Dataset Information

Differential Expression of Ccn4 and Other Genes Between Metastatic and Non-metastatic EL4 Mouse Lymphoma Cells.

ABSTRACT: BACKGROUND:Previous work characterized variants of the EL4 murine lymphoma cell line. Some are non-metastatic, and others metastatic, in syngenic mice. In addition, metastatic EL4 cells were stably transfected with phospholipase D2 (PLD2), which further enhanced metastasis. MATERIALS AND METHODS:Microarray analyses of mRNA expression was performed for non-metastatic, metastatic, and PLD2-expressing metastatic EL4 cells. RESULTS:Many differences were observed between non-metastatic and metastatic cell lines. One of the most striking new findings was up-regulation of mRNA for the matricellular protein WNT1-inducible signaling pathway protein 1 (CCN4) in metastatic cells; increased protein expression was verified by immunoblotting and immunocytochemistry. Other differentially expressed genes included those for reproductive homeobox 5 (Rhox5; increased in metastatic) and cystatin 7 (Cst7; decreased in metastatic). Differences between PLD2-expressing and parental cell lines were limited but included the signaling proteins Ras guanyl releasing protein 1 (RGS18; increased with PLD2) and suppressor of cytokine signaling 2 (SOCS2; decreased with PLD2). CONCLUSION:The results provide insights into signaling pathways potentially involved in conferring metastatic ability on lymphoma cells.

SUBMITTER: Chahal MS

PROVIDER: S-EPMC5219917 | biostudies-literature | 2016 11-12

REPOSITORIES: biostudies-literature

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Differential Expression of Ccn4 and Other Genes Between Metastatic and Non-metastatic EL4 Mouse Lymphoma Cells.

Chahal Manpreet S MS Ku H Teresa HT Zhang Zhihong Z Legaspi Christian M CM Luo Angela A Hopkins Mandi M MM Meier Kathryn E KE

Cancer genomics & proteomics 20160101 6

<h4>Background</h4>Previous work characterized variants of the EL4 murine lymphoma cell line. Some are non-metastatic, and others metastatic, in syngenic mice. In addition, metastatic EL4 cells were stably transfected with phospholipase D2 (PLD2), which further enhanced metastasis.<h4>Materials and methods</h4>Microarray analyses of mRNA expression was performed for non-metastatic, metastatic, and PLD2-expressing metastatic EL4 cells.<h4>Results</h4>Many differences were observed between non-met ...[more]

PMID: 27807066

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Project description:BackgroundTo utilize the large volume of gene expression information generated from different microarray experiments, several meta-analysis techniques have been developed. Despite these efforts, there remain significant challenges to effectively increasing the statistical power and decreasing the Type I error rate while pooling the heterogeneous datasets from public resources. The objective of this study is to develop a novel meta-analysis approach, Consistent Differential Expression Pattern (CDEP), to identify genes with common differential expression patterns across different datasets.ResultsWe combined False Discovery Rate (FDR) estimation and the non-parametric RankProd approach to estimate the Type I error rate in each microarray dataset of the meta-analysis. These Type I error rates from all datasets were then used to identify genes with common differential expression patterns. Our simulation study showed that CDEP achieved higher statistical power and maintained low Type I error rate when compared with two recently proposed meta-analysis approaches. We applied CDEP to analyze microarray data from different laboratories that compared transcription profiles between metastatic and primary cancer of different types. Many genes identified as differentially expressed consistently across different cancer types are in pathways related to metastatic behavior, such as ECM-receptor interaction, focal adhesion, and blood vessel development. We also identified novel genes such as AMIGO2, Gem, and CXCL11 that have not been shown to associate with, but may play roles in, metastasis.ConclusionsCDEP is a flexible approach that borrows information from each dataset in a meta-analysis in order to identify genes being differentially expressed consistently. We have shown that CDEP can gain higher statistical power than other existing approaches under a variety of settings considered in the simulation study, suggesting its robustness and insensitivity to data variation commonly associated with microarray experiments.AvailabilityCDEP is implemented in R and freely available at: http://genomebioinfo.musc.edu/CDEP/.Contactzhengw@musc.edu.

Dataset Information

Differential Expression of Ccn4 and Other Genes Between Metastatic and Non-metastatic EL4 Mouse Lymphoma Cells.

Publications

Differential Expression of Ccn4 and Other Genes Between Metastatic and Non-metastatic EL4 Mouse Lymphoma Cells.

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