Dataset Information

Investigating the link between molecular subtypes of glioblastoma, epithelial-mesenchymal transition, and CD133 cell surface protein.

ABSTRACT: In this manuscript, we use genetic data to provide a three-faceted analysis on the links between molecular subclasses of glioblastoma, epithelial-to-mesenchymal transition (EMT) and CD133 cell surface protein. The contribution of this paper is three-fold: First, we use a newly identified signature for epithelial-to-mesenchymal transition in human mammary epithelial cells, and demonstrate that genes in this signature have significant overlap with genes differentially expressed in all known GBM subtypes. However, the overlap between genes up regulated in the mesenchymal subtype of GBM and in the EMT signature was more significant than other GBM subtypes. Second, we provide evidence that there is a negative correlation between the genetic signature of EMT and that of CD133 cell surface protein, a putative marker for neural stem cells. Third, we study the correlation between GBM molecular subtypes and the genetic signature of CD133 cell surface protein. We demonstrate that the mesenchymal and neural subtypes of GBM have the strongest correlations with the CD133 genetic signature. While the mesenchymal subtype of GBM displays similarity with the signatures of both EMT and CD133, it also exhibits some differences with each of these signatures that are partly due to the fact that the signatures of EMT and CD133 are inversely related to each other. Taken together these data shed light on the role of the mesenchymal transition and neural stem cells, and their mutual interaction, in molecular subtypes of glioblastoma multiforme.

SUBMITTER: Zarkoob H

PROVIDER: S-EPMC3667082 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Investigating the link between molecular subtypes of glioblastoma, epithelial-mesenchymal transition, and CD133 cell surface protein.

Zarkoob Hadi H Taube Joseph H JH Singh Sheila K SK Mani Sendurai A SA Kohandel Mohammad M

PloS one 20130529 5

In this manuscript, we use genetic data to provide a three-faceted analysis on the links between molecular subclasses of glioblastoma, epithelial-to-mesenchymal transition (EMT) and CD133 cell surface protein. The contribution of this paper is three-fold: First, we use a newly identified signature for epithelial-to-mesenchymal transition in human mammary epithelial cells, and demonstrate that genes in this signature have significant overlap with genes differentially expressed in all known GBM su ...[more]

PMID: 23734191

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Project description:BackgroundPancreatic cancer is a lethal disease due to the high incidence of metastasis at the time of detection. CD133 expression in clinical pancreatic cancer correlates with poor prognosis and metastasis. However, the molecular mechanism of CD133-regulated metastasis remains unclear. In recent years, epithelial-mesenchymal transition (EMT) has been linked to cancer invasion and metastasis. In the present study we investigated the role of CD133 in pancreatic cancer metastasis and its potential regulatory network.MethodsA highly migratory pancreatic cancer cell line, Capan1M9, was established previously. After shRNA was stable transducted to knock down CD133 in Capan1M9 cells, gene expression was profiled by DNA microarray. Orthotopic, splenic and intravenous transplantation mouse models were set up to examine the tumorigenesis and metastatic capabilities of these cells. In further experiments, real-time RT-PCR, Western blot and co-immunoprecipitate were conducted to evaluate the interactions of CD133, Slug, N-cadherin, ERK1/2 and SRC.ResultsWe found that CD133+ human pancreatic cancer cells were prone to generating metastatic nodules in in vivo models using immunodeficient mice. In contrast, CD133 knockdown suppressed cancer invasion and metastasis in vivo. Gene profiling analysis suggested that CD133 modulated mesenchymal characteristics including the expression of EMT-related genes, such as Slug and N-cadherin. These genes were down-regulated following CD133 knockdown. Moreover, CD133 expression could be modulated by the extracellular signal-regulated kinase (ERK)1/2 and SRC signaling pathways. The binding of CD133 to ERK1/2 and SRC acts as an indispensable mediator of N-cadherin expression.ConclusionsThese results demonstrate that CD133 plays a critical role in facilitating the EMT regulatory loop, specifically by upregulating N-cadherin expression, leading to the invasion and metastasis of pancreatic cancer cells. Our study provides a novel insight into the function of CD133 in the EMT program and a better understanding of the mechanism underlying the involvement of CD133 in pancreatic cancer metastasis.

Project description:Epithelial-mesenchymal transition (EMT), a reversible cellular program, is critically important in tumor progression and is regulated by a family of transcription factors, induction factors, and an array of signaling pathway genes. The prognostic role and biological functions of EMT-related lncRNAs in ccRCC are largely unknown. In the present study, we analyzed the gene expression data and clinical information retrieved from The Cancer Genome Atlas (TCGA) database (N=512) and International Cancer Genome Consortium (ICGC) database (N=90) which served as training and external validation dataset, respectively. Then, we constructed an EMT-related lncRNA risk signature based on the comprehensive analysis of the EMT-related lncRNA expression data and clinical information. The Kaplan-Meier curve analysis revealed that patients in the low-risk and high-risk groups exhibited significant divergence in the overall survival (OS) and disease-free survival (DFS) of ccRCC, as was confirmed in the validation dataset. The Cox regression analysis of the clinical factors and risk signature in the OS and DFS demonstrated that the risk signature can be utilized as an independent prognostic predictor. Moreover, we developed an individualized prognosis prediction model relying on the nomogram and receive operator curve (ROC) analysis based on the independent factors. The Gene Set Enrichment Analysis (GSEA) indicated that patients in the low-risk group were associated with adherens junction, focal adhesion, MAPK signaling pathway, pathways in cancer, and renal cell carcinoma pathway. In addition, we identified three robust subtypes (named C1, C2 and C3) of ccRCC with distinct clinical characteristics and prognostic role in the TCGA dataset and ICGC dataset. Among them, C1 was associated with a better survival outcome, whereas C2 and C3 was associated with a worse survival outcome and have more advanced-stage patients. Moreover, C2 was more likely to respond to immunotherapy and was sensitive to chemo drugs, this may provide insights to clinicians to develop an individualized treatment. Collectively, this work developed a reliable EMT-related lncRNA risk signature that can independently predict the OS and DFS of ccRCC. Besides, we identified three stable molecular subtypes based on the EMT-related lncRNA expression, which may comprehensively be vital in elucidating the underlying molecular mechanism of ccRCC.

Dataset Information

Investigating the link between molecular subtypes of glioblastoma, epithelial-mesenchymal transition, and CD133 cell surface protein.

Publications

Investigating the link between molecular subtypes of glioblastoma, epithelial-mesenchymal transition, and CD133 cell surface protein.

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