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Transforming growth factor [beta]s (TGF-[beta]s) regulate key aspects of embryonic development and major human diseases. Although Smad2, Smad3, and extracellular signal-regulated kinase (ERK) mitogen-activated protein kinases (MAPKs) have been proposed as key mediators in TGF-[beta] signaling, their functional specificities and interactivity in controlling transcriptional programs in different cell types and (patho)physiological contexts are not known. We investigated expression profiles of genes controlled by TGF-[beta] in fibroblasts with ablations of Smad2, Smad3, and ERK MAPK. Our results suggest that Smad3 is the essential mediator of TGF-[beta] signaling and directly activates genes encoding regulators of transcription and signal transducers through Smad3/Smad4 DNA-binding motif repeats that are characteristic for immediate-early target genes of TGF-[beta] but absent in intermediate target genes. In contrast, Smad2 and ERK predominantly transmodulated regulation of both immediate-early and intermediate genes by TGF-[beta]/Smad3. These results suggest a previously uncharacterized hierarchical model of gene regulation by TGF-[beta] in which TGF-[beta] causes direct activation by Smad3 of cascades of regulators of transcription and signaling that are transmodulated by Smad2 and/or ERK.

Abstract Background Gene expression data can be analyzed by summarizing groups of individual gene expression profiles based on GO annotation information. The mean expression profile per group can then be used to identify interesting GO categories in relation to the experimental settings. However, the expression profiles present in GO classes are often heterogeneous, i.e., there are several different expression profiles within one class. As a result, important experimental findings can be obscured because the summarizing profile does not seem to be of interest. We propose to tackle this problem by finding homogeneous subclasses within GO categories: preclustering. Results Two microarray datasets are analyzed. First, a selection of genes from a well-known Saccharomyces cerevisiae dataset is used. The GO class "cell wall organization and biogenesis" is shown as a specific example. After preclustering, this term can be associated with different phases in the cell cycle, where it could not be associated with a specific phase previously. Second, a dataset of differentiation of human Mesenchymal Stem Cells (MSC) into osteoblasts is used. For this dataset results are shown in which the GO term "skeletal development" is a specific example of a heterogeneous GO class for which better associations can be made after preclustering. The Intra Cluster Correlation (ICC), a measure of cluster tightness, is applied to identify relevant clusters. Conclusions We show that this method leads to an improved interpretability of results in Principal Component Analysis.

Epithelial-mesenchymal transitions (EMTs) are an essential manifestation of epithelial cell plasticity during morphogenesis, wound healing, and tumor progression. Transforming growth factor-[Beta] (TGF-[Beta]) modulates epithelial plasticity in these physiological contexts by inducing EMT. Here we report a transcriptome screen of genetic programs of TGF-[Beta]-induced EMT in human keratinocytes and propose functional roles for extracellular response kinase (ERK) mitogen-activated protein kinase signaling in cell motility and disruption of adherens junctions. We used DNA arrays of 16,580 human cDNAs to identify 728 known genes regulated by TGF-[Beta] within 4 hours after treatment. TGF-[Beta]-stimulated ERK signaling mediated regulation of 80 target genes not previously associated with this pathway. This subset is enriched for genes with defined roles in cell-matrix interactions, cell motility, and endocytosis. ERK-independent genetic programs underlying the onset of EMT involve key pathways and regulators of epithelial dedifferentiation, undifferentiated transitional and mesenchymal progenitor phenotypes, and mediators of cytoskeletal reorganization. The gene expression profiling approach delineates complex context-dependent signaling pathways and transcriptional events that determine epithelial cell plasticity controlled by TGF-[Beta]. Investigation of the identified pathways and genes will advance the understanding of molecular mechanisms that underlie tumor invasiveness and metastasis.

Background: Gene expression data can be analyzed by summarizing groups of individual gene expression profiles based on GO annotation information. The mean expression profile per group can then be used to identify interesting GO categories in relation to the experimental settings. However, the expression profiles present in GO classes are often heterogeneous, i.e., there are several different expression profiles within one class. As a result, important experimental findings can be obscured because the summarizing profile does not seem to be of interest. We propose to tackle this problem by finding homogeneous subclasses within GO categories: preclustering. Results: Two microarray datasets are analyzed. First, a selection of genes from a well-known Saccharomyces cerevisiae dataset is used. The GO class "cell wall organization and biogenesis" is shown as a specific example. After preclustering, this term can be associated with different phases in the cell cycle, where it could not be associated with a specific phase previously. Second, a dataset of differentiation of human Mesenchymal Stem Cells (MSC) into osteoblasts is used. For this dataset results are shown in which the GO term "skeletal development" is a specific example of a heterogeneous GO class for which better associations can be made after preclustering. The Intra Cluster Correlation (ICC), a measure of cluster tightness, is applied to identify relevant clusters. Conclusions: We show that this method leads to an improved interpretability of results in Principal Component Analysis. [ABSTRACT FROM AUTHOR]

Transforming growth factor βs (TGF-βs) regulate key aspects of embryonic development and major human diseases. Although Smad2, Smad3, and extracellular signal-regulated kinase (ERK) mitogen-activated protein kinases (MAPKs) have been proposed as key mediators in TGF-β signaling, their functional specificities and interactivity in controlling transcriptional programs in different cell types and (patho)physiological contexts are not known. We investigated expression profiles of genes controlled by TGF-β in fibroblasts with ablations of Smad2, Smad3, and ERK MAPK. Our results suggest that Smad3 is the essential mediator of TGF-β signaling and directly activates genes encoding regulators of transcription and signal transducers through Smad3/Smad4 DNA-binding motif repeats that are characteristic for immediate-early target genes of TGF-β but absent in intermediate target genes. In contrast, Smad2 and ERK predominantly transmodulated regulation of both immediate-early and intermediate genes by TGF-β/Smad3. These results suggest a previously uncharacterized hierarchical model of gene regulation by TGF-β in which TGF-β causes direct activation by Smad3 of cascades of regulators of transcription and signaling that are transmodulated by Smad2 and/or ERK. [ABSTRACT FROM AUTHOR]