with a predominating myeloid gene expression signature, excluded from the profiling analyses, had more favorable baseline characteristics and superior prognosis to those lacking this signature.
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              Stattic: a small-molecule inhibitor of STAT3 activation and dimerization.

              Signal transducers and activators of transcription (STATs) are a family of latent cytoplasmic transcription factors that transmit signals from the cell membrane to the nucleus. One family member, STAT3, is constitutively activated by aberrant upstream tyrosine kinase activities in a broad spectrum of cancer cell lines and human tumors. Screening of chemical libraries led to the identification of Stattic, a nonpeptidic small molecule shown to selectively inhibit the function of the STAT3 SH2 domain regardless of the STAT3 activation state in vitro. Stattic selectively inhibits activation, dimerization, and nuclear translocation of STAT3 and increases the apoptotic rate of STAT3-dependent breast cancer cell lines. We propose Stattic as a tool for the inhibition of STAT3 in cell lines or animal tumor models displaying constitutive STAT3 activation.
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                Author and article information

                Contributors
                +0039 049 7923243 , francesco.piazza@unipd.it
                Journal
                Blood Cancer J
                Blood Cancer J
                Blood Cancer Journal
                Nature Publishing Group UK (London )
                2044-5385
                13 February 2018
                13 February 2018
                2018
                : 8
                : 2
                : 20
                Affiliations
                [1 ]ISNI 0000 0004 1757 3470, GRID grid.5608.b, Department of Medicine, Division of Hematology, , University of Padova, ; Padova, Italy
                [2 ]GRID grid.428736.c, Laboratory of Normal and Malignant Hematopoiesis, , Venetian Institute of Molecular Medicine, ; Padova, Italy
                [3 ]ISNI 0000 0004 1757 8749, GRID grid.414818.0, Hematology Unit, Fondazione IRCCS Ca’ Granda, , Ospedale Maggiore Policlinico, ; Milan, Italy
                [4 ]ISNI 0000 0004 1757 2822, GRID grid.4708.b, Department of Oncology and Hemato-Oncology, , University of Milano, ; Milano, Italy
                [5 ]ISNI 0000 0004 1757 3470, GRID grid.5608.b, Surgical Pathology and Cytopathology Unit, Department of Medicine - DIMED, , University of Padova, ; Padova, Italy
                [6 ]ISNI 0000 0001 2106 9910, GRID grid.65499.37, Present Address: Department of Medical Oncology, , Dana-Farber Cancer Institute, ; Boston, MA USA
                Author information
                http://orcid.org/0000-0003-0861-9951
                http://orcid.org/0000-0003-0271-7200
                http://orcid.org/0000-0002-7447-2946
                Article
                53
                10.1038/s41408-018-0053-z
                5811530
                29440639
                45bedcd7-5b95-40fe-9fab-7ca060236f20
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 October 2017
                : 19 December 2017
                : 8 January 2018
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                © The Author(s) 2018

                Oncology & Radiotherapy
                Oncology & Radiotherapy

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