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      Decorin Protein Core Affects the Global Gene Expression Profile of the Tumor Microenvironment in a Triple-Negative Orthotopic Breast Carcinoma Xenograft Model

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          Abstract

          Decorin, a member of the small leucine-rich proteoglycan gene family, exists and functions wholly within the tumor microenvironment to suppress tumorigenesis by directly targeting and antagonizing multiple receptor tyrosine kinases, such as the EGFR and Met. This leads to potent and sustained signal attenuation, growth arrest, and angiostasis. We thus sought to evaluate the tumoricidal benefits of systemic decorin on a triple-negative orthotopic breast carcinoma xenograft model. To this end, we employed a novel high-density mixed expression array capable of differentiating and simultaneously measuring gene signatures of both Mus musculus (stromal) and Homo sapiens (epithelial) tissue origins. We found that decorin protein core modulated the differential expression of 374 genes within the stromal compartment of the tumor xenograft. Further, our top gene ontology classes strongly suggests an unexpected and preferential role for decorin protein core to inhibit genes necessary for immunomodulatory responses while simultaneously inducing expression of those possessing cellular adhesion and tumor suppressive gene properties. Rigorous verification of the top scoring candidates led to the discovery of three genes heretofore unlinked to malignant breast cancer that were reproducibly found to be induced in several models of tumor stroma. Collectively, our data provide highly novel and unexpected stromal gene signatures as a direct function of systemic administration of decorin protein core and reveals a fundamental basis of action for decorin to modulate the tumor stroma as a biological mechanism for the ascribed anti-tumorigenic properties.

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          Stromal gene expression predicts clinical outcome in breast cancer.

          Although it is increasingly evident that cancer is influenced by signals emanating from tumor stroma, little is known regarding how changes in stromal gene expression affect epithelial tumor progression. We used laser capture microdissection to compare gene expression profiles of tumor stroma from 53 primary breast tumors and derived signatures strongly associated with clinical outcome. We present a new stroma-derived prognostic predictor (SDPP) that stratifies disease outcome independently of standard clinical prognostic factors and published expression-based predictors. The SDPP predicts outcome in several published whole tumor-derived expression data sets, identifies poor-outcome individuals from multiple clinical subtypes, including lymph node-negative tumors, and shows increased accuracy with respect to previously published predictors, especially for HER2-positive tumors. Prognostic power increases substantially when the predictor is combined with existing outcome predictors. Genes represented in the SDPP reveal the strong prognostic capacity of differential immune responses as well as angiogenic and hypoxic responses, highlighting the importance of stromal biology in tumor progression.
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            Molecular characterization of the tumor microenvironment in breast cancer.

            Here we describe the comprehensive gene expression profiles of each cell type composing normal breast tissue and in situ and invasive breast carcinomas using serial analysis of gene expression. Based on these data, we determined that extensive gene expression changes occur in all cell types during cancer progression and that a significant fraction of altered genes encode secreted proteins and receptors. Despite the dramatic gene expression changes in all cell types, genetic alterations were detected only in cancer epithelial cells. The CXCL14 and CXCL12 chemokines overexpressed in tumor myoepithelial cells and myofibroblasts, respectively, bind to receptors on epithelial cells and enhance their proliferation, migration, and invasion. Thus, chemokines may play a role in breast tumorigenesis by acting as paracrine factors.
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              Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression.

              Many studies have used DNA microarrays to identify the gene expression signatures of human cancer, yet the critical features of these often unmanageably large signatures remain elusive. To address this, we developed a statistical method, comparative metaprofiling, which identifies and assesses the intersection of multiple gene expression signatures from a diverse collection of microarray data sets. We collected and analyzed 40 published cancer microarray data sets, comprising 38 million gene expression measurements from >3,700 cancer samples. From this, we characterized a common transcriptional profile that is universally activated in most cancer types relative to the normal tissues from which they arose, likely reflecting essential transcriptional features of neoplastic transformation. In addition, we characterized a transcriptional profile that is commonly activated in various types of undifferentiated cancer, suggesting common molecular mechanisms by which cancer cells progress and avoid differentiation. Finally, we validated these transcriptional profiles on independent data sets.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                19 September 2012
                : 7
                : 9
                : e45559
                Affiliations
                [1 ]Department of Pathology, Anatomy and Cell Biology, and the Cancer Cell Biology and Signaling Program, Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, Pennsylvania, United States of America
                [2 ]LifeCell Corporation, Branchburg, New Jersey, United States of America
                [3 ]Roche NimbleGen, Inc., Research and Development, Madison, Wisconsin, United States of America
                [4 ]Department of Pharmacology, Goethe University, Frankfurt, Germany
                National Cancer Institute at Frederick, United States of America
                Author notes

                Competing Interests: RTO works for LifeCell Co. and has provided the recombinant decorin used for the studies. LAI works for Roche-NibleGen Co. and has provided expertise in performing the microarray data. There are no patents, products in development or marketed products to declare. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: RVI SB TN. Performed the experiments: SB TN. Analyzed the data: RVI SB TN GP RV BE LS Z-XW. Contributed reagents/materials/analysis tools: RTO LAI SCP Z-XW. Wrote the paper: RVI SB TN.

                Article
                PONE-D-12-13779
                10.1371/journal.pone.0045559
                3446891
                23029096
                d410e64a-ca49-4b79-99f5-92685cccfb34
                Copyright @ 2012

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 14 May 2012
                : 21 August 2012
                Page count
                Pages: 13
                Funding
                This work was in part supported by the National Institutes of Health grants RO1 CA39481, RO1 CA47282 and RO1 CA120975 (to RVI), and training grant T32 AA07463 (to TN). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. No additional external funding received for this study.
                Categories
                Research Article
                Biology
                Biochemistry
                Glycobiology
                Proteoglycans
                Proteins
                DNA-binding proteins
                Extracellular Matrix Proteins
                Growth Factors
                Immune System Proteins
                Regulatory Proteins
                Transmembrane Proteins
                Medicine
                Obstetrics and Gynecology
                Breast Cancer
                Oncology
                Cancers and Neoplasms
                Breast Tumors

                Uncategorized
                Uncategorized

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