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      Analysis of gene expression of secreted factors associated with breast cancer metastases in breast cancer subtypes

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          Abstract

          Breast cancer is a heterogeneous disease, having multiple subtypes with different malignant phenotypes. The triple-negative breast cancer, or basal breast cancer, is highly aggressive, metastatic, and difficult to treat. Previously, we identified that key molecules (IL6, CSF2, CCL5, VEGFA, and VEGFC) secreted by tumor cells and stromal cells in basal breast cancer can promote metastasis. It remains to assess whether these molecules function similarly in other subtypes of breast cancer. Here, we characterize the relative gene expression of the five secreted molecules and their associated receptors (GP130, GMRA, GMRB, CCR5, VEGFR2, NRP1, VEGFR3, NRP2) in the basal, HER2 (human epidermal growth factor receptor 2) positive, luminal A, and luminal B subtypes using high throughput data from tumor samples in The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). IL6 and CCL5 gene expression are basal breast cancer specific, whereas high gene expression of GP130 was observed in luminal A/B. VEGFA/C and CSF2 mRNA are overexpressed in HER2 positive breast cancer, with VEGFA and CSF2 also overexpressed in basal breast cancer. Further study of the specific protein function of these factors within their associated cancer subtypes may yield personalized biomarkers and treatment modalities.

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          Most cited references 30

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          Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

           J. Gao,  B. Aksoy,  U Dogrusoz (2013)
          The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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            Inducible formation of breast cancer stem cells and their dynamic equilibrium with non-stem cancer cells via IL6 secretion.

            Tumors are often heterogeneous, being composed of multiple cell types with different phenotypic and molecular properties. Cancer stem-like cells (CSCs) are a highly tumorigenic cell type found in developmentally diverse tumors or cancer cell lines, and they are often resistant to standard chemotherapeutic drugs. The origins of CSCs and their relationships to nonstem cancer cells (NSCCs) are poorly understood. In an inducible breast oncogenesis model, CSCs are generated from nontransformed cells at a specific time during the transformation process, but CSC formation is not required for transformation. MicroRNA profiles indicate that CSCs and NSCCs are related, but different cell types arising from a common nontransformed population. Interestingly, medium from the transformed population stimulates NSCCs to become CSCs, and conversion of NSCCs to CSCs occurs in mouse xenografts. Furthermore, IL6 is sufficient to convert NSCCs to CSCs in genetically different breast cell lines, human breast tumors, and a prostate cell line. Thus, breast and prostate CSCs and NSCCs do not represent distinct epigenetic states, and these CSCs do not behave as or arise from classic stem cells. Instead, tumor heterogeneity involves a dynamic equilibrium between CSCs and NSCCs mediated by IL6 and activation of the inflammatory feedback loop required for oncogenesis. This dynamic equilibrium provides an additional rationale for combining conventional chemotherapy with metformin, which selectively inhibits CSCs.
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              Chemokines in innate and adaptive host defense: basic chemokinese grammar for immune cells.

              Chemokines compose a sophisticated communication system used by all our cell types, including immune cells. Chemokine messages are decoded by specific receptors that initiate signal transduction events leading to a multitude of cellular responses, leukocyte chemotaxis and adhesion in particular. Critical determinants of the in vivo activities of chemokines in the immune system include their presentation by endothelial cells and extracellular matrix molecules, as well as their cellular uptake via "silent" chemokine receptors (interceptors) leading either to their transcytosis or to degradation. These regulatory mechanisms of chemokine histotopography, as well as the promiscuous and overlapping receptor specificities of inflammation-induced chemokines, shape innate responses to infections and tissue damage. Conversely, the specific patterns of homeostatic chemokines, where each chemokine is perceived by a single receptor, are charting lymphocyte navigation routes for immune surveillance. This review presents our current understanding of the mechanisms that regulate the cellular perception and pathophysiologic meaning of chemokines.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                15 July 2015
                2015
                : 5
                Affiliations
                [1 ]Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University , Baltimore, MD, USA
                [2 ]Department of Biomedical Engineering, Johns Hopkins University School of Medicine , Baltimore, MD, USA
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                srep12133
                10.1038/srep12133
                4648401
                26173622
                Copyright © 2015, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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