Blog
About

339
views
0
recommends
+1 Recommend
0 collections
    4
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Stromal gene expression defines poor-prognosis subtypes in colorectal cancer.

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Recent molecular classifications of colorectal cancer (CRC) based on global gene expression profiles have defined subtypes displaying resistance to therapy and poor prognosis. Upon evaluation of these classification systems, we discovered that their predictive power arises from genes expressed by stromal cells rather than epithelial tumor cells. Bioinformatic and immunohistochemical analyses identify stromal markers that associate robustly with disease relapse across the various classifications. Functional studies indicate that cancer-associated fibroblasts (CAFs) increase the frequency of tumor-initiating cells, an effect that is dramatically enhanced by transforming growth factor (TGF)-β signaling. Likewise, we find that all poor-prognosis CRC subtypes share a gene program induced by TGF-β in tumor stromal cells. Using patient-derived tumor organoids and xenografts, we show that the use of TGF-β signaling inhibitors to block the cross-talk between cancer cells and the microenvironment halts disease progression.

          Related collections

          Most cited references 22

          • Record: found
          • Abstract: found
          • Article: not found

          A faster circular binary segmentation algorithm for the analysis of array CGH data.

          Array CGH technologies enable the simultaneous measurement of DNA copy number for thousands of sites on a genome. We developed the circular binary segmentation (CBS) algorithm to divide the genome into regions of equal copy number. The algorithm tests for change-points using a maximal t-statistic with a permutation reference distribution to obtain the corresponding P-value. The number of computations required for the maximal test statistic is O(N2), where N is the number of markers. This makes the full permutation approach computationally prohibitive for the newer arrays that contain tens of thousands markers and highlights the need for a faster algorithm. We present a hybrid approach to obtain the P-value of the test statistic in linear time. We also introduce a rule for stopping early when there is strong evidence for the presence of a change. We show through simulations that the hybrid approach provides a substantial gain in speed with only a negligible loss in accuracy and that the stopping rule further increases speed. We also present the analyses of array CGH data from breast cancer cell lines to show the impact of the new approaches on the analysis of real data. An R version of the CBS algorithm has been implemented in the "DNAcopy" package of the Bioconductor project. The proposed hybrid method for the P-value is available in version 1.2.1 or higher and the stopping rule for declaring a change early is available in version 1.5.1 or higher.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Dependency of colorectal cancer on a TGF-β-driven program in stromal cells for metastasis initiation.

            A large proportion of colorectal cancers (CRCs) display mutational inactivation of the TGF-β pathway, yet, paradoxically, they are characterized by elevated TGF-β production. Here, we unveil a prometastatic program induced by TGF-β in the microenvironment that associates with a high risk of CRC relapse upon treatment. The activity of TGF-β on stromal cells increases the efficiency of organ colonization by CRC cells, whereas mice treated with a pharmacological inhibitor of TGFBR1 are resilient to metastasis formation. Secretion of IL11 by TGF-β-stimulated cancer-associated fibroblasts (CAFs) triggers GP130/STAT3 signaling in tumor cells. This crosstalk confers a survival advantage to metastatic cells. The dependency on the TGF-β stromal program for metastasis initiation could be exploited to improve the diagnosis and treatment of CRC. Copyright © 2012 Elsevier Inc. All rights reserved.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Inactivation of the type II TGF-beta receptor in colon cancer cells with microsatellite instability.

              Transforming growth factor-beta (TGF-beta) is a potent inhibitor of epithelial cell growth. Human colon cancer cell lines with high rates of microsatellite instability were found to harbor mutations in the type II TGF-beta receptor (RII) gene. Eight such examples, due to three different mutations, were identified. The mutations were clustered within small repeated sequences in the RII gene, were accompanied by the absence of cell surface RII receptors, and were usually associated with small amounts of RII transcript. RII mutation, by inducing the escape of cells from TGF-beta-mediated growth control, links DNA repair defects with a specific pathway of tumor progression.
                Bookmark

                Author and article information

                Journal
                Nat. Genet.
                Nature genetics
                1546-1718
                1061-4036
                Apr 2015
                : 47
                : 4
                Affiliations
                [1 ] Institute for Research in Biomedicine (IRB) Barcelona, Barcelona, Spain.
                [2 ] 1] Department of Pathology, Hospital del Mar, Barcelona, Spain. [2] Cancer Research Program, Hospital del Mar Research Institute (IMIM), Barcelona, Spain. [3] Universitat Autónoma de Barcelona, Barcelona, Spain.
                [3 ] 1] Institute for Research in Biomedicine (IRB) Barcelona, Barcelona, Spain. [2] Institució Catalana de Recerca i Estudis Avançats (iCREA), Barcelona, Spain.
                Article
                ng.3225
                10.1038/ng.3225
                25706628

                Comments

                Comment on this article