CITED4 gene silencing in colorectal cancer cells modulates adherens/tight junction gene expression and reduces cell proliferation

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Abstract

Purpose

CITED4 is one member of a family of transcriptional cofactors, several of which are deregulated in a variety of tumors, including colorectal cancer (CRC). We modulated CITED4 expression, in vitro, and analyzed the associated phenotypic and gene expression changes.

Methods

CITED4-overexpressing and shRNA-mediated knockdown cell lines and control cell lines were established in the CRC cell line SW480. The cells were analyzed for changes in proliferation, apoptosis/cell cycle, migration, invasion, colony formation and adhesion. mRNA expression changes were determined by microarray and pathway analysis, and several deregulated genes were validated by qRT-PCR and Western blotting. Based on results obtained from these studies, the status of the actin cytoskeleton was evaluated by phalloidin/vinculin staining.

Results

Phenotypically, the CITED4-overexpressing cell line showed only moderate changes in adhesion. Microarray analysis identified several deregulated genes, including several G protein-coupled receptors. Phenotypic analysis of the CITED4 shRNA knockdown cell line demonstrated decreased cell proliferation and G2 cell cycle blockage. Microarray analysis identified many deregulated genes, and pathway analysis discovered genes linked to actin-associated adherens junctions/tight junctions (claudin-4, claudin-7, ezrin, MET, ß-catenin). Phenotypically, no morphological changes of the actin cytoskeleton were seen.

Conclusions

Upregulation of CITED4 in SW480 resulted in no obvious phenotype. CITED4 shRNA-mediated knockdown led to decreased cellular proliferation and modulation of a large number of genes, including the c-MET tyrosine kinase and several actin-associated adherens junctions/tight junction genes.

Electronic supplementary material

The online version of this article (doi:10.1007/s00432-015-2011-5) contains supplementary material, which is available to authorized users.

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Most cited references 40

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ERM proteins and merlin: integrators at the cell cortex.

Anthony Bretscher, Kevin Edwards, Richard Fehon (2002)

A fundamental property of many plasma-membrane proteins is their association with the underlying cytoskeleton to determine cell shape, and to participate in adhesion, motility and other plasma-membrane processes, including endocytosis and exocytosis. The ezrin-radixin-moesin (ERM) proteins are crucial components that provide a regulated linkage between membrane proteins and the cortical cytoskeleton, and also participate in signal-transduction pathways. The closely related tumour suppressor merlin shares many properties with ERM proteins, yet also provides a distinct and essential function.

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Metastasis-Associated Gene Expression Changes Predict Poor Outcomes in Patients with Dukes Stage B and C Colorectal Cancer.

Robert Jorissen, Peter E.M. Gibbs, Michael Christie … (2009)

PURPOSE: Colorectal cancer prognosis is currently predicted from pathologic staging, providing limited discrimination for Dukes stage B and C disease. Additional markers for outcome are required to help guide therapy selection for individual patients. EXPERIMENTAL DESIGN: A multisite single-platform microarray study was done on 553 colorectal cancers. Gene expression changes were identified between stage A and D tumors (three training sets) and assessed as a prognosis signature in stage B and C tumors (independent test and external validation sets). RESULTS: One hundred twenty-eight genes showed reproducible expression changes between three sets of stage A and D cancers. Using consistent genes, stage B and C cancers clustered into two groups resembling early-stage and metastatic tumors. A Prediction Analysis of Microarray algorithm was developed to classify individual intermediate-stage cancers into stage A-like/good prognosis or stage D-like/poor prognosis types. For stage B patients, the treatment adjusted hazard ratio for 6-year recurrence in individuals with stage D-like cancers was 10.3 (95% confidence interval, 1.3-80.0; P = 0.011). For stage C patients, the adjusted hazard ratio was 2.9 (95% confidence interval, 1.1-7.6; P = 0.016). Similar results were obtained for an external set of stage B and C patients. The prognosis signature was enriched for downregulated immune response genes and upregulated cell signaling and extracellular matrix genes. Accordingly, sparse tumor infiltration with mononuclear chronic inflammatory cells was associated with poor outcome in independent patients. CONCLUSIONS: Metastasis-associated gene expression changes can be used to refine traditional outcome prediction, providing a rational approach for tailoring treatments to subsets of patients. (Clin Cancer Res 2009;15(24):7642-51).

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Is Open Access

Chipster: user-friendly analysis software for microarray and other high-throughput data

M Kallio, Jarno Tuimala, Taavi Hupponen … (2011)

Background The growth of high-throughput technologies such as microarrays and next generation sequencing has been accompanied by active research in data analysis methodology, producing new analysis methods at a rapid pace. While most of the newly developed methods are freely available, their use requires substantial computational skills. In order to enable non-programming biologists to benefit from the method development in a timely manner, we have created the Chipster software. Results Chipster (http://chipster.csc.fi/) brings a powerful collection of data analysis methods within the reach of bioscientists via its intuitive graphical user interface. Users can analyze and integrate different data types such as gene expression, miRNA and aCGH. The analysis functionality is complemented with rich interactive visualizations, allowing users to select datapoints and create new gene lists based on these selections. Importantly, users can save the performed analysis steps as reusable, automatic workflows, which can also be shared with other users. Being a versatile and easily extendable platform, Chipster can be used for microarray, proteomics and sequencing data. In this article we describe its comprehensive collection of analysis and visualization tools for microarray data using three case studies. Conclusions Chipster is a user-friendly analysis software for high-throughput data. Its intuitive graphical user interface enables biologists to access a powerful collection of data analysis and integration tools, and to visualize data interactively. Users can collaborate by sharing analysis sessions and workflows. Chipster is open source, and the server installation package is freely available.

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Author and article information

Contributors

Peter Lichter: +(49)-7221-424619 , peter.lichter@dkfz.de

Journal

Journal ID (nlm-ta): J Cancer Res Clin Oncol

Journal ID (iso-abbrev): J. Cancer Res. Clin. Oncol

Title: Journal of Cancer Research and Clinical Oncology

Publisher: Springer Berlin Heidelberg (Berlin/Heidelberg )

ISSN (Print): 0171-5216

ISSN (Electronic): 1432-1335

Publication date (Electronic): 5 August 2015

Publication date PMC-release: 5 August 2015

Publication date (Print): 2016

Volume: 142

Pages: 225-237

Affiliations

Division of Molecular Genetics (B060), German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany

Article

Publisher ID: 2011

DOI: 10.1007/s00432-015-2011-5

PMC ID: 4705123

PubMed ID: 26243458

SO-VID: 8b4e29b1-2b73-4262-b6ae-0093e836f7eb

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

History

Date received : 17 March 2015

Date accepted : 27 June 2015

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;

Award ID: LI406/12-2

Award Recipient : Peter Lichter

Custom metadata

ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: gene expression,colorectal cancer,microarray,tight junctions,adherens junctions,c-met,actin,claudins,ezrin,cited4

Data availability: