Unknown,Transcriptomics,Genomics,Proteomics

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A combinatorial extracellular matrix platform identifies cell-extracellular matrix interactions that correlate with metastasis

ABSTRACT: Extracellular matrix interactions play essential roles in normal physiology and many pathological processes. Here, we report a novel screening platform capable of measuring phenotypic responses to combinations of ECM molecules. While the importance of ECM interactions in metastasis is well documented, systematic approaches to identify their roles in distinct stages of tumorigenesis have not been described. Using a genetic mouse model of lung adenocarcinoma, we measured the ECM-dependent adhesion of tumor-derived cells. Hierarchical clustering of adhesion profiles generated using this platform differentially segregated metastatic cell lines from primary tumor lines. Furthermore, we uncovered that metastatic cells selectively associate with fibronectin when in combination with galectin-3, galectin-8, or laminin. These interactions appear to be mediated in part by Î±3Î²1 integrin both in vitro and in vivo. We show that these galectins also correlate with human disease at both a transcriptional and histological level. Thus, our in vitro platform allowed us to interrogate the interactions of metastatic cells with their surrounding environment, and identified ECM and integrin interactions that could lead to therapeutic targets for metastasis prevention. Cell lines derived from murine lung primary adenocarcinomas and their metastases (Winslow et al., 2011 Nature 473:101-104)

ORGANISM(S): Mus musculus

SUBMITTER: Charles Whittaker

PROVIDER: E-GEOD-40222 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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A combinatorial extracellular matrix platform identifies cell-extracellular matrix interactions that correlate with metastasis.

Reticker-Flynn Nathan E NE Malta David F Braga DF Winslow Monte M MM Lamar John M JM Xu Mary J MJ Underhill Gregory H GH Hynes Richard O RO Jacks Tyler E TE Bhatia Sangeeta N SN

Nature communications 20120101

Extracellular matrix interactions have essential roles in normal physiology and many pathological processes. Although the importance of extracellular matrix interactions in metastasis is well documented, systematic approaches to identify their roles in distinct stages of tumorigenesis have not been described. Here we report a novel-screening platform capable of measuring phenotypic responses to combinations of extracellular matrix molecules. Using a genetic mouse model of lung adenocarcinoma, we ...[more]

PMID: 23047680

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Project description:Despite the high prevalence and poor outcome of patients with metastatic lung cancer, the mechanisms of tumour progression and metastasis remain largely uncharacterized. We modelled human lung adenocarcinoma, which frequently harbours activating point mutations in KRAS1 and inactivation of the p53-pathway2, using conditional alleles in mice3-5. Lentiviral-mediated somatic activation of oncogenic Kras and deletion of p53 in the lung epithelial cells of KrasLSL-G12D/+;p53flox/flox mice initiates lung adenocarcinoma development4. Although tumours are initiated synchronously by defined genetic alterations, only a subset become malignant, suggesting that disease progression requires additional alterations. Identification of the lentiviral integration sites allowed us to distinguish metastatic from non-metastatic tumours and determine the gene expression alterations that distinguish these tumour types. Cross-species analysis identified the NK-2 related homeobox transcription factor Nkx2-1 (Ttf-1/Titf1) as a candidate suppressor of malignant progression. In this mouse model, Nkx2-1-negativity is pathognomonic of high-grade poorly differentiated tumours. Gain- and loss-of-function experiments in cells derived from metastatic and non-metastatic tumours demonstrated that Nkx2-1 controls tumour differentiation and limits metastatic potential in vivo. Interrogation of Nkx2-1 regulated genes, analysis of tumours at defined developmental stages, and functional complementation experiments indicate that Nkx2-1 constrains tumours in part by repressing the embryonically-restricted chromatin regulator Hmga2. While focal amplification of NKX2-1 in a fraction of human lung adenocarcinomas has focused attention on its oncogenic function6-9, our data specifically link Nkx2-1 downregulation to loss of differentiation, enhanced tumour seeding ability, and increased metastatic proclivity. Thus, the oncogenic and suppressive functions of Nkx2-1 in the same tumour type substantiate its role as a dual function lineage factor. 23 cell lines derived from primary tumor or metastasis. 6 samples analyzed to determine the effect of Nkx2-1 knockdown on gene expression

Project description:Background Rheumatoid arthritis (RA) is a chronic inflammatory disease, characterized by joint destruction and perpetuated by the synovial membrane (SM). In the inflamed SM, activated synovial fibroblasts (SFB) form the major cell type promoting development and progression of the disease by an abnormal expression/secretion of pro-inflammatory cytokines, tissue-degrading enzymes resulting in a predominant degradation of the extra-cellular matrix (ECM), and collagens causing joint fibrosis. We developed a new procedure, based on human knowledge and formal concept analysis (FCA), to simulate and analyze the temporal behaviour of regulatory and signaling networks. It was applied to a regulatory network (containing 18 genes from 5 functional groups) representing ECM formation and destruction in TGFβ - and TNFα -stimulated SFB. Results For the modelling of SFB-controlled ECM turnover in rheumatic diseases, Boolean network architecture was used as well as extensive literature information and revision by experimental gene expression data from stimulated SFB. In course of revision, the additional experimental information resulted in different biologically reasonable changes, yielding two Boolean networks that describe TGFβ and TNFα effects, respectively. The final simulations were further analyzed by the attribute exploration algorithm of FCA, integrating again the observed time series in a more fine-grained and automated manner. The generated temporal rules clearly reveal subtle regulatory relationships between different genes, co-expression patterns and converse gene expression regulation in rheumatic diseases. Conclusion The developed Boolean network based method for the dynamical analysis of regulatory and signaling networks represents a reliable systems biological solution for the improved understanding of complex regulatory pathways and the interactions among different genes in disease. The resulting knowledge base can be used for further analysis of the ECM system in human fibroblasts and may be queried to predict the functional consequences of observed (e.g. in diseases as RA) or hypothetical (e.g. for therapeutic purposes) gene expression disturbances.

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A combinatorial extracellular matrix platform identifies cell-extracellular matrix interactions that correlate with metastasis

Publications

A combinatorial extracellular matrix platform identifies cell-extracellular matrix interactions that correlate with metastasis.

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