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      A Multi-Cancer Mesenchymal Transition Gene Expression Signature Is Associated with Prolonged Time to Recurrence in Glioblastoma

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          Abstract

          A stage-associated gene expression signature of coordinately expressed genes, including the transcription factor Slug (SNAI2) and other epithelial-mesenchymal transition (EMT) markers has been found present in samples from publicly available gene expression datasets in multiple cancer types, including nonepithelial cancers. The expression levels of the co-expressed genes vary in a continuous and coordinate manner across the samples, ranging from absence of expression to strong co-expression of all genes. These data suggest that tumor cells may pass through an EMT-like process of mesenchymal transition to varying degrees. Here we show that, in glioblastoma multiforme (GBM), this signature is associated with time to recurrence following initial treatment. By analyzing data from The Cancer Genome Atlas (TCGA), we found that GBM patients who responded to therapy and had long time to recurrence had low levels of the signature in their tumor samples ( P = 3×10 −7). We also found that the signature is strongly correlated in gliomas with the putative stem cell marker CD44, and is highly enriched among the differentially expressed genes in glioblastomas vs. lower grade gliomas. Our results suggest that long delay before tumor recurrence is associated with absence of the mesenchymal transition signature, raising the possibility that inhibiting this transition might improve the durability of therapy in glioma patients.

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          Most cited references14

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          Epithelial-mesenchymal transitions in development and disease.

          The epithelial to mesenchymal transition (EMT) plays crucial roles in the formation of the body plan and in the differentiation of multiple tissues and organs. EMT also contributes to tissue repair, but it can adversely cause organ fibrosis and promote carcinoma progression through a variety of mechanisms. EMT endows cells with migratory and invasive properties, induces stem cell properties, prevents apoptosis and senescence, and contributes to immunosuppression. Thus, the mesenchymal state is associated with the capacity of cells to migrate to distant organs and maintain stemness, allowing their subsequent differentiation into multiple cell types during development and the initiation of metastasis.
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            Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis.

            Previously undescribed prognostic subclasses of high-grade astrocytoma are identified and discovered to resemble stages in neurogenesis. One tumor class displaying neuronal lineage markers shows longer survival, while two tumor classes enriched for neural stem cell markers display equally short survival. Poor prognosis subclasses exhibit markers either of proliferation or of angiogenesis and mesenchyme. Upon recurrence, tumors frequently shift toward the mesenchymal subclass. Chromosomal locations of genes distinguishing tumor subclass parallel DNA copy number differences between subclasses. Functional relevance of tumor subtype molecular signatures is suggested by the ability of cell line signatures to predict neurosphere growth. A robust two-gene prognostic model utilizing PTEN and DLL3 expression suggests that Akt and Notch signaling are hallmarks of poor prognosis versus better prognosis gliomas, respectively.
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              TWIST1 promotes invasion through mesenchymal change in human glioblastoma

              Background Tumor cell invasion into adjacent normal brain is a mesenchymal feature of GBM and a major factor contributing to their dismal outcomes. Therefore, better understandings of mechanisms that promote mesenchymal change in GBM are of great clinical importance to address invasion. We previously showed that the bHLH transcription factor TWIST1 which orchestrates carcinoma metastasis through an epithelial mesenchymal transition (EMT) is upregulated in GBM and promotes invasion of the SF767 GBM cell line in vitro. Results To further define TWIST1 functions in GBM we tested the impact of TWIST1 over-expression on invasion in vivo and its impact on gene expression. We found that TWIST1 significantly increased SNB19 and T98G cell line invasion in orthotopic xenotransplants and increased expression of genes in functional categories associated with adhesion, extracellular matrix proteins, cell motility and locomotion, cell migration and actin cytoskeleton organization. Consistent with this TWIST1 reduced cell aggregation, promoted actin cytoskeletal re-organization and enhanced migration and adhesion to fibronectin substrates. Individual genes upregulated by TWIST1 known to promote EMT and/or GBM invasion included SNAI2, MMP2, HGF, FAP and FN1. Distinct from carcinoma EMT, TWIST1 did not generate an E- to N-cadherin "switch" in GBM cell lines. The clinical relevance of putative TWIST target genes SNAI2 and fibroblast activation protein alpha (FAP) identified in vitro was confirmed by their highly correlated expression with TWIST1 in 39 human tumors. The potential therapeutic importance of inhibiting TWIST1 was also shown through a decrease in cell invasion in vitro and growth of GBM stem cells. Conclusions Together these studies demonstrated that TWIST1 enhances GBM invasion in concert with mesenchymal change not involving the canonical cadherin switch of carcinoma EMT. Given the recent recognition that mesenchymal change in GBMs is associated with increased malignancy, these findings support the potential therapeutic importance of strategies to subvert TWIST1-mediated mesenchymal change.
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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
                6 April 2012
                : 7
                : 4
                : e34705
                Affiliations
                [1 ]Center for Computational Biology and Bioinformatics, Columbia University, New York, New York, United States of America
                [2 ]Institute for Cancer Genetics, Columbia University, New York, New York, United States of America
                [3 ]Department of Surgery, Columbia University, New York, New York, United States of America
                [4 ]Department of Pediatrics, Columbia University, New York, New York, United States of America
                [5 ]Department of Pathology and Cell Biology, Columbia University, New York, New York, United States of America
                [6 ]Columbia Stem Cell Initiative, Columbia University, New York, New York, United States of America
                [7 ]Department of Electrical Engineering, Columbia University, New York, New York, United States of America
                University of Florida, United States of America
                Author notes

                Conceived and designed the experiments: WYC DA. Performed the experiments: WYC DA. Analyzed the data: WYC JJK DJY PC DA. Wrote the paper: DA.

                Article
                PONE-D-11-24344
                10.1371/journal.pone.0034705
                3321034
                22493711
                11b1931f-1628-44e4-9363-d246ede5fbb6
                Cheng et al. 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
                : 2 December 2011
                : 6 March 2012
                Page count
                Pages: 8
                Categories
                Research Article
                Biology
                Computational Biology
                Genomics
                Genome Analysis Tools
                Developmental Biology
                Stem Cells
                Genomics
                Genome Analysis Tools
                Systems Biology
                Medicine
                Oncology
                Cancers and Neoplasms
                Neurological Tumors

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                Uncategorized

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