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Confrontation of fibroblasts with cancer cells in vitro: gene network analysis of transcriptome changes and differential capacity to inhibit tumor growth.

Alexeyenko A, Alkasalias T, Pavlova T, Szekely L, Kashuba V, Rundqvist H, Wiklund P, Egevad L, Csermely P, Korcsmaros T, Guven H, Klein G - J. Exp. Clin. Cancer Res. (2015)

Bottom Line: The combination of our methods pointed to proteins, such as members of the Rho pathway, pro-inflammatory signature and the YAP1/TAZ cascade, that warrant further investigation via tools of experimental perturbation.We also demonstrated functional congruence between the in vitro and ex vivo models.The microarray data are made available via the Gene Expression Omnibus as GSE57199.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology, Tumor and Cell Biology (MTC), Karolinska Institutet, Stockholm, Sweden. andrej.alekseenko@scilifelab.se.

ABSTRACT

Background: There is growing evidence that emerging malignancies in solid tissues might be kept under control by physical intercellular contacts with normal fibroblasts.

Methods: Here we characterize transcriptional landscapes of fibroblasts that confronted cancer cells. We studied four pairs of in vitro and ex vivo fibroblast lines which, within each pair, differed in their capacity to inhibit cancer cells. The natural process was modeled in vitro by confronting the fibroblasts with PC-3 cancer cells. Fibroblast transcriptomes were recorded by Affymetrix microarrays and then investigated using network analysis.

Results: The network enrichment analysis allowed us to separate confrontation- and inhibition-specific components of the fibroblast transcriptional response. Confrontation-specific differences were stronger and were characterized by changes in a number of pathways, including Rho, the YAP/TAZ cascade, NF-kB, and TGF-beta signaling, as well as the transcription factor RELA. Inhibition-specific differences were more subtle and characterized by involvement of Rho signaling at the pathway level and by potential individual regulators such as IL6, MAPK8, MAP2K4, PRKCA, JUN, STAT3, and STAT5A.

Conclusions: We investigated the interaction between cancer cells and fibroblasts in order to shed light on the potential mechanisms and explain the differential inhibitory capacity of the latter, which enabled both a holistic view on the process and details at the gene/protein level. The combination of our methods pointed to proteins, such as members of the Rho pathway, pro-inflammatory signature and the YAP1/TAZ cascade, that warrant further investigation via tools of experimental perturbation. We also demonstrated functional congruence between the in vitro and ex vivo models. The microarray data are made available via the Gene Expression Omnibus as GSE57199.

No MeSH data available.


Related in: MedlinePlus

Expression patterns of transcription factors and their likely targets as related to confrontation with tumor cells. The plots are using log2-transformed expression values from Affymetrix. The text labels refer to cell sample IDs (see Methods) and are centered at the respective coordinates without offset. Green: gene expression before confrontation with tumor cells; Red: gene expression after 72 h of confrontation
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Fig3: Expression patterns of transcription factors and their likely targets as related to confrontation with tumor cells. The plots are using log2-transformed expression values from Affymetrix. The text labels refer to cell sample IDs (see Methods) and are centered at the respective coordinates without offset. Green: gene expression before confrontation with tumor cells; Red: gene expression after 72 h of confrontation

Mentions: Four cadherin-related pathways available in our collection were significantly associated with the confrontational response (NEA FDR < 10−19 for each of the pathways). In particular, we found that CAMK2A (calcium/calmodulin-dependent protein kinase II delta) was likely to be controlled by two transcription factors. The promoter region for CAMK2A contained binding sites for the transcription factors RORA and REL. RORA and REL were differentially expressed during the confrontation and their expression patterns were significantly correlated during that process (Pearson r = 0.777, p0 = 0.00018; Fig. 3) across the samples. Importantly, our network enrichment analysis was able to summarize bi-directional relations between DEGs and pathways. For example, we established, in a similar manner as above, that RORA could regulate two members of the KEGG pathway “Cytokine-cytokine receptor interaction”: colony stimulating factor CSF3 and CD40LG (the CD40 ligand). The latter genes were not included in the DEG list, because of lower significance of differential expression, but their expression pattern was still highly correlated with RORA expression.Fig. 3


Confrontation of fibroblasts with cancer cells in vitro: gene network analysis of transcriptome changes and differential capacity to inhibit tumor growth.

Alexeyenko A, Alkasalias T, Pavlova T, Szekely L, Kashuba V, Rundqvist H, Wiklund P, Egevad L, Csermely P, Korcsmaros T, Guven H, Klein G - J. Exp. Clin. Cancer Res. (2015)

Expression patterns of transcription factors and their likely targets as related to confrontation with tumor cells. The plots are using log2-transformed expression values from Affymetrix. The text labels refer to cell sample IDs (see Methods) and are centered at the respective coordinates without offset. Green: gene expression before confrontation with tumor cells; Red: gene expression after 72 h of confrontation
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4472614&req=5

Fig3: Expression patterns of transcription factors and their likely targets as related to confrontation with tumor cells. The plots are using log2-transformed expression values from Affymetrix. The text labels refer to cell sample IDs (see Methods) and are centered at the respective coordinates without offset. Green: gene expression before confrontation with tumor cells; Red: gene expression after 72 h of confrontation
Mentions: Four cadherin-related pathways available in our collection were significantly associated with the confrontational response (NEA FDR < 10−19 for each of the pathways). In particular, we found that CAMK2A (calcium/calmodulin-dependent protein kinase II delta) was likely to be controlled by two transcription factors. The promoter region for CAMK2A contained binding sites for the transcription factors RORA and REL. RORA and REL were differentially expressed during the confrontation and their expression patterns were significantly correlated during that process (Pearson r = 0.777, p0 = 0.00018; Fig. 3) across the samples. Importantly, our network enrichment analysis was able to summarize bi-directional relations between DEGs and pathways. For example, we established, in a similar manner as above, that RORA could regulate two members of the KEGG pathway “Cytokine-cytokine receptor interaction”: colony stimulating factor CSF3 and CD40LG (the CD40 ligand). The latter genes were not included in the DEG list, because of lower significance of differential expression, but their expression pattern was still highly correlated with RORA expression.Fig. 3

Bottom Line: The combination of our methods pointed to proteins, such as members of the Rho pathway, pro-inflammatory signature and the YAP1/TAZ cascade, that warrant further investigation via tools of experimental perturbation.We also demonstrated functional congruence between the in vitro and ex vivo models.The microarray data are made available via the Gene Expression Omnibus as GSE57199.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology, Tumor and Cell Biology (MTC), Karolinska Institutet, Stockholm, Sweden. andrej.alekseenko@scilifelab.se.

ABSTRACT

Background: There is growing evidence that emerging malignancies in solid tissues might be kept under control by physical intercellular contacts with normal fibroblasts.

Methods: Here we characterize transcriptional landscapes of fibroblasts that confronted cancer cells. We studied four pairs of in vitro and ex vivo fibroblast lines which, within each pair, differed in their capacity to inhibit cancer cells. The natural process was modeled in vitro by confronting the fibroblasts with PC-3 cancer cells. Fibroblast transcriptomes were recorded by Affymetrix microarrays and then investigated using network analysis.

Results: The network enrichment analysis allowed us to separate confrontation- and inhibition-specific components of the fibroblast transcriptional response. Confrontation-specific differences were stronger and were characterized by changes in a number of pathways, including Rho, the YAP/TAZ cascade, NF-kB, and TGF-beta signaling, as well as the transcription factor RELA. Inhibition-specific differences were more subtle and characterized by involvement of Rho signaling at the pathway level and by potential individual regulators such as IL6, MAPK8, MAP2K4, PRKCA, JUN, STAT3, and STAT5A.

Conclusions: We investigated the interaction between cancer cells and fibroblasts in order to shed light on the potential mechanisms and explain the differential inhibitory capacity of the latter, which enabled both a holistic view on the process and details at the gene/protein level. The combination of our methods pointed to proteins, such as members of the Rho pathway, pro-inflammatory signature and the YAP1/TAZ cascade, that warrant further investigation via tools of experimental perturbation. We also demonstrated functional congruence between the in vitro and ex vivo models. The microarray data are made available via the Gene Expression Omnibus as GSE57199.

No MeSH data available.


Related in: MedlinePlus