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Validated prediction of pro-invasive growth factors using a transcriptome-wide invasion signature derived from a complex 3D invasion assay.

Oehrle B, Burgstaller G, Irmler M, Dehmel S, Grün J, Hwang T, Krauss-Etschmann S, Beckers J, Meiners S, Eickelberg O - Sci Rep (2015)

Bottom Line: Unbiased pathway analysis (Ingenuity) identified significant enrichment for the functional clusters 'invasion of cells', 'idiopathic pulmonary fibrosis', and 'metastasis'.Matrix metalloprotease 13 (MMP13), transforming growth factor (TGF)-β1, Caveolin (Cav) 1, Phosphatase and Tensin Homolog (Pten), and secreted frizzled-related protein (Sfrp) 1 were among the highest regulated genes, confirmed by qRT-PCR and Western Blotting.We next performed in silico analysis (Ingenuity Pathway Analysis) to predict mediators that induced fibroblast invasion.

View Article: PubMed Central - PubMed

Affiliation: Comprehensive Pneumology Center, University Hospital of the Ludwig-Maximilians-University Munich and Helmholtz Zentrum München, Member of the German Center for Lung Research, 81377 Munich, Germany.

ABSTRACT
The invasion of activated fibroblasts represents a key pathomechanism in fibrotic diseases, carcinogenesis and metastasis. Invading fibroblasts contribute to fibrotic extracellular matrix (ECM) formation and the initiation, progression, or resistance of cancer. To construct transcriptome-wide signatures of fibroblast invasion, we used a multiplex phenotypic 3D invasion assay using lung fibroblasts. Microarray-based gene expression profiles of invading and non-invading fibroblasts demonstrated that 1,049 genes were differentially regulated (>1.5-fold). Unbiased pathway analysis (Ingenuity) identified significant enrichment for the functional clusters 'invasion of cells', 'idiopathic pulmonary fibrosis', and 'metastasis'. Matrix metalloprotease 13 (MMP13), transforming growth factor (TGF)-β1, Caveolin (Cav) 1, Phosphatase and Tensin Homolog (Pten), and secreted frizzled-related protein (Sfrp) 1 were among the highest regulated genes, confirmed by qRT-PCR and Western Blotting. We next performed in silico analysis (Ingenuity Pathway Analysis) to predict mediators that induced fibroblast invasion. Of these, TGFβ1, epidermal growth factor (EGF), fibroblast growth factor (FGF) 2, and platelet-derived growth factor (PDGF)-BB were tested in our 3D invasion assay and found to significantly induce invasion, thus validating the transcriptome profile. Accordingly, our transcriptomic invasion signature describes the invading fibroblast phenotype in unprecedented detail and provides a tool for future functional studies of cell invasion and therapeutic modulation thereof using complex phenotypic assays.

No MeSH data available.


Related in: MedlinePlus

A time-dependent gene expression overlap of the conducted microarrays at 72 and 96 hours and predictive in silico analysis.Venn diagrams depict the expression overlap in deregulated genes (>1.5x) comparing the expression ratios of invading (inv.) and non-invading (non-inv.) fibroblasts at 96 hours and 72 hours after invasion. Note, 621 targets were found to overlap which comprise 166 up- and 455 down-regulated genes (a). An IPA generated heatmap that shows the ten most significantly over-represented ‘disease processes’ and ‘biological functions’ including ‘invasion of cells’, ‘idiopathic pulmonary fibrosis’, and ‘metastasis’ (b). Causal network analysis of underlying pathways of ‘invasion of cells’, ‘idiopathic pulmonary fibrosis’, and ‘metastasis’. Targets that were significantly up-, or down-regulated in the invading fibroblast phenotype are represented in green and red, respectively. The dashed orange lines illustrate activating relationships, yellow lines point out findings that are inconsistent with the state of downstream molecules, and grey lines indicate that the mode of effect is not defined (c).
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f3: A time-dependent gene expression overlap of the conducted microarrays at 72 and 96 hours and predictive in silico analysis.Venn diagrams depict the expression overlap in deregulated genes (>1.5x) comparing the expression ratios of invading (inv.) and non-invading (non-inv.) fibroblasts at 96 hours and 72 hours after invasion. Note, 621 targets were found to overlap which comprise 166 up- and 455 down-regulated genes (a). An IPA generated heatmap that shows the ten most significantly over-represented ‘disease processes’ and ‘biological functions’ including ‘invasion of cells’, ‘idiopathic pulmonary fibrosis’, and ‘metastasis’ (b). Causal network analysis of underlying pathways of ‘invasion of cells’, ‘idiopathic pulmonary fibrosis’, and ‘metastasis’. Targets that were significantly up-, or down-regulated in the invading fibroblast phenotype are represented in green and red, respectively. The dashed orange lines illustrate activating relationships, yellow lines point out findings that are inconsistent with the state of downstream molecules, and grey lines indicate that the mode of effect is not defined (c).

Mentions: The gene expression profiles of the invading fibroblasts at 72 hours and 96 hours (>1.5-fold) greatly overlapped: among the differentially regulated genes in the invading subtype at 72 and 96 hours, 621 genes overlapped in total: 166 in the up- and 455 in the down-regulated group (Fig. 3A). Of note, there were more than twice as many overlapping down-regulated genes than overlapping up-regulated genes. This comparative approach allowed us to enrich for those targets that are commonly regulated after 72 and 96 hours of invasion and to define the invasion signature of fibroblasts. Enrichment analyses using IPA’s ‘disease and function’ ontology revealed that ‘invasion of cells’, ‘idiopathic pulmonary fibrosis (IPF)’, and ‘metastasis’ ranked as the top three most significantly over-represented ‘disease processes’ and ‘biological functions’ within the invasion signature (Fig. 3B). In agreement with the well-known role of TGFβ1 in invasion and fibrosis, TGFβ1 associated with all three key networks of invasion (Fig. 3C). These data clearly corroborate our experimental approach. In order to further validate the profiling approach used, several known invasion-promoting genes were chosen for confirmative expression analysis by qRT-PCR. These targets included matrix metalloprotease 13 (MMP13)2021, TGFβ11022, Caveolin 1 (Cav1)23, secreted frizzled-related protein (Sfrp) 1 24, and Phosphatase and Tensin Homolog (Pten)2526 (Fig. 4A,B). Consistent with our microarray data (Fig. 4C), qRT-PCR analysis demonstrated a significant up-regulation of MMP13 and TGFβ1 in the invading fibroblasts by 6- and 1.8-fold, respectively (Fig. 4D). By contrast, Cav1, Sfrp1, and Pten were significantly down-regulated by 3.5-, 2.9-, and 2.6-fold, respectively (Fig. 3D). Reduced Sfrp1 and Cav1 protein expression was further corroborated by immunoblot analysis (Fig. 4E). Furthermore, TGFβ1 and MMP1319 were up-regulated on protein level as well (Fig. 4E). Interestingly, the protein expression of Pten, which was strongly diminished on transcript level, was found to be largely unchanged. Additionally, in primary human lung fibroblasts we identified a corresponding regulation of the same target genes in the invading subpopulation (Fig. 4F). The qRT-PCR analyses of selected target genes thus validated the robustness of our invasion assay and the identified gene signature for invading fibroblasts.


Validated prediction of pro-invasive growth factors using a transcriptome-wide invasion signature derived from a complex 3D invasion assay.

Oehrle B, Burgstaller G, Irmler M, Dehmel S, Grün J, Hwang T, Krauss-Etschmann S, Beckers J, Meiners S, Eickelberg O - Sci Rep (2015)

A time-dependent gene expression overlap of the conducted microarrays at 72 and 96 hours and predictive in silico analysis.Venn diagrams depict the expression overlap in deregulated genes (>1.5x) comparing the expression ratios of invading (inv.) and non-invading (non-inv.) fibroblasts at 96 hours and 72 hours after invasion. Note, 621 targets were found to overlap which comprise 166 up- and 455 down-regulated genes (a). An IPA generated heatmap that shows the ten most significantly over-represented ‘disease processes’ and ‘biological functions’ including ‘invasion of cells’, ‘idiopathic pulmonary fibrosis’, and ‘metastasis’ (b). Causal network analysis of underlying pathways of ‘invasion of cells’, ‘idiopathic pulmonary fibrosis’, and ‘metastasis’. Targets that were significantly up-, or down-regulated in the invading fibroblast phenotype are represented in green and red, respectively. The dashed orange lines illustrate activating relationships, yellow lines point out findings that are inconsistent with the state of downstream molecules, and grey lines indicate that the mode of effect is not defined (c).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4525140&req=5

f3: A time-dependent gene expression overlap of the conducted microarrays at 72 and 96 hours and predictive in silico analysis.Venn diagrams depict the expression overlap in deregulated genes (>1.5x) comparing the expression ratios of invading (inv.) and non-invading (non-inv.) fibroblasts at 96 hours and 72 hours after invasion. Note, 621 targets were found to overlap which comprise 166 up- and 455 down-regulated genes (a). An IPA generated heatmap that shows the ten most significantly over-represented ‘disease processes’ and ‘biological functions’ including ‘invasion of cells’, ‘idiopathic pulmonary fibrosis’, and ‘metastasis’ (b). Causal network analysis of underlying pathways of ‘invasion of cells’, ‘idiopathic pulmonary fibrosis’, and ‘metastasis’. Targets that were significantly up-, or down-regulated in the invading fibroblast phenotype are represented in green and red, respectively. The dashed orange lines illustrate activating relationships, yellow lines point out findings that are inconsistent with the state of downstream molecules, and grey lines indicate that the mode of effect is not defined (c).
Mentions: The gene expression profiles of the invading fibroblasts at 72 hours and 96 hours (>1.5-fold) greatly overlapped: among the differentially regulated genes in the invading subtype at 72 and 96 hours, 621 genes overlapped in total: 166 in the up- and 455 in the down-regulated group (Fig. 3A). Of note, there were more than twice as many overlapping down-regulated genes than overlapping up-regulated genes. This comparative approach allowed us to enrich for those targets that are commonly regulated after 72 and 96 hours of invasion and to define the invasion signature of fibroblasts. Enrichment analyses using IPA’s ‘disease and function’ ontology revealed that ‘invasion of cells’, ‘idiopathic pulmonary fibrosis (IPF)’, and ‘metastasis’ ranked as the top three most significantly over-represented ‘disease processes’ and ‘biological functions’ within the invasion signature (Fig. 3B). In agreement with the well-known role of TGFβ1 in invasion and fibrosis, TGFβ1 associated with all three key networks of invasion (Fig. 3C). These data clearly corroborate our experimental approach. In order to further validate the profiling approach used, several known invasion-promoting genes were chosen for confirmative expression analysis by qRT-PCR. These targets included matrix metalloprotease 13 (MMP13)2021, TGFβ11022, Caveolin 1 (Cav1)23, secreted frizzled-related protein (Sfrp) 1 24, and Phosphatase and Tensin Homolog (Pten)2526 (Fig. 4A,B). Consistent with our microarray data (Fig. 4C), qRT-PCR analysis demonstrated a significant up-regulation of MMP13 and TGFβ1 in the invading fibroblasts by 6- and 1.8-fold, respectively (Fig. 4D). By contrast, Cav1, Sfrp1, and Pten were significantly down-regulated by 3.5-, 2.9-, and 2.6-fold, respectively (Fig. 3D). Reduced Sfrp1 and Cav1 protein expression was further corroborated by immunoblot analysis (Fig. 4E). Furthermore, TGFβ1 and MMP1319 were up-regulated on protein level as well (Fig. 4E). Interestingly, the protein expression of Pten, which was strongly diminished on transcript level, was found to be largely unchanged. Additionally, in primary human lung fibroblasts we identified a corresponding regulation of the same target genes in the invading subpopulation (Fig. 4F). The qRT-PCR analyses of selected target genes thus validated the robustness of our invasion assay and the identified gene signature for invading fibroblasts.

Bottom Line: Unbiased pathway analysis (Ingenuity) identified significant enrichment for the functional clusters 'invasion of cells', 'idiopathic pulmonary fibrosis', and 'metastasis'.Matrix metalloprotease 13 (MMP13), transforming growth factor (TGF)-β1, Caveolin (Cav) 1, Phosphatase and Tensin Homolog (Pten), and secreted frizzled-related protein (Sfrp) 1 were among the highest regulated genes, confirmed by qRT-PCR and Western Blotting.We next performed in silico analysis (Ingenuity Pathway Analysis) to predict mediators that induced fibroblast invasion.

View Article: PubMed Central - PubMed

Affiliation: Comprehensive Pneumology Center, University Hospital of the Ludwig-Maximilians-University Munich and Helmholtz Zentrum München, Member of the German Center for Lung Research, 81377 Munich, Germany.

ABSTRACT
The invasion of activated fibroblasts represents a key pathomechanism in fibrotic diseases, carcinogenesis and metastasis. Invading fibroblasts contribute to fibrotic extracellular matrix (ECM) formation and the initiation, progression, or resistance of cancer. To construct transcriptome-wide signatures of fibroblast invasion, we used a multiplex phenotypic 3D invasion assay using lung fibroblasts. Microarray-based gene expression profiles of invading and non-invading fibroblasts demonstrated that 1,049 genes were differentially regulated (>1.5-fold). Unbiased pathway analysis (Ingenuity) identified significant enrichment for the functional clusters 'invasion of cells', 'idiopathic pulmonary fibrosis', and 'metastasis'. Matrix metalloprotease 13 (MMP13), transforming growth factor (TGF)-β1, Caveolin (Cav) 1, Phosphatase and Tensin Homolog (Pten), and secreted frizzled-related protein (Sfrp) 1 were among the highest regulated genes, confirmed by qRT-PCR and Western Blotting. We next performed in silico analysis (Ingenuity Pathway Analysis) to predict mediators that induced fibroblast invasion. Of these, TGFβ1, epidermal growth factor (EGF), fibroblast growth factor (FGF) 2, and platelet-derived growth factor (PDGF)-BB were tested in our 3D invasion assay and found to significantly induce invasion, thus validating the transcriptome profile. Accordingly, our transcriptomic invasion signature describes the invading fibroblast phenotype in unprecedented detail and provides a tool for future functional studies of cell invasion and therapeutic modulation thereof using complex phenotypic assays.

No MeSH data available.


Related in: MedlinePlus