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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

Expression levels of growth factor receptors.The baseline expression levels of transforming growth factor (TGF)β receptors I (TGFβRI) and II (TGFβRII), epidermal growth factor (EGF) receptor (EGFR), fibroblast growth factor (FGF) receptor 1 (FGFRI) and 2 (FGFR2), and platelet derived growth factor (PDGF) receptor alpha (PDGFRα) and beta (PDGFRβ) were determined by immunoblot analysis (a–d upper panel). Expression levels upon invasion at 72 hours (72 h) (a–d middle panel) and 96 hours (96 h) (a–d lower panel) were extracted from the microarray data. Statistical analysis: paired t-test. *p < 0.05, **p < 0.01, and ***p < 0.001.
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f6: Expression levels of growth factor receptors.The baseline expression levels of transforming growth factor (TGF)β receptors I (TGFβRI) and II (TGFβRII), epidermal growth factor (EGF) receptor (EGFR), fibroblast growth factor (FGF) receptor 1 (FGFRI) and 2 (FGFR2), and platelet derived growth factor (PDGF) receptor alpha (PDGFRα) and beta (PDGFRβ) were determined by immunoblot analysis (a–d upper panel). Expression levels upon invasion at 72 hours (72 h) (a–d middle panel) and 96 hours (96 h) (a–d lower panel) were extracted from the microarray data. Statistical analysis: paired t-test. *p < 0.05, **p < 0.01, and ***p < 0.001.

Mentions: In order to further validate the generated transcriptomic fibroblast invasion signature, gene expression lists were evaluated with the causal analysis tool ‘upstream regulator analysis’ (URA), implemented in IPA. This approach allowed the identification of putative upstream regulators for subsequent functional testing in regards to fibroblast invasion. In order to measure the enrichment of potentially activated upstream regulators we used a ranking based on the p-value27 obtained from the overlap between our experimentally derived gene datasets and those from the IPA’s database. As physiological upstream regulators were of particular interest, we excluded ‘drugs’, and ‘chemicals’ from the URA. The ‘p-value of overlap’ in supplementary Table 1 depicts a ranking of physiological upstream regulators according to their p-values for the comparison of gene expression data at 72 and 96 hours upon invasion. The cut-off value for the ranking (negative logarithmic p-value) was set to 4. By using a more stringent filter for ‘growth factors’, we were able to extract four growth factors, which all were found to be associated with fibrotic and/or cancerous diseases in the literature (Fig. 5A). Notably, TGFβ1, which is a prominent and potent activator of fibroblasts, ranked high among the predicted upstream regulators (p-value 96 hours = 3.2 × 10−10, p-value 72 hours = 1.4 × 10−6). In line with its key role in fibrogenesis, in the microarrays we found the expression of TGFβ1 to be significantly increased in the invading fibroblast fraction and moreover, also predicted to be associated with the generated functional gene clusters ‘IPF’, ‘invasion of cells’, and ‘metastasis’ in the in silico gene cluster analysis (Fig. 3C). Further putative upstream regulators from the URA, which were chosen for functional analysis in the following due to their association to fibrotic and cancerous diseases, comprised epidermal growth factor (EGF), basic fibroblast growth factor (FGF) 2, and platelet derived growth factor (PDGF)-BB. EGF, was predictively activated in the invading fibroblast fraction with a p-value 96 hours = 10.0 × 10−6 and a p-value 72 hours = 4.8 × 10−5 (Fig. 5A), while its receptor EGFR was also predicted to be activated (p-value 96 hours = 6.3 × 10−9 and a p-value 72 hours = 4.0 × 10−5) (supplementary Table 1). In our transcriptomic invasion signature, FGF2 was another highly ranked candidate in the predicted list of upstream regulators (p-value 96 hours = 7.0 × 10−8 and p-value 72 hours = 2.8 × 10−5), which was associated with fibrotic or cancerous diseases. Furthermore, PDGF-BB was predicted to be activated based on the invasion signature with p-value 96 hours = 3.8 × 10−6 and a p-value 72 hours = 2.3 × 10−5. Grounded on these computational predictions of activated upstream regulators, we next performed functional confirmative studies in vitro. Therefore, the invasive capacity of MLg fibroblasts was assessed by using the automated software-based invasion assay recently established in our lab19. The fibroblasts were treated with the particular growth factor and the invasion capacity was measured after 72 hours total invasion time as previously described19. TGFβ1 (1 and 5 ng/ml) significantly enhanced the fibroblast invasion capacity to 138.2 ± 28.7% (p-value ≤ 0.01) and 141.7 ± 38.1% (p-value ≤ 0.01), compared to untreated controls (Fig. 5B). EGF (10 and 50 ng/ml) significantly increased the cellular invasion to 178 ± 57.0% and 193.3 ± 64.2% (p-value ≤ 0.05), respectively (Fig. 5C). FGF2 exhibited the strongest significant effect on the invasion capacity with a mean relative induction of 246.8 ± 58.9% (10 ng/ml) (p-value ≤ 0.05) and 235.0 ± 64.2% (50 ng/ml) (p-value ≤ 0.05) (Fig. 5D). PDGF-BB (5 and 25 ng/ml) initiated a significant effect of 114.4 ± 17.6% (p-value ≤ 0.05) and 134.9 ± 23.0% (p-value ≤ 0.001) relative invasion (Fig. 5D). Supplementary Fig. S1 depicts representative images of either untreated or TGFβ1-, and FGF2-treated fibroblasts invading the collagen gel. Next, we used immunoblot analyses to demonstrate expression of the receptors for the above identified growth factors in lung fibroblasts. Protein expression of TGFβRI and II, EGFR, FGFR1 and 2, as well as PDGFRα and β was assessed in fibroblasts cultured on the 3D collagen matrix at the time of cell treatment. In addition, the expression levels of these receptors upon invasion were extracted from the microarray data for 72 and 96 hours of invasion (Fig. 6). While mRNA expression levels of TGFβRII and EGFR were detected but significantly reduced in invading cells at both time-points, FGFR1 and FGFR2 mRNA levels were increased. PDGFRα and β were expressed, but unchanged during invasion. Taken together, we have generated and identified, using a novel high content 3D invasion assay, a specific transcriptome signature of fibroblast invasion that shows a strong relation to invasive diseases, such as fibrosis and cancer.


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)

Expression levels of growth factor receptors.The baseline expression levels of transforming growth factor (TGF)β receptors I (TGFβRI) and II (TGFβRII), epidermal growth factor (EGF) receptor (EGFR), fibroblast growth factor (FGF) receptor 1 (FGFRI) and 2 (FGFR2), and platelet derived growth factor (PDGF) receptor alpha (PDGFRα) and beta (PDGFRβ) were determined by immunoblot analysis (a–d upper panel). Expression levels upon invasion at 72 hours (72 h) (a–d middle panel) and 96 hours (96 h) (a–d lower panel) were extracted from the microarray data. Statistical analysis: paired t-test. *p < 0.05, **p < 0.01, and ***p < 0.001.
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Related In: Results  -  Collection

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

f6: Expression levels of growth factor receptors.The baseline expression levels of transforming growth factor (TGF)β receptors I (TGFβRI) and II (TGFβRII), epidermal growth factor (EGF) receptor (EGFR), fibroblast growth factor (FGF) receptor 1 (FGFRI) and 2 (FGFR2), and platelet derived growth factor (PDGF) receptor alpha (PDGFRα) and beta (PDGFRβ) were determined by immunoblot analysis (a–d upper panel). Expression levels upon invasion at 72 hours (72 h) (a–d middle panel) and 96 hours (96 h) (a–d lower panel) were extracted from the microarray data. Statistical analysis: paired t-test. *p < 0.05, **p < 0.01, and ***p < 0.001.
Mentions: In order to further validate the generated transcriptomic fibroblast invasion signature, gene expression lists were evaluated with the causal analysis tool ‘upstream regulator analysis’ (URA), implemented in IPA. This approach allowed the identification of putative upstream regulators for subsequent functional testing in regards to fibroblast invasion. In order to measure the enrichment of potentially activated upstream regulators we used a ranking based on the p-value27 obtained from the overlap between our experimentally derived gene datasets and those from the IPA’s database. As physiological upstream regulators were of particular interest, we excluded ‘drugs’, and ‘chemicals’ from the URA. The ‘p-value of overlap’ in supplementary Table 1 depicts a ranking of physiological upstream regulators according to their p-values for the comparison of gene expression data at 72 and 96 hours upon invasion. The cut-off value for the ranking (negative logarithmic p-value) was set to 4. By using a more stringent filter for ‘growth factors’, we were able to extract four growth factors, which all were found to be associated with fibrotic and/or cancerous diseases in the literature (Fig. 5A). Notably, TGFβ1, which is a prominent and potent activator of fibroblasts, ranked high among the predicted upstream regulators (p-value 96 hours = 3.2 × 10−10, p-value 72 hours = 1.4 × 10−6). In line with its key role in fibrogenesis, in the microarrays we found the expression of TGFβ1 to be significantly increased in the invading fibroblast fraction and moreover, also predicted to be associated with the generated functional gene clusters ‘IPF’, ‘invasion of cells’, and ‘metastasis’ in the in silico gene cluster analysis (Fig. 3C). Further putative upstream regulators from the URA, which were chosen for functional analysis in the following due to their association to fibrotic and cancerous diseases, comprised epidermal growth factor (EGF), basic fibroblast growth factor (FGF) 2, and platelet derived growth factor (PDGF)-BB. EGF, was predictively activated in the invading fibroblast fraction with a p-value 96 hours = 10.0 × 10−6 and a p-value 72 hours = 4.8 × 10−5 (Fig. 5A), while its receptor EGFR was also predicted to be activated (p-value 96 hours = 6.3 × 10−9 and a p-value 72 hours = 4.0 × 10−5) (supplementary Table 1). In our transcriptomic invasion signature, FGF2 was another highly ranked candidate in the predicted list of upstream regulators (p-value 96 hours = 7.0 × 10−8 and p-value 72 hours = 2.8 × 10−5), which was associated with fibrotic or cancerous diseases. Furthermore, PDGF-BB was predicted to be activated based on the invasion signature with p-value 96 hours = 3.8 × 10−6 and a p-value 72 hours = 2.3 × 10−5. Grounded on these computational predictions of activated upstream regulators, we next performed functional confirmative studies in vitro. Therefore, the invasive capacity of MLg fibroblasts was assessed by using the automated software-based invasion assay recently established in our lab19. The fibroblasts were treated with the particular growth factor and the invasion capacity was measured after 72 hours total invasion time as previously described19. TGFβ1 (1 and 5 ng/ml) significantly enhanced the fibroblast invasion capacity to 138.2 ± 28.7% (p-value ≤ 0.01) and 141.7 ± 38.1% (p-value ≤ 0.01), compared to untreated controls (Fig. 5B). EGF (10 and 50 ng/ml) significantly increased the cellular invasion to 178 ± 57.0% and 193.3 ± 64.2% (p-value ≤ 0.05), respectively (Fig. 5C). FGF2 exhibited the strongest significant effect on the invasion capacity with a mean relative induction of 246.8 ± 58.9% (10 ng/ml) (p-value ≤ 0.05) and 235.0 ± 64.2% (50 ng/ml) (p-value ≤ 0.05) (Fig. 5D). PDGF-BB (5 and 25 ng/ml) initiated a significant effect of 114.4 ± 17.6% (p-value ≤ 0.05) and 134.9 ± 23.0% (p-value ≤ 0.001) relative invasion (Fig. 5D). Supplementary Fig. S1 depicts representative images of either untreated or TGFβ1-, and FGF2-treated fibroblasts invading the collagen gel. Next, we used immunoblot analyses to demonstrate expression of the receptors for the above identified growth factors in lung fibroblasts. Protein expression of TGFβRI and II, EGFR, FGFR1 and 2, as well as PDGFRα and β was assessed in fibroblasts cultured on the 3D collagen matrix at the time of cell treatment. In addition, the expression levels of these receptors upon invasion were extracted from the microarray data for 72 and 96 hours of invasion (Fig. 6). While mRNA expression levels of TGFβRII and EGFR were detected but significantly reduced in invading cells at both time-points, FGFR1 and FGFR2 mRNA levels were increased. PDGFRα and β were expressed, but unchanged during invasion. Taken together, we have generated and identified, using a novel high content 3D invasion assay, a specific transcriptome signature of fibroblast invasion that shows a strong relation to invasive diseases, such as fibrosis and cancer.

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